The building environment has high energy consumption and carbon emission which contributes to the rapid climate change. The changing climate condition not only impacts the natural environment but also our habitation. To improve the building performance in both energy and indoor comfort, performance-based design is commonly applied in architectural design. In general, a building lifespan is around 80 years, which means the buildings are designed and constructed now would face different climate conditions than the weather we used to evaluate the performance. To prevent the influence caused by climate change, this research develops computational workflows to generate predicted future climate conditions and multi-objective optimization to study the relationship between design decisions, climate conditions, and building performance. The conclusion of this research is based on the comparison and discussion of the result of optimization from five different climate and design scenarios with a single case study building.

In recent time, there has been a rise in the number of coworking and activity-based working spaces. This increase has brought a high return to the real-estate developers but at the same time has compromised with occupant satisfaction. It brings an additional challenge for the architects and designer to look into the user-centred design for workspaces and offices. The current design process relies heavily on the experience. There is a need to evaluate the design from a user’s perspective.
It is known that user’s in an office environment are impacted by various Indoor environmental quality factors. The most important of those factors is the noise disturbance which leads to decreased concentration, reduced satisfaction, and sick building syndrome in some cases. The noise disturbance is caused by speech interactions, appliances and services. These disturbances are relatively unknown to the designer in the early design phase and depend on user behaviour. This graduation project challenges the current design process by proving a digital intervention in the form of workflow. The workflow aims to help architects and designers in the early design process to evaluate spatial layout with respect to disturbances in the office.
This research combines the knowledge of design informatics, psychology and building physics to come up with a simulation workflow. It uses the knowledge of the psychology of workspaces to understand the user behaviour towards the noise disturbance. This knowledge is put to use through an agent-based model simulating the user movement and interactions through the office layout. It is made possible by combining existing methodologies of acoustic simulation, trajectory evaluation with the newly developed agent-based model that is simulating user behaviour. The results are then visualized on the spatial layout to get further insights into the design by testing with two case studies. As a result of prototyping, a simulation workflow is proposed which can be used to evaluate workspace layout in terms of user behaviour towards the noise.

One result of climate change is the increasing strength and frequency of wind events. This creates a problem for the also increasing number of high-rise buildings many of which are of unconventional shape. However, current methods for calculating wind response either do not account for these geometries, such as the Eurocode or are prohibitively expensive and time-consuming, such as physical wind tunnel tests. This thesis aims to address this issue by developing a computational method by which one can analyse the structural effects of wind on a building and optimise the external geometry to reduce those effects in the early design phase. The method involves the combination of three main algorithms: Computational Fluid Dynamics (CFD) to simulate the wind and the pressure it exerts on a building, Finite Element Analysis (FEA) which calculates the structural effects such as deflection and stresses due to these forces, and an optimisation algorithm which can iteratively manipulate an input geometry to obtain better performance. For this thesis, a tool based on the method was developed in Grasshopper, the visual scripting plugin for Rhinoceros3D. Existing plugins were used for the main algorithms while custom scripting was used to combine them into a single tool that was made relatively easy to use and returned quick results.
The methodology involved extensive research into the various aspects of the method. This was followed by the development of the method throughout which testing and validation were performed to determine its accuracy and timeliness. Case study buildings were tested with the goal of reducing structural material use. In all tests, the mass of structural material needed was reduced by allowing the optimisation algorithm to manipulate only the external geometry of the building. This produced a tool within Grasshopper and a set of guidelines for developing such a method.