The Constructing industry around the world is growing exponentially. In the Netherlands itself there is a need of constructing 1 million affordable new homes by 2030. Such a massive demand for new buildings has given rise to a need for a solution for mass customization of architectural configurations. Simple repetition or a badly configured building is not ideal and can lead to a lot of social and environmental problems. Generative Design can offer a digital solution for this mass customization problem. It can utilize the power of Artificial intelligence in design to generate a system where users can create custom solutions rapidly. The second part of the customization problem is the user participation in determining the customization goals. More often than not the end users of the built space do not get an opinion in the configuration process and this leads to unsatisfactory and undemocratic design solutions producing urban inequality. In this thesis a comprehensive digital solution by means of a digital platform is provided in an attempt to solve the 3D layout problem in a participatory manner. The platform built in the thesis is intended for designing Open buildings at a scale of support structures. The concept of Open buildings calls for separation of the structure and the infill layer making the buildings open for modification and customization. The 3D-Layout configuration problem in its full sophistication is a classical example of a wicked problem. So, in this thesis the problem is methodically broken down into a group of nested smaller problems with local goals to achieve the global spatial planning goals and various computational methods are tested for solving the problems. The nature of the smaller problems is often iterative hence a robust decision support system is also designed for stakeholder participation and control over the problem-solving method. The computational methods used in the thesis are inspired from various other disciplines like Computer science, Industrial engineering, Operations research, etc. where they are used to solve similar problems in their respective domains. Techniques like Multi-agent systems, Multi-criteria decision analysis, Techniques for solving the clustering and packing problems in operations research are explored to solve the various nested smaller problems in the 3D-Layout problem. Finally, all the methods developed in the project are used to solve a test case for the design of a mixed used Open building consisting of Housing and Commercial spaces in the Buiksloterham region which is one of the first circular neighbourhoods in Amsterdam to showcase the potential of the platform and the feed forward design process developed in the thesis.

The demand for lower construction costs comes at the price of duplicating architectural designs. As a result, the misperception that modular architecture is repetitive prevails. However, the developments in computational design and MMC (modern methods of construction) can suggest a standardized manufacturing approach to provide mass customization. The research explores the computation of Modular building envelope systems using the Boolean marching cube algorithm under the premise of a ‘participatory generative design framework’ of the 'GO-Design' developed by Pirouz Nourian and Shervin Azadi [1]. In this project, (1) a set of architectural tilesets is developed that incorporates mass-customization by providing the potential for generating various configurations, and (2) a prototype of an interactive digital tool is established to enable future inhabitants to customize the configuration of their modular houses based on the predefined tileset. The algorithm is developed and applied in the Rhino & Grasshopper environment. The BMC algorithm reads the voxels' labels pertaining to each cube's vertices (a collection of 8 neighboring voxels) to load and choose the corresponding tile from a predefined tileset. The project's focus is the design of such a tileset, its engineering consistency, and architectural coherence. As an input, a voxelated massing will be the input, possibly later accompanied by a colored zoning scheme. and the output will be a modular architectural assembly. This workflow is envisaged to become a procedural component of a Configure, Price, & Quote (CPQ) system for the industrialization of mass customizable housing.

In 2018, a new standard was released for daylight in buildings: EN 17037. This is the first standard for daylight in buildings for Europe. In the Netherlands it will replace the NEN 2057. The determination method for daylight provision for EN 17037 is based on internal illuminance. Additional ambitions for the design quality factors: view, direct sunlight and the prevention of glare have been added to the standard. A sustainable design is all about balancing daylight performance and energy consumption. Large windows will cause the building to overheat and use too much cooling energy. Too small windows will result in low levels of daylight availability and visual comfort. For this reason, it was still unclear whether it is possible to achieve these new recommendations for daylight and at the same time meet the energy requirements for Green building certificates, such as BREEAM and LEED. The main aim of this research was therefore to investigate how much influence the European standard has on the energy consumption of a typical office building and whether the requirements for BREEAM and LEED can still be met. The analysis shows that the European standard has an influence on the daylight and energy credits for BREEAM and LEED. For the daylight credits this standard has a positive influence. For the minimum performance level for daylight provision for the European standard this is not yet enough to meet the requirements for daylight provision for BREEAM and LEED. For BREEAM and LEED, the variants only meet the requirements if the medium and high recommendation levels for the European standard are met. However, the ASE is often too high for a design that meets the high performance level for EN 17037. It should also be taken into account that when a certain performance level for daylight provision has been achieved for the European standard using method 2 (based on internal illuminance per hour for a typical year) this same variant will usually score lower with method 1 (based on daylight factors). The energy consumption goes up when the recommendation level for the European standard is higher. When comparing the average energy consumption of variants with the minimum performance level for the European norm with the high performance level, the total energy consumption goes up 8.33 kWh/m2 . These values can be higher or lower with different orientations. To reduce the negative impact of the European standard on BREEAM and LEED, certain parameters for the design can be chosen differently. The most important parameters for meeting the high-performance level and minimizing primary fossil energy consumption is the window-to-wall ratio and width/depth ratio. To find a balance between daylight and energy consumption, the optimal width/depth ratio is between 1.33 and 0.75. The optimum window-to-wall ratio is between 40% and 60%. To reduce the cooling consumption and ASE even more, designers can consider the introduction of overhangs in the façade, or other interventions that reduce the window SHGC.

The typical solar energy potential simulation workflows used in the AEC industry require an abundance of information regarding the detailed geometry and materialization of the design. These requisites render them incompatible with early-stage design decision-making pertaining to form-finding. By performing solar energy potential simulations at the pre-conceptual design phase, the necessary time for later-stage environmental assessments and design improvements is reduced considerably, while building designs with high performance but low environmental footprint are attained. This research proposes a computational framework to navigate voxel-based morphologies of building envelopes in a performative design space. It investigates a generative workflow through an embedded multi-criteria optimization of solar-related indicators, which are mapped in a solar energy potential field. The formulation of this field consists of an a priori assessment of the solar energy potential in every discrete volumetric unit (voxel) and a vectorized description of the interdependency of them. The astronomical size of this solution space renders the use of metaheuristic methods more appropriate. More specifically, a subtractive strategy that incorporates an MCDA approach is being applied in order to reach user-defined optimization targets. The novelty and potential of the proposed methodology lies in streamlining the early decision making process for designers and architects and expanding the morphological possibilities. Through this framework, the performative design space is effectively navigated and nearly optimal solutions are generated, to act as suggestive mechanisms for informed architectural decisions.

With the advent of Computer-Aided Design, the design and fabrication of complex free-form shells have become easier to achieve. However, this results in extensive usage of custom-made formworks for the production of shell components and falseworks which provide support for the shell during the construction process. Therefore, a modular design method is proposed for generating form-active spatial structures out of stackable blocks of a few types, having in mind its potential applications such as housing. Instead of shells, spatial masonry structures are thus the main consideration in the design process considering building on top of a vaulted ceiling. By designing a 3D interlocking grid and introducing a four-step topological design that is coupled with structural verification processes based on finite element modelling and discrete element modelling simulations, the geometry of interlocking stackable modular blocks can be automatically generated for constructing such spatial masonry structures. The proposed method ensures that the designed vaults are modular, reconfigurable, and self-supporting during construction, thus increasing the efficiency of mass production while allowing for combinatorial mass customization in designs.

This thesis concerns the application of different multi-objective optimization (MOO) methods and strategies for finding the optimal envelope for a given building plot and lighting performance indicators. More specifically, the PV potential and daylighting potential of the building are maximized using different optimization solvers. Auxilliary objectives are introduced to constrain the model to a certain compactness and size. The method utilises an existing data framework called TopoGenesis and solves the problem using the PyGmo library. A ray tracing is used to find all possible collisions between the objective test points and the building mass and environment. The problem is first presented as a standard integer programming problem, but solving this problem is not feasible if complexity needs to be kept at a reasonable level. An alternative method of continuous optimization is therefore proposed that uses (meta)heuristics to find an optimal solution for maximizing the objective functions. The occupation status of the massing is used as inputs for the decision variables. After the application of this method on small scale toy problems, a few of the design options are selected and evaluated by their performance indicators, as well as the measure with which the option makes sense from a more traditional design perspective. The comparison of the performance and results of both methods give insight into the recommended workflow, settings, and pitfalls for finding an optimal solution to a multi-criteria design problem with visibility objectives. From the initial results, the Non-Sorted Genetic Algorithm seems to be the best option for solving these types of problems, and the PV potential objective is validated. The daylighting potential objective performs less satisfactory and suggestions are made on alternative approaches for this metric.

The emic structure of space heavily depends on the social, cultural, and economic context (Hillier, 1989). Yet, many social housing projects disregard this crucial aspect by standardizing the configuration of space (Sanoff, 2000). To be able to avoid the standardization of configuration and benefit from the cost-efficiency of mass production (Pine, 1993, Tseng, 2007), we propose a serious game that utilizes participatory design and gamification to facilitate co-creation and enable people to re-enforce their social and cultural preferences in the configuration of the spaces while benefiting from the economic viability of a mass-produced kit-of-parts. The proposed construction game is a mix of board game with Lego pieces. Each Lego piece have different possible dimension depending on the function which is being represented. The gameboard represents the plot on which the housing will be implemented. During the Planning phase of the game the players will use those components to generate a draft configuration that translates their preferences and requirements. Later in the Configuration stage, the game mechanisms are introduced to engage the players to communicate and discuss their ideas, make trades and commitments between them. The proposed configuration comprises fully modular pieces, so it could be easily manufactured and replicated. A test case base is conducted to further analyse on how effective the game has been in facilitating the participation in housing configuration, without the obstacle of technical knowledge of the architectural design and construction.

The injection of renewable energy into the grid requires meticulous planning and execution due to the unpredictable nature of weather and in-turn the energy generated by these sources. Moreover, the inclusion of grid-independent energy generators requires accurate tools to predict energy yield in order to simplify matters such as grid-congestion management. One such tool useful to compute solar energy yield, which is under development, is the PVMD toolbox from the PhotoVoltaic Devices and Materials research group within the Delft University of Technology. This toolbox, which is completely based on MATLAB , allows users to specify parameters ranging from the micro-scale (such as the chemistry and characteristics of a single cell) to the macro-scale (such as the electrical parameters of the whole system). However, in its present version, the toolbox can simulate the yield only for simple systems, such as a single PV panel without any obstructions present nearby. This makes it incompatible to solve complex problems such as models with solar panels installed in the built environment. Therefore, the primary focus of this thesis is on the optical side of the PV simulation, by enabling the toolbox to precisely compute reflected component of irradiance and include shading effects on modules from nearby objects in the scene. This functionality will help consider the presence of features such as dormers, chimneys and highly reflective surfaces present in urban environments which contribute to solar power output. To achieve this, attention was paid towards the formats and sources of geometric data (3D objects in particular) which could be used as an input in the toolbox. Once the data format was selected, the 3D object is parsed into a MATLAB readable format and refined in order to preserve geometric information. Afterwards, the scene was completed by enumerating the geometric data of the solar cells and placing them beside the object or on an external surface of the object. Optical properties were then obtained in the form of spectral reflectance data from NASA’ ECOSTRESS Library and converted into the appropriate format to assign these material properties to the geometries. This Opto-geometric data is then parsed back into a file which can be read by RADIANCE, a visual rendering software capable of backward ray-tracing. This ray-tracing technique is used to obtain the irradiance available for each solar cell at a given time instant. The developed workflow is validated by comparing it with real data stored at the PV Monitoring Station within the TU Delft Campus. For the given data-set, the mean percentage error is computed to be 1.89% , with a standard deviation of 12.49%. This proves that the proposed workflow is suitable to visualise shading performance and the effect of reflected irradiance. This model can be further improved by considering parameters such as spectrally responsive albedo and inclusion of other geometry formats. The outputs from this project can also be used as inputs to compute the spectral absorptance of different layers within a solar cell, such as tandem solar cells or develop sensitivity maps for different modules present in the scene.