Multi-dimensional performance-based intelligent optimization of atrium building prototype with informed approach - Yiquan Zou; Yanyan Li; Han Chen; Benlin Xiao; Zhou Li (Discover Applied Sciences)
Abstract In the initial design phase, decisions about building programs significantly influence the energy, physical, and space performance of a building. However, as the design process advanced, the potential to optimize building physical properties, space, and related performance gradually diminished, and the costs to achieve the same benefits were progressively increased. In this study, an enclosed atrium-style office space was chosen as a case study, and an intelligent optimization method for the atrium prototype space was proposed. This method, which integrated multi-dimensional performance data such as light environment, thermal environment, energy consumption, space, and cost, was used to investigate morphological optimization strategies for the atrium prototype space under the influence of multiple environmental factors during the architectural design phase. Furthermore, the ranges for optimal solutions when pursuing different design objectives were analyzed, series of global optimal solutions were identified, and the optimization process was accelerated using machine learning technology. Ultimately, architects were provided with prototype forms of the atrium space in an "Informed" manner, which expedited the architectural design process. The case study is based on a light industrial building at Hubei University of Technology, which was evaluated through 377 building form prototypes generated by this "Informed" design platform. Compared to the existing building, the optimized building form showed significant improvements in cost, lighting, energy consumption, spatial performance, and sunlight and solar radiation quality, with an overall assessment score of 15.15 to 73.35, a performance improvement of 380%. The effectiveness of the method in improving building performance and accelerating the design decision-making process is demonstrated, providing an innovative optimization tool for the field of building design.