Thesis : Adaptive Shading System

SMART SHADING SYSTEM: IMPROVING ENERGY EFFICIENCY OF A BUILDING USING KINETIC SHADING TECHNOLOGY IN MUMBAI

UNIVERSITY OF SHEFFIELD, SCHOOL OF ARCHITECTURE, MSC IN DIGITAL ARCHITECTURE AND DESIGN.

RASHI RAJNIKANT BHAVSAR REGISTRATION NO: 190184092 RESEARCH MENTOR: DR CHENGZHI PENG

ACKNOWLEDGEMENT I would like to express my deep and sincere gratitude to my research mentor Dr Chengzhi Peng for providing invaluable guidance throughout this research. His dynamism, vision, sincerity and motivation have deeply inspired me. He has taught me the methodology to carry out the research and to present the research works as clearly as possible.

Furthermore, I would like to thank Dr Tsung-Hsien Wang for his expertise in parametric architectural geometry that was the driving force behind my work. I would also like to thank him for his friendship and empathy while teaching me.

I am grateful to Prof Peter G Keogh for mediating and helping me relate the knowledge of my mentors effectively.

Last but not least, I would like to thank the entire University of Sheffield for their continued support and proactivity in assisting me. All the staff members have shown immense support while helping me channel my efforts into my thesis.

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ABSTRACT The general use of glass on a commercial building, especially in a hot and humid climate zone has always been a controversial topic of discussion. Through the faรงades, solar gain tends to increase the HVAC system's load significantly. This raises serious concerns over the design methodology of commercial buildings in Mumbai.

This paper focuses on computational design tools to craft an authentic solution to a persistent issue, i.e., 3D modelling with Rhino and machine learning with Grasshopper, ladybug, and honeybee plugins for weather analysis and PV calculations. Through the advanced architectural tools at hand, the newly devised shading system and PV integration will mitigate the solar heat gain making the building more energy-efficient. The methodology limits solar irritation in a commercial building by designing a prototype using a solar tracking device with multiple variations while evaluating each module's performance.

The most efficient module design is for an existing building in Mumbai. The proposal shall further be testing the different parameters affecting the efficiency of the system. Integrating Photovoltaic is a significant factor in making the proposal energy efficient.

The paper opens new design areas and investigates strategies with an active shading system and integrated PV to make structure energy-efficient and provide a reasonable solution to the use of glass faรงade commercial buildings in Hot and humid climate zone.

Keywords: Building envelope , adaptive shading sytsem , Integrated Photovoltaic, Mean Radiant temperature, Occupant comfort.

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Table of Contents ABSTRACT………………………………………………………………………….…………………………2 CHAPTER 1: INTRODUCTION………………………………………………...........................6 1.1 BACKGROUND……………………………………………………………………………..6 1.2 LOCATION…………………………………………………………………………………….6 1.3 RESEARCH OBJECTIVE………………………………………………………………….7 1.4 RESEARCH STATEMENT…………………………………………………................7 CHAPTER 2: CASE STUDY………………………………………………………………………………8 CHAPTER 3: METHODOLOGY..…………………………………………...............................9 3.1 GENERAL APPROACH……………………………………………………………………9 3.2 PHASE I………………………………………………………………………………………..10 3.3 PHASE II………………………………………………………………………………………..10 3.4 PHASE III……………………………………………………………………………………….10 CHAPTER 4: DESIGN PROCESS……………………………………………………………………….12 4.1 BACKGROUNG……………………………………………………………………………....12 4.2 COMPUTATIONAL DESIGN……………………………………………………………..13 CHAPTER 5: FINAL PARAMETRIC MODEL……………………………………………………….16 CHAPTER 6: RESULTS……………………………………………………………………………………..19 6.1 MUMBAI WEATHER ANALYSIS………………………………………………………..19 6.2 MODEL ANALYSIS…………………………………………………………………………..20 6.3 ADAPTIVE COMFORT……………………………………………………………………..20 6.4 DISTANCE FROM THE FAÇADE………………………………………………………..21 6.5 PHOTOVOLTAICS…………………………………………………………………………….21 CHAPTER 7: PROJECT OUTPUT ……………………………………………………………………..23 CHAPTER 8: DISCUSSION AND CONCLUSION…………………………………………………25 8.1 DISCUSSION AND CONCLUSION…………………………………………………….25 8.2 LIMITATIONS OF THE STUDY………………………………………………………....25 8.3 IMPLIMENTATIONS FOR THE FUTURE STUDIES………………………………25 REFERENCES………………………………………………………………………………………………….26

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List of Figures

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FIGURE 1: Location Details…………………………………………………………………………………………………..7 Source(google.com/maps)

FIGURE 2: Al Bhar Towers…………………………………………………………………………………………………….8 Source(www.glassonweb.com/article/evaluation-adaptive-facades-case-study-al-bahr-towers-uae)

FIGURE 3: Details ………….…………………………………………………………………………………………………….8 Source(www.glassonweb.com/article/evaluation-adaptive-facades-case-study-al-bahr-towers-uae)

FIGURE 4: Adaptive Modules……………………………………………………………………………………………….8 Source(www.glassonweb.com/article/evaluation-adaptive-facades-case-study-al-bahr-towers-uae)

FIGURE 5: General Approach ………………………………………………………………………………………………9 FIGURE 6: Computational workflow ……………………………………………………………………………………9 FIGURE 7: Building Location………………………………………………………………………………………………..12 Source(google.com/maps)

FIGURE 8:Prototype …………………………………………………………………………………………………………..13 FIGURE 9: Prototype Design ……………………………………………………………………………………………….13 FIGURE 10: Design Variables ………………………………………………………………………………………………14 FIGURE 11: Graph……………………………………………………………………………………………………………….15 FIGURE 12: Test Model ..…………………………………………………………………………………………………….15 FIGURE 13: Test Analysis ..………………………………………………………………………………………………….15 FIGURE 14: Parametric Modeling……………………………………………………………………………………….16 FIGURE 15: Parametric building model………………………………………………………………………………16 FIGURE 16: Indoor Environment ……………………………………………………………………………………….17 FIGURE 17: User-Interface ………………………………………………………………………………………………..17 FIGURE 18: Solar Heat Gain ………………………………………………………………………………………………18 Source(Development of empirical models for estimation of global solar radiation exergy in India)

FIGURE 19: Solar Radiation Analysis ……………………………………………………………………………..….18 FIGURE 20: Solar Radiation Analysis ……………………………………………………………………………..….19 FIGURE 21: Adaptive Comfort ……………………………………………………………………………..…………..19 FIGURE 22: Solar Radiation Analysis ……………………………………………………………………………..….20 FIGURE 23: Indoor Comfort …………..……………………………………………………………………………..….21 FIGURE 24: Analysis…………………………………………………………………………………..……………………..21 FIGURE 25: Power generation annually …………………………………………………………………………….22 FIGURE 26: Application Model ……………………………………………………………………………..………….23 FIGURE 27: Interior view of the Building …………………………………………………………………………..23 FIGURE 28: Rotation Details ……………………………………………………………………………..………………24

List of Tables TABLE 1: Calculations ……………………………………………………………………………..………………………19 Source ( R.V.Simha , Thermal Comfort in India, 2012)

TABLE 2: Details of the Orientation…………………………………………………………………………………24

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CHAPTER 1: INTRODUCTION 1.1 BACKGROUND: In recent years, sustainability and reducing primary energy usage has become a significant factor in the construction industry. The building industry contributes to 6% of overall greenhouse gas emissions (2010) that has resulted in a new design goal, i.e., "carbon neutral" or "zero-energy buildings." Generating a renewable source of energy, solar energy, helps to achieve the set goal by integrating PV to the building system. Additionally, optimizing the energy consumption of the building will contribute significantly to reducing primary energy usage.

Improving indoor comfort contributes significantly to energy optimization by reducing the primary energy consumption in a building. For instance, if we reduce solar heat gain to improve the indoor thermal comfort in a building, then we will directly reduce the HVAC system load hence sustainably contribute to energy optimization.

The building envelope plays a significant role in improving the appearance of a structure aesthetically while enhancing and improving its energy performance and occupant comfort.

A building's shading system can control factors such as glare, natural lighting, and solar gain while reducing the electrical demands of heating and cooling inside a building. Traditionally, designers used passive building envelopes, but with the recent advancement in technology, we have different active building types, such as smart glazing systems and kinetic shading systems.

1.2 LOCATION: Mumbai, India's financial capital, is located in Maharashtra and is climatically categorized as a hot and humid city. The city is the commercial hub of India. The architecture of the city is an amalgamation of different styles ranging from art deco to modern. The colonial history in India has created an architectural diversity in the city.

Over the years, we have observed a dynamic shift in architectural style towards modernism due to the city’s commercial development. As a result, there has been a dramatic increase in the construction of multi-story structures and skyscrapers.

Glass is an ideal façade material for tall buildings as it can create large transparent screens, roofs, and floors. Using glass also has architectural advantages such as construction lightness, transparency, and large window spans. Consequently, glass façade s have globally become the ideal choice for tall buildings. However, the use of glass façade in tropical climates such as Mumbai has been a topic of discussion for decades. According to a study by Bharathi Vidyapeeth University, Pune, a glass façade caused up to 30% of solar heat gain in the Jet Airways headquarters Mumbai. This paper shall focus on solving the problems mentioned above.

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FIGURE 1: Location details – Bandra Kurla Complex ,Mumbai, India.

1.3 RESEARCH OBJECTIVE: The study aims to design a smart shading device for a hot and humid climate. The idea revolves around minimizing the solar heat gain of an office building by integrating it with a sun tracking device. For further energy-efficiency, PV is incorporated into the shading system to generate solar power.

To achieve this goal, we need to design a smart shading prototype which can rotate according to sun position and test the idea with different variation to get the optimal result in reducing solar heat gain. At the same time, we shall analyze the amount of energy produced with the integrated PVs. Specific Objective: • To design a prototype to test the panel rotation according to sun position.

• To test the design variables for the rotating panels.

• To design a computational workflow for the parametric geometry model • To test and analyze the environmental effects on the parametric model.

• To calculate the power generated by Integrated Photovoltaics

1.4 RESEARCH STATEMENT: Design an energy-efficient smart shading system for a commercial building in Mumbai (Hot and humid Climatic Zone), by optimizing the solar radiation gains and improving the occupant comfort. Additionally, making it sustainable by generating renewable power.

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CHAPTER 2: CASE STUDY Adaptive façades are efficient in reducing solar irritation while adding to the sustainability factor. An adaptive façade in the Al bahar towers, UAE is an ideal example. The building envelope adopts a traditional Islamic architectural element called "Mashrabiya.“

FIGURE 2: Al Bhar Towers – “Mashrabiya”

FIGURE 3: Details – Mechanism detail (Adaptive module)

It is a wooden lattice screen, designed to achieve privacy and environmental control. The project is primarily an office high-rise (Bank) with a total project area of 56,000 square meters. It is a 29-storey structure with a height of 145 meters. The two towers, are located in Abu Dhabi city, UAE. The two towers' glass curtain walls are separated, from the adaptive shading system with the help of movement joints. The shading system operates through automation and is computer-controlled to respond to optimal solar and light conditions. The adaptive shading units are grouped into different segments and are controlled with a sun tracking device that controls each segment's opening and closing, according to the algorithm. Each shading device comprises of a series of stretched PTFE panels, driven by a linear actuator. The actuator operates the opening and closing once per day, based on a programmed algorithm sequence to prevent direct solar radiation. Under extreme weather conditions or high wind storms, a series of sensors on the building envelope sends its logged signals to the control unit to open all units. Siemens technology is used with preset controls to follow the sun's path throughout the year to operate the adaptive units. The system updates every 15 minutes using a light meter and an anemometer on the roof. In the case of weather events, the automated program gets overridden. The project has been coordinated between engineers, architects, and other authorities that use BIM modelling tools, and have actualized a series of innovations. It was a successful collaboration between the client, design team, and builder. The “Mashrabiya” concept and its implementation are groundbreaking. Moreover, the towers have succeeded as an iconic landmark. The design team pushed design boundaries and set new standards for quality in the AEC industry.

FIGURE 4: Adaptive Modules – Framework

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CHAPTER 3: METHODOLOGY 3.1 GENERAL APPROACH: The main objective of using a shading system is to reduce solar radiation, thermal gains and improve visual and indoor comfort. The passive shading system is cost-effective, though it has various limitations, dealing with location, context, buildings massing, and nature. In contrast, the adaptive shading system is expensive but adjusts to any climate/ weather.

Designers have a limited role in sustainable design when this technology is applied.

The problem mentioned above indicates the importance of coming up with a workflow that can invite more architects to become conscious regarding their design choices using the new design tools and new exploration forms. As we develop the workflow, we need to take an approach that can take design further than aesthetics and focus on factors such as climate responsiveness and occupant comfort.

In order to test our idea to design a smart shading system with integrated PV, we need to develop a computational framework that can test and analyze the adaptive shading system.

We must break the framework into specific tasks such as designing the shading system modular array, testing the modules with different sets of parameters to achieve the best results, and performing environmental analysis to check the design's sustainability element.

Figure 5 shows the general approach to design the workflow.

FINAL DESIGN GEOMETRY

PROTOTYPE DESIGN

DATA COLLECTION

DESIGN TESTING

TESTING ANALYSIS

PHASE II :

STIMULATION

PHASE II :

PHASE I :

PROTOTYPE DESIGN

VISUALIZATION RESULT ANALYSIS

FIGURE 5: General approach – Design Methodology

Stage I

Stage II

Stage III

SITE DATA

PARAMETRIC MODELLING

ENVIRONMETAL ANALYSIS

ELETRIC POWER GENERATION (PV PANEL)

VISUALIZATION

RESULT ANALYSIS

WEATHER DATA

Data collection

Design Process

FIGURE 6: Computational workflow - Process

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3.2 PHASE I: The selection of the location is one of the most crucial factors in this design. The concept of applying a building envelope on an existing structure first requires us to identify a building considering certain factors such as location, building typology, and climatic zone.

3.3 PHASE II: Design - Prototype: In this phase, to understand the computational workflow's basics and workability, we must first evaluate it by developing a modular prototype. The prototype is to test the design's responsive aspect, i.e., the panel rotation according to the sun position. The building's prototype will allow us to develop shading devices according to the project's conceptual needs, such as the level of responsiveness according to the building's general concept and the desired level of customization.

Simulation: To develop an adequate smart shading system, we must first test the primary design prototype with different design variables. The following computational workflow tests the design variables and gets the optimal result output. The design variable that can achieve the best result, in reducing the solar heat gain inside the structure, will then be applied to the main building. Figure 6 shows the details of the workflow.

3.4 PHASE III: Design: The developed computational workflow, while designing the smart shading system, is categorized into different stages. The final building model will consist of the tested prototype. The first step is to collect data from the site and environmental data. We move forward by designing a computational model of the site-building selected. While designing the building, we need to keep in mind the site constraints, building material & microclimate.

The virtual 3D model of the building developed is done so by using the Rhino – Grasshopper software.

Once we define the geometric approach, we can manipulate the design variable according to the user requirement. We shall test the shading devices' capability to perform parametric features such as rotation, distance from the façade , and scaling towards a direction. This will help the user understand the implications and feasibility of the shadings' geometry, in terms of design, improving the functionality and capability of adaptation of the system to determine the environment essential in the methodology's following steps on constrained parameters.

Simulation: The model showcases the relation between the inside faces of a model room's surfaces, reacting to the sunlight and solar radiation allowed into the interior, and the effect of shading devices as the regulator for lighting performance. Light reflectivity, glare, and energy absorbed through the generation of metrics can help the user perform a series of analyses for indicators at this workflow. To achieve accurate results, the model has to be computerized, into three different aspects: zones, decomposition of surfaces into 10

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construction elements, and material assignation. The specific data is provided to the computational workflow to get the desired accuracy. The simulation investigates solar radiation analysis and occupant comfort in detail using the designed workflow. Once we analyze the results of the stimulation, we proceed towards optimization.

Optimization: To perform optimization, we use the computational tool grasshopper along with the ladybug and honeybee plugin. To get optimum results Energy Plus is used. The design variable is changed to get desired results with the change in different parameters such as the rotation angle of the shading device and the faรงade 's distance. The results will show us the level of optimization our model can achieve.

Visualization: We finish analyzing the building model to check the energy performance. To be aware of the management's capabilities and to showcase the performance model results, we add visualization representation to the computational workflow. The values generated for the indicators will still go through a post-optimization process where the designer's technical knowledge and creativity to use data interpretation will be determined to demonstrate the helpfulness of a shading device by using the visual representation of the parametric design.

Results: The building energy performance results will give a broader perspective on how the shading design performs, given that the design parameters might create substantial differences depending on their position. The model generates an assessment given the different degrees of communication complexity between statistical information and the 3-D environmental visualizations. These Visual results are studied to understand the performance of the design.

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CHAPTER 4: DESIGN PROCESS 4.1 BACKGROUND: Site location: To study the adaptive shading device, we have selected the site location in Mumbai, India. Mumbai is the largest metropolitan city in India and has been developing rapidly. BKC is the most significant commercial sector in the city. BNP Paribas headquarters, BKC, is the commercial building owned by BNP Bank.

Banking is the function of the building.

Leisure and refreshment provided on the 4th and 5th floor are essential to the building's functionality as well.

Building Details : Number of Floors: 12 Total Built-up Area: 12,381.336 sqm Building Type: Commercial building Distance from Railway Station: 1.2 Km Distance from Highway: 600m

FIGURE 7: Building Location – Distance from Major Stations

Weather Analysis: Due to the large scale of the land and its topography, India experiences diverse climatic conditions. Even though most of the country experiences a tropical climate, there is a wide variety of climatic conditions to consider.

The site is in Mumbai city which lies on the western coast of the country, resulting in a hot and humid climate. The city experiences a mean average temperature of 27.2 °C, while the average precipitation is 242.2 cm (95.35 inches). The mean maximum average temperature is 32 °C (90 °F) in the summer period while the winter period has a mean maximum temperature of 32 °C. Similarly, the average minimum temperature is 25 °C (77 °F) in summer and 18 °C (64 °F) in winter.

Mumbai is known to have three seasons. The city’s winter experienced between October and February has a temperature ranging from 15-20°C. During the peak winter-time, that is December to mid-February the temperature ranges from 12–19°C; 2.

The city’s summer experienced between March and May has an average temperature range of 30 to 27°C. During the peak summer-time, that is Mid March to 1st June week the temperature shoots up to 30–40°C with humidity being approximately 70-80%.

The city’s monsoon experienced between June and September varies significantly. The peak monsoon period between July & August has a temperature ranging from 24-29°C. Harsh winds, heavy rainfalls and thunderstorms are common during this time.

Mean radiant temperature and Adaptive comfort can be studied using the ASHRAE Std. 552010 Model.

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4.2 COMPUTATIONAL DESIGN: Prototype: The computational workflow designed will use Rhino 6 - 3D modelling software and Grasshopper to script the program. We also use ladybug and honeybee to perform environmental analysis. Figure 8 shows the workflow.

FIGURE 8: Prototype – Computational Workflow

The climatic data collected from weather station Mumbai 430030 (ISHRAE), is an integral part of the process. The epw file downloaded from the energy plus database is an additional requirement for the design.

The design geometry’s basic principle is to rotate the panel from the central axis while linking the rotation to the sun’s vector. Furthermore, the design functions on variables categorized as Constrained Parameters and Unconstrained Parameters. The import epw function used to import the weather file is done after the completion of the design geometry. The rotation of the panel using the sun vector, is linked with the design geometry. Figure 9 shows the final prototype.

Rotation At 45°

Rotation At 180°

Rotation At 225°

FIGURE 9: Prototype Design – Sunpath Diagram

Design Test: Firstly, the designed prototype tested in a single room with different design variables. The prototype design is the outcome of combining the conceptual idea of the shading devices as a final product, and the adaptation of such a system in the orientation rules for shading devices. This step looks at some parametric aspects of the model that could be considered, such as variant dimensions like depth, height, and rotation.

As proceed with the computational workflow, we categories the design process into different stages, as we see in figure 8. The first stage aims to design the 3D room model on which we shall apply the shading device. The objective of assigning the surface analysis point, is fulfilled at this point. The second stage is the application of the design skin, i.e.

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the adaptive shading device. The panel is to be designed with flexibility so that the user can change the length, width, height, and orientation to get the desired results. The rotation of the panel, is fixed from the central axis. The next stage is to develop the environmental analysis for the stimulation. We import the weather file 'Mumbai 430030 (ISHRAE)' from the energy plus database. To perform the study, we use the ladybug and honeybee Legacy version. The environmental analysis is supposed to investigate solar radiation, daylight factor, and indoor comfort on an hourly basis while performing the analysis with and without the adaptive shading device.

We are ready with the basic workflow at this stage, but to make the interface user-friendly, we will design an interface that makes it easier for the user to use the application. To do so, we use the grasshopper plugin Human UI. This interface's task is to collect information from the user to get the unconstrained parameter input. The interface shall also ask you for the epw file input and the type of analysis you want the program to perform, i.e., solar radiation, indoor comfort, or daylight factor.

The study aims to perform the analysis with three different Design variables by changing the length, weight, height, and orientation. We have categorized the design variables into three categories, long vertical, short vertical, and horizontal. As seen in Figure 10.

a) Long Vertical Louvers

b) Short Vertical Louvers

c) Horizontal Louvers

FIGURE 10: Design Variables – a) Long ,b) Short ,c) Horizontal

The long vertical louvres are a one-unit module. This modular array is applied to the design geometry of the model. The unit module is 350mm in width and 3000mm in height; 15 units are applied to the building model. The short vertical louvres is a two-unit module. This unit's dimension is 300mm in width and 1500mm in height; 30 units are applied to the building model. The horizontal louvres (1000mm width, 300mm height). All the design variables rotate from the central axis and according to the sun position.

The stimulation’s design variables shall be performed on the hottest day of the year and a different time of the day to investigate the adaptive shading system's overall performance.

The analysis is performed on 18 May at 8:00 am, 10:00 am, 1:00 pm, 6:30 pm, and 9:00 pm

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Long Vertical

Solar Radiation (W/hr2)

Solar Radiation (W/hr2)

Solar Radiation (W/hr2)

6:30 PM

1:00 PM

10:00 AM

Surface Point

Horizontal

Short Vertical

Surface Point

Surface Point

FIGURE 11: Graph – Illustrating Solar radiation Analysis at a) 10:00 AM b) 1:00 AM c) 6:30 AM

Figure 11 shows the results of the stimulation. As we look at all the stimulations, the chart compares the solar radiation (W/hr2) gain in the design geometry with and without the shading device. Looking at the chart, it is clear, as we compare the design variables, the one with optimal results is the long vertical louvres. In contrast, the horizontal louvre and analysis show the highest range of solar heat gain.

In conclusion, as we complete the assessment, we can see the design variable with signification optimization for solar heat gain and high performing shading device is the long vertical louvre system. The shading device reduces up to 30% of solar heat gain, significantly more than the other two design variables. Therefore, we have our final design geometry (Long vertical louvre) for the smart shading device to be applied as a building envelope on the BNP Headquarter building.

FIGURE 12: Test Model: Surface Point for analysis

FIGURE 13: Test analysis – Solar Radiation Analysis

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CHAPTER 5: FINAL PARAMETRIC MODEL As mentioned in chapter 3, the computational workflow is divided into 5 phases, as seen in Design figure 14.

Stimulation And Optimization (Parametric Geometry)

Photovoltaics Calculation

User-Interface

Visualization

FIGURE 14: Parametric Modeling – Computational workflow

Design: In this phase, the main focus is to define the building geometry.

We also take into consideration environmental factors and introduce the building location at this stage with a basic outline of the building’s massing and program. It is important to assign the location details at this point as we need to provide the weather data to analyze the façade for solar radiation.

Defining the massing of the building allows us to establish the conceptual need of the design goal. The parametric model also decomposes the building elements such as walls, roofs, slabs, and columns. This can be further used for alteration while providing design flexibility to the user, as a starting point of reference, to generate an adapted shading device concept.

FIGURE 15: Parametric Building Model – Building Geometry

At this point, we introduce the epw file from the energy plus weather database. The Mumbai based project is in Bandra-Kurla Complex. Therefore, we use Mumbai 430030 (ISHRAE) weather station data to perform the stimulation. The weather data will allow us to perform environmental visualization and energy performance, such as mean radiant temperature, sun path diagram, and so on. Additionally, sun path plays a significant role in linking the panel rotation with sun position. We analyze the building geometry to investigate the surface receiving maximum solar radiation hereafter we use of the information retrieved from the epw file, in combination with the shading device. Consequently, the designer can adjust the parametric model so that it can adapt to different conditions. The model’s functionalities, such as the link between the environmental data and the rotation of the panel, are to be scripted.

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Stimulation: The parametric model shall undergo stimulation to investigate the solar heat gain caused due to solar radiation.

We use ladybug, honeybee legacy version to perform the stimulations. The program uses libraries based on ASHRAE codes, which validate the inputs used in the simulations.

Based on the environmental data, we analyze the physical properties of the building model. This is why the precision of the building model is so important. The floor surface has points extracted to analyze the MRT and adaptive comfort observed per annum; We perform the stimulation without the façade to gather the environmental stimulation before the shading device is applied.

FIGURE 16: Indoor Environment – For solar radiation and occupant comfort analysis

Optimization: In this phase, we will program the environmental analysis and bring the MRT and adaptive comfort to optimization by applying the designed shading device. We use energy plus version 9.3.0 to perform the stimulation. Additionally, to reduce primary energy usage, in this step, we calculate the PV performance and power generated by the PV panels.

Hence, the ladybug tool is used (Photovoltaics surface). This component required multiple inputs from the program to generate the output. The reading is in KWh (unit) throughout the year. We will discuss the results in the later chapter. Figure 14 shows the details of the program.

Visualization: After we complete all the environmental analysis, it is important to provide an adequate visualization map to the designer. As we confirm the analysis, we finalize the reading, which is taken further in the program to present visualization. Not only do we achieve the analysis’ results, but we also investigate the outdoor environment and comfort level in the city of Mumbai. For this, we use the psychrometric chart for the visualization purposes.

User Interface: The designer must alter the duration for the environmental analysis is to take place. We use the plugin ‘Human UI’ to program the user-interface. The interface works by taking the input from the user and transferring it to the program. The epw file is also a user input provided to the program using the user interface.

FIGURE 17: User- Interface – Interface developed using human UI

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Theory Solar Heat Gain: Solar heat gain is associated with four major components - solar loads, direct radiation, diffuse sky radiation, and reflected radiation.

Direct radiation is the direct sun’s radiation reaching the Earth’s surface while following a straight path with no clouds in the sky.

Diffuse sky radiation is the sun’s radiation reaching the Earth’s surface after a direct sunray has been dispersed by the suspended particulate matter or molecules in the atmosphere.

Reflected radiation is attained sunlight that has been reflected off of elements, like the ground or the built environment.

Radiation can be usually visualized through radiation analysis, which will help the designer envision a gradient that effects of the solar loads on a building. Figure 19 shows the façade analysis done BNP Paribas headquarters.

FIGURE 18: Solar Heat Gain – Details

FIGURE 19: Solar Radiation Analysis – on the building façade

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CHAPTER 6: RESULTS 6.1 MUMBAI WEATHER ANALYSIS: Figure 20 displays the outdoor analysis on the model. As it is observed, The PMV ranges the highest from 8 AM-8 PM; The PMV is in the range of 24 째C - 43.5 째C throughout the year. As we can see, the PMV value is highest in April, May, June through out the day. Whereas, during other months, PMV is low from 9 PM - 9 AM.

FIGURE 20: Solar radiation Analysis : Outdoor radiation analysis - MUMBAI

We also look at the Adaptive comfort chart performed on the model, as shown in figure 21.

The diagram illustrates the Outdoor comfort rate experienced in Mumbai Annual hourly.

(Cold < 0 < Hot ). After observing the illustration, Mumbai annually experiences a hot climate. Furthermore, May has been identified, as the hottest month. Whereas, from Nov Feb, the city experiences cold weather.

FIGURE 21: Adaptive comfort - Mumbai

For Calculating Adaptive comfort, tn = 17.8 + 0.31.tm where tn (temperature corresponding to Thermal Neutrality) and tm = Outdoor mean temperature.

We calculate can comfort temperature using the above equation.

Table 1 displays the results.

TABLE 1: Calculation- Thermal comfort

The ASHRAE Comfort model standards, are used in the calculations, as per the study. The mean monthly temperature observed in Mumbai is >33 째C, while the fix comfort temperature is 28.째C (R.V.Simha) 19

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6.2 MODEL ANALYSIS: The design model analysis, was conducted to get the Heat map for Annual hourly ΔMRT (°C).

This is done to understand the solar gains in the indoor environment, through the glass façade , along with the optimization after applying the smart shading system. During the total occupied hours, i.e., 8 AM - 7 PM. As we see in Figure 13, the PMV is highest during the occupied hours. After careful observation, it is evident that the PMV is highest from April June. The PMVadj shows us promising results with optimization of up to 40%. Moreover, the temperature drops lower during the total occupied hour to around 29°C, bringing it close to the range of the comfort temperature range.

PMV

ΔMRT (°C) PMVadj

ΔMRT (°C) FIGURE 22: Solar Radiation analysis – a) Without the adaptive façade , b) With the Adaptive façade

6.3 ADAPTIVE COMFORT: Adaptive indoor comfort is investigated for the design model to understand in detail about the occupant comfort inside the building, with and without the smart shading system to analyze the level of optimization we have achieved by designing the shading device. For a detailed insight, figure 23 displays the reading for adaptive indoor comfort (0= cold, 1 = comfortable, 2 =hot). Looking at the illustration, it is clear that during the total occupied hour, i.e. (9 AM - 8 PM), the reading is at 2, making it hot for the occupants and otherwise during the day is at 1.20, making it a comfortable environment. The goal is to bring the reading in the range of comfort zone with the ICadj reading.

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IC

ICadj FIGURE 23: Indoor Comfort – a) Without the adaptive façade , b) With the Adaptive façade

6.4 DISTANCE FROM THE FAÇADE:

INDOOR COMFORT

The smart shading system's distance is a signification factor in understanding the device's energy performance. The analysis is performed at distances of 1.5m and 2m on 18th May, as it is the hottest day of the year. Looking at the line diagram in figure 24, we see that at 2m, it reduces up to 20% of the discomfort hour. At the same time, 1.5m proves to have higher rates of solar radiation. Looking at the results, we can finalize the distance of the shading system from the glass façade to be 2m for minimal solar radiation entering the building.

FIGURE 24: Analysis – At distance of 1.5m and 2m (Distance from the facade)

6.5 PHOTOVOLTAICS: The effects of integrated photovoltaics on the building shading system, are investigated in this process. The energy generated by the monolithic thin-film PV modules, in the orientation and rotation based sun-tracking device finalized earlier in the study, is investigated. To make the shading device energy-efficient, it is important to study the quantity of the energy generated by the PV panel, as seen in Figure 25. The diagram illustrates the energy generated by the PV (kWh) annual and monthly.

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Electrical energy (kWh month-1 m-2)

FIGURE 25: Power generation annually â&#x20AC;&#x201C; electrical power generation by the integrated PV on the panel

The maximum power generation is from March-June while the energy generated drops significantly from July â&#x20AC;&#x201C; Sept, due to heavy rainfall. Additionally, the reading improves in the month of Oct-Nov and marginally drops from Dec-Feb. We can see promising results as the device generates renewable energy while reducing the solar gain inside the building, improving the sustainability factor of the building.

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CHAPTER 7: PROJECT OUTPUT: The framework for the smart shading device is applied to the BNP Paribas headquarters.

With the device's energy performance, we can also see the aesthetical appeal the building envelope provides to the structure in Figure 16. The south façade of the structure has the PV integrated shading system. A total of 275-panel modules are applied on the glass façade , each module is of 0.45M width and 4M Height, and 60mm thick at a distance of 2m from the façade surface.

Without Adaptive shading façade

With Adaptive Shading façade

FIGURE 26: Application model – adaptive shading system

FIGURE 27: Interior View of the building

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Facing West Rotation - 225°

EVENING

Facing South Rotation - 180 °

Facing East Rotation - 45 °

NOON MORNING FIGURE 28: Rotation Details – At a) Evening , b) Noon , c) Morning

Orientation of the adaptive shading modules at 45 ° , At 10:00 AM

Orientation of the adaptive shading modules at 180 ° , At 1:00 PM

Orientation of the adaptive shading modules at 225 ° , At 6:00 PM

TABLE 2: Details of the orientation – Panel Orientations

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CHAPTER 8: DISCUSSION AND CONCLUSION 8.1 DISCUSSION AND CONCLUSION: The paper investigates the use of adaptive shading device in a hot and humid climate.

Designers tend to prefer using the traditional building envelope due to the lack of technology and study in the kinetic shading devices. The research displays a new approach to the Kinetic shading system and how it can provide energy efficiency to the building performance.

As mentioned earlier, we have witnessed a successful adaptation of the kinetic building envelope in structures like the Al-Bahar towers and the Q1 headquarters. The developed framework in this research brings additional functionality to the kinetic faรงade , i.e., Integrate PV system to the adaptive shading device. The advantage here is that as the shading device is sun responsive, the PV's performance to generate power becomes higher than the usual.

In conclusion, we can reiterate that the adaptive shading device brings a new approach to the building envelope. The reduction in solar heat gain inside the building is a unique alternative to improve the building's energy performance.

To achieve the most efficient design geometry, for the smart shading device, the study first investigated different design variables. The design with the highest performance to improve the occupant comfort was selected to apply to the BNP Paribas headquarters. It is important to note that precision was essential while developing the design framework for the building geometry's 3D model.

Furthermore, the study was able to achieve optimization by reducing the solar gains inside the building while increasing the occupant comfort in the work environment. The smart shading system also adds to the sustainability factor by generating renewable energy and reducing the grid's primary power.

8.2 LIMITATIONS OF THE STUDY: The application of the smart shading system requires the analysis of the physical mechanism. The physical mechanism to rotate the panel module according to the sun position is a crucial factor. However, with the lack of resources and time in hand, the study could not research the physical model.

8.3 IMPLIMENTATIONS FOR FUTURE STUDIES: Storing the generated renewable electricity is a field of study we can further look into, As it is a vast topic of research, Also as mentioned earlier the physical mechanism is an important aspect that can be researched in detail. The design project has potential for further development.

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REFERENCES Basharat Jamil (2019), Development of empirical models for estimation of global solar radiation exergy in India R.V. Simha (2012) , Thermal Comfort in India, Airtron Consulting Engineers Pvt Ltd Bangalore.

Luis D (2018) Building Envelopes in Warm Climates like Uganda, Jordan and Saudi Arabia Masri, Y. (2015). Intelligent Building Envelopes: Design and Applications. In Advanced Building Skins, Proceedings of the International Conference on Building Envelope Design and Tenchlogy (pp. 37-46). Graz, Austria: Institute of Buildings Construction, Graz University of Technology.

Review and statistical analysis of different global solar radiation sunshine models Renew. Sustain. Energy Rev., 52 (2015), pp. 1869-1880 Sergio Altomonte, Daylight Factor, University of Nottingham, Nottingham, UK. Olgyay, A., Olgyay. V (1957), Solar control and shading devices. Princeton University Press (London: Oxford University Press).

ASHRAE Standard 55-2010 (2010). Thermal Environement Standards for Human Occupancy.

American Society of Heat-ing, Refrigerating and Air-Conditioning Engineers. Atlanta,GA.

Arens, E., Hoyt, T., Zhou, X., Huang, L., Zhang, H., & Schiavon, S. (2015). Modeling the comfort effects of short-wave solar radiation indoors. Building and Environment, 88, 3–9.

D., S. K. (2017). CBE Thermal Comfort Tool. Retrieved from http://comfort.cbe.berkeley.edu/ Marino, C., Nucara, A., & Pietrafesa, M. (2017). Thermal comfort in indoor environment: Effect of the solar radiation on the radiant temperature asymmetry. Solar Energy, 144, 295–309.

Lai, D., Zhou, X., & Chen, Q. (2017). Measurements and predictions of the skin temperature of human subjects on outdoor environment. Energy and Buildings, 151, 476–486. ayathissa, P., Z. Nagy, N. Offedu, and A. Schlueter. (2015). Numerical Simulation of Energy Performance, and Construction of the Adaptive Solar Façade. Proceedings of Advanced Building Skin Conference.

Shady Attia (2018) Evaluation of adaptive facades: The case study of Al Bahr Towers in the UAE Marco Casini (2015) , Smart windows for energy efficiency of buildings.

D Malmquist and N. Sbar (2013) , "The Benefits of Dynamic Glazing" SAGE Electrochromics, Inc. 26

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Christoph F. Reinhart (2013), DEFINITION OF A REFERENCE OFFICE FOR STANDARDIZED EVALUATIONS OF DYNAMIC FAÇADE AND LIGHTING TECHNOLOGIES ANSI/ASHRAE/USGBC/IES. 189.1 Standard for the design of high-performance green buildings, Atlanta, GA, USA, ASHRAE standard, 2010.

Chris Mackey (2010), PAN CLIMATIC HUMANS Shaping Thermal Habits in an Unconditioned Society Cherif Ben bacha (2016), Effect of kinetic façades on energy efficiency in office buildings - hot dry climates H. Modin. (2014). “Adaptive building envelopes,” Chalmers University of Technology.

J. Majed and J. Alkhayyat. (2013). “strategy for adaptive kinetic patterns: creating a generative design for dynamic solar shading systems,” University of Salford Design.

K. Grijalva. (2012). “Associative design for building envelopes, sun control and shading devices” Arizona State University.

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APPENDIX A SR TYPE OF NO. DOCUMENT 1.

Journal artical

2.

Journal artical

3.

Journal artical

AUTHOR Johannes Hofer (2017)

MAIN FINDINGS

IMPLIMCATION

Evaluate the performance of different dynamic BIPV shading system configurations, as well as its sensitivity to faรงade orientation and module arrangement. The analysis shows, that there is a trade-off between tracking performance and mutual shading of modules.

Parametric modeling framework of solar insolation and electric energy yield for building integrated dynamic PV systems.

Cherif Ben Bacha (2017)

Examine and evaluate the effect and performance of smart faรงades in the context of the indoor thermal comfort and energy efficiency. These parameters are achieved by controlling the levels of solar radiation and by calculating shading element sizes for sun control in response to environmental changes.

proposed skin delayed the periods of solar penetration and potential glare to the indoor office building space achieved acceptable thermal comfort and illumination level.

Andrea G. Mainini (2018)

Calculation of the hourly effective radiant field (ERF) and mean radiant temperature (MRT) for an occupant near various faรงade systems and office layouts.

Allows the designer to predict more accurate thermal sensations of the occupants across the room at every hour of the year,

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SR TYPE OF NO. DOCUMENT 4.

Journal artical

AUTHOR Jaepil Choi (2017)

MAIN FINDINGS

study explores new ways to design an exterior louver. The study presents a parametric louver design system that is composed of three parts: analysis part, parametric louver design part, and optimization part. This system finds the best performing louver forms for any given site.

IMPLIMCATION

Parametric system calculates which louver form controls the direct solar radiation the best and offers a solution for the user.

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APPENDIX B SR NO.

PLUGIN

1.

Human UI

2.

VERSION FOUNDER First version Human UI 0.8.0.0 2017 Latest - Human UI 0.8.1.3 2019-Aug-05 The Developer: Andrew Huemann

First version Ladybug.0.0.64 and Honeybee 0.0.61 2018-Oct-06 Latest -Ladybug LADYBUG & 0.0.69 and HONEYBEE Honeybee 0.0.66 [Legacy Plugins] 2020-Aug-27 The Developer: Mostapha Sadeghipour Roudsari

FUNCTION

Extends Grasshopper's ability to create User Interface to simplify the applications and makes it easier interface for someone using the program.

Extends Grasshopper's ability to perform various Environmental stimulations on a parametric model, This tool has various sub versions â&#x20AC;&#x201C; Butterfly, Honeybee, ladybug etc. This tool gives the user the opportunity to use energy plus weather database and import the epw from selected location.

Softwares Used For the Program

Rhino 3D Model Version 6 (https://www.rhino3d.com/download/rhino-for-windows/6/evaluation) Grasshopper (Rhino Plugin - Default) Plugins: As mentioned in the table To use the Advanced Honeybee tool , Set installations are needed: Radiance 5.2 Official Open Studio 3.0.1 Energy plus 9.3.0 DAYSIM 4.0

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