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MOOSAS - A systematic solution for multiple objective building performance optimization in the early design stage

机译：Moosas - 在早期设计阶段进行多重客观建筑性能优化的系统解决方案

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There is great potential for building performance optimization (BPO) in the early design stage, but there is still a lack of methods, algorithms, and tools to support the BPO process in this stage. Through a comprehensive review, this study identified three critical issues that affect the implementation of the BPO process in the early design stage: model integration, real-time performance analysis, and interactive optimization design. This study provides a systematic solution to these three critical issues. In terms of model integration, a feature-based and graph based 3D building space recognition algorithm is proposed to automatically convert the computer-aided design (CAD model) into a computer-aided engineering model (CAE model). In terms of real-time performance analysis, a simplified physical method, an HPC-accelerated method, and an AI-based method are explored, and a real-time energy modeling module and a real-time daylighting analysis module are developed. In terms of the interactive optimization design, a preference-based multi-objective BPO design algorithm that can consider user preferences is proposed to make full use of the decision-making ability of humans and the computing power of machines and significantly improve the optimization efficiency and result satisfaction. Based on the systematic solution, a multi-objective BPO design software, MOOSAS, is developed. MOOSAS allows real-time performance feedback, dynamic parameter analysis, and interactive optimization, supporting the BPO process in the early design stage. The innovations of this study are as follows: first, this study proposes a systematic solution to the three critical issues of the BPO process, i.e., model integration, real-time performance analysis, and interactive optimization design; second, this study develops a multi-objective BPO design software (MOOSAS) for the early design stage.
机译：在早期设计阶段建立性能优化（BPO）有很大的潜力，但仍然缺乏方法，算法和支持BPO过程的方法。通过全面的审查，本研究确定了三项关键问题，这些问题影响了早期设计阶段的BPO过程的实施：模型集成，实时性能分析和交互式优化设计。本研究为这三个关键问题提供了系统的解决方案。在模型集成方面，提出了一种基于图谱的基于图形的3D建筑空间识别算法，以自动将计算机辅助设计（CAD模型）转换为计算机辅助工程模型（CAE模型）。在实时性能分析方面，探索了简化的物理方法，HPC加速方法和基于AI的方法，并且开发了实时能量建模模块和实时日光分析模块。就交互式优化设计而言，提出了一种基于优先的多目标BPO设计算法，可以考虑用户偏好，以充分利用人类的决策能力和机器的计算能力，并显着提高优化效率和显着提高优化效率结果满意度。基于系统解决方案，开发了一种多目标BPO设计软件Moosas。 Moosas允许实时性能反馈，动态参数分析和交互式优化，支持早期设计阶段的BPO过程。本研究的创新如下：首先，本研究提出了对BPO过程的三个关键问题的系统解决方案，即模型集成，实时性能分析和交互式优化设计;其次，本研究开发了一个用于早期设计阶段的多目标BPO设计软件（Moosas）。

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