A Performance and Data-Driven Method for Optimization of Traditional Courtyards

Zhixin Xu, Xia Huang, Xin Zheng (), Ji-Yu Deng and Bo Sun
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Zhixin Xu: School of Architecture, Southeast University, Nanjing 210096, China
Xia Huang: School of Art and Design, Wanjiang University of Technology, Ma’anshan 243031, China
Xin Zheng: School of Architecture, Southeast University, Nanjing 210096, China
Ji-Yu Deng: School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou 510080, China
Bo Sun: School of Architecture, Southeast University, Nanjing 210096, China

Sustainability, 2024, vol. 16, issue 13, 1-30

Abstract: As urbanization and rapid industrialization accelerate, rural areas face increasing pressure on resources and the environment, leading to challenges such as energy waste and reduced comfort. Traditional village planning and design methods are based on economic benefits and often lack consideration of climate adaptability. To address these issues, a comprehensive assessment of building and courtyard performance should be introduced early in the planning of traditional villages. This approach can better adapt the buildings to their climatic conditions. Introducing relevant performance indicators, such as outdoor comfort, indoor lighting, and building energy consumption, at the initial design stage is crucial. This article employs performance-based multi-objective optimization algorithms and machine learning techniques to investigate the design workflow of courtyards and their combinations. The goal is to enhance planners’ design efficiency in village planning by integrating data-driven and performance-driven methods. The research results show that during the performance-driven phase, by adjusting the spatial morphology and architectural parameters, the performance of the courtyard significantly improved compared to the baseline model. Energy efficiency increased by 32.3%, the physiological equivalent temperature (PET) comfort time ratio in winter was enhanced by 8.3%, and the ratio in summer increased by 3.8%. During the data-driven phase, the classification prediction accuracy of courtyard performance can reach 83%, and the F 1 score is 0.81. In the project validation phase, it has also been proven that the performance of different plans can be quickly verified. Compared to the base’s original status, the design solutions’ performance score can be improved from 59.12 to 85.62. In summary, this workflow improves the efficiency of the interaction between design decisions and performance evaluation in the conceptual stage of village planning, providing a solid foundation for promoting subsequent solutions.

Keywords: traditional courtyards; multi-objective optimization; building performance simulation; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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