الفهرس 
Design Process in the Architectural Practice
Barriers against the Integration of Optimization Methods with Building Simulation ToolsOnly 14 pages are availabe for public view
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Abstract
Building simulation tools are used in many domains for the evaluation of various performance criteria. Due to the uprising awareness of more efficient and greener buildings besides, the recent progress in computational techniques, this trend became easier to evolve than ever before. However, design problems cannot be completely explored merely through these tools. They are useful in the analysis and the evaluation of a specific design, or a limited number of alternatives, according to certain criteria. On the other hand, they are not efficient for evaluating a large number of solutions. Hence, the integration of parametric design with genetic algorithms as an optimization tool was investigated as an approach to overcome this problem. A focus of this integration was in conceptual design phase, which returns to the key impacts of decisions taken in this phase.
In chapter one, an emphasis was on performance models and how “performance” issues were incorporated in different design models to serve as the driving engine for design exploration. By paying attention to the capabilities of generative models in capturing formal qualities, the integrated approach “generative Performative approach” was highlighted. Moreover, contributions of optimization algorithms in reaching high performance designs were investigated.
In chapter two, the investigated performance criteria was set to be daylighting design. Daylighting is an important building aspect that needs concern from the early beginning of the design process. Still successful daylighting design is a challenging task due to the conflicting requirements to reach the balance between daylighting adequacy and visual comfort. Besides, the fluctuating nature of daylight along the day and year complicates the process. Hence, the significance of integrating optimization algorithms for efficient daylighting design was discussed.
In chapter three, different generative systems were explored for pattern generation, focusing on cellular automata (CA). As a matter of fact, they lack the capability of meeting performance requirements without being guided by performance feedback. Thus, CA was integrated with Genetic Algorithms (GAs) to explore their effectiveness in solar screen formation. The designed solar screen was intended to meet daylighting performance requirements of a south oriented classroom in Cairo. An exhaustive search method was first applied and then was replaced by GAs.
In chapter four, findings of the classroom case study were discussed. All investigated CA rules proved their applicability in reaching satisfactory solutions in terms of the assigned daylighting criteria. In addition, GAs revealed their robustness in finding satisfactory solutions with less computational demands than the exhaustive search method which could be impractical in other cases.
The last chapter introduced the conclusions and recommendations. It elaborated the potentials of parametric design coupled with Genetic Algorithms (GAs) as an optimization tool in reaching highly efficient solutions. A workflow for utilizing generative performative design approach was suggested to meet designers’ subjective visual demands and the required performance criteria. At last, future research concerned with optimization studies for building design was suggested.