A system proposal for generative design processes and space analysis in architecture

Computational technologies have mostly been utilized in architectural design for visualization and representation purposes, as well as an optimal alternative for similar analogical applications. However, new improvements enabled architects to include generative approaches into design processes. The implementation of algorithmic design techniques and programming platforms also provides enormous potential, suggesting new methods to generate spatial layouts, environment typologies and allowing unique design patterns discovery. Additionally, recent generative design competencies permit data analysis, interpretation, and emergence of complicated forms and spontaneous evolving processes as well. Due to the extensiveness of the study materials covered, interdisciplinary research methodologies were integrated, and the entire research was carried out in two parts; conceptualization (concept shift and development) and experimentation (data analysis and system implementation). The conceptualization part establishes the fundamentals of various conceptions' classifications and organizations for understanding the generative design paradigm, where essential features that had not been included in early studies were explored. The experimentation part of the research explains the development and implementation of a generative system with an algorithmic model that facilitates the collaboration of human creativity with computer capabilities. The data collection and site analysis phases were essential in defining the perspective of the case study area and establishing the generative design system's parameters. A design studio-based experiment, spatial and computational analysis techniques were involved to explore design problems and environment requirements. The gathered data were classified into several categorical dimensions based on the research intents. The assessment process of layout and spatial arrangement, connectivity and accessibility, built area and open space was the emphasis of spatial analysis. Whereas computational analysis allowed for the inquiry of density and visibility measurements through several indicators and techniques such as GSI, OSR, FAR, and Isovist. Correspondingly, the generative design process examined designs based on three independent variables, "Functional connectivity", "Responsive density", "Design pattern". Various performance operations were built into the algorithm model representation at each level to address the specific requirements of the relevant data collecting and analysis outcomes. The system supports the collaboration of generative design approaches and patterns optimization. The main purpose of the research is to enhance the efficiency of design expansion and to develop a generative design system for Eskişehir Technical University's eco-campus development plan. It addresses the background of generative design in order to provide a more in-depth investigation into the domain of architectural design. The experimental study takes into account the usage of generative design approaches and systems in the design process, as well as the capacity to create and evaluate a diverse range of possibilities that an architect could accomplish. Compared to other patterns, the results of the third pattern optimization showed effective evolutionary mechanisms with self-generated design possibilities, spatial morphologies, and building typologies for the university campus master plan. This research offered then a conceptual design comprehension as well as a proposed generative design system for architectural design. The system interconnection represents the predominant research contribution, while other contributions were presented through system application and optimization. The results also reveal that the proposed system may be effectively incorporated into design education and architectural practice, enhancing the learning and use of algorithmic design systems in architecture.