Multi-Objective Optimal Design of a Building Envelope and Structural System Using Cyber-Physical Modeling in a Wind Tunnel
Multi-Objective Optimal Design of a Building Envelope and Structural System Using Cyber-Physical Modeling in a Wind Tunnel
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DOI：
10.3389/fbuil.2018.00013
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发表时间：
2018-03-22
影响因子：
3
通讯作者：
Davis, Justin R.
中科院分区：
文献类型：
--
作者：
Whiteman, Michael L.;Fernandez-Caban, Pedro L.;Davis, Justin R.
本文探讨了使用网络物理系统（CPS）“模型循环”方法来优化设计受风荷载影响的低层建筑的围护结构和结构系统。构件和覆层（C&C）以及主抗风系统（MWFRS）均通过多目标优化进行考虑。 CPS 方法结合了风洞测试的物理精度和数值优化算法的效率，以获得最佳设计。该方法是自主的：实验在边界层风洞 (BLWT) 中执行，传感器反馈由计算机监控和分析，优化算法通过执行器指示 BLWT 中结构模型的物理变化。为了探索多目标优化的 CPS 方法，考虑了一座具有可变高度女儿墙的低层建筑。在 BLWT 中，伺服电机用于将护墙调整到特定高度。女儿墙改变了屋顶角涡的位置，减少了迎风屋顶角和边缘的吸力载荷（C&C 设计载荷）。同时，女儿墙增加了建筑物的表面积，导致对 MWFRS 的需求增加。采用非随机和随机优化算法的组合来最小化低层建筑模型屋顶上的吸力和正压力的大小，然后进行随机多目标优化以同时最小化吸力和基础剪力的大小。实验是在美国国家科学基金会 (NSF) 自然灾害工程研究基础设施 (NHERI) 项目的佛罗里达大学实验设施 (UFEF) 中进行的。
This paper explores the use of a cyber-physical systems (CPS) "loop-in-the-model" approach to optimally design the envelope and structural system of low-rise buildings subject to wind loads. Both the components and cladding (C&C) and the main wind force resisting system (MWFRS) are considered through multi-objective optimization. The CPS approach combines the physical accuracy of wind tunnel testing and efficiency of numerical optimization algorithms to obtain an optimal design. The approach is autonomous: experiments are executed in a boundary layer wind tunnel (BLWT), sensor feedback is monitored and analyzed by a computer, and optimization algorithms dictate physical changes to the structural model in the BLWT through actuators. To explore a CPS approach to multi-objective optimization, a low-rise building with a parapet wall of variable height is considered. In the BLWT, servo-motors are used to adjust the parapet to a particular height. Parapet walls alter the location of the roof corner vortices, reducing suction loads on the windward facing roof corners and edges, a C&C design load. At the same time, parapet walls increase the surface area of the building, leading to an increase in demand on the MWFRS. A combination of non-stochastic and stochastic optimization algorithms were implemented to minimize the magnitude of suction and positive pressures on the roof of a low-rise building model, followed by stochastic multi-objective optimization to simultaneously minimize the magnitude of suction pressures and base shear. Experiments were conducted at the University of Florida Experimental Facility (UFEF) of the National Science Foundation's (NSF) Natural Hazard Engineering Research Infrastructure (NHERI) program.