RE-MYCE: Landslide-Responsive Design, Mountainous Region, Biocomposite Structural System (MSc)

RE-MYCE LANDSLIDE-RESPONSIVE DESIGN MOUNTAINOUS REGION

BIOCOMPOSITE STRUCTURAL SYSTEM

Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 1

ARCHITECTURAL ASSOCIATION SCHOOL OF ARCHITECTURE GRADUATE SCHOOL PROGRAMMES PROGRAMME

EMERGENT TECHNOLOGIES AND DESIGN

YEAR

2022-2023

COURSE TITLE

MSc. Dissertation

DISSERTATION TITLE Re-Myce

STUDENT NAMES

Ran An (MSc) Shengyao Zhang (MSc) Chuheng Tan (MArch) Haipeng Zhong (MArch)

DECLARATION

“I certify that this piece of work is entirely my/our and that my quotation or paraphrase from the published or unpublished work of other is duly acknowledged.”

SIGNATURE OF THE STUDENT: Ran An

Shengyao Zhang

DATE

22 September 2023 Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 2

Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 3

ACKNOWLEDGEMENT We would like to thank all the people who, in one way or another, have contributed their knowledge and experience to this work.

The great support, assistance and critique havehelped us commit ourselves to the fulfilment of this project. Firstand foremost, we would like to express our gratitude to our coursedirectors, Michael Weinstock, for his kind supervision, support and valuable guidance throughout the pursuance of this work. Many thanks to course director Dr. Elif Erdine Dr. Milad Shawkatbakhsh, course tutors Felipe Oeyen, Lorenzo Santelli, Fun Yuen and Paris Nikitids for their constant support and commitment throughout our EmTech course. Their experience and assistance has greatly helped us to further our knowledge, skill and understanding in the field of architecture.

We would also like to thank our M.Sc team members Ran An and Shengyao Zhang for their contributions to the research.

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CONTENTS

01. INTRODUCTION

01

02. RESEARCH DOMAIN

03

2.1 Context: Malong district,Qujing city, Yunnan province

04

2.2 Landslide problem

15

2.3 Vernacular building

18

2.4 Landslide damage to buildings

26

2.5 Landslide impact resistance structure strategy

29

2.5.1 Rigid and flexible protection 2.5.2 Sandwich protective envelope

29 30

2.7 Mycelium-bound composites

31

2.8 Local agriculture industry

35

2.9 Case study

36

03. METHOD

39

04. RESEARCH DEVELOPMENT

43

4.1 Landslide prediction

45

4.2 Urban planning

47

05. DESIGN DEVELOPMENT 5.1 Regional Planning

5.1.1 Spatial distribution 5.1.2 Cellular automata algorithm 5.1.3 Cellular automata algorithm rule 1 5.1.4 Genetic algorithm 5.1.5 Genetic Algorithm Selection 5.1.6 Sequential Cellular Automata Simulation 5.1.7 Genetic Algorithm II 5.1.8 Genetic Algorithm Selection II 5.1.9 Reorganization Grids

Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong

5.2 Morphology Design 5.2.1 Initial data from regional planning 5.2.2 Grids clustering 5.2.3 Space characteristics and relationship 5.2.4 Space and building generation 5.2.5 Final floor plan and morphology library 5.2.6 Method of cluster to morphology 5.2.7 Evolutionary Algorithm set-up 5.2.8 Evolutionary Algorithm result 5.2.9 Final floor plan and morphology 5.2.10 Master plan

5.3 Structural System 5.3.1 Mycelium composite 5.3.2 Sandwich structure 5.3.3 Sandwich components physical experiment 5.3.4 Landslide resistance structure design principles 5.3.5 Structure principles 5.3.6 Finite element analysis and Force Flow Lines 5.3.7 Primitive Geomotry and Rationaliztion 5.3.8 Final Facade Generation 5.3.9 Rigidity Test Under Landslide Simulation to Define Gene Domain 5.3.10 Flexibility test under Landslide simulation to define gene domain 5.3.11 Structure optimization (Evolutionary algorithm set-up) 5.3.12 Optimization result(Evolutionary algorithm result ) 5.3.13 Landslide simulation 5.3.14 Building generation process 5.3.15 Protective sandwich envelope detail 5.3.16 Structure detail

66 68 69 70 71 72 73 74 75 76 77 79 81 82 83 84 85 86 87 88 89 90 92 93 94 96 97 98

53 55 57 58 59 60 61 62 63 64 65

5.4 Paradigm Expansion

99

5.5 Rendering

106

06. LIMITATIONS AND CONCLUSION

111

07. BIBLIOGRAPHY

112

ABSTRACT This project is about landslide-responsive design in the Yunnan mountainous region, which expands from urban planning strategy to a mycelium biocomposite structural system.

Buildings on slopes in mountainous areas are prone to damage due to the erosion of debris flows, leading to serious loss of life and property. The current landslide resistance structure strategy can be summarized as rigid protection and flexible protection.

Rigid protective structural materials rely on overall stiffness to resist dynamic forces; flexible protective structural materials are lightweight and cushioned, distributing forces through their deformability. However, the erosion of the building structure by landslide is a nonlinear dynamics problem under the action of complex impact loads, the integrated materials and structure systems driven by dynamic behaviour under landslide flow are still a difficult problem to be studied and solved urgently.

Our investigation is anchored in the Malong district of Yunnan, China, an isolated area grappling with poverty and recurring landslides. At the city planning level, we aim to deploy computational methods to gauge risk and refine prevailing rural planning, weaving urban designs that can potentially divert or diminish landslide impact. Shifting to the architectural realm, our objective is to unearth sustainable and eco-resilient local materials. With these, we intend to devise a structural system resistant to landslides, suitable for local dwelling designs and construction. In this endeavor, we've introduced a sandwich panel concept where timber ensures substantial external defense, while the inner mycelium composite enhances both the structure's protective and strength attributes.

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01. INTRODUCTION This thesis delves into the profound effects of landslides on infrastructure and the environment, primarily in the context of Malong County, Yunnan Province. A region marked by its unstable geological and climatic conditions, Yunnan finds itself at the intersection of the Himalayan volcanic earthquake belt and a series of escalating geological disruptions attributed to climate change(Xiwen and Walker 1986). These conditions make landslides an increasingly frequent and devastating threat, endangering both the region's architectural stability and its socio-economic fabric(Sun et al. 2021).

Initiating with an in-depth examination of landslide hazards, the study explores the origins, classifications, and potential ramifications of these geological disturbances.

Particular emphasis is laid on assessing the impact of landslides on reinforced concrete structures, scrutinizing the varied damage levels, energy changes, and the principles of structural design essential for combatting such disasters, namely rigid and flexible protection(Zhao 2021).

Adopting an urban strategy, an extensive phase of urban planning was executed, focusing on gauging the region's vulnerability to landslides through climatic and geological data. With the aid of the Houdini heightfield erode system, predictions of severe landslide events were formulated, facilitating the classification of terrains into high, medium, and low-risk sectors. Amidst this backdrop, the study identified challenges like inadequate housing, ineffective drainage systems, and an under-skilled workforce. Concurrently, the government's rural development agenda emphasizes facets like housing development, agricultural expansion, educational facilities, aquaculture, industrialization, and tourism.

Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 01

Expanding the urban planning horizon, the research articulates a comprehensive strategy, embedding a precise evaluation of landslide susceptibility based on climatic and geological data.

The Houdini heightfield erode system serves as a pivotal tool in this phase. Regional planning then harnesses Cellular Automata to craft an urban design that seamlessly integrates the region's residential and economic needs, culminating in an architectural blueprint emphasizing the dual protection paradigm.

Zooming into regional design, Cellular Automata plays a pivotal role in formulating an urban layout that effectively diverts landslides while catering to the population's demands.

This approach entails the definition of governing rules and search parameters to optimize spatial distribution, further dissecting these spaces for varied functionalities. The study then transitions into residential building design, initiating with an analysis of space adjacency. By correlating the attributes of various spaces with distinct rooms, a coherent adjacency matrix is formed, paving the way for optimized building clusters.

A significant pivot in the study then revolves around the innovative integration of composite materials and timber frameworks. This is where the transformative potential of mycelium-based composite material is spotlighted.

Post high-temperature processing, this material emerges as a formidable cushioning solution, standing as an environmental-friendly material. Yunnan's mushroom cultivation landscape underscores its value, significantly curtailing the logistics involved in material procurement.

In culmination, the research molds a composite framework designed to simulate the intricate dynamics between structures and landslides. This paves the way for datadriven decisions regarding sandwich panel configurations based on landslide vulnerability. Collectively, the insights and solutions presented in this thesis hold the potential to steer Yunnan towards a more landslide-resilient future.

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02. RESEARCH DOMAIN In the literature review, we explored Yunnan's unique attributes, from its climate and economy to its geophysical nuances. Using Geographic Information System(GIS), we assessed land-use in landslide-prone areas, prioritizing safety and sustainability.

Our analysis spotlighted structural strategies for landslide resilience, namely Rigid and Flexible Protection. Furthermore, we studied the potential of mycelium biocomposite as an ecofriendly cushion in construction, especially within sandwich panels. Together, this review harmoniously blends Yunnan's distinct features with modern architectural insights, charting a course for constructing buildings that withstand landslides while complementing Yunnan's environmental and urban landscape.

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

2.1.1 Yunnan

Site: Malong District, Qujing City, Yunnan Province, China

Digital Elevation Model (DEM)

China Administrative Divisions​

Figure 2.1.1Site location and China Digital Elevation Model (DEM)

The research commences in Yunnan Province, China, known as the “South of the Clouds”. This province locates in the southwestern part of China, which topography is ranging from the world’s deepest valley to the highest peaks in the Himalayas (Xiwen and Walker 1986). Our specific site for investigation is situated in the Malong District, Qujing City, the northeastern part of Yunnan province (Figure 2.1.1).

Yunnan’s varied terrain, transitioning from the alpine mountains in the north to the subtropical rainforest in the south, creates a myriad of microclimates. These unique microclimates and have a pronounced influence on the province’s abundant plant and animal life, the rich cultures of ethnic groups, and the varied agricultural practices in this region(Sun et al. 2021). Yunnan is home to more than seven ethnic minorities, each possessing its own distinct culture, language, and way of life. These diverse groups have crafted fascinating traditions, architectural styles, and agricultural practices that contribute to the rich tapestry of the region's cultural and physical landscape(Yang 2016).

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

2.1.2 Malong District Overview

Figure 2.1.2 Yunnan climate

Figure 2.1.3 Temperature anomaly and precipitation changing

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

2.1.3 Climate of Malong District

Figure 2.1.4 Bioclimatic stratification prediction

Yunnan’s climate has a subtropical highland variety character, with average temperature ranging from 8°C to 22°C. The province experiences an annual average rainfall of about 1100 millimeters. The average annual length of rainy days ranges from 80 days to 180 days, concentrated primarily during the monsoon season(Shi and Chen 2018) (Figure 2.1.2).

Between 1961 and 2011, Yunnan observed a noticeable increase in temperature anomalies and annual precipitation. These emerging unstable climatic trends intensify the province's environmental challenges, particularly the frequency and severity of droughts and flash floods (Shi and Chen 2018)(Figure 2.1.3). By 2050, some studies suggest a significant shift in Yunnan's bioclimatic stratification (Zomer et al. 2015). The mean elevation of these zones is expected to ascend by an average of 269 m. This shift would expand warmer zones, while colder, higher elevation zones would likely shrink. The damage caused by these changes not only poses risks to the bioclimatic zones, vegetation types, and habitats currently present in the region, but also has the potential to significantly alter Yunnan's landscape, biodiversity, and overall livability. Additionally, it can lead to an increased occurrence of environmental disasters such as floods, landslides, and collapses. It is important to address and mitigate these risks to ensure the long-term sustainability and resilience of the region(Zomer et al. 2015) (Figure 2.1.4).

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

2.1.4 Disaster Statistics to Gauge Vulnerability to Landslides

Site location

Site: Malong District, Qujing City, Yunnan Province

Yunnan Digital Elevation Model (DEM)

Natural disaster types and distribution

Figure 2.1.5 Yunnan elevation and disasters

Seismic intensity

Other disasters

Figure 2.1.6 Malong district disaster evaluation (2000-2020)

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Destroyed houses count

2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

Malong district is affiliated to the eastern part of Yunnan Province, between Kunming and Qilin District of Qujing City. It borders Qilin District and Zhanyi County in the east and northeast, Luliang County and Yiliang County in the south, and Yuming and Xun in the west and northwest. This expansive district, spanning 1614 km2, is home to near 210,000 people (Figure.2.1.5). There were Yi, Bai, Hui, Yao and Buyi ethnic groups living in Malong district. Malong district is located at east longitude 103 ° 16 '- 103 ° 45', north latitude25 ° 08 '- 25 ° 37', and the average sea level is 2050 meters, and the annual average temperature is 13.6 °C. There are 5 districts and 5 towns in Malong Subdistrict of Qujing: Tongquan Subdistrict ( 通泉街道 ), Wangjiazhuang Subdistrict ( 王家庄街道 ), Jiuxian Subdistrict ( 旧县街道 ), Zhang'andun Subdistrict ( 张安屯街道 ), Jitoucun Subdistrict ( 鸡头村街道 ), Maguohe Town( 马过河镇 ), Maming Town( 马鸣乡 ), Yuewang Town( 月望乡 ), Nazhang Town( 纳章镇 )and Dazhuang Town( 大庄乡 ). (‘Malong District Overview: Travel Information of Malong District, Weather, Climate, History, Administrative Division, Tourism, Landmarks, History & Culture – Yunnan Exploration: Yunnan Travel, Yunnan Trip, Yunnan Tours 2020/2021’ n.d..

Malong district belongs to the subtropical plateau monsoon type dry winter and summer wet climate zone. It has the characteristics of no cold in winter, no heat in summer, warm and dry in spring, and cool and humid in autumn.The annual average temperature is 14.7°C, the annual rainfall is 900-1000 mm, the frost-free period is 249 days, the annual sunshine hours are 2442.5 hours, and the annual solar radiation is 125.2 kcal/cm². (The Weather Channel China_https://weather.com/en-GB/ weather).

In terms of environmental challenges, Malong District contends with an array of severe weather conditions, such as rainstorms, hail, frost, ad disruptive floods.

Landslides, however, stand out as the most frequent and disruptive occurrences, significantly affecting the daily lives and livelihoods of the local population. Over the past two decades, from 2000 to 2020, the district has identified 82 disaster-prone areas, including 76 susceptible to collapse and 6 prone to landslides. Additionally, there are 25 seismic intensity regions registering over 5 on the Richter scale. The disasters have resulted in significant damage to the built environment, with over 300 houses destroyed in milder events, and up to 500 in the most severe instances. (‘Malong District Overview: Travel Information of Malong District, Weather, Climate, History, Administrative Division, Tourism, Landmarks, History & Culture – Yunnan Exploration: Yunnan Travel, Yunnan Trip, Yunnan Tours 2020/2021’ n.d.)

(Figure.2.1.6).

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

2.1.5 Land Use Evaluation and Site Selection

Figure 2.1.7 Land Use Evaluation Definition

In the pursuit of selecting a suitable site in Malong with both significant development potential and a higher risk of landslides, we've adopted a land use evaluation strategy. This strategy consists of two main parts.

1. Evaluation of Resource and Environmental Carrying Capacity: This assessment considers the maximum extent of human activities such as agricultural production and urban construction that can be supported by the local resources and environment. Factors such as the current developmental stage, economic and technological standards, and existing modes of production and lifestyle are taken into account.

2. Evaluation of Suitability for National Spatial Development: This assessment estimates the suitability of a specific geographic area for human activities like agricultural production and urban construction, always prioritizing the health of the ecosystem. It also considers location conditions and the status of resources and the environment.

The evaluation is based on regulations from the Chinese government. The aim is to analyze the conditions of regional resources and environmental endowment, to identify problems and risks associated with land space development and utilization, and to pinpoint crucial and ecologically sensitive spaces for ecosystem service functions. This process defines the maximum reasonable scale and suitable spaces for agricultural production and urban construction, providing a basis for improving the layout of the main functional areas, outlining the ecological protection red line, designating permanent basic farmland and urban development boundaries, optimizing the pattern of land space development and protection, and scientifically preparing for land spatial planning(Tinghai Wu et al. 2019).

Our comprehensive evaluation encompasses four primary areas: 1.

Land resource evaluation for agricultural production 2.

Land resource evaluation for building construction 3.

Climate evaluation for urban construction 4.

Disaster statistics to gauge vulnerability to landslides This strategy assures that our decisions regarding land development in Malong are both informed and sustainable.

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

step 1: Landuse distribution

(1)Land resources evaluation for agricultural production

=

+

step 2: Agricultural land

(1) Evaluation Method: The condition for agricultural cultivation [Agricultural Cultivation Condition] is a function of [Slope] and [Soil Texture] ([Agricultural Cultivation Condition] = f ([Slope], [Soil Texture])).

This refers to the degree of suitability of land resources for agricultural production, which requires satisfying certain conditions such as slope and soil texture. Areas covered by rivers, lakes, and reservoirs are excluded during this evaluation.

(2) Evaluation Steps: Step 1: Spatial Data Standardization: Using the National Geodetic Coordinate System of 2000 (CGCS2000) as a basis, all kinds of spatial data projection coordinate systems are unified, forming a seamless connection and consistent boundary of regional spatial data series. Available agricultural land from the land use planning is extracted.

Step 2: Slope Element Analysis: Utilizing Digital Elevation Model (DEM), the terrain slope is calculated and divided into five levels according to ≤2°, 26°, 615°, 15~25°, >25°. These are respectively labeled as flatland, flat slope, gentle slope, moderately steep slope, and steep slope, generating a slope classification map.

Step 3: Land Resource Evaluation and Classification: Based on the slope classification results and combined with soil texture, The results of the evaluation of the suitability of agricultural production are categorized into five levels: suitable, more suitable, generally suitable, less suitable and unsuitable. The evaluation should take into account the current situation of agricultural development, and for areas where food security is very important, the degree of agricultural space suitability can be given some flexibility. Areas where the soil's silt content is ≥80%, the agricultural land resources are taken directly at the lowest level; areas where the silt content is between 60% and <80%, the slope classification is lowered by one level to be used as the agricultural land resource level (Figure 2.1.8).

+

step 3: slope grading

Figure 2.1.8 Land resources evaluation for agricultural production

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

step 1: Landuse distribution

(2)Land resources evaluation for building construction

=

+

step 2: Slope grading

Figure 2.1.9 Land resources evaluation for building construction

(1) Evaluation Method: The condition for urban construction [Urban Construction Condition] is a function of [Slope], [Elevation], and [Terrain Roughness] ([Urban Construction Condition] = f ([Slope], [Elevation], [Terrain Roughness])). This refers to the degree of suitability of land resources for urban construction, which requires satisfying certain conditions such as slope and elevation. For regions with severe terrain undulations (such as the southwest region), the terrain roughness index should also be considered.

(2) Evaluation Steps: Step 1: Spatial Data Standardization: Using the National Geodetic Coordinate System of 2000 (CGCS2000) as a basis, all kinds of spatial data projection coordinate systems are unified, forming a seamless connection and consistent boundary of regional spatial data series. Available land for construction from the land use planning is extracted.

Step 2: Slope Element Analysis: Utilizing Digital Elevation Model (DEM), the terrain slope is calculated and generally classified according to ≤3°, 3~8°, 8~15°, 15~25°, >25°, generating a slope classification map.

Step 3: Land Resource Evaluation and Classification: Based on the slope classification results and combined with elevation, the conditions for urban construction are divided into five levels: Very High, High, Medium, Low, Very low. For areas where the elevation is ≥5000m, the urban land resource level is taken directly at the lowest level; for areas where the elevation is between 3500~5000m, the slope classification is lowered by one level to be used as the urban land resource level.

Step 4: Evaluation Result Adjustment for Complex Terrain Regions: In regions with severe terrain undulations, the terrain roughness index is further used to correct the urban land resource level. The terrain roughness is calculated using the DEM neighbourhood analysis function, with a neighbourhood range usually around 20 hectares (e.g., for a 50m×50m grid, a 9×9 neighbourhood is recommended; for a 30m×30m grid, a 15×15 neighbourhood is recommended). For areas with terrain roughness >200m, the evaluation result is lowered by two levels as the urban land resource level; for terrain roughness between 100~200m, the evaluation result is lowered by one level as the urban land resource level. Adjustments can be made based on the terrain characteristics of each region (Figure 2.1.9).

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

step 1: Landuse distribution

(3)Climate evaluation for urban construction

It reflects the relative ability of the atmospheric environment to accommodate major pollutants through the atmospheric environmental capacity index under the conditions of being able to maintain ecological balance and not exceeding the threshold value required by human health; Besides, it is the relative ability of the water environment to accommodate major pollutants under the conditions of being able to maintain ecological balance and not exceeding the threshold value required by human health

+

=

step 2: River level

1) Evaluation Method: The [Urban Construction Environmental Condition] is a function of [Atmospheric Environmental Capacity] and [Water Environmental Capacity] ([Urban Construction Environmental Condition] = f ([Atmospheric Environmental Capacity], [Water Environmental Capacity])). [Atmospheric Environmental Capacity] is reflected by an index that represents the relative ability of the atmospheric environment to accommodate main pollutants under conditions that maintain ecological balance and do not exceed human health thresholds.

[Water Environmental Capacity] refers to the relative ability of the water environment to accommodate major pollutants under conditions that maintain ecological balance and do not exceed human health thresholds.

(2) Evaluation Steps: Step 1: Calculation of atmospheric and water environmental capacity: The basic evaluation units are delineated by administrative units or watershed partitions. The atmospheric and water environmental capacity is calculated using the above method. Taking full advantage of related environmental capacity research experiences and according to the distribution characteristics of the data, the indicators of atmospheric and water environmental capacity are divided into high, higher, average, lower, low levels Sbased on the intensity per unit area. The levels for atmospheric and water environmental capacity are determined based on the lower level of the evaluation results of each index. Finally, the atmospheric and water environmental capacity classification map is generated through spatial overlay of level distribution maps.

Step 2: Division of urban construction environmental condition levels: The relatively lower results among the two evaluation indicators of atmospheric environmental capacity and water environmental capacity are taken as the evaluation unit to divide the urban construction environmental condition levels. Accordingly, the urban construction environmental condition is divided from suitable to not suitable (Figure 2.1.10).

+

step 3: temperature and precipitation

Figure 2.1.10 Climate evaluation for urban construction Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 12

2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

(4)Disaster Statistics to gauge vulnerability to Landslides

Seismic intensity

Other disasters

Destroyed houses count

Figure 2.1.11 Malong district disaster evaluation (2000-2020)

(1) Evaluation Method: [Disaster Risk] = Max([Earthquake Risk], [Geological Disaster Susceptibility]) (2) Evaluation Steps: Step 1: Evaluation of earthquake risk: The highest level between active fault distance and peak ground acceleration is taken as the earthquake risk level. Areas with a statistical earthquake level greater than 5 are extracted.

Step 2: Geological disaster susceptibility: The high incidence areas of landslides and debris flows are statistically determined using main indicators such as slope, ruggedness, geomorphic type, engineering geological rock group, slope structural type, and historical development degree of geological disasters.

Step 3: Calculate the number of damaged houses, roads, and underground facilities (Figure.2.11).

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2.1 Context: Malong district, Qujing city, Yunnan province | 2.0 Research domain

(4)Final comprehensive evaluation for site selection

Site selection

Figure 2.1.12 Comprehensive evaluation for site selection

(1) Evaluation method: Step 1: Standardization of spatial data. Taking the 2000 national geodetic coordinate system (CGCS2000) as the basis, standardizing the projection coordinate system of various types of spatial data, forming a spatial data series of potentials and constraints that are seamlessly connected to the region and have consistent boundaries.

Step 2: The evaluation process begins with the removal of useless, invalid, or missing data. Afterwards, a weighted average calculation is performed on the GIS data with a weight distribution of 3:3:3:1. This is done to account for the various different criteria in the site selection process, ensuring that the evaluation is holistic and comprehensive [Comprehensive evaluation grade] = f (30% [LA]+30%[LB]+30%[CB]+10%[D]) LA = Land resource evaluation for agricultural production CB = Climate evaluation for urban construction

LB = Land resources evaluation for building construction D = Disaster Statistics to gauge vulnerability to Landslides

Guidance for this project: 1. The final evaluation results can support the delineation of the red line for ecological protection, permanent basic farmland and urban development boundary. The ecosystem service function is extremely important and ecologically sensitive areas are used as the spatial basis for the delineation of the ecological protection red line. Areas suitable for agricultural production and more suitable areas are used as preferred areas for permanent basic farmland; areas within areas suitable for agricultural production and unsuitable areas should be prioritized for returning farmland to forests and grassland.

Cultivated land in the less suitable and unsuitable zones for agricultural production should be prioritized in the delineation of urban development boundaries.

2. The final evaluation results can support the determination and decomposition of planning target indicators. The target indexes of arable land retention, scale of construction land and development intensity shall not exceed the maximum scale that can carry agricultural production and urban construction.

The comprehensive evaluation map is divided into five levels: Unsuitable, less suitable, generally suitable, suitable, and more suitable. Based on this evaluation, the site that exhibits both significant development potential and a higher risk of landslides is selected for further planning, as shown in Figure 2.1.12.

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2.2 Landslide Problem | 2.0 Research domain

2.2.1 Damage Assessment Level of danger Velocity Frequency

Rockfall Falls are sudden downward movements of rock or earth, detached from steep slopes or cliffs. They occur globally on steep slopes, including coastal areas and rocky river banks. They can be extremely rapid and life-threatening.

Level of danger Velocity Frequency

Debris Flows A form of rapid mass movement in which loose soil, rock and sometimes organic matter combine with water to form a slurry that flows downslope. Debris flows occur around the world and are prevalent in steep gullies and canyons. Can be rapid to extremely rapid (35 miles per hour or 56 km per hour).

Level of danger Velocity Frequency

Topple Forward rotation of soil or rock mass from a slope, common in volcanic areas and steep river banks. Speed varies from slow to rapid.

Level of danger Velocity Frequency

Lahars (Volcanic Debris Flows) Lahars are also known as volcanic mudflows.

Found in nearly all volcanic areas of the world.

Lahars can be very rapid (more than 35 miles per hour or 50 kilometers per hour)

Level of danger Velocity Frequency

Rotational Landslide Spoon-shaped landslide, curved upward rupture surface with rotational slide movement along a contouraligned axis. Occurs on slopes of 20-40 degrees. Speed ranges from very slow (less than 0.3 meters or 1 foot every 5 years) to moderately fast (1.5 meters or 5 feet per month) to rapid.

Level of danger Velocity Frequency

Debris Avalanche Debris avalanches are essentially large, extremely rapid, often open-slope flows formed when an unstable slope collapses and the resulting fragmented debris is rapidly transported away from the slope. Occur worldwide in steep terrain environments. Rapid to extremely rapid; such debris avalanches can travel close to 100 meters/sec.

Level of danger Velocity Frequency

Translational Landslide Translational landslides move outward on a flat surface without rotation. They can cover long distances on inclined surfaces, occurring along geologic discontinuities with loose soil or rocks.

They are widespread and vary in velocity from moderate (5 feet or 1.5 meters per day) to extremely rapid.

Level of danger Velocity Frequency

Earthflow The mass in an earthflow moves as a plastic or viscous flow with strong internal deformation. Earthflows occur worldwide in regions underlain by fine-grained soil or very weathered bedrock. Velocity of travel is slow to very rapid.

Level of danger Velocity Frequency

Lateral Spreads Lateral spreads occur on gentle slopes or flat terrain, typically when a stronger upper layer extends and shifts over a weaker layer below. known to occur where there are liquefiable soils. May be slow to moderate and sometimes rapid after certain triggering mechanisms, such as an earthquake.

Level of danger Velocity Frequency

Slow Earthflow (Creep) Creep is a slow earthflow characterized by the gradual, barely noticeable downward movement of soil or rock on slopes. It is a widespread and commonly observed type of landslide, often preceding faster and more destructive landslides. Typically, the movement is less than 1 meter (0.3 foot) per decade.

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2.2 Landslide Problem | 2.0 Research domain

2.2.2 Slope Protection Retaining Wall

Gabion Protection

Eco Bag Protection

Advantage Save material, Variety of shapes, easy construction, good earthquake resistance, no noise during construction

Advantage Strong integrity, water permeability, erosion resistance, and ecological suitability, it has a wide range of applications.

Advantage Strong stability, with water- and water-impermeable filtering function, conducive to rapid restoration of the ecosystem, easy and fast construction

Disadvantage Large amount of stone and easy to cause convex corners

Disadvantage Large amount of stone

Disadvantage Easy to age, regeneration of plant seeds in ecological bags.

Porous Structure Protection

Vegetation-type Ecological Concrete Protection

Geotechnical material planting protection

Advantage Various forms, and porous bricks with different shapes can be selected according to different needs.

Advantage Provide a substrate for plant growth, good erosion resistance, high slope porosity

Advantage Good soil fixation effect, strong erosion resistance, economic and environmental protection

Disadvantage Grade of side slope must not be too large.

Disadvantage Alkali reduction issues, strength and durability to be verified, reseal ability needs further verification

Disadvantage Weak anti-rainstorm ability

Slope Protection As landslides can have a significant effect on the economy and people's lives, it is necessary to protect slopes. In slope protection projects, what is generally used is ecological slope protection technology, which can also be divided into physical, biological and chemical slope protection. In slope biological protection, microbial induction, bio enzymes and biochar are often used to change the physicochemical properties of the slope soil matrix and promote plant growth (Choi et al. 2020).

Slope chemical protection is the use of chemical methods to improve slope soils. Polymers, lignin and geopolymers are often used as chemical protection materials to strengthen slopes and enhance nutrients in slope soils (Chibwe et al. 2017).

In slope protection projects, physical slope protection techniques are widely used, of which the main physical protection projects include geotechnical material composite planting protection, vegetation-type ecological concrete protection, porous structure protection, retaining wall protection, Ecological gabion protection and Eco bag protection. protection.) The first three require planting to reinforce the slope, while the last three use a barrier form of protection.

Mature slope protection techniques essentially involve the use of rigid or flexible protection methods, or a combination of both. These techniques provide guidance for the further landslide resistance buildings construction design.

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2.2 Landslide Problem | 2.0 Research domain

2.2.3 Landslide in Yunnan

Figure 2.2.1 Landslide types in Yunnan

Yunnan landslides occur frequently due to the unique topography and climate. There are twofold reasons behind the landslides in Yunnan: natural causes and human activities(‘Landslide Classification’ 2023; ‘Landslides and Mudslides|CDC’ 2020; He et al. 2015).

Natural causes of landslide include: 1.

Yunnan's rugged mountainous geography 2.

Unstable weather patterns, alternating between heavy rainfall and snowfall 3.

Saturation by rain water infiltration, snow melting, or glaciers melting 4.

Ground shaking caused by earthquakes, which can destabilize the slope directly Landslides are aggravated by human acivities: 1.

Unrestricted deforestation, cultivation forestry activities (logging), and construction for urbanization which change the amount of water infiltrating the soil.

2.

Blasting and mining 3.

Temporal variation in land use and land cover. Land degradation and extreme rainfall can increase the frequency of erosion and landslide phenomena

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2.3 Vernacular building | 2.0 Research domain

2.3.1 Rural and Colony Life

Figure 2.3.1 Malong district overview

Yunnan, locates on the southwestern border of China, has a long history of settlement and migration development. This rich history stems from its diverse natural environment, intricate ethnic composition, unique social development, and multi-faceted cultural characteristics. As a result of its socio-economic development being somewhat underdeveloped, and significant regional development differences, Yunnan primarily remains a province underpinned by a traditional subsistence agricultural economy. The cities and towns in Yunnan have never fully escaped from the primitive state of the village to the modern city. Most of its towns are rural in nature, maintaining strong economic, social, and cultural ties with the countryside. Rural architecture in Yunnan encompasses two main categories: residential and non-residential buildings. Residential buildings primarily serve the daily needs of the residents, with their spatial structure and division influenced by people's living behaviours. Non-residential buildings, particularly religious structures, cater to the spiritual and lifestyle requirements of the community. These buildings follow spatial designs dictated by religious practices. However, both types of buildings ultimately revolve around fulfilling the needs of daily life. It is common to find religious activities within residential buildings, while daily life activities can be observed within religious buildings (Gao 2008).

In Yunnan's Malong district, the towns predominantly exhibit the natural form of a village. As Lewis Mumford once stated, "The stable form of the village is a loose association woven together by numerous small population groups." The formation of the village as a cohesive entity is a result of spatial differentiation and aggregation. This differentiation of space is intricately linked to human behaviour and activities(Figure 2.3.1).

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Figure 2.3.2 Community behaviors space distribution

The spatial organization of the village reflects the cultural significance attributed to it by the people who inhabit it. Various elements such as people, crops, livestock, grass, trees, and spiritual beliefs are intricately connected to the specific spaces within the village.

The selected site from GIS final comprehensive evaluation is a landslide-affected village in the suburbs of Malong District, 5 kilometers away from the city centre. The population is near 5000 residents (Figure.2.3.1). The settlement space becomes a backdrop for social, economic, religious, and recreational activities. Each aspect of village life occupies a distinct space, which can be broadly categorized as follows: 1. Mountain and forest space: Hilltops hold significance as sacred places for rituals and religious practices.

2. Countryside space: Hill slopes are dedicated to farming activities, serving as the living space for both farmland and livestock.

3. Settlement space: Located at the foot of the hills, this space encompasses the areas where people reside and engage in social interactions.

These spaces, shaped by the behaviours and practices of the local inhabitants, form the essence of village life in the Malong district (Figure 2.3.2).

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Current landslide point Figure 2.3.3 Community life and agricultural distribution

Situated in a remote location, the site presents significant transportation hurdles. Narrow, winding paths and limited infrastructure make accessing the region both time-consuming and treacherous. This isolation, however, hasn't deterred the local inhabitants. Vast stretches of land are dedicated to agriculture, where a diverse range of crops flourish, painting a vibrant tapestry across the terrain. Yet, this agricultural bounty comes with its perils. The juxtaposition of farmlands against the mountains creates vulnerable zones. It's in these transitional areas that landslides are most frequent, posing a constant threat to both the livelihoods and the safety of the local community (Figure 2.3.3).

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2.3.2 Vernacular Dwelling

Figure 2.3.4 Vernacular dwelling

The main traditional residential dwellings in Malong are “courtyard residence”, which exhibit variations in size. Regardless of their size, these dwellings are characterized by orderly combinations. The "courtyard" is composed of "rooms" and "courtyards," and multiple "courtyard groups" form the overall dwelling. The houses may be connected or separated by corridors, and each house features a solid outer eave decoration. The houses are situated around a spacious central open courtyard, with doors and windows facing the inner courtyard and thick walls on the exterior. The function of the rooms can be divided into 3 types as “service room”(kitchen, bathroom, living room, storage), “side room”(the rooms for children, sisters, and servants), and “master room”(the rooms for master and mistress (Figure 2.3.3).

The overall layout demonstrates central symmetry, with the courtyard positioned in the middle. The roof structure of these dwellings follows the raised-beam style.

This architectural design allows for cool natural breezes and ample outdoor space during the summer while providing increased sunlight exposure and protection from cold winds in the winter. There are four main types of architecture found in the area: "Yikeyin" ( 一颗印 ), "Three workshops a screen wall" ( 三坊一照壁 ), "stilt building"( 干栏式建筑 ) and "Well-frame building" ( 井干式建筑 ).Each type has its own variations that have evolved to suit different environmental conditions(Gaochen Jiang 2001) (Figure 2.3.2).

The ‘Yikeyin' is considered to be one of the simplest, most basic and most functional of the traditional Yunnan houses. It is a simple house with a square and symmetrical shape. The entrance gate is set in the centre of the main façade, and the main house and the rooms are dominated by a hard hill roof with a long and short slope, with the long slope facing inwards and the short slope facing outwards. The overall architectural form of the house is very closed, centripetal and secure.

The “Three workshops a screen wall” is courtyard house, also known as the 'palace', 'patio' or 'courtyard' style, which is characterized by the fact that it is an enclosed, domestic or family home. The following characteristics are common to the courtyard style dwellings:1. the spatial layout of the courtyard 2. The traditional architectural concepts 3. The localization of wood construction techniques.

Stilt buildings are mainly small, simple buildings with wooden beams and pillars, but in some areas bamboo and wood are used instead of wood. The upper floor of a dry-pen dwelling is occupied by people, while the lower floor is a livestock pen or a miscellaneous room. This is one of the most distinctive features of dry-pen dwellings, where the ground floor is left empty for other uses and no one lives in it.

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2.3 Vernacular building | 2.0 Research domain

Figure 2.3.5 Vernacular building layout features

Well-frame buildings have a more primitive, rugged and simple method of construction than the dry-rail cabin, and has many similarities to the North American log cabin. The logs are roughly finished and joined into a rectangular frame, which is then rebuilt layer by layer into a wall, on top of which the roof is made.

The structure of some of the Stilt buildings and well-frame buildings can be called "Diaojiaolou" ( 吊 脚 楼 ). Deriving its name from the Chinese words “diaojiao” (meaning “hanging feet” and “lou” denoting “building”, the term "diaojiaolou" aptly translates to “hanging feet building”. This nomenclature alludes to its unique architectural design.

Diaojiaolou manifest as rectangular or square wooden structures characterized by their ganlan-style, signifying buildings elevated on wooden pillars or stilts. Typically rising to two or three stories, they feature prominent upper floors supported by robust wooden columns. At first glance, these stilts lend a seemingly precarious aspect to the structure. However, their foundational integrity is fortified with stone blocks, ensuring that even if a pillar is compromised or a block is displaced, the overall edifice remains unaffected. Their construction showcases the brilliance of traditional carpentry, often devoid of nails or rivets. Instead, the building's stability and form are dictated by meticulously crafted groove joints that seamlessly interlock beams and columns.

The ground level, predominantly composed of the foundational columns, usually lacks walled enclosures. This space primarily serves functional purposes like housing livestock or storing essentials like firewood and agricultural tools. Also the elevated bottom can be for ventilation and mitigating the impact of water flow. The upper floors, in contrast, cater to habitation. On occasion, the topmost layer may be repurposed as an additional storage area. These residential levels come equipped with balconies or verandas, serving as convenient spots for drying clothes or enjoying the outdoors. Affluent families occasionally invest in diaojiaolou variants equipped with attics or added extensions, providing additional room (Figure 2.3.4).

In synthesizing a solution for landslide protection, it is crucial to consider and adapt these traditional methodologies and styles, marrying them with innovative, sustainable materials and designs. This not only safeguards heritage but ensures the resilience and longevity of structures in this landslide-prone region.

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Figure 2.3.6 Living scene of "Diaojiaolou" in Yunnan

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Figure 2.3.7 Vernacular building material and shearing layer

The concept of “shearing layers”, introduced by architect Frank Duffy, recognizes that a building consists of multiple layers with different performances. In the context of traditional dwellings, we apply the concept of shearing layers to classify the material structure of these buildings. In this region, vernacular building materials encompass a range from timber to stone. The primary building materials include wood, tile, rammed earth, adobe wall, stone, brick, grass, sand, and bamboo. Each material forms a distinct "shear layer" with its own lifespan. For instance, grass used for interior purposes and other interior components have a lifespan of no more than 3 years before replacement. Bamboo, serving as space dividers and providing auxiliary and farming services, has a lifespan of 7-20 years. Load-bearing structures and exterior walls made of wood, stone, brick, and tile have a lifespan of over 20-30 years. But frequent natural disasters such as landslides, floods, pests, erosion, and earthquakes often result in varying degrees of damage to these building materials. It is essential to consider the resilience and durability of the shear layers when designing and constructing traditional dwellings in order to mitigate the impact of these disasters and ensure the longevity of the structures (Figure.2.3.5).

The foundation layer plays a critical role in anchoring the building to the ground, ensuring a stable base upon which the superstructure rests. Built using robust materials, this layer provides the primary resistance against any ground movement, such as that from landslides or seismic activity. The columns, often constructed from sturdy timber, rise from this foundation layer, serving as primary vertical supports and transferring loads from the floors above to the ground.

The middle layer, with its square plan brackets complexes, showcases the ingenuity of traditional architectural techniques. These brackets, typically crafted with intricate joinery details, are more than just functional elements; they often feature decorative motifs, reflecting the region's cultural and artistic sensibilities. The large cross-sectional dimensions of the beams ensure strength and stability. These beams span across columns, forming a rigid frame that both supports the upper layer and partitions the internal spaces. The lattice arrangement also allows for flexibility, enabling the structure to absorb and dissipate energy, thus enhancing its resistance to dynamic loads, a feature that is invaluable in regions prone to landslides.

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2.3 Vernacular building | 2.0 Research domain

Figure 2.3.8 Vernacular building timber structure form

The upper layer's sloping roof trusses are masterfully designed to provide protection and ventilation. The converging design ensures effective water runoff during heavy rainfall, preventing waterlogging and damage to the structure. Additionally, the slope facilitates natural ventilation, keeping the interiors cool in the summer months. The trusses, usually constructed from lightweight yet durable timber, support a covering of local materials, ranging from clay tiles to thatch, depending on the specific architectural style and availability of materials.

However, despite the architectural wisdom evident in these vernacular buildings, they remain susceptible to the damaging forces of landslides. The very nature of landslides – a rapid downward movement of large masses of earth – means that even the most robust traditional structures can be overwhelmed by their sheer force.

Therefore, while acknowledging the merits of traditional design, there is a pressing need to consider modern interventions. Local materials, although sustainable and culturally significant, may need to be supplemented or replaced by more resilient alternatives. Moreover, incorporating contemporary construction methods that enhance the foundation's depth or improve the structure's lateral resistance can offer increased protection against the destabilizing effects of landslides. Combining traditional knowledge with modern engineering solutions may be the key to ensuring both the preservation of cultural heritage and the safety of inhabitants in this landslide-prone region (Figure 2.3.6).

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2.4 Landslide Damage to buildings | 2.0 Research domain

2.4.1 Damage Pattern Analysis

In this section, we studied two modes of damage caused by landslides to buildings. We studied how landslides can damage buildings under each mode, the varying parts of buildings that are affected by the damage, and the impact of landslides at different levels. We also analyzed the types and extent of damage that landslides can inflict on reinforced concrete (RC) structures. Finally, we presented two common methods for buildings to resist landslides and provided a structural analysis of these defensive measures.

Figure 2.4.1 Geological Subsidence (indirect impact)

According to the ways in which landslides affect buildings, they can be classified into direct impacts and indirect impacts.

(1) Indirect impacts Indirect impacts refer to the effects of landslides on the surrounding environment and foundation, which subsequently affect the buildings indirectly. Landslides can alter the topography and trigger geological hazards such as soil erosion, settlement, or soil liquefaction. These indirect impacts can indirectly affect the stability and safety of the buildings and may result in cracks in the walls and structural components.(Palmisano, Vitone, and Cotecchia 2018). The indirect impacts of landslides on buildings primarily result in the formation of cracks, which can be categorized into I. Architectural, damaging the appearance of the facade; II. Functional, influencing the utility of the structure; III. Structural, affecting the stability of the building. And the classification for recognizable damage on structures is differentiated into five levels: Very slight; Slight; Moderate; Severe; Very severe(Del Soldato et al. 2017) (Figure 2.4.1).

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2.4 Landslide Damage to buildings | 2.0 Research domain

(2) Direct impacts Direct impacts refer to the direct effects of landslides on the buildings themselves, resulting in structural damage or destruction. This includes the direct forces of impact, thrust, and compression exerted by landslides on the buildings. Direct impacts can lead to tilting, displacement, collapse, or partial damage to the buildings.

Due to the direct impacts of landslides, the damage caused to buildings can also be categorized into three levels(Figure.2.4.2): 1.Slight damage: This level of damage typically involves minor injuries, such as small cracks or localized displacement. The overall structure of the building is not significantly affected and can maintain relative stability and functionality.

2.Moderate damage: At this level, the building experiences more noticeable structural damage. There may be wider cracks, wall tilting, or partial collapse. The stability and functionality of the building are moderately affected.

3.Severe damage: This level of damage is the most severe, where the building may undergo significant structural collapse, complete collapse, or complete loss of stability. In such cases, the building may be rendered unusable and require reconstruction or extensive repairs.

Figure 2.4.2 The direct impact of rock and slurry on construction

2.4.2 Reinforced Concrete(RC) Building Damage Analysis

With the increasing income and raised safety awareness among residents in mountainous areas, people have higher expectations for housing. Masonry structures can no longer meet housing needs as they fall short in terms of safety and flexibility in spatial arrangement. As a result, frame structures, which offer higher safety and more adaptable spatial layouts, have gradually become the primary form of construction for houses in mountainous regions. Therefore, in this section, we will focus on analyzing the impact of landslides on RC frame buildings.

1. The damage to RC buildings varies according to different impact speed(Figure 2.4.3).

(1) Low impact level (low speed: 6m/s): Under low impact, RC buildings may show minor damage, such as small cracks or localized displacements. The overall structural stability of the building remains relatively intact, with no significant impact on functionality.

(2) Medium impact level (Medium speed: 8m/s): With a moderate impact, RC buildings may experience more noticeable structural damage. This could include wider cracks, wall tilting, or partial collapse. The stability and functionality of the building are moderately affected.

(3) High impact level (high speed: 10m/s): Under severe impact, RC buildings may undergo severe structural collapse, complete collapse, or total loss of stability. In such cases, the building may become uninhabitable and require reconstruction or extensive repairs。 Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 27

2.4 Landslide Damage to buildings | 2.0 Research domain

Figure 2.4.3 Reinforced concrete (RC) building damage analysis

2. Different angles have different impact Landslides can have varying impact angles on buildings, and studying the angles of impact is important to understand the potential damage caused. By altering the angle of impact that the structure receives from a landslide, it is possible to increase the critical failure velocity of frame structures. Notably, when the angle of impact falls within the range of 45-75 degrees, the extent of damage is relatively lower. Changing the angle of impact allows for a more favourable distribution of forces within the structure. When the angle is within the mentioned range, the load is spread more evenly across the framework, reducing the concentration of stress, and minimizing the potential for severe damage(Figure 2.4.4).

Figure 2.4.4 The angle of impact also change the level of damage

In this section, by studying the ways in which landslides can harm buildings, we can understand that the closer a building is to the source of a landslide, the higher the probability of it being directly affected by the landslide, although the area of direct impact is relatively small. Conversely, buildings located farther away from the landslide source are more likely to be indirectly affected by the landslide, with a relatively larger area of impact.

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2.5 Landslide impact resistance structure | 2.0 Research domain

2.5.1 Rigid and Flexible Protection

Figure 2.5.1 Rigid and flexible protection

In current landslide resistance construction studies, there are two main principles: the rigid protection, and flexible protection, Currently, the protective measures against landslide impact on housing structures can be divided into two main strategies: strengthening the building itself and installing barrier structures. For strengthening the building, measures include increasing column cross-sections, reinforcing the facing walls on the impact side, reducing floor heights, and decreasing the span between supports. However, the drawback of these measures is that they require altering the structure of the building, which can affect its functionality and usability. Additionally, directly exposing the building to the impact may compromise its safety. The first impact of a landslide is the most energetic, and survivability is greatly improved by resisting the first impact(Zhao 2021)(Figure 2.5.1).

For local buildings in Yunnan, the main structure should firstly be strengthened so that it can withstand the first impact; secondly, the cushion structure should be integrated into the whole architecture, so that when the landslide strikes, it can be utilized to consume the energy of the first impact so as to protect the main structure.

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2.5 Landslide impact resistance structure | 2.0 Research domain

2.5.2 Sandwich Protective Envelope

The proposed protection envelope explores the innovative integration of mycelium composite into a sandwich panel design inspired by the intrinsic properties of both timber and mycelium composite materials.

Traditional sandwich panels generally consist of two external, rigid sheets, usually fabricated from high-strength materials like metals or composites, adhesively bonded to a lightweight, low-density core material. This configuration maximises the panel's stiffness and bending strength while minimising weight.

Mycelium composite, derived from the vegetative part of fungi, has garnered considerable attention for its unique cushioning capacities, biodegradability, and renewability. However, its application in structural contexts has been limited due to its inherently low tensile and compressive strengths and its brittle nature. Nevertheless, these limitations can be mitigated through the sandwich panel configuration, which synergistically combines the strengths of timber and mycelium composite(Saez et al., 2021).

In this specific architecture, known as a "Mycelium-Timber ThreeLayer Sandwich Panel," timber sheets are the external layers, providing the necessary bending strength and rigidity. The central core comprises mycelium composite, contributing lightweight cushioning and insulation properties. The bonding between the layers could be achieved through a range of bio-adhesives, selected based on their compatibility with timber and mycelium and their environmental footprint.

Timber Mycelium Timber Figure 2.5.2 Mycelium-Timber sandwich panel (Saez et al., 2021)

The incorporation of mycelium composite as the core material enhances the bending and compressive properties of the sandwich panel. The natural flexibility of mycelium composite can effectively distribute stresses across the panel, particularly under bending and shear conditions. This is crucial for applications that balance structural rigidity and the ability to absorb and dissipate impact energy(Saez et al., 2021).

From a sustainability standpoint, using mycelium composite introduces a renewable, biodegradable element into the building envelope. Mycelium composites can be used to replace plastic and expanded polystyrene (EPS) in known studies (Aiduang et al. 2022; Peng et al. 2023).

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2.6 Mycelium-bound composites | 2.0 Research domain

2.6.1 The Feature of Mycelium

Figure.2.6.1 Diagrammatic representation of mushroom life cycle (Lull et al., 2005, p. 64)

Mycelium is the root network of fungi, which can digest plant or agricultural waste, use it as a substrate, grow continuously, form a dense network, and bond with the substrate to form a composite material. The new material, which combines filamentous fungi and agricultural leftover by-products, is called a mycelium composite (Kuribayashi et al. 2022).

Mycelium composites can be used to replace plastic and expanded polystyrene (EPS) in known studies (Aiduang et al. 2022; Peng et al. 2023), because of its good cushioning properties (López Nava et al. 2016). In (Cai et al. 2023) experiments, it was found that the energy dissipation coefficients of mycelium composites with rice straw as substrate could all be higher than 90%, indicating that mycelium composites are suitable for use as impactresistant materials, but they are also affected by the species of the substrate.

As a building material it also has good thermal and acoustic insulation performance (Jones et al. 2020; Aiduang et al. 2022).

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2.6 Mycelium-bound composites | 2.0 Research domain

2.6.2 Selection of Substrates in Mycelium Growing

Sawdust

Corn silk

Sugarcane bagasse

Cotton

Flax

Lavender straw

Rose flowers

Bamboo

Apple wood

Wheat straw

Hemp hurds

Miscanthus fibers

Hemp shives

Wood pulp

(Peng et al., 2023)

Yunnan local material

(Peng et al., 2023)

(Appels et al., 2019)

(Tacer-Caba et al., 2020)

(Angelova et al., 2021)

(Angelova et al., 2021)

Yunnan local material

(Attias et al., 2019)

(López Nava et al., 2016)

(Elsacker et al., 2019)

(Dias et al., 2021)

(Jones et al., 2017)

(Yang et al., 2017)

Beechwood sawdust

Chinese albizia

Coconut powder

Oat husks

Rapeseed cake

Vinewood chips

Rice straw

Coir pith

Corn straw

Cotton stalk

Rice hull

Shredded cardboard

Shredded newspaper

Soy silk fibers

(Schritt et al., 2021)

(Chan et al., 2021)

(Santos et al., 2021)

(Attias et al., 2019)

(Peng et al., 2023)

(Peng et al., 2023)

(Peng et al., 2023)

(Gou et al., 2021)

(Teixeira et al., 2018)

(Vašatko et al., 2022)

(Vašatko et al., 2022)

(Vašatko et al., 2022)

(Tacer-Caba et al., 2020) (Tacer-Caba et al., 2020)

Figure.2.6.2 Mycelium substrates study

Rice straw 0.35 μm

Bagasse 0.77 μm

Coir pith 0.69 μm

Sawdust 0.58 μm

Corn straw 0.55 μm

Different combinations of mycelium species and substrate species result in composites with different physical properties (Appels et al. 2019), The team studied the different research results available for mycelial substrate selection, from single substrates to mixed substrates, and found that mycelium growth performed best when sugarcane was used as the substrate (Peng et al. 2023) (Figure2.6.3). Simultaneously, in conjunction with an inquiry into the primary agricultural products prevalent in the Yunnan region and their byproducts, a determination was made to employ sugarcane waste, a significant local crop, as the primary substrate.

Figure 2.6.3 Mycelium diameters in different substrates (Peng et al., 2023, p. 82)

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2.6.3 Processing Method of Mycelium Composite

Boil the substrate for 30 minutes

Cooling substrates

Cut a big water bottle

Perforate

Scatter the seeds

Mix with substrates

Add more substrates and seeds

Fill the whole bottle

Seal the bottle with tape

Put all prepared bottle in a cool, ventilated place away from light.

Spray water everyday

20 days to harvest

Figure 2.6.4 Home grown mycelium process (Nongcun Xiaoye. “How to Grow Mashroom at Home - Bilibili.” bilibili, November 1, 2022)

In the relevant studies so far, the processing of mycelium composites also has different effects on the physical properties (Appels et al. 2019; Aiduang et al. 2022; Nussbaumer et al. 2023). However, the team will choose the approach that requires less equipment, with the aim of controlling the overall cost of producing the composite and trying to be user-friendly(Figure 2.6.4).

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2.6.4 Compare with Other Material

The main difference between mycelium composites and other lightweight materials is that it is completely degradable, and the waste can be used for composting. If it is not baked dry, it can grow itself indefinitely, making it a very environmentally friendly material; secondly, it is quite lightweight. It including lightweight substrates like rice hulls (59 kg/m3), offer comparable weight to conventional synthetic insulation foams, including heavier variants like pine shavings or oak sawdust, have densities lower or similar to typical wood products used in construction, such as plywood, softwood, and hardwood(Jones et al. 2020).

Mycelium Composites WO2018068456A1

In patent WO2018068456A1 shows that the compressive strength of mycelium composites is much higher than ordinary sintered bricks. More importantly, the mycelium substrate can produce spores, so that the mycelium can grow infinitely, and the waste mycelium composite can be composted and completely degraded (Peng et al. 2023). Based on the above information we know that mycelium can be used for packaging, transportation, construction filler and temporary construction materials. The material is readily available, cost-effective, and easy to work with, requiring simple operations without the need for complex equipment. This makes it easily understandable even for unskilled individuals.

Brencich, Antonio and Enrico Sterpi. “Compressive strength of solid clay brick masonry: calibration of experimental tests and theoretical issues.” (2006).

Advantages of the mycelium composites Environment

Construction

biodegradable

Light weight

suitable environment

Local material

Reduce carbon emissions

Affordability

Replacement of EPS

Infinite self-reproduction

Biomass production

Cushion material

Structure Compressive strength of brick

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2.7 Local agriculture industry | 2.0 Research domain

Figure 2.7.1 Agriculture productions in Yunnan

Yunnan province, with its varied climate and fertile soils, has a thriving agricultural sector that forms the backbone of its economy. The region is best known for its production of paddy, tea, sugar cane, bamboo, mushroom, flower, silkworm and coffee, etc. (Figure 2.7.1). The distribution of agriculture in Yunnan is not uniform, with different crops being cultivated in different areas. In the mountainous regions of northern Yunnan, tea is the primary crop, particularly the famous Pu’er tea.

In further south, in the subtropical zones, sugarcane and bamboo thrive. The cultivation of mushrooms, the most vital agriculture product in Yunnan, is scattered throughout the province, capitalizing on the diverse climate and rich biodiversity. Bamboo is also cultivated in areas with well-drained soil, typically on the slopes, valleys, and along the river banks. Yunnan’s paddy is also important for the local economy, the region’s terraced paddy fields are particularly notable and are often associated with the Hani and Yi ethnic groups(Yunnan Provincial Department of Agriculture and Rural Development, ed. Yunnan Agriculture Yearbook, 2022).

The most famous of these terraced landscapes are in Yuanyang County, where the stunningly intricate terraces are a testament to the profound agricultural wisdom of the local people and have been recognized as a UNESCO World Heritage Site. Yunnan's flower industry, centred mainly around the capital city of Kunming, known as the "Spring City," is thriving due to the city's year-round mild climate, which is ideal for flower growth. The city even hosts a large flower market, recognized as the largest in Asia. In recent years, coffee cultivation has expanded in the southwestern parts of the province, particularly in regions like Pu'er and Baoshan(Yunnan Provincial Department of Agriculture and Rural Development, ed. Yunnan Agriculture Yearbook, 2022).

In Malong County, Yunnan Province, where agriculture plays a crucial role in the local economy, significant amounts of agricultural waste such as bagasse and wood chips are generated. Traditionally, these wastes are disposed of through burning, resulting in environmental pollution and the release of harmful gases. However, due to their rich lignin content, these agricultural wastes can be effectively utilized as substrates for mushroom cultivation. By locally growing mushrooms using agricultural waste as a raw material, several benefits can be achieved. Firstly, it helps to reduce harmful emissions and environmental pollution associated with waste burning. Secondly, it creates a sustainable economic cycle by utilizing the waste as a valuable resource for mushroom production. This approach not only addresses waste management concerns but also contributes to the local economy and promotes sustainable agriculture practices in the region.

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2.8 Case study | 2.0 Research domain Drawing upon insights into Yunnan's landslide predicament, we consult architectural exemplars from Sri Lanka and Japan—locales notably afflicted by frequent landslides. These structures have successfully circumvented landslide damage through two distinct methodologies: firstly, by environmentally addressing the root causative factors of landslides, and secondly, by implementing supplementary impact-resistant encasements from an architectural perspective. Both design stratagems have been seminal in shaping our ensuing research.

Location: Sri Lanka Designer: Lowil Fred Espada In addressing hydro-geological hazards akin to those in Yunnan, the Ratnapura area of Sri Lanka implemented a comprehensive risk-mitigation program. This involved the construction of model residential and community structures equipped with erosion-resistant foundations and systems designed to cope with flooding, high winds, and landslides. The initiatives also included site-specific drainage solutions, soil stabilisation measures, and responsible well placement for preventing slope destabilisation.

Construction methodologies were particularly tailored to enhance structural resilience. Foundations were reinforced with concrete, and alternative materials like rubble masonry and clay mixes were employed for durability.

Special attention was given to minimising topographical disruptions, including geotechnical investigations, contour-aligned road planning, and engineered retaining walls. These measures are aimed at physical robustness and environmental conservation, evident from preserving natural vegetation and minimising excavation depths(Hewawasam 2005)(Figure 2.8.1).

Figure 2.8.1: Case 1(Hewawasam 2005)

Conclusion In this Sri Lankan case, we can see the general approach to the type of construction for landslide protection, i.e., the strengthening of slopes with traditional slope protection, which requires large quantities of concrete and other materials for pouring and deep excavation of slopes and building foundations. A considerable degree of material consumption and environmental damage can occur. Although they eventually used some local building materials, pouring concrete for the berms and foundations could not be avoided.

Location: Japan Designer: Irish. Mach In response to the Niigata-Chuetsu earthquake in 2004, architectural projects have been carried out to demonstrate "risk management" and "reconstruction activities." One such project is the "Landslide-proof Theatre and Exhibition Hall for Niigata," where the structure is anchored to the stable ground using anchorfoundations, and the access way is protected by a wall. The design of the shell structure was inspired by the shape of an eggshell, with angles that minimize the direct vertical impact of mountain landslide. The shell structure is divided into multiple buffering plates with different angles using calculus(Simoncsics 2006) (Figure 2.8.2).

Figure 2.8.2: Case 2 (Simoncsics, 2006)

Conclusion In this case, instead of focusing on the overall manual rectification of the slope, the emphasis is on the building itself, which is cleverly mitigated by the landslide but is still protected by a rigid structure, and the degree of protection continues to depend only on how thick the rigid material is added to the building.

However, the disadvantage of rigid protective structures is the wastage of materials, lack of environmental friendliness, and the indirect damage caused by the significant energy impact resulting from their rigid nature.

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RESEARCH DOMAIN CONCLUSION In the literature review, we delved deep into Yunnan’s multifaceted identity including the location, climate, agricultural industry, economic conditions.

Firstly, we utilize Geographic Information System (GIS) tool to conduct land use patterns, specifically focusing on agricultural and construction feasibilities within landslide-prone areas. The analysis provided invaluable insights into optimizing land use while ensuring safety and sustainability.

Second, through an exhaustive study, the research delineated the varying degrees and forms of damages buildings can sustain due to landslides.

This exploration resulted in the discernment of two principal strategies for constructing landslide-resistant structures: 1. Rigid Protection: Enhancing the structural elements like beams and columns to withstand the brute force of landslides. 2. Flexible Protection: Designing structures to dissipate the energy from landslides, thereby reducing potential damage.

Third, the research dive into mycelium biocomposite and sandwich panels.

When subjected to high-temperature baking, mycelium transforms into an effective cushioning agent. Furthermore, the integration of this biocomposite within sandwich panels highlighted its potential as an eco-friendly buffering material. Such panels not only align with the principles of flexible protection but also echo the sentiment of sustainability and eco-consciousness in construction.

Finally, we learned from the Sri Lankan and Japanese architectural cases about methods to avoid and protect against mudslides from both a site and environmental perspective and an architectural perspective. this research domain integrates an understanding of Yunnan's unique geographical, climatic, and socio-economic context with cutting-edge architectural and material science innovations. It presents a comprehensive roadmap to develop buildings that are both resilient to landslides and harmonious with Yunnan's environmental and urban tissue.

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03. METHOD This section showcases the methods and tools we employ during research, analysis, and design.

The methods used at different stages assist us in conducting effective analysis, obtaining experimental data, and providing guidance for the next steps of the design process.

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3.0 Method

3.1 Geographic Information System(GIS) In the site research phase, we analyzed local geospatial information, population distribution, satellite imagery, and geographic data. We compiled and synthesized these data and transformed them into visual images to analyze and summarize specific design locations. These findings serve as guidance for subsequent design processes. So that for the selection of a suitable site in Malong with both significant development potential and a higher risk of landslides, we've adopted a land use evaluation strategy by using ArcGIS(‘ArcGIS’ 2023).

ArcGIS provides a range of powerful tools and features for site surveys, enabling users to conduct detailed and comprehensive site analysis and evaluation. Firstly, ArcGIS offers robust spatial data management capabilities for integrating, organizing, and managing various types of site data. Users can import and process diverse geospatial data formats, including maps, satellite imagery, building layers, and terrain data. With ArcGIS's data management capabilities, users can efficiently organize and store large volumes of site data while ensuring data consistency and accuracy.

Secondly, ArcGIS provides powerful spatial analysis tools for site assessment and decision support. Users can utilize spatial analysis functions for site selection analysis, evaluating the potential and suitability of different sites by considering various factors such as transportation accessibility, land use, market demand, and more. Additionally, ArcGIS offers land use planning tools to analyze current land use conditions, develop optimal land use plans, and visualize them spatially.

Figure 3.1.1: Geographic Information System(GIS)

3.2 Finite Element Analysis FEA (Finite Element Analysis) is a numerical analysis method widely used in the field of architectural structural engineering to evaluate and predict the performance of architectural structures under various load conditions(‘Finite Element Method’ 2023). We conduct the FEA analysis by using Karamba3 which is a powerful FEA software plugin specifically developed for architectural structural analysis and design, providing a range of functionalities and tools.

FEA divides the architectural structure into small finite element units and applies mathematical models to simulate the behavior of the structure. It accurately calculates parameters such as stress, deformation, and vibration, providing critical design information.

Karamba3D is a finite element-based architectural structural analysis and design software plugin that integrates with modeling software such as Rhino or Grasshopper(‘Karamba3D’ n.d.). It offers a set of powerful features, including structural optimization, parametric design, and automated workflows, enabling to conduct structural analysis and design more efficiently.

Figure 3.2.1: Finite Element Analysis(FEA)

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3.0 Method

3.3 Rigid Body Dynamics Rigid Body Dynamics, often referred to as RBD, is the field of study and application focused on analyzing and understanding the motion and behavior of rigid bodies(‘Rigid Body Dynamics’ 2023). The Houdini Rigid Body solver is a powerful tool used in physics simulations to replicate the motion and collisions of objects with the characteristics of rigid and solid bodies. Unlike fluid simulations, cloth simulations, or soft bodies, the Rigid Body solver treats objects as hard and inflexible entities. It accurately models the dynamics of objects that do not deform under external forces, making it suitable for simulating materials such as metal, wood, or stone. Conducting the RBD experiment in Houdini, we simulated the landslide in Yunnan, and studied how landslide impact the building in that area. In the simulation, we set the buildings and the rocks from the landslide as rigid body objects. We can adjust parameters such as the velocity, mass to simulate different types and scales of collisions to analyze how landslide impact the building(Figure 3.3.1).

Figure 3.3.1 Rigid body dynamics

3.4 Evolutionary Multi-objective Optimization The multi-objective optimization genetic algorithm helps us achieve optimal solutions that align with multiple design objectives (Deb 2015). Unlike singleobjective optimization, the multi-objective optimization genetic algorithm offers more selection strategies to cater to different scenarios and target solutions. Through WallaceiX, an engine for multi-objective optimization genetic algorithms, integrated with Grasshopper, we can set up the entire optimization process, define gene ranges, set genetic rules, and mutation probabilities to optimize the phenotype((Showkatbakhsh and Makki, 2022).

By using the analysis tools provided by WallaceiX, we can evaluate the performance of the design phenotype and further optimize the gene ranges to achieve the design objectives. This combined approach enables us to better understand and explore the design space and find the best solutions that align with multiple objectives.

Figure 3.4.1 Pareto Front and SD lines from WallaceiX

3.5 Cellular Automata

Cellular automata is the computational method which can simulate the process of growth by describing a complex system by simple individuals following simple rules. Cells can take on a given finite number of cell states, which can change according to simple rules each cell executes in relation to its cell neighborhood. The connection to architecture is the ability of cellular automata to generate patterns, from organized patterns we might be able to suggest architectural forms. Cellular automata, viewed as a mathematical approach, differs from a traditional deterministic methods in that current results are the basis for the next set of results. This recursive replacement method continues until some state is achieved. Fractals and strange attractors are also created in a similar manner. Many digital methods in architecture are parametrically driven, an initial set of parameters is used to generate one result. If an alternative is desired, the parameters need to be modified and the generation is repeated anew. The difference between these two methods is that in parametric methods the results can be easily anticipated, while in recursive methods the outcome usually can not. This offers an interesting and rich platform from which to develop possible architectural patterns.（Krawczyk, 2002） Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 41

Figure 3.5.1 Cellular automata

3.0 Method

3.6 Space Adjacency The theoretical underpinning of space adjacency posits that spatial elements within a building are interconnected, forming an intricate communication structure that serves as the core of the design.

This conception aligns with computational methods of spatial organisation, where an algorithmic approach generates layouts based on evacuation plans and corridor structures. In such a framework, each room is an entity with its corridor, extending along one or more sides and directly attached to the main corridor. Rooms are added iteratively, adhering to functional requirements and algorithmic constraints, until no suitable space remains. This algorithmic method deploys quasi-evolutionary algorithms to evaluate solutions, usually considering metrics like the number or total area of rooms placed.

The conceptualisation of space as having its "personality" adds a nuanced layer to our understanding of space adjacency. Just as human personality reacts differently in different contexts, spaces exhibit varying "spatial characters" that influence their interaction with adjacent spaces. These spatial characters can be categorised into expressions resembling human behaviours, further divided into inner space interactions and environmental conditions.

Thus, the choice of adjacent spaces is not solely a question of functionality or algorithmic optimisation but is deeply influenced by these 'personalities,' adding complexity to the design process. Architects utilise these behavioural frameworks, often presented in tabulated formats, to make informed decisions regarding space adjacency, catering to functional needs while also considering each space's unique 'character'. (Hsu and Krawczyk, 2004)

(Hsu and Krawczyk, 2004)

Iteration: 100

Iteration: 300

Iteration: 600

Iteration: 900

3.7 Houdini Heightfield Erosion Houdini, developed by SideFX, is a powerful 3D animation software used extensively in the film, gaming, and VFX industries for procedural modeling, animation, and visual effects. One of the features it offers is the Heightfield system, which is specifically tailored for creating terrains.

The Heightfield system in Houdini allows users to generate terrains using a grid of values representing heights. It offers various tools to sculpt, modify, and erode these terrains, creating realistic and detailed landscapes. The erosion tools within the Heightfield allow users to simulate natural erosion caused by water flow and thermal processes, resulting in terrains that look realistic and believable. This makes the Heightfield system especially useful for simulating phenomena like landslides, as it can replicate the natural forces and effects that shape landscapes over time. In this project, the Houdini heightfield system was employed to create and manipulate terrain data in a procedural manner. Using its scalable and integrated toolset, we accurately simulated the landscape's topographical features and potential vulnerabilities. The system's procedural nature enabled flexible, non-destructive workflows, allowing for iterative terrain modifications and refinements. Furthermore, real-world data integration capabilities facilitated the creation of realistic terrains, while erosion and hydrology tools helped simulate natural processes, vital for predicting landslides and assessing environmental impacts. This was instrumental in accurately mapping high, medium, and low-risk areas for informed urban planning and architectural interventions(‘Heightfield Erosion 2023).

Figure 3.3.1: Houdini heightfield erosion Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 42

04. RESEARCH DEVELOPMENT In this chapter, we developed an initial phase of urban planning, a thorough assessment of the region's susceptibility to landslides was conducted using climate and geological data.

The Houdini heightfield erode system aided in predicting severe landslides, allowing us to categorize terrain into high, medium, and low-risk zones. Pressing issues included poor housing conditions, drainage problems, and a low-skilled labor force.

The government's rural development vision highlighted housing expansion, agriculture, education, aquaculture, and industrial facilities, along with tourism. Our preliminary plan accommodated these aspects with red zones for housing, yellow zones for protective measures, purple zones for industry, and blue nodes for infrastructure.

This planning are the guidance for the next step regional scale planning, which focuses on local residential housing expansion and planning to achieve holistic growth.

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Research development

Design development

Regional planning

Morphology

Structure system

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4.0 Research development

4.1 Landslide Prediction

Bird view

Plan view

Light

Serious

Extreme

Figure 4.1Landslide condition prediction for the site Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 45

4.0 Research development

Simulation parameters Precipitation Amount: 1500mm Density:0.05 Evaporation rate: 0.04 Thermal erosion Removal rate: 0.07 Grid bias: 0.1 Hydro erosion Removal rate:0.1 Grid bias:0 Debris Flow Spread speed: 10m/s Water absorption: 1.0 Expand radius: 5.0m Bedrock Erosion rate factor: 1 Max height: 0.5

In the initial phase of urban planning, it was imperative to root our approach in an understanding of the natural environment, and to anticipate challenges that could arise from it. Drawing upon the region's climatic and geological data, we collated information on factors that directly impact the region's susceptibility to landslides. This included studying the local annual rainfall patterns, thermal erosion effects, debris flow velocities, bedrock erosion rates, evaporation tendencies, and water erosion statistics. Such a comprehensive analysis aids in painting a clear picture of the region's vulnerability to natural disasters.

To better predict the most severe landslides that could potentially afflict the area, we employed the Houdini heightfield erosion system. This advanced simulation tool allowed us to model the terrain's response to various environmental factors.

By inputting the gathered data, the system generated scenarios showcasing how the landscape might evolve over time under extreme conditions.

Incorporating the Houdini heightfield erode system's predictions, we were able to delineate the terrain based on varying levels of landslide risks. This involved extracting zones that were categorized as high, medium, and low risk. Each risk category was determined by a combination of factors, such as the proximity to potential landslide origins, the slope of the terrain, and the underlying soil and rock types, among other factors.

The high-risk zones were areas with the most immediate and severe vulnerability to landslides, often characterized by steep slopes, loose soil, and frequently occurring erosional processes. Medium-risk zones, while not as critically exposed as the high-risk ones, still held significant vulnerability, especially during extreme weather events or rapid changes in environmental conditions. Low-risk zones were relatively stable, with minimal susceptibility to landslides, but still required consideration for potential long-term changes and safety precautions.

Segmenting the region into these risk zones was of paramount importance for the subsequent planning stages. High-risk areas were generally recommended to remain undeveloped or, if needed, to house structures that can withstand landslides, like retaining walls or diversion channels. Medium-risk areas required specific building strategies, incorporating robust foundation systems and erosion control measures. Meanwhile, the low-risk zones were the most suitable for more intensive development, although with continued monitoring and mitigation measures in place (Figure 4.1).

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4.0 Research development

4.2 Urban Planning

Figure 4.2 Current site context

In the present site map, a distinct highway bisects the valley, creating two separate settlements: Xia Village to one side and Zhong Village on the other. This division not only marks a geographic boundary but also signifies the differential utilization of resources and infrastructure between the two villages.

Xia Village is characterized predominantly by expansive farmlands, with fields stretching across significant portions of the landscape. This agricultural expanse suggests that the majority of Xia's residents rely heavily on farming, producing both staple and cash crops that likely serve as the primary source of livelihood for many.

While the Zhong Village appears to be more industrially oriented, as evidenced by its three major crop processing factories. Among these is a breeding farm, possibly specializing in poultry or livestock, and an aquaculture farm, indicating fish or other aquatic cultivation. The presence of these factories suggests that Zhong Village has a more diversified economy compared to Xia, with a production chain that extends from raw material cultivation right up to processing and potentially even distribution (Figure 4.2).

The presence of only a few factories and facilities across both villages implies a delicate balance between maintaining the traditional way of life and embracing modern industrial practices. It's crucial to note that these limited facilities play an essential role in sustaining the villages' infrastructure, enabling both Xia and Zhong to meet their basic needs and maintain a degree of economic activity.

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4.0 Research development

Figure 4.3 Landslide risky mapping

Overlaying the landslide risk level map onto our current site assessment, we obtain a comprehensive picture of the challenges and vulnerabilities of the area. The map distinctly categorizes regions into high, medium, and low-risk zones, each indicative of the potential threat posed by landslides to the corresponding areas (Figure 4.3 ) A deeper dive into the current context of the site unveils more about the living conditions and socio-economic status of its inhabitants. Demographically, the area's population is broken down into age groups, family sizes, and occupational distributions. Economically, income levels paint a picture of the residents' purchasing power and standard of living. This data is crucial for understanding the kind of solutions and interventions that would be most beneficial for the community.

Agriculturally, the main crops cultivated are catalogued along with their respective yields, shedding light on food security and potential export commodities. The expansive farmlands and their acreage further delineate the agricultural capacity and the dependency of the community on farming activities.

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4.0 Research development

Figure 4.4 Current economic and living conditions

However, a closer inspection reveals several pressing issues that need immediate attention. Firstly, housing conditions are far from ideal. Many residences appear to be in a state of disrepair, signaling the need for safer and more sustainable housing solutions. The prevalent poor drainage system, likely a contributor to landslide vulnerability, needs a comprehensive overhaul to prevent water logging and the associated risks.

The low skill level among the labor force also emerges as a concern. This not only affects productivity but also limits the avenues for economic diversification and growth. Efforts to enhance skill training can potentially elevate the living standards of the community (Figure 4.4).

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4.0 Research development

Figure 4.5 Design requirements

In addition to our initial observations and assessments, we delved into the government's vision for rural development to ensure our planning aligns with broader regional strategies. The government's roadmap for the area presents a blend of sustainable growth and infrastructural enhancement.

A salient feature of the government's rural development plan is the emphasis on housing expansion. With an increasing population and the present challenges surrounding housing conditions, there is a clear mandate to broaden the residential area. This expansion not only means increasing the number of homes but also ensuring they are built sustainably and resiliently, especially considering the landslide risks. Beyond housing, there's a highlighted need for diversified agricultural facilities, including establishing cattle sheds, chicken coops, and pigsties. In particular, Zhong village is prioritizing education with plans for more schools. Additionally, its water resources make it an ideal location for a new aquaculture factory, aiming to boost local jobs and the economy (Figure 4.5).

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4.0 Research development

Figure 4.6 initial planning

Furthermore, there's a push for more advanced facilities like agriculture processing factories. Such establishments can drastically change the economic landscape of the area by adding value to raw products locally, reducing transportation costs, and enhancing the market value of the region's produce. A proposed transit center, likely a hub for goods movement, can further streamline the supply chain, making the village a pivotal point in regional trade.

Tourism, often overlooked in rural development strategies, finds its place in the government's vision too. Tourist stations, possibly combined with cultural centers, can attract visitors, injecting the local economy with the revenue from tourism while showcasing the region's rich heritage and natural beauty.

In essence, the government's rural development plan paints a future of holistic growth for the region, where modern amenities intertwine with traditional values, ensuring progress without compromising the area's unique identity (Figure 4.6).

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4.0 Research development

Next step regional scale planning

Figure 4.7 urban planning strategy

From the gathered data and information above, we've mapped out a preliminary plan that aligns with both human needs and environmental constraints. The red zones are predominantly in safer areas, making them ideal for housing and community expansion. Contrastingly, yellow areas indicate regions at risk, suggesting the need for protective measures or even relocation of dwellings. The purple zones, currently hosting some factories, present opportunities for further industrial development. Meanwhile, the blue nodes, which we've designated as infrastructure nodes, encompass tourist and transit centers. These nodes, currently in nascent stages, will undergo further refinements based on environmental limitations and community needs. These nodes are strategically placed to interconnect the entire village, echoing existing pathways (Figure 4.7).

The next step in Msc face we will focus on the housing area expansion and planning.

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05. DESIGN DEVELOPMENT In this chapter, we developed an initial phase of urban planning, a thorough assessment of the region's susceptibility to landslides was conducted using climate and geological data.

The Houdini heightfield erode system aided in predicting severe landslides, allowing us to categorize terrain into high, medium, and low-risk zones. Pressing issues included poor housing conditions, drainage problems, and a low-skilled labor force.

The government's rural development vision highlighted housing expansion, agriculture, education, aquaculture, and industrial facilities, along with tourism. Our preliminary plan accommodated these aspects with red zones for housing, yellow zones for protective measures, purple zones for industry, and blue nodes for infrastructure.

This planning are the guidance for the next step regional scale planning, which focuses on local residential housing expansion and planning to achieve holistic growth.

Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 53

Research development

Design development

Regional planning

Morphology

Structure system

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5.1 REGIONAL PLANNING On a regional scale, our objective is to mitigate landslides through urban patterns focusing on two primary functions: residential buildings and public spaces. To achieve an appropriate spatial layout, we employ the Cellular Automata Algorithm. This algorithm offers discrete models of space and time, typically emphasizing the interactions of cells on uniform lattice grids. It's a valuable instrument for determining cell relationships and for creating spaces governed by specific rules.

Subsequently, we utilize the multi-objective optimization genetic algorithm, it refines and analyzes the results of the cellular automata. By setting multiple design objectives, it facilitates the reorganization of the urban tissue. Using this restructured urban tissue, we aim to reduce the impact of landslides on urban areas.

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Research development

Design development

Regional planning

Morphology

Structure system

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5.1 Regional planning | 5.0 Design development

5.1.1 Spatial Distribution

Figure 5.1.2: Current Building Layout

Building units Public units Path

Figure 5.1.1: Design Area

Figure 5.1.3: Proposed Spatial Distribution

The area 1 has 19464 square meters, in this area the current building layout may cause the potential domino effect when the landslides coming, also there is less public area for local residents. For reducing the landslide impact, building footprint should be kept within a reasonable range and increase the public area for local residents.The proposed spatial distribution shows the new layout we try to follow.

The spatial layout of such residential buildings interspersed with public green spaces allows for an integration of architecture and nature. In terms of mitigating the effects of landslides, it provides space to divert the landslide, reducing the potential impact of a secondary shock (the domino effect) caused by the initial impact on buildings. Moreover, it can accommodate population growth changes over the next 20-50 years and create shared farmlands, leading to economic benefits.

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5.1 Regional planning | 5.0 Design development

5.1.2 Cellular Automata Algorithm Cellular automata algorithm is the computational method which can simulate the process of growth by describing a complex system by simple individuals following simple rules.To achieve the proposed spatial layout, we employed the cellular automaton algorithm in this step, which offers the following advantages: 1.The entire area is divided using regular cells, facilitating calculation and generation.

2.It emphasizes the spatial relationship between individual cells.

3.By establishing rules, the algorithm determines whether the existence of a cell is reasonable and its relationship with neighboring cells.

4.It effectively controls the number of cells under various functions.

5.In urban layout, it allows for the organic growth and integration of cells with different functions, aligning with our proposed spatial distribution.

The grid around each building‘s cell should not be larger than 3 and should not be smaller than 1

v

In order to minimize the chain reaction of landslides on buildings, the density of building units should not be too high. And to maximize spatial connections between clusters, the density of building units should not be too small.

Subdivide the grid, and run a secondary CA for public space

v

The grid is subdivided in order to allow the public spaces to be interspersed among the architectural spaces as much as possible.

Using the shortest walk to define the path along the public. And preserving space for expansion for the next decade.

Definition of roads within clusters based on the grid.

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5.1.3 Celluar Automata Algorithm Rules

Figure 5.1.6 Rule I Gen.10

Figure 5.1.7 Rule I Gen.20

Figure 5.1.8 Rule I Gen.30

Figure 5.1.9 Rule I Gen.50

Figure 5.1.10 Rule II Gen.10

Figure 5.1.11 Rule II Gen.20

Figure 5.1.12 Rule II Gen.30

Figure 5.1.13 Rule II Gen.50

Figure 5.1.4 Searching range I

Figure 5.1.5 Searching range II

Through the analysis of the algorithm and anticipation of results, to achieve a reasonable architectural spatial layout while reserving space to divert the landslide, cells suitable for construction in this area can utilize two rules for algorithmic generation: 1.If two to three neighboring cells are alive, the current cell remains alive for the next generation.

2.If only two neighboring cells are present, the current cell remains alive for the next generation.

Considering the need to control the cells based on population requirements, these two rules examine either 8 surrounding cells or 4 surrounding cells respectively.

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5.1 Regional planning | 5.0 Design development

5.1.4 Evolutionary Algorithm Set-up After generating the cells of buildings using CA, the results need to be constrained by using an evolutionary algorithm due to the stochastic nature of the algorithm. This step optimises the objectives according to the needs of the population in the area and the number of impact points calculated from the water flow simulation lines, leading to a better use of the urban patterns to divert the landslide.

2D View

3D View

Figure 5.1.14 Fitness Criteria 1.Minimize the distance between cluster

2D View

3D View

Figure 5.1.15 Fitness Criteria 2.Minimize the hitting units

2D View

3D View

Figure 5.1.16 Fitness Criteria 3.The number of the units near to 210 Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 60

5.1 Regional planning | 5.0 Design development

5.1.5 Evolutionary Algorithm Selection

Figure 5.1.17 Pareto Front

Figure 5.1.18 Select a type contains 210 units

Figure 5.1.20 SD and PCP graphs

Figure 5.1.19 Select minimal hitting points in the risky area

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The pareto front shows the optimization result. And pick out the phenotypes which meet the population’s needs of around 70 families each family needs 75 square meters. Then rank them, and select the minimal hitting points in the risky area.

5.1 Regional planning | 5.0 Design development

5.1.6 Sequential Cellular Automata Simulation

Figure 5.1.21 Searching range I

Figure 5.1.23 Rule I Gen.10

Figure 5.1.24 Rule I Gen.20

Figure 5.1.25 Rule I Gen.30

Figure 5.1.26 Rule I Gen.50

Figure 5.1.27 Rule II Gen.10

Figure 5.1.28 Rule II Gen.20

Figure 5.1.29 Rule II Gen.30

Figure 5.1.30 Rule II Gen.50

Figure 5.1.22 Searching range II

After the initial processing through the Cellular Automata algorithm, the remaining cells are subjected to a second Cellular Automata algorithm to generate cells for public spaces.

To maximize the area of the public space, this simulation only considers the eight adjacent cells surrounding each cell.

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5.1.7 Evolutionary Algorithm II

In our secondary of multi-objective optimization using the evolutionary algorithm. Research has proven that these green spaces not only provide a recreational area for residents but also effectively mitigate the impact of landslides. Consequently, our optimization objective is to maximize the number of green space cells and ensure they closely encircle building cells, thereby reducing the distance between them and further enhancing the protective function of the green spaces.

Figure 5.1.31 Maximize the number of public units

Figure 5.1.32 Minimize the distance between units and surrounding residential units

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5.1.8 Evolutionary Algorithm Selection II

Figure 5.1.33 The Pareto Front

Building cells Public cells Empty space Figure 5.1.34 The Final Selection

Figure 5.1.35 SD Graph

Utilizing the cellular automata algorithm and evolutionary algorithm optimization, we've derived the final site phenotype. By integrating results from two simulations, we've achieved a new spatial distribution for the site. The specifics are: the site spans 19,464 square meters, consisting of 212 building cell units (around 5,300 square meters) and 754 public area cell units (roughly 4,712 square meters). While accommodating the regional population's needs, the design strategically minimizes intersections between building units and the simulated landslide runoff paths, aiming to mitigate potential landslide damage to the urban layout.

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5.1 Regional planning | 5.0 Design development

5.1.9 Reorganization Grids

Figure 5.1.36 rainwater runoff lines and contour lines

Figure 5.1.37 generate new grid with boundary

To more effectively divert landslides, and with the architectural cells set, we restructured the grid to ensure the public areas align better with the topography. By using rainwater runoff lines and contour lines.

Using rainwater runoff paths and contour lines, we developed two alternating sets of lines in the UV orientation to closely match the digital model of the mountainous landscape.

Figure 5.1.38 remap the points

Take the public cells generated by the second step of the cellular automata algorithm as sampling points and map them onto the new 3D grid.

Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 65

Figure 5.1.39 new public grid

Within the updated grid, select grids with more than three mapped sampling points to serve as the new public area grids.

5.2 MORPHOLOGY DESIGN The data gleaned from this aspect of regional planning is principally aimed at the genesis and distribution of built structures. Initial challenges encompass morphological location, scalar dimensions, and generative logic. Firstly, building dimensions are ascertained from clustering parameters, which are controlled by manipulating the quantity and capacity of k-means clusters on the site. Secondly, given that the prevailing morphology consists predominantly of residential units, our approach commences with an analysis of demographic metrics and building capacities. This facilitates an exploration of spatial adjacency and the schematics of residential configurations.

Additionally, in a bid to maximize landslide diversion at each design juncture, convex corners within the plan are interconnected, ensuring no angles are less than 90 degrees in the morphological layout. Lastly, we compile a comprehensive morphological lexicon based on all cluster combinations related to landslide scenarios. An algorithm is then employed to link each morphological variant appropriately as cluster configurations alter. The evolutionary algorithm is calibrated to allow for individualized rotation of each structure, further enhancing their efficacy in diverting landslides.

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Research development

Design development

Regional planning

Morphology

Structure system

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5.2.1 Initial Data from Regional Planning

Housing area

Green area

Contour ( 3m elevation interval) Figure 5.2.1 Initial data for morphology

morphology from this step, we have data from the previous sections, such as housing areas, green areas, contour lines at 3-meter intervals along the Z-axis, and water flow simulation lines at approximately 3-meter horizontal intervals after normalization.

Waterflow simulation lines (3m interval) Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 68

5.2 Morphology | 5.0 Design development

5.2.2 Grids Clustering We use k-means clusters for the building's grids; all grids are divided into clusters of roughly 70 or so, corresponding to the number of existing housing units known from urban planning, and then the number of grids contained in the clusters is controlled to be between 2 and 5, which corresponds to between 50 square meters and 125 square meters, and If the number of grids is more than 5, then k-means iteration is performed until the number of grids meets the demand.

We also list all possible combinations of 2 to 5 grids, which will become our next library, and each time the k-means cluster seed changes, it will be selected from the library based on the combinations that exist in the site.

Figure 5.2.2 K-means clustering of grids

2 Units

3 Units

4 Units

5 Units

Figure 5.2.3 All combination of 2-5 grids Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 69

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5.2.3 Space Characteristics and Relationship Leading

Worker

Main space, must be followed by others

Following

Cannot stay alone, must follow some main space

Kitchen

Grouping

Can be multiple and close to each other

Leading

Outreaching Wathcher

Following

Loner

Isolated space, should be quiet

Living room

Dining room

Servant

Can be reached by other space with service function

Servant

Main bathroom

Watcher

Close to attraction, should be able to see them

Outreaching

Bathroom

Master bedroom

Bedrooms

Accessible to the outside Servant

Worker

Close to second entrance with service function Figure 5.2.4 Space characters (Hsu and Krawczyk, 2004)

Loner

Watcher

Watcher

Loner

Figure 5.2.5 Space characters

From Krawczyk et al's stated, we know that space can be classified into different characters based on different properties, and that each character corresponds to a room in a building of the corresponding function, so that there are different magnetic relationships between rooms that affect their degree of adjacency; we use this as a basis for defining the rooms that we need in a house and deriving adjacency relationships between them.

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5.2.4 Space and Building Generation

Iteration: 100

Iteration: 300 Living room

Bedroom

Iteration: 600 Dining room

Kitchen

Iteration: 900 Bathroom

Figure 5.2.6 Floor plan generation iteration

Copy and move Bathroom and Bedroom to 1F

Copy and move Bathroom and Bedroom to 1F

Link convex coner Easier to divert landslide

Figure 5.2.7 Morphology generation

The team iteratively generated the floor plans based on the spatial magnetic relationships and properties, and currently all combinations of grids as boundary floor plans are iterated for 900 generations as the final floor plan for each combination.

The floor plan in the iteratively generated setup has only the ground floor, which typically has only one to two bedrooms and bathrooms, but according to the capacity, the team needs to replicate and move the bedrooms and bathrooms along the Z-axis again to reach the capacity of the house.

All of the convex corners of the morphology were connected so that all of the vertical corners of the building were larger than 90 degrees in order to more easily divert landslide

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5.2.5 Final Floor Plan and Morphology Library

14 m²

2 Units

3 Units

50m2

75m2

13 m²

Index

10 m²

10 m²

15 m²

Content

14 m²

11 m²

Index

4 Units

5 Units

100m2

17 m²

11 m²

Content

16 m²

12 m²

11 m²

125m2

12 m²

Index

15 m²

Content

20 m²

16 m²

Index

12 m²

12 m²

16 m²

16 m²

12 m²

Content

Figure 5.2.8 Cluster and Morphology Reference diagram

This is a library of all combinations of 2 to 5 units and their corresponding floor plans and morphology, which is equivalent to a dictionary whose indexes are combinations of units and whose indexes correspond to morphology.Each time the seed of the K-means cluster changes, the program will traverse the dictionary to find the matching clusters and replace the corresponding morphology to the position of the clusters.

Infrastructure 2 Units house 3 Units house 4 Units house 5 Units house Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 72

5.2 Morphology | 5.0 Design development

5.2.6 Method of Cluster to Morphology

Index

Content

This diagram illustrates this substitution process in more detail.

Step1, k-means clustering produces clusters.

Step2, we iterate through all the clusters in our dictionary to find all the shapes present in the site Step3, the corresponding morphology is replaced to the position of each cluster.

If the clusters in the field have the same shape as the clusters in the dictionary but different angles or mirrors, the same mirrors and rotations are performed to maximize the replacement of the morphology according to the position of the clusters.

Figure 5.2.9 Morphology replacement process

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5.2.7 Evolutionary Algorithm Set-up

X°

Fitness Objective 01

Gene 04

Gene 01

Rotation angels for 3 units buildings

K-means clustering seeds

Angel between flowlines and buildings close to 180° Divert landslide/Mitigate landslide effects

Gene 02

Rotation angels for infrastructure

Gene 05

Rotation angels for 4 units buildings

Fitness Objective 02

Minimize the differences in quantity of buildings To distribute the number of different types of houses equally

Gene 03

Gene 06

Rotation angels for 2 units buildings

Rotation angels for 5 units buildings

Figure 5.2.11 Genes

Daily shops: 3 units​ Medical: 3 units​ Force electricity Well: 3 units​ Weak electricity well: 2 units​ Community office: 3 units​ Community activity room: 3 units​ Total amount: 17 units (425sqm)

We already tried to avoid impact from landslide in regional part, here, we are introduced Evolutionary Algorithm for diverting landslide by rotate each building to maximize the angle of the water flow simulation lines to be close to 180 degrees, this is the fitness objective 1. Fitness objective 2 is to control the number of individual TYPES so that this number is distributed more evenly and reasonably; Fitness objective 3 is to control the total number of square meters of infrastructure closer to the 425 square meters required by the site.

Fitness Objective 03

Infrastructure building area close to 425m2 The size of the infrastructure is closer to siteneeded Figure 5.2.10 Fitness objectives Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 74

5.2 Morphology | 5.0 Design development

FO3

5.2.8 Evolutionary Algorithm Result

Add (Angels between flow lines and buildings - 180)

FO2

Average of Fitness Ranks

FO1

Add (Differences of Numbers of 4 groups of buildings)

Numbers of single grid * 25m2

Figure 5.2.12 Evolytionary algorithm SD lines and parallel coordinate graph

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5.2.9 Final Floor Plan and Morphology

Figure 5.2.13 Phenotype of average of fitness ranks - rank0

Fitness objectives 01 3282.18°

Fitness objectives 02 19

Fitness objectives 03 3

Average of Fitness Ranks

Rank 0 - The most balanced individual

Infrastructure

2 Units house

3 Units house

4 Units house

5 Units house

475 sqm

Number: 25

Number: 19

Number: 8

Number: 11

Based on the above three fitness criteria we performed a evolutionary algorithm to find an individual that can relatively balance our three objectives. The result we chose is not the best value for a single criteria, but it is the closest optimized and balanced result, and of course avoid some extreme results.

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5.2.10 Master plan

Housing distribution

Pathway

Green land

20

40

60

80

100m

Field

Infrastructure

2 Units house

3 Units house

4 Units house

5 Units house

Secondary road

475 sqm

Number: 25

Number: 19

Number: 8

Number: 11

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Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 78

5.3 STRUCTURE SYSTEM The structural system comprises three pivotal components.

Initially, we focus on cultivating and producing mycelium sandwich panels, supplemented with requisite physical tests to ascertain their architectural utility.

Subsequently, our emphasis shifts to the genesis of this structural system and its universal application rationale.

Given the intense impact force of landslides and the challenges of real-world simulation, our reliance is predominantly on digital impact simulations. These guide the positioning, dimensioning, and density determinations of mycelium sandwich panels within the edifice.

In the last phase, we extrapolate the wall generation logic from the prior section across the entire site, refining site designs culminating in our illustrative renderings.

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Research development

Design development

Regional planning

Morphology

Structure system

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5.3.1 Mycelium Composite Production Step 01

100 ℃ 1.5 hours

Sugarcane bagasse

Into transparent boxes

High-temperature sterilization

Sealed by transparent film

Cooling in fridge for 1 hour

Add seeds Re-seal and close the cover

INGREDIENTS

%

Sugarcane bagasse

45%

Pleurotus ostreatus seeds

45%

Flour

10%

waterproof coating

YES

Step 02

Day 01 to Day 05

Day 06 to Day 10

Step 03 Microwave baking 100℃ 3-4 Hours Figure 5.3.1 Mycelium grow and composite production

Our substrate treatment procedure employs a high-temperature steaming technique for sterilization. After approximately a ten-day maturation period, our material samples achieved a state conducive for the curing process. We then employed microwave baking to finalize the mycelium composites.

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5.3.2 Sandwich Structure

Figure 5.3.2 Mycelium-timber sandwich panel

We fabricated wooden casings precisely tailored to the dimensions of the cured mycelium composite, thereby encapsulating the mycelial mass to create our specialized composite bricks. Our empirical evaluations will employ individual bricks, each weighing 2.7 kg, in a stacking configuration until either all available units are exhausted or structural integrity is compromised.

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5.3.3 Sandwich Components Physical Experiment

Compression test

Minor deformation

Compressive stress: 81 kg/0.03m² =27000 N /m²​ Compressive strain: 0.002m​ Shear modulus: 13,500 Kpa

Compressive stress: 81 kg/0.03m² =27000 N /m²​ Compressive strain: 0.002m​ Shear modulus: 13,500 Kpa

Shear stress: 51.3 kg/0.03m² =18000 N /m²​ Shear strain: 0.005m​ Shear modulus: 3600 Kpa

Shear stress: 40.5 kg/0.03m² =13500 N /m²​ Shear strain: 0.03m​ Shear modulus: 450 Kpa

Shear stress: 56.7 kg/0.03m² =18900 N /m²​ Shear strain: 0.002m​ Shear modulus: 9450 Kpa

Shear test

The data presented in the figure elucidates that all three materials exhibit commendable compressive properties. However, mycelium distinctly lags in shear resistance, while timber and the sandwich composite manifest superior shear attributes. Notably, under the influence of shear forces, timber exhibits greater displacement compared to the sandwich composite.

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5.3.4 Landslide Resistance Structure Design Principles

Rigid Protection

Have sufficient strength and rigidity to withstand the forces Have a stable foundation and be designed to resist overturning

Flexible Protection

Have sufficient strength and rigidity to withstand the forces Have a stable foundation and be designed to resist overturning

Figure 5.3.3 Main structure system

From the studies that have been performed, it can be seen that there are two main methods to reduce the damage caused by landslides on buildings. The first is rigid protective structures, which are characterised by having sufficient strength to counter the impact of landslides on buildings. The other is flexible protective structures, which are capable of spreading out the forces and allowing for a certain degree of deformation and are made of lightweight and buffer materials. These two types of protection will guide the subsequent design.

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5.3.5 Structure Principles

Landslide Distribution

Risk Distribution

High Risk

Force Direction

Medium Risk Low Risk

Figure 5.3.4 Houdini landslide simulation result

1

2

Finite Element Analysis

Get Principle Stress Lines Initial Facade Generation

4

5

6

Spilit Facade

Get the Distance

Final Generation

Figure 5.3.5 Structure design principle

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3

The team started by simulating landslides on the site to derive the areas where the buildings would be affected and classified these areas into high, medium and low risk zones. The team then selected one of the buildings as the paradigm based for generating the façade for the protection of the building. To generate the façade system for the protection of the building, a finite element analysis of the building was carried out to analyse the areas of the building that had experienced relatively severe displacements and to obtain the principle stress lines, and then the distribution of the principle stress lines was observed to determine the distribution of the sandwich panel of the façade based on the sparsity of these lines.

In order to reproduce the process of the building impacted by the landslide, the team will apply different loads to different risk zones of the impacted surface, and in the process of façade generation, the three different risk zones will be divided and optimised separately.

5.3 Structure system | 5.0 Design development

5.3.6 Finite Element Analysis and Force Flow Lines Get the displacement information In order to get information about the displacement of the building under the influence of landslides, the team first performed a finite element analysis of the building. The structure of the building is based on a frame structure and support structures were added to the walls to counter the landslide. After applying loads to the impacted surfaces, the maximum length of the building that was displaced was 134cm, which is the pink part.

134CM

South View

0CM

North View

Displacement Analysis Get the Principle stress lines After performing the finite element analysis, the principle stress line is generated. Principal stress lines are pairs of orthogonal curves that indicate trajectories of internal forces. Stress-line analysis has the potential to offer a direct and geometrically provocative approach to optimization that can synthesize both design and structural objectives.

It provides a basis for guiding the generation of the next façade.

South View

North View

Get the Principle Stress Lines Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 86

5.3 Structure system | 5.0 Design development

5.3.7 Primitive Geomotry and Rationaliztion Initial Facade Generation Through the distribution and density of the principle stress lines, the team bulge out the façade, and it can be seen that the denser the principle stress lines are, the more the façade bulges outwards, and the more the bulge is, the more material will be used, which will make the building more resistant to landslides.

South View

North View Facade will bulge out depend on the density of the Principle Stress Lines

Split Facade In this step, the team further split the building façade by combining the risk distribution map derived from the previous landslide simulation results. As can be seen from the diagram, in order to further minimise the impact of the high risk areas in the landslide, the high risk areas will be offset outwards for a longer distance than the medium risk areas, and as the low risk areas will be virtually unaffected by the landslide, the team will reduce the use of protective structures in this area, and in turn add components such as doors and windows.

South View

North View

Risk Distribution Facade will be spilited in different zones according to the risk distribution

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5.3.8 Final Facade Generation Get the Distances Since the building façade consists of sandwich panels and the sandwich panels have a thickness, the distance between the primary building and the generated façade is needed, which determines how many sandwich panels will be placed. to summarise the previous generation procedure, the denser the principle stress lines, the longer the façade bulges out, the more sandwich panels will be placed, and the more protective the façade will be.

South View

North View

Connect the two surfaces to get the length of curves Final Generation Summarise the previous generation procedure, the more dense the principle stress lines are, the longer the distance the façade projects outwards, the more sandwich panels will be placed, and the stronger the protective effect of the façade will be.

South View

North View

Assemble the facade according to the distance of two surfaces Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 88

5.3 Structure system | 5.0 Design development

5.3.9 Rigidity Test Under Landslide Simulation to Define Gene Domain

Column and beam width: 20cm

Column and beam width: 40cm

Column and beam width: 60cm

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

Figure 5.3.6 Rigidbody simulation on building

Landslide simulatin to get the size range of beam and column Since the protective system of the building consists of both rigid protective structures and flexible protective structures, but there is no reference for the exact size of the structures, the team first used rigid body dynamics simulation to derive a range of sizes for the structures, and then optimised them using a multi-objective algorithm to get a fitting size. The team firstly used rigid body dynamics simulation to get the size range of the structure, and then used a multi-objective algorithm to optimise the structure to get a suitable size. The calculation is shown in equation1.

The peak impact force of landslide equation 𝐹𝐹! = 𝐺𝐺𝜆𝜆"!𝑣𝑣!#ℎ! 𝑏𝑏! sin 𝑎𝑎⁄g

𝑦𝑦! =17.248KN/m³， ℎ! = 1.8m， 𝑏𝑏! =9m， a = 75°, G =gravity(9.8N/kg)

𝐹𝐹𝑓𝑓 is the mudflow slurry impact force (kN); 𝑣𝑣!" is the mudflow velocity (m/s); 𝜆𝜆#! is the mudflow capacity (kN/m3); 𝑏𝑏! is the mudflow width (m); 𝑏𝑏! is the mudflow depth (m); sin 𝑎𝑎 is the angle (degree) between the facing surface of the building and the direction of the landslide

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5.3.10 Flexibility Test under Landslide Simulation to Define Gene Domain Panel Scale: 40cm

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

40cm

Panel Scale: 60cm

60cm

Panel Scale: 80cm

80cm

Figure 5.3.7 Rigidbody simulation on panels

Landslide simulatin to get the size range of Sandwich Panel This step is the range of sizes obtained for the RIGID protective structures and the FLEXIBLE protective structures, from the simulation results, it can be seen that when the size of the columns and beams is less than 20cm, the building will be completely damaged by the impact of the landslide, if it is more than 60cm, the building will not be damaged but further increase will no longer make a difference.

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Panel Scale: 100cm

1

2

3

4

5

6

1

2

3

4

5

6

1

2

3

4

5

6

100cm

Panel Scale: 120cm

120cm

Panel Scale: 140cm

140cm

Figure 5.3.8 Rigidbody simulation on panels

Landslide simulatin to get the size range of Sandwich Panel In flexible protective structures, when the width of panel is less than 0.4 metres, the building will be completely damaged, but when it is greater than 1.4 metres, the building will not be damaged, and there will not be much change if its width is increased again.

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5.3.11 Structure Optimization (Evolutionary Algorithm Set-up)

Optimization of Rigid Protection

Optimization of Flexible Protection

Figure 5.3.9 Structure optimization

Structure optimization In order to use less material while allowing less displacement to occur when the building is impacted by a landslide, the team inputs the resulting range of dimensions into an evolutionary algorithm for iterative optimisation, which then produces the dimensions of columns, beams, and sandwich panels.

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5.3.12 Optimization Result (Evolutionary Algorithm Result )

Parallel Coordinate Plot

Figure 5.3.10 Evolutionary algorithm result Ran An | Shengyao Zhang | Chuheng Tan | Haipeng Zhong 93

5.3 Structure system | 5.0 Design development

FC1 Rank 1 (G5 I6)

1

2

3

4

Material Usage: 43.72m3 FC2 Rank 1 (G13 I0)

Panel Scale: 1m

1

2

3

4

Material Usage: 27.97m3

Panel Scale: 0.6m

5.3.13 Landslide Simulation

Displacement: 5.49cm

Panel Thickness: 0.3m

Displacement: 17.92cm

Panel Thickness: 0.3m

Figure 5.3.11 Secondary simulation from evolutionary algorithm result

Further Selection The Pareto front solution shows the optimization of GA , because of the smaller number of genes and optimisation objectives, the differences among the optimized solution are subtle, but it still causes the vast different impact under the water flow.

The peak impact force of landslide equation 𝐹𝐹! = 𝐺𝐺𝜆𝜆"!𝑣𝑣!#ℎ! 𝑏𝑏! sin 𝑎𝑎⁄g

𝑦𝑦! =17.248KN/m³， ℎ! = 1.8m， 𝑏𝑏! =9m， a = 75°, G =gravity(9.8N/kg)

𝐹𝐹𝑓𝑓 is the mudflow slurry impact force (kN); 𝑣𝑣!" is the mudflow velocity (m/s); 𝜆𝜆#! is the mudflow capacity (kN/m3); 𝑏𝑏! is the mudflow width (m); 𝑏𝑏! is the mudflow depth (m); sin 𝑎𝑎 is the angle (degree) between the facing surface of the building and the direction of the landslide

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Average of objectives (G26 I5)

1

2

3

4

Material Usage: 31.02m3 Relative Difference of Objectives (G0 I7)

Panel Scale: 0.6m

1

2

3

4

Material Usage: 35.22m3

Panel Scale: 1m

Displacement: 9.57cm

Panel Thickness: 0.25m

Displacement: 14.08cm

Panel Thickness: 0.17m

Figure 5.3.12 Secondary simulation from evolutionary algorithm result

Therefore, we chose four representative optimisation results for further landslide simulation verification, which are the optimal FC1 results, the optimal FC2 results, the average of both FC1 and FC2 results and the relative differences between objectives results. These results were then subjected to landslide simulation, and the average of objectives was found to be the least affected by landslides among the four.

The peak impact force of landslide equation 𝐹𝐹! = 𝐺𝐺𝜆𝜆"!𝑣𝑣!#ℎ! 𝑏𝑏! sin 𝑎𝑎⁄g

𝑦𝑦! =17.248KN/m³， ℎ! = 1.8m， 𝑏𝑏! =9m， a = 75°, G =gravity(9.8N/kg)

𝐹𝐹𝑓𝑓 is the mudflow slurry impact force (kN); 𝑣𝑣!" is the mudflow velocity (m/s); 𝜆𝜆#! is the mudflow capacity (kN/m3); 𝑏𝑏! is the mudflow width (m); 𝑏𝑏! is the mudflow depth (m); sin 𝑎𝑎 is the angle (degree) between the facing surface of the building and the direction of the landslide

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5.3.14 Building Generation Process 1

Protective Envelope Map High Risk

2 Pile Foundation

Medium Risk Low Risk

Platform

Inner Wall 3

5

Sandwich panels: Mycelium Composite Blocks

Windows

4

Outer Planks

6 Roof Panels

Doors

Figure 5.3.13 Building generation process Architectural Association School of Architecture | EmTech | Thesis | 2022-2023 96

5.3 Structure system | 5.0 Design development

5.3.15 Protective Sandwich Envelope Detail

Mycelium composite blocks as sandwich core

Planks as Sandwich side sheet Figure 5.3.14 Sandwich panel detail

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5.3.16 Structure Detail Detail and Assembling

Mycelium composite Material Figure 5.3.15 Envelope system details

Assembling and Detail In terms of the assembling process, The sandwich protective envelopes are composed of modular components, and these components are installed into a customisable frame structure for dismantling and installation. The connecting and framing parts are made of steel, and the layers of these modular components can be stacked and dismantled according to the user's actual needs and changing environment.

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STRUCTURE SYSTEM CONCLUSION Utilizing both rigid and flexible protective frameworks, but bereft of standardized dimensional guidelines, the team initially applied rigid-body dynamics simulations to ascertain a prospective size range for the structures.

These dimensions were subsequently refined through a multi-objective optimization algorithm. The simulation revealed that rigid elements, such as columns and beams, proved ineffective if their dimensions were under 20 cm, while exceeding 60 cm yielded diminishing returns.

Similarly, flexible components like panels demonstrated vulnerability under 0.4 meters in width, yet exhibited stability beyond 1.4 meters.

To achieve material efficiency coupled with minimal structural displacement upon landslide impact, the dimension ranges were incorporated into an evolutionary algorithm for iterative optimization. Subtle variations emerged in the Pareto-optimal solutions due to the fewer genes and objectives in the Evolutionary Algorithm(EA).

However, these nuances had significant implications under hydrodynamic conditions. Consequently, we selected four exemplar outcomes for further landslide simulation validation, among which the average objective demonstrated superior landslide resilience.

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5.4 Paradigm expansion | 5.0 Design development

Step 1. Previous urban layout and building morphology

In scaling up this paradigm across the entire site, there's a pressing need to recalibrate the urban fabric in harmony with natural water flows and functional necessities derived from the preceding cellular automata analyses.

Our prior results at the regional scale bifurcate the landscape into two distinct zones: the green and the empty. The green zones are earmarked for agricultural endeavors, tapping into the area's innate fertility, while the empty zones have been deliberately kept devoid of immediate development. These empty spaces act as buffers, providing flexibility for future growth, infrastructure needs, and unforeseen contingencies, ensuring the village's long-term resilience and adaptability. As the plan progresses, these zones will organically evolve based on the village's growing needs and environmental interactions.(Step 1)

Previous Urban tissue planning Green area Empty area Step 2. Landslide flow prediction

To effectively rearrange the urban tissue, we firstly simulate te patterns and potential pathways of landslide flows by using Houdini heightfield erosion system. A comprehensive assessment of the terrain, combined with historical data and predictive modeling, enabled us to produce a detailed risk map. (Step 2)

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Step 3. Land use risky map from landslide flow prediction

This map has been categorized into three distinct levels of vulnerability: high risk, medium risk, and low risk areas. (Step 3)

Risky mapping High risk area Medium risk area Low risk area Step 4.Land use redistribution

In synthesizing the risks associated with landslides and the urban tissues identified as green and empty areas, we've achieved a comprehensive understanding of the site's potential. This has allowed us to create a four-tiered categorization for site planning (Step 4): Risky Green Area: This zone represents areas with a higher vulnerability to landslides but is currently occupied by vegetation or proposed for planting.

Conservation efforts should be balanced with landslide mitigation strategies.

Introducing deep-rooted vegetation could serve a dual purpose: ensuring green cover and acting as a natural barrier against soil erosion.

Risky Empty Area: These are landslideprone zones with no significant green cover. Priority in these regions should be on landslide mitigation. Our approach is to design sinks or pools to divert and manage the flow of water, reducing the immediate threat of landslides. Any development in this area should prioritize safety and sustainable water management solutions.

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Risky mapping Risky green area Risky empty area Safe green area Safe empty area

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Step 5. Land use redistribution

Safe green area

Risky green area

Risky mapping Risky green area Risky empty area

Risky empty area

Safe empty area

Safe green area Safe empty area Step 6.Building risky map from landslide flow prediction Safe Green Area: With diminished landslide vulnerability and abundant green space, this zone is ripe for conservation, ecotourism, or agriculture. It offers opportunities not only to preserve nature but also to catalyze economic development through ecotourism. Shared fields or community farming can be introduced as new facets of a tourism-driven economy.

Safe Empty Area: Given its low susceptibility to landslides, this zone is prime for future sustainable community development, encompassing residential and infrastructural projects. Furthermore, given its strategic safety, portions of this area can be earmarked for emergency shelters and designated evacuation points.(Step 5) For building, there is also a risky mapping for the sandwich protective envelope.(Step 6)

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Step 7. Building protective envelope pattern distribution map

In the subsequent step, we also generate the risky map on the buildings for guiding the assembling of sandwich protective envelopes. The risk levels of different zones necessitate varied approaches to this protective measure. The premise of this mapping is to match the degree of risk with the number of protective envelope layers.

Specifically, buildings in higher risk areas will be fortified with more layers of sandwich envelopes. (Step 7)

This layered system not only ensures greater safety but also allows for adaptability as conditions change. As we monitor and update the risk map, the envelope distribution can be adjusted accordingly, offering a dynamic solution to the region's evolving challenges.

Besides, the sandwich envelope are ade from modular components, which are specifically designed for flexibility and adaptability. They offer convenience for local residents, allowing them to easily reconfigure, rearrange, recycle, and replace parts as required. Given the everevolving nature of landslide risks, such a system is invaluable. It's not just about immediate protection; it's about equipping the community with tools that can adapt over time. This dynamic system, which is responsive to changing landslide conditions, also stands as a testament to sustainable and environmentally-friendly design principles. (Step 8)

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Step 8.Building protective envelope pattern

5.4 Paradigm expansion | 5.0 Design development

Step 9. Inner wall, bottom and foundation

Then is the inner wall, foundation, columns and beams, bottom elevated bottom like "diaojiaolou" style.(Step 9)

Step 10. Roof panels

Final is the sloping roof panels which taking cues from the architectural nuances of vernacular buildings. Additionally, the angle is optimized based on the region's rainfall data, showcasing a harmonious blend of tradition and function.(Step 10)

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Step 11. Tree planting

Tree planting (Step 11)

Village scenes recreation (Step 12)

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5.5 Rendering | 5.0 Design development

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5.5 Rendering | 5.0 Design development

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LIMITATIONS AND CONCLUSION In the face of ever-evolving geological challenges, particularly the recurring threat of landslides in regions like Malong County, Yunnan Province, proactive and innovative strategies are imperative. This thesis provides a comprehensive exploration of such challenges, focusing on their far-reaching consequences on infrastructure, the environment, and socio-economic paradigms.

Through a synthesis of detailed analyses, urban and regional planning techniques, and the introduction of innovative materials, it not only identifies the vulnerabilities but also offers sustainable solutions.

One of the most significant revelations of this research lies in its emphasis on the importance of integrating traditional architectural practices with pioneering materials, such as the mycelium-based composite. This eco-friendly alternative, coupled with the region's unique mushroom cultivation landscape, presents an opportunity to address structural challenges while also emphasizing sustainability.

Furthermore, the application of advanced tools like the Houdini heightfield erode system and the use of Cellular Automata in urban design showcases the importance of technology in addressing and mitigating natural calamities. Such a blend of traditional and modern approaches positions the region on a trajectory towards resilience.

While this thesis offers a comprehensive exploration of landslides' impact on infrastructure within Yunnan and presents innovative strategies for mitigation, it's important to acknowledge certain limitations inherent in the study: 1. Morphology of Buildings: The research predominantly focuses on individual building structures, without adequately delving into the interconnectedness of these structures. The potential web and connection between each building, which can play a crucial role in dictating the overall stability and resilience of a built environment during landslides, has not been extensively addressed. This oversight may have implications on how buildings collectively respond to the pressures of a landslide and may warrant further exploration to ensure the holistic safety of a region.

2. Landslide Simulation Limitations: The Rigid Body Dynamics (RBD) used for landslide simulation predominantly examines the macro impact of landslides on buildings. However, the subtleties associated with varying landslide materials, such as stones and mud, and their specific impacts on infrastructure, have not been incorporated. These finer details can significantly affect the structural integrity of buildings and influence the design requirements for landslide resilience. Future research could benefit from a more nuanced landslide simulation that accounts for the diverse materials involved and their unique impacts on structures.

3. The lack of alignment of vernacular buildings: One limitation in the research is its omission of the region's vernacular architectural style, like the center courtyard prevalent in many traditional Chinese buildings, Future adaptations and designs must consider integrating such key vernacular features to ensure cultural compatibility and acceptance.

Acknowledging these limitations not only strengthens the credibility of the research but also highlights areas of potential future exploration to further enhance our understanding and mitigation strategies for landslides. In conclusion, while landslides, exacerbated by climate change and geological disruptions, pose a formidable challenge to Yunnan's growth and safety, this research underscores the region's potential to innovate and adapt. By harnessing both cutting-edge techniques and sustainable materials, there is a clear path forward to not only safeguard its infrastructure but also ensure the well-being of its residents. The findings of this thesis serve as a beacon for other regions grappling with similar challenges, emphasizing the power of informed research and innovative thinking in charting a safer, sustainable future.

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RE-MYCE COURSE DIRECTOR Dr. Elif Erdine Dr. Milad Shawkatbakhsh

STUDIO TUTORS

Felipe Oeyen, Lorenzo Santelli, Fun Yuen, Paris Nikitids

FOUNDING DIRECTOR Dr. Michael Weinstock

[EmTech] AA Emergent Technologies & Design Graduate Programme

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Ran an (MSc) Shengyao Zhang (MSc) Chuheng Tan (MArch) Haipeng Zhong (MArch)

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