The continued advancement of Building Information Modelling (BIM) has enabled Automated Compliance Checking (ACC). Despite improvements in highly advanced code compliance checkers to ensure adherence to regulatory standards and adjust building designs for compliance, there remains a significant gap in automating and optimizing this process for complex and diverse design scenarios. Manually adjusting building models based on building code specifications takes time, effort, and is typically error-prone, reducing total project efficiency. This thesis proposes a code compliance framework to automate code checking and adjust violation-related parameters, ensuring code-compliant building designs, specifically focusing on building egress requirements. It also integrates the use of Generative Design (GD) and Genetic Algorithm (GA) with parametric BIM modeling to optimize the means of egress by finding the optimal parameter configuration that yields the least travel distances. It ensures that the building design not only complies with building regulations but is also optimized to enhance the safety of occupants. The proposed approach was validated using a case study. The results illustrate the significance of the proposed framework in automating compliance checking, adjusting violation-related parameters, and optimizing building design to enhance the safety of occupants during emergency scenarios.
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The continued advancement of Building Information Modelling (BIM) has enabled Automated Compliance Checking (ACC). Despite improvements in highly advanced code compliance checkers to ensure adherence to regulatory standards and adjust building designs for compliance, there remains a significant gap in automating and optimizing this process for complex and diverse design scenarios. Manually adjusting building models based on building code specifications takes time, effort, and is typically error-...
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