Multi-fidelity shape optimization methodology for pedestrian-level wind environment
Multi-fidelity shape optimization methodology for pedestrian-level wind environment
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DOI：
10.1016/j.buildenv.2021.108076
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发表时间：
2021-10
影响因子：
7.4
通讯作者：
M. Shirzadi;Y. Tominaga
中科院分区：
文献类型：
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作者：
M. Shirzadi;Y. Tominaga
提出了一种适用于行人水平风环境(PLWE)的多保真形状优化框架。在该框架中，将基于定常雷诺平均N-S方程(RANS)的低保真计算流体力学(CFD)模型和基于大涡模拟(LES)的高保真CFD模型有效地集成到优化过程中，以提高优化的可靠性，同时将其计算速度保持在实际工程应用所能承受的范围内。优化求解器与使用实验设计(DOE)技术获得的低保真CFD样本生成的近似模型相耦合。然后，根据目标函数相对于参考情况的改进程度来评价最佳候选者。如果改进程度在低保真模型和高保真模型之间显示出明显的偏差，则应用适当的修正和修改来提高优化过程的可靠性。以高层建筑周围的高风速面积最小为优化目标，研究了该方法的适用性，考虑了(A)均匀的城市街区和(B)具有不同风向频率分布的真实城市街区与两种不同的局部风气候相关联的情况。综上所述，利用所提出的优化框架，目标建筑周围的临界大风面积显著减少。此外，建议的多保真度优化框架的应用突出了在建筑设计中考虑当地风气候的重要性。
In this study, a multi-fidelity shape optimization framework is proposed for the pedestrian-level wind environment (PLWE). In the proposed framework, low-fidelity computational fluid dynamics (CFD) models based on steady Reynolds-averaged Navier–Stokes equations (RANS) models and high-fidelity CFD models based on large-eddy simulation (LES) are efficiently integrated into the optimization process to improve the optimization reliability while maintaining its computational speed in an affordable range for practical engineering applications. The optimization solver is coupled with an approximation model generated by low-fidelity CFD samples obtained using a design of experiments (DOE) technique. The optimal candidates are then evaluated according to the degree of improvement of the objective function compared to the reference case. If the degree of improvement shows significant deviations between the low-fidelity and high-fidelity models, suitable corrections and modifications are applied to improve the reliability of the optimization process. The applicability of the proposed method was investigated in terms of minimizing the high-wind-speed area, as the optimization objective, around a high-rise building considering (a) uniform urban blocks and (b) real urban blocks with different frequency distributions of wind directions associated with two different local wind climates. In summary, a significant reduction in the critical strong-wind area around the target building was realized using the proposed optimization framework. Furthermore, the application of the proposed multi-fidelity optimization framework highlighted the importance of considering the local wind climate in architectural design.