In front of you lies the fifth edition of the BT-Bundle. This publication was compiled by the 30th Board of Praktijkvereniging BouT, the study association of the MSc Building Technology Track at the Faculty of Architecture, TU Delft. The BT-Bundle showcases theses created by our graduates. This bundle includes work from students who completed their theses between June 2024 and September 2024.
The field of Building Technology represents a multitude of research areas that students can choose from for their graduation topics. These topics are represented in the following groups:
Facades & Product
Energy & Climate
Transparent Structures / Glass Design
Circular Building Design
Computational Design
Nature-Inclusive Design
Sustainable Structures
We would like to thank all the students who voluntarily took the time to create their contributions and for trusting us with their work. As the interests and field of Building Technology expand, the interdisciplinary topics that students focus on also evolve. Therefore, to our readers, we hope that this edition of graduation topics will spark interest and provide insight into the field of BT.
Wishing the graduates the best of luck in their future endeavors!
Daniel Lux Education Chair, 30th BouT Board
Table of Contents
Multi-objective Optimization of External Shading Systemising Genetic Algorithm Based Workflow to Enhance Energy Efficiency of Existing Building Envelope by Alkiviadis Oikonomidis
Freeform Transparency by Anna Konstantopoulou
Towards Zero Waste Structures through Integration of Reclaimed Wood and 3D printing by Aron Arend Bakker
Stock Discretized Structural Timber by Daan Weerdesteijn
Computational Optimization of Hempcrete Integration by Dimitra Mountaki
ML Indoor Wayfinding Assessment Tool for Dementia Care Spaces by Feras Alsaggaf
Bio-based Binders for Rammed Earth Construction by Fieke Konijnenberg
Circular Facade Design by Gargi Gokhale
Deep reinforcement learning for performance-based design assistance by Jair Lemmens
ReiforceRay - Planning of PV and BESS with Reinforcement Learning by Kuba Wyszomirski
Bio - composites from Food-waste by Lara Neuhaus
Flexible Formwork: A Textile-Centric Approach by Lucy Flieger
Beyond Noise by Niroda Vitusha Smit
TO3DPGS - The Future of Glass by Pim Brueren
Re - P - Tile by Ramya Kumaraswamy
Interactive Breezemaker by Roelof Kooistra
Inspection and Maintenance Planning of Timber Structures by Sasipa Vichitkraivin
Recycled Composite Cast Glass Panels made of C&D waste by Véronique van Minkelen
Enhancing Autonomy on Construction Sites through Implementation of Swarm Robotics as adaptive Material-Handling logistics system by Zahra Khoshnevis
Multi-objective optimization of external shading system using genetic algorithm based workflow to enhance energy efficiency of existing building envelope
This master thesis rigorously explores the integration of a genetic algorithm-based workflow in the design and optimization of a fixed shading system utilizing ETFE cushion panels, with the objective of enhancing the thermal resilience of an existing building envelope in an annual basis or during a heatwave. The case study focuses on a mid-rise office building located in the port of Athens, Greece namely the “Tower of Piraeus”.
The central research question addressed is:
“How can a genetic algorithm-based workflow be effectively employed in the multi-objective optimization of a shading system to improve the energy efficiency of an existing building envelope?”
To answer this question, the research investigates four interconnected domains: ETFE double skin structures, resilience quantification, multi-criteria decision-making approaches with genetic algorithms, and the analysis of the case study building facade system. The study centers on the preliminary design phase of the shading system, highlighting its potential as a retrofit solution for existing infrastructures challenged by rising temperatures. The outcomes of this research include the development of a versatile workflow for evaluating the energy performance of existing buildings, facilitating interdisciplinary feedback within a design team, and applying multi-objective optimization to design problems.
This work provides a comprehensive framework for integrating advanced computational methods in architectural design, thereby contributing to the improvement of building energy efficiency and thermal resilience.
Alkiviadis Oikonomidis 2024
Simona Bianchi, Charalambos Andriotis, Maria Meizoso
Freeform Transparency
Introducing a novel fabrication technique for curved glass utilizing knitted moulds
Glass, a transparent and durable material with significant structural potential, is extensively used for architectural and structural applications in buildings. Existing approaches mostly use float glass, which is confined by planar designs, resulting in two-dimensional facades. Several examples of curved glass applications exist which, due to the limitations of current fabrication techniques, result in repetitive panels. Emerging architectural trends demand more fluid, threedimensional freeform shapes, which present glass shaping processes cannot provide without incurring excessive costs and material waste in the fabrication process.
Research in other materials shows that flexible moulds are able to produce complex geometrical results. More recently, knitted fabric formworks have proven to be very successful in creating concrete shells of high complexity and low material usage and waste.
This thesis aims to address the gap by investigating the viability of using knitted basalt moulds for glass slumping, a novel fabrication approach that might allow for the manufacture of customizable, freeform curved glass components. The research investigates the possibility of this technology to accomplish extreme geometries while remaining simple and cost-effective in mould manufacture.
The originality of this graduation subject stems from the second part of the thesis, which is an experimental exploration. Basalt yarn is chosen to create hand-woven and CNC-knitted moulds to test with glass slumping. The experimental phase involves
testing several knitted basalt moulds and combinations with coatings to determine ideal material combinations to improve surface quality and geometric precision in curved glass. After reflecting on the experiment results, experimental data is used to create a final prototype attempting to achieve geometrical control and repeatability to prove the potential of the proposed fabrication technique.
As early as the first experiments performed, it became evident that using a lightweight textile mould made of continuous basalt fibers yarn is a feasible and promising fabrication method for curving glass by slumping. Throughout the experimental research, testing with both woven and knitted textile mould proved that there are many possibilities in the development of such a technique for creating freeform glass geometries, but also, they entail several constraints and limitations. The experimental work conducted within the framework of this thesis proved that this novel fabrication method enables the easy customization of freeform curved glass, showing the great potential of using such flexible moulds to enrich the potential of a fluid architectural language using glass. The potential of using knitted moulds thus, lies in creating forms with multiple curvatures and forming complex geometries but also introducing the dimension of texture on glass which can be used towards increasing the aesthetic value of the result. Several limitations, however, were encountered while experimenting with basalt knitted moulds regarding the achieved deformations but also the sustainability aspect of using basalt fibers for this method.
Name
Graduation year
Tutors
Anna K onstantopoulou 2024
Faidra Oikonomopoulou & Mariana Popoescu
Glass slumping using CNC knitted basalt mould process: basalt mould before and after firing (a) & resulting double curved glass slumped on the mould (b).
TOWARDS ZERO-WASTE STRUCTURES THROUGH INTEGRATION OF RECLAIMED
In the pursuit of sustainable development, the construction industry faces the dual challenges of material scarcity and the environmental impact of its material usage. This thesis explores the potential of hybrid structures, specifically employing reused wooden elements, to address these challenges and transition towards a zero-waste economy. The research investigates the application of computational design and digital fabrication techniques in order to maximize the reuse of wooden structural elements without the need for remanufacturing, thereby reducing waste and carbon footprint.
Using the TU Delft modelling hall of the BK faculty, this study introduces a new approach that combines stock-constrained design with additive manufacturing. This approach utilizes 3D printing technology to create flexible, adaptable connections
that accommodate the irregular dimensions of reclaimed wood, thus optimizing the use of available materials. The study evaluates the environmental impact through a lifecycle assessment. In the end it will compare the proposed method to the traditional construction practice and other methods that stimulate the reuse of wood.
The findings indicate that the proposed hybrid design methodology effectively reduces waste over the successive generations. However, the data also reveals that the carbon footprint has not yet decreased. Further research is necessary to identify the next steps for reducing carbon emissions and achieving a sustainable, zero-waste methodology. This study contributes to the body of knowledge by bridging the gap between theoretical design and practical application, offering a scalable model that can eventually be implemented
Aron Arend Bakker 2024
Mauro Overend & Paul de Ruiter
From up to down: Rendered impression of the created roof structure, Created physical model
Stock discretized structural timber elements
Timber is becoming a more popular sustainable alternative to concrete or steel due to its positive ecological footprint, high strength to low weight ratio and new engineering and processing techniques. However, this popularity also has a downside the life cycle of timber is far from circular and currently almost all the collected waste wood is either incinerated to produce energy or down-cycled into engineered board products. In The Netherlands alone around 1.740 kiloton of waste wood is collected annually, 26% of this wood consists of solid non-glued wood, translating to potential a waste stream of 450kton that could be directly reused. Using programming and optimisation techniques, this thesis focused on creating an efficient and adaptable structural system able to directly use the parts form a varying stock of reclaimed timber pieces. A computational tool was developed with the goal to minimize the cutting-losses and material consumption, tackling both a matching and structural optimisation problem. Used techniques involve dynamic programming, principal
stress line analysis and a ground structure optimisation approach, which combined ensure an efficient discrete aggregation. The algorithm discretizes a given design space into the pieces stored in a database by sequentially solving three combinatorial problems. The placement of pieces and the final aggregation are both optimised resulting in a final efficient structure. The algorithm’s performance is tested on stability of results, optimisation method, size influence of parts, filling rate of the design space, strength grade influence and buckling. A novel structural system, designed for the outputted discrete aggregation, maximizes the future reuse potential of the used parts, closing the current wasteful lifecycle of timber. This work serves as a prove of concept for design with a highly versatile stock of reclaimed components and answers the research question: How can programming be utilised to create a discrete structural system using reclaimed timber parts that maximizes efficiency and adaptability but minimizes the need for virgin materials in construction?
Computational optimization of hempcrete integration: improving energy performance and minimizing embodied energy in a variety of building types and climates
The growing threat of climate change highlights the necessity for long-term solutions in the construction industry. Buildings account for a large share of worldwide energy consumption and carbon dioxide emissions, so there is an urgent need for creative techniques to improve energy efficiency and reduce their ecological footprint. Therefore, the research question was developed: How can a computational workflow optimize hempcrete’s integration in various types of buildings across diverse climates, with the objective to support preliminary designs that achieve high energy performance and minimize global warming potential? This approach uses a multi-objective optimization process to offer optimal
solutions adapted to various climates and building types, optimizing energy efficiency and daylight while limiting global warming potential. Architects and engineers can get greater performance and sustainability results by experimenting with different layout options and design parameters using parametric modelling, energy analysis, and optimization algorithms. The suggested workflow provides a systematic technique to facilitate decision-making during the key design steps, promoting hempcrete implementation and accelerating the shift to performance-driven architectural design in response to climate change problems.
Overall workflow. The workflow is divided into 3 stages. The initial stage involve parametric modelling of the building. The second stage includes energy simulation, daylight analysis and life cycle assessment. The final stage focuses on optimization and visualization.
Interface using the interface’s sliders and drop-down options. Coordinate Plot results after the optimization. Finally, the chosen design is displayed, allowing the user to inspect either the building’s envelope or structure.
The model provides a wide range of building element possibilities for each component. Example of wall layers
Interface. The most important part of the interface is the comparison tab, on which the user can select 4 different designs and compare their visualized results by checking diagrams.
Dimitra Mountaki 2024
Dr. Michela Turrin, Dr. Martin Tenpierik
ML Indoor Wayfinding Assessment Tool for Dementia Care Spaces
The design of residential care facilities for individuals with dementia profoundly impacts their quality of life and wellbeing. Dementia-friendly architecture, thoroughly reviewed in literature, provides guidelines and assessment tools to evaluate residential spaces and enhance living conditions. Key to residents’ wellbeing is their autonomy and control over their environment, which is facilitated by optimizing wayfinding within indoor spaces. Effective spatial layouts, particularly those offering good visual access, not only promote autonomy but also improves social integration by enabling residents to see and be seen by others.
This MSc thesis examines the use of artificial intelligence to advance dementia-friendly architectural design, focusing particularly on wayfinding—a critical element of environmental design for individuals with dementia. The study quantitatively assesses the relationship between floor plan layouts and wayfinding ease using the isovist method, linking floor plan
geometry with the navigational experiences of dementia patients. This is based on established Dementia Design Principles (DDP) within universal design guidelines.
A computational framework was developed to evaluate wayfinding quality using isovist analysis techniques, which were integrated into a machine learning model. The model was trained on a dataset of 256 floor plans, employing features derived from two sources: spatial metrics such as distances and centrality from the Swiss Dwellings dataset, and compactness and distance-based features extracted via the Grasshopper. The model was tested using two supervised machine learning algorithms—Random Forest and Artificial Neural Networks—and achieved consistent accuracy for two visual access multiclass outputs between 70-80%. This demonstrates AI’s potential as a decision-support tool in the early stages of architectural design, offering architects insights into the wayfinding quality of their designs.
Fig 1: measuring visual acess in residential care spaces
Fig 2: wayfinding quality indicators based on dementia design principles
Bio-based Binders for Rammed Earth Construction
This research aims to improve rammed earth performance by using a bio-based binder. The resulting main research question is: How can the use of bio-based binders improve the material performance of rammed earth in Northwestern European building construction?
To learn from past trial-and-error, an overview of the commonly known historical earth binders was made. This overview was placed in a criteria matrix, resulting in a top 5 of binders most suitable for use in Northwestern Europe. During initial sampling, a proposed optimum percentage of the chosen binders are 2% or 5% granulated sugar, and 5% chicken egg albumen. The 5% in liquid albumen equals to 1.25% dehydrated albumen.
To get an indication of the increased material performance while using binders, a series of tests is chosen based on available literature. These tests are conducted to determine a hypothetical performance related to weathering circumstances in Northwestern European climates.
To compare the results of samples with implemented biobased binders, samples with no binder and samples with 5% cement were made.
The conducted tests are:
-Impact test
Name
Graduation year
Tutors
- Shrink box test - Abrasion test - Penetration test - Drip test- Spray test - Moisture absorption test
- Wetting and drying test
- Freeze and thaw test - Strength tests
In each test, the samples that did not include any binder reached failure. Samples using binders show a significant delay, or the absence, of damage. The samples most frequently withstanding damage use dehydrated albumen or cement.
The overall result of the research is a hypothesis that dehydrated albumen might be a viable bio-based alternative to cement, allowing rammed earth to reach the required material performance necessary for large-scale construction. Further research is required to prove this hypothesis.
Drip
Drip test - Nozzle
Strength test - Flexural strength
Abrasion
Circular Facade Design
The different circular scenarios are identified for each of the standardised materials The circular EoL scenarios are highlighted with a red circle in Figure 52 The façade system for panel A is reused the EoL of the first façade lifecycles and then recycled at the EoL of the second lifecycle. On the other hand, panel B has an active window system with the window component that needs to be replaced after 20-40 years. The other components in the panel B are reused as a system at the EoL of the first lifecycle. Panel C consists of active components that are replaced at the end of life the first lifecycle. The structural steel and the stone wool insulation used in the system are reused for a second lifecycle.
3.5 Multi-lifespan flowchart
The linear economy of Take-Make-Dispose creates environmental pollution, increases the cost of raw materials, increases waste and creates CO2 emissions. The new Circular Economy Action Plan aims to design products that prevent waste and retain resources in the EU economy. The building and construction industry contributes to 35% of the total waste produced globally. Facades are complex multilayered system with lifespan shorter than the structure. A façade system reaches its end of technical life often compared to the structure. Effective End-of-Life management of a façade can enable material recovery, recycling and reuse. The environmental impacts play an important role in the End-of-Life decision making of a system followed by the material costs. Design aids like MFA and LCA act as the evaluative design aids to access circularity based on the environmental impacts. But these evaluative design aids are time-consuming. Thus, the generative design aids that are based on the evaluative design aids can guide the façade
The GWP impacts are high when virgin materials are used. The GWP impacts are reduced by using the recycled materials. If the GWP impacts produced during the manufacturing and construction stage by using the recycled materials are high then the preferred choice would be to use virgin materials. The GWP impacts are less when the system/ components of the system/ standardised materials in the system are reused. The GWP impacts of the reuse cycle can be further reduced by opting for on-site reuse, thereby eliminating the transportation impacts. A further reduction in the overall GWP impacts can be observed if the strategies of reuse and recycle are combined. This will reduce the impacts over the years. When considering 300 years impacts, the variants with long lifespan materials and the biobased materials exhibit a similar trend of increase in the GWP impacts The impacts for various lifecycles can be reduced by reusing at the EoL and using the standardised materials that can be recycled multiple times. Thus, for the technical materials, it is necessary to combine the circular strategies for slowing and closing the loop. In case of the bio-based variants, a less impact is created during each cycle even though the virgin materials are used it is because of the less GWP at the manufacturing stage.
The flowchart below indicates the different lifecycle stages considered for the evaluation of the results along with different materials used in the system and the various circular EoL scenarios taken into consideration.
Figure 42 Impact of the selected materials over a span of 330 years by author
5.3.4 GWP impacts of stage C (EoL) over 90 years
While considering the impacts of the EoL stage, it can be seen that the impacts of the materials which are bio based are more as compared to impacts caused by the technical materials with a long lifespan or short lifespan. This implies that the current market scenarios for EoL processes for bio-based materials should be revised. It is advisable to use bio -based materials with a longer lifespan and materials that help in closing the loop. Incineration is not a preferred option.
The long lifespan Variant 1 the bricks end up getting crushed and added to the sub-base layer, the EPS insulation is incinerated, thus the EoL processing impact is more at LC2 compared to the other two long lifespan variants which have a more circular EoL compared to Variant 1.
63
C impacts over a span of 90 years
designers in designing a façade system which is circular at the End-of-Life. The project derives guidelines for a circular End-of-Life design of a façade system. The project employs a mixed methodology consisting of literature research and research through design process. Several design variants with different End-of-Life scenarios were designed and evaluated for environmental impacts and market-based material and installation costs. Results indicated that reuse scenarios had the least environmental impacts, but the reuse scenario was governed by the lifespan of the materials in the system. The market-based material and installation costs of the materials were found to be high for long lifespan materials compared to the short lifespan materials. For the bio-based variants, it was found that despite having lower global warming potential impacts at the manufacturing stage, in most of the cases, the materials are downgraded at the End-of-Life.
6 Design Guidelines and Information Considerations
Design guidelines and considerations
Figure 54 indicates that the impacts of GWP impacts are significantly reduced by integrating the design guidelines stated in section 6 in the façade design. A decrease of GWP impact of 50% was observed compared to the average value of long lifespan materials in the final design which helps to validate the proposed guidelines. The circularity percentage of the new design is 55% which is higher than the circularity percentage of bio-based materials and a 34 kgCO2 eq/m2 of the embodies carbon value which is lower than the long lifespan and short lifespan variants and the biobased variant 9 (rammed earth system) and equal to the variant 7 (timber system). The cost of the final variant is equivalent to the cost of the Variant 3 or less since recycled materials are used in the system. While the ODP, AP and POCP impacts are higher than the long lifespan variants, the
Gargi Gokhale
Dr. Ing Thaleia Konstantinou, Ir. Dr. Sultan Çetin, Dr.ir. Magdalena Zabek
7.4 Evaluation results
Figure 54 GWP impact over 90 years (Stage A and Stage C)
Figure 55 GWP impacts of stage C over 90 years
Deep reinforcement learning for performance-based design assistance
Architects play a pivotal role play in the sustainable development of the built environment, shaping spaces that minimize environmental impact while enhancing human well-being. However, due to the escalating complexity of design requirements, designers are becoming underequipped to solve today’s design challenges. Solving such problems involves balancing multiple different co-dependent factors, such as spatial configuration, daylight satisfaction and embodied carbon. Currently this is addressed through interdisciplinary collaboration where different parties focus on their own specialisation. As a result, a significant gap exists between design and building performance analysis leading to underperforming and expensive solutions.
An artificial intelligence-powered platform could aid in the design process by bridging the gap between different disciplines. Such a platform could ensure that all aspects of a project are considered holistically, reducing the risk of conflicting decisions that cause lacking performance and unnecessary expenses. Simply consolidating information, as done with building information modelling (BIM), is not sufficient. Instead, the platform must provide performance-driven recommendations, offering deeper insights when conflicts between different disciplines arise.
This work aims to develop a framework through which deep learning methods can be applied to create floorplans informed by performance-based criteria and user guidance. Since functionality is heavily dependent on site-conditions and requirements laid out by the client, the relationship between form and function must be uncovered dynamically. To achieve this, inspiration will be drawn from the field of reinforcement learning which allows the training of a neural network without the use of training data.
Resulting building design.
Tutors
Jair Lemmens 2024
Charalampos Andriotis & Michela Turrin
Automated floorplan segmentation Informed by connectivity graphs.
Performance informed design variants. In this example heat stress minimization.
ReinforceRay - Planning of PV and BESS with Reinforcement Learning
As the consumer electricity prices rise, european policymakers are increasingly focused on decarbonizing the power grid, which requires homeowners and local administrators to adopt renewable energy sources amidst a complex set of often conflicting objectives and constraints.
This thesis project introduces an innovative application of deep reinforcement learning (DRL) for long-term strategic planning of rooftop photovoltaic systems and battery energy storage within the residential sector, aiming to balance environmental and financial objectives considering the ever-evolving system condition and uncertainties inherent in the market. Unlike existing methods based on discounted cash flow, it allows not only to assess planning strategies (including delay) but also to validate dynamic performance and implement system modifications or expansions throughout its lifespan.
The problem is modeled as a Markov Decision Process (MDP), facilitating sequential decision-making across 25 annual steps. The DRL environment incorporates a comprehensive
set of variables identified through extensive literature review and market analysis. To account for their long-term dynamics, scenarios were simulated using appropriate stochastic and propabilistic processes for agent’s training. A policy-based DRL agent is evaluated, exploring various residential and technological scenarios, including three single-family houses, different PV models and various optimisation scopes.
Moreover, a deployment workflow and a user interface are developed to support real-world decision-making applications (a video demo available under youtube.com/ watch?v=CbG2Y-1GYr0). Furthermore, a separate DRL model is developed to simulate battery management system’s charging and discharging protocol.
The findings suggest that deep reinforcement learning offers a promising solution for addressing this complex problem. It provides enhanced flexibility in decision-making and helps mitigate investment risks.
Workflow Flowchart for model’s development, training and evaluation
Bio-composites from Food-waste
Exploring the impact of waste sourced fillers from the food industry on the functional and mechanical characteristics of bio-composites.
This thesis explores the potential of integrating waste-based fillers from the food waste industry into bio-composites for facade applications.
The limited use of waste materials in building products, combined with a rising demand in sustainable materials, leaves the opportunity for new fully bio-based building material from underutilised by-products.
The approach involves integrating organic waste as granular filler into polymeric composites.
The methodology consists of a literature review and three experimental phases: identifying and evaluating various food waste sources for the use as fillers, optimizing grain size and composition of the recipe, and assessing the bestperforming filler combinations in facade panel designs regarding sustainability and structural merits.
Spent coffee and walnut shells were identified as promising fillers, while the shells of cacao beans, de-oiled coffee
grounds and cherry pits did not perform well as fillers. The walnut shell composites, especially those with 55% filler of a blend of different grain sizes, resulted in the most promising balance between of mechanical properties and filler content.
The results indicate that walnut shell-based composites exhibit promising structural characteristics and a lower carbon impact compared to conventional facade materials. However, further research is required to explore their potential in other applications. This project illustrates the viability of using bio-composites with waste-based fillers in building products, presenting a sustainable alternative to traditional materials.
Over all is the use of bio-waste from the food industry as filler material for bio-plastics a promising way to reduce the need for new material mass and lower the carbon impact of polymeric materials.
WASTE-BASED GRANULAR FILLERS
BIO-POLYMER MATRIX
Furan Resin
• Thermo-set resin
• Heat and UV-Resistant
• 100% Bio-based
• Derived from (waste) Bio-mass
• Dark brown colour
Tutors
Lara Neuhaus
Colour variations of samples in sunlight
Different filler grain-size brackets
Decorative 3D-moulded tile
Process of perparing samples
Various samples and filler materials
Cacao Bean Shells
Co ee Grounds
Fruit Pits
Nut Shells
Flexible Formwork: A TextileCentric Approach
This thesis explores the use of CNC-knit textiles as flexible formwork for concrete construction. The research aims to develop a pattern-specific knowledge base that can support a more precise and informed design process for creating CNCknit flexible formwork. Traditional concrete construction is materially intensive, wasteful, and highly polluting. This research focuses on KnitCrete, a building technology that uses CNC-knit textiles to shape concrete into complex, efficient structures without the need for rigid formwork, thereby reducing material consumption and waste.
The research is structured into three main phases. In the first phase, a pattern repository is developed which catalogs 19 different knit patterns. These patterns, sourced from knitting standards and translated to Model9 software, are knitted on a flatbed weft knitting machine and carefully documented. Gauge calibration tests contribute to a detailed analysis of pattern behavior. In the second phase, each knit pattern is
tested under hydrostatic loading to observe how it deforms and adheres to concrete. 3D scanning is employed to analyze the principal curvatures of the resulting forms and draw pattern-based conclusions. The third phase explores the strategic combination of different patterns to create innovative architectural components inspired by existing shell structures.
A key outcome of the research is that the choice of knit pattern greatly affects the physical behavior of a textile under concrete loading as well as the structural and aesthetic properties of the cast form. Overall, this research provides a robust foundation for future studies in the field of CNC-knit textile formwork. It bridges the gap between textile engineering, material studies, and architectural design, offering a replicable approach for exploring the potential of this innovative construction technique. By advancing our understanding of knit pattern behavior, the study contributes to the ongoing effort to make concrete construction more sustainable and efficient.
Tutors
Lucy Flieger 2024 Dr. Stijn Brancart & Dr. Mariana Popescu
(Left) Close-up of knit textile adhered to concrete (Top Right) Flexibly formed element (Middle Right) Flexibly formed element (Bottom Right) Textile being removed from a concrete cast.
Beyond Noise
Despite its importance to public health, environmental noise and soundscapes are a forgotten topic in urban design. This study creates a framework for a design tool for soundscape design. The aim of this framework is to bridge the knowledge gap of soundscapes for urban designers. This is done by looking at the relationship between design elements and the percevied pleasantness in the soundscape. This pleasantness will be predicted by machine learning methods.
Machine learning methodologies present a promising approach for predicting and evaluating the efficacy of potential solutions aimed at improving urban soundscapes. By analyzing datasets that include environmental factors, noise levels, architectural designs, and community preferences, machine learning algorithms can help identify optimal interventions. Predictive models can also streamline decision-making processes by forecasting the potential impact of proposed solutions on soundscape quality.
This thesis investigated the complexities of urban soundscapes, examines the feasibility and limitations of using machine learning to predict viable solutions, and proposes a data-driven framework to guide decision-making in urban development. The goal is to enhance auditory environments in urban areas without the necessity of consulting soundscape experts.
The random forest regressor that was used for the prediction model in this research had an R2 of 0.41, explainig 41% of the variance of the model. This framework is tried and tested on a new location to verify its use. The prediction maps and section are a helpful tool in communicatig the value of the soundscape pleasantness and understanding the effect that the design elements have on its prediction.
Niroda Vitusha Smit 2024
Martin Tenpierik & Michela Turrin
TO3DPGS – The Future Of Glass
‘Development
This thesis explores the application of topology optimization for large-scale glass structures in architecture, addressing the limitations of traditional casting methods and exploring the potential of 3D printed glass. Previous research emphasized the importance of manufacturing methods, but highlighted the lack of transparency in topology optimized cast glass. This study uses 3D printing to overcome these challenges, focusing on the unique properties and manufacturing techniques of 3D printed glass, including the limitations of its brittle nature and different tensile and compressive strengths.
An extensive literature review provides a foundation for glass properties, manufacturing techniques and the principles of topology optimization. The research advances the use of SIMP methodology and adapts it to 3D printed glass constraints such as overhang, path continuity and nozzle size. Therefore, it incorporates an adapted layer-to-layer overhang filter and addresses the island effect and path control using advanced computing techniques.
The implementation of these methodologies is described in detail, with specific adjustments to the overhang angles and connection strategies for island structures. Testing within a predefined design domain evaluates the limitations and capabilities of the proposed solutions, culminating in the selection and 3D printing of a feasible design.
The results validate the approach and highlight the need for further research, especially regarding the anisotropy of glass layers.
This work demonstrates significant advances in structural glass architecture and paves the way for innovative applications of 3D printed glass.
Two physical glass models were produced through casting and waterjet cutting. The thesis was rewarded 9.5.
Pim Brueren 2024
Faidra Oikonomopoulou, Charalampos Andriotis
Render of bridge in British museum
Waterjet cutted prototype
Casted prototype out of float glass
Render of other outcome of the algorithm
Re-P-Tile
Recycling PVC into a façade Tile
“Waste does not start as waste; instead, it is useful material in the wrong place”. Increase in waste is relevant as global population and industrialization continue to rise, accompanied by higher standards of living. This has led to a rapid increase in waste production, projected to grow from 2.1 billion tonnes in 2023 to 3.8 billion tonnes by 2050, according to the UNEP’s Global Waste Management Outlook 2024. This surge highlights the critical need to reframe waste as a potential resource rather than mere garbage.
The report indicates that a significant portion of the world’s waste consists of biodegradable materials like food, garden waste, paper, and infinitely recyclable materials like glass
and metal. However, plastics, especially PVC, present a major recycling challenge due to their diverse compositions and contaminants. In Europe, the construction and demolition industry significantly contributes to plastic waste, particularly through PVC.
The thesis “Re-P-Tile” explores innovative ways to recycle PVC waste, especially from construction. It examines the recycling potential of PVC into architectural components, such as cladding materials. Experimental tests on the material’s properties led to the creation of a PVC sheet suitable for façade panels, offering a sustainable and aesthetically versatile alternative to traditional materials.
Conventional technique with other resins
Change in technique used for PVC resin
burns when heated releasing Chlorine, which can harm human health and rust machinery
pressure also releases heat as a thermodynamic response which can burn
Ramya K umaraswamy 2024
Dr.Telesilla Bristogianni & Dr. Olga Ioannou
Thesis ideation
Production methology
Mould
Shred
Shred
Focus on maintaining pure waste stream Melt
Soften
PVC
Applying
PVC
Cool to harden
Pressure pressed Product Product
Interactive Breezemaker
During this master’s thesis, the implementation of personalized airspeed for employees in open-plan offices during the summer was investigated, with the aim of improving comfort and productivity while conserving energy. By addressing dissatisfaction arising from limited control over environmental conditions, this research proposes a solution that integrates individual control over airspeed and distribution within openplan offices in temperate maritime climates.
Increasing the airspeed locally is an energy-efficient and effective way to dissipate heat from the human body in more humid climates. In this research, individual control is central. Employing a theoretical framework of perceived control, the study delineates environmental and perception domains crucial for effective implementation.
Through interviews with both end-users and experts related to the design and maintenance of such systems, and through
theoretical analysis, a design framework is developed, focusing on the domains of control, performance, and robustness. The study identifies essential design factors and criteria, distinguishing between must-have and optional elements. Notably, user preferences and environmental constraints shape the design process, highlighting the need for tailored solutions.
Key findings underscore the significance of a more holistic approach to user-centric design, considering factors like noise, draft avoidance, ergonomic placement of controls, and device flexibility, ensuring compatibility with the office layout’s adaptability.
This research contributes to the advancement of personalized environmental control systems, offering insights applicable to various workplace settings and climatic conditions.
Roelof ooistra 2024
Atze Boerstra & Alessandra Luna Navarro
View of an Acoustic Desk Partition with Adjustable Airflow, Featuring Controllable Buttons and an Intuitive Interface for Personalized Comfort
Interactive Breezemaker
Inspection and Maintenance planning of timber structures
This thesis investigates the integration of reinforcement learning (RL) techniques to enhance inspection and maintenance planning for timber structures, considering the increasing impact of climate change on their structural integrity. Timber is vulnerable to environmental factors such as temperature, moisture, and biological degradation. These vulnerabilities are exacerbated by climate change, leading to significant alterations in mechanical properties and thereby challenging the longevity and safety of these structures.
Given the dynamic nature of these challenges, traditional inspection methods, which rely heavily on manual processes and individual expertise, are insufficient. This research employs reinforcement learning to develop a predictive maintenance model that adapts to the evolving conditions affecting timber. The model aims to improve the accuracy and efficiency of inspections and maintenance planning, facilitating timely interventions to preserve the structural integrity of timber constructions.
The study specifically focuses on timber decay caused by fungi, assuming that all components are intact at the time of maintenance. This initial study does not consider other factors such as natural timber defects, direct decay from temperature, moisture, UV radiation, wood aging, extreme events, or
failures from timber joints. These are identified as areas for further development.
A case study of a historical timber Buddhist temple in Japan is employed to illustrate the reinforcement framework, demonstrating its potential applicability across global timber structures. This framework provides a novel maintenance strategy that focuses on repairing decayed components rather than undertaking extensive structural disassembly. In the study, the timber decay by the decay fungi is the only factor that is included in the framework as an initial study. It is also assumed that at the time of maintenance, all of the components are in an intact state. The other exclusions including the natural defects of timber, the direct decay by temperature, moisture, UV radiation, wood aging, extreme events, and the failure from the timber joints are suggested as further development
By leveraging advanced RL methodologies, this thesis not only contributes significantly to the field of timber engineering but also proposes a scalable and adaptable solution to enhance sustainable construction practices in response to evolving climate patterns. The exclusions and assumptions made in this initial framework outline a pathway for future research to expand the model’s comprehensiveness and applicability.
Recycled Composite Cast Glass Panels made of C&D waste
This thesis addresses the research gap in sustainable architectural construction practices by effectively using C&D glass waste. This project aims to transition architectural glass from an open-loop to a closed-loop system, emphasizing circularity in line with EU regulations. The novelty of this project lies in manufacturing composite cast glass panels using different types of glass waste, reducing energy consumption and CO2 emissions.
Studies from TU Delft already looked a bit into this topic. And started to analyse the potentials of recycled glass. However, a lot is still unknown about the optimal geometry and parameters of these composite panels and also have these affect the structural performance
Which led to the following research question:
“What is the effect of the different parameters in respect to the geometry and glass composition of composite cast glass panels to their overall structural performance made out of C&D flat glass waste?”
Four different types of experiments are used. Experiment type 1: homogeneous beams, focussed on a comprehensive analysis of three different type of homogeneous beams, type A cullet, type B cullet and type C cullet. Experiment type 2: composite beams, focussing on analysing the optimal ratio between surface and bulk. Experiment type 3: composite beams, focussing on the material composition of the bulk. And experiment type 4: composite beams, focussing on the material composition of the surface.
The methodology involved experimental design, mechanical testing, microscopic analysis, and optimization of beams with varying surface-bulk ratios and material compositions. Key findings show that composite beams with higher purity glass on the surface and lower purity glass in the bulk perform best structurally. The optimal strength ratio is 8 mm float glass on the surface with CSP pollutants in the bulk.
The main outcome demonstrates the feasibility of using recycled composite cast glass panels in architectural use, effectively reducing C&D waste and CO2 emissions while maintaining good structural performance. These recycled panels have the potential to significantly lessen environmental impact and integrate into existing building systems.
Tutors
Véronique van Minkelen 2024
Faidra Oikonomopoulou & Marcel Bilow
Recycled cast glass beams
Recycled Composite Cast Glass Panel
Enhancing Autonomy on Construction Sites through Implementation of Swarm Robotics as adaptive Material-Handling logistics system
This thesis explores the application of swarm robotics in addressing construction sites’ dynamic and complex challenges by using them as material handling units. Despite significant technological advances, the construction industry continues to face substantial challenges related to the human workforce including skilled labor shortages, high safety risks, and inefficient communication, all of which impede productivity and safety. Swarm robotics, inspired by the decentralized behaviors of social insects, offers a promising solution to these issues by enabling distributed task management and enhanced flexibility and robustness in dynamic environments.
The research specifically investigates the implementation of swarm robotics as an adaptive on-site logistics system for dynamic construction sites. Using Ant Colony Optimization, a path-planning swarm intelligence-based algorithm derived from the foraging behavior of ants, this study examines the algorithm’s applicability for enhancing material handling within the unpredictable conditions of construction sites. The study includes the development of an architectural scenario for a virtual simulation environment and practical experiments on two different architectural scenarios to evaluate the effectiveness of swarm robotics in real construction scenarios.
This study demonstrates the advantages of decentralized control in swarm robotics for enhancing operational efficiency, reducing safety risks, and improving communication on construction sites. The outcomes include the development of a Design-to-Construction workflow using a scalable and resilient construction logistics system that takes advantage of the unique capabilities of swarm robotics. This outcome has the potential to revolutionize construction practices through the integration of advanced robotic technologies and decentralized management systems.
Additionally, virtual experiments results as a part of the workflow indicate that achieving optimal values for parameters in the simulation, such as the required number of robots and pheromone evaporation rate, is highly scenario-dependent. This conclusion highlights the necessity of using the developed workflow that enables designers and construction groups to create their desired architectural layouts, simulate their construction process, and optimize them for further construction using swarm robots, effectively bridging the gap from initial design to final construction.
