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Comparative metrics for computational approaches in non-uniform street-canyon flows

机译:非均匀街道峡谷流动计算方法的比较度量

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Three different computational fluid dynamics (CFD) methods are assessed for their ability to predict topological flow features in idealized street canyons with uneven building heights. Mean velocity-fields from step-up (i.e., a high-rise building downwind of a low-rise building) and step-down (i.e., a low-rise building downwind of a high-rise building) street canyons are evaluated against high-spatial-resolution wind-tunnel data. Each method represents a different level of flow physics using: a mass-conserving model entitled Quick Urban & Industrial Complex wind model (QUIC-URB), a Reynolds-averaged Navier-Stokes (RANS) model, and a large-eddy simulation (LES) model. A new metric that represents the equally weighted trade-off between accuracy and efficiency is introduced to evaluate the CFD methods' capabilities to capture major-flow topological features in uneven building height street canyons. For step-up street canyons, all three methods qualitatively predict primary topological features, however, none simultaneously capture all secondary features. For step-up street canyons and step-down street canyons with narrow-streets, QUIC-URB captures most of the primary flow topological features including stagnation and saddle points and rooftop recirculation zones. RANS captures primary vortices for step-up street canyons and step-down street canyons with wide-streets. LES is computationally costly but it is the only method that successfully predicts secondary flow topological characteristics for step-down street canyons with wide-streets. When examining our trade-off metric, QUIC-URB has the highest score for step-up street canyons, while QUIC-URB and RANS have equally high trade-off scores for step-down street canyons with narrow-streets, and QUIC-URB and LES have nearly equal trade-off scores for step-down street canyons with wide-streets.
机译:评估了三种不同的计算流体动力学(CFD)方法以预测理想的街道峡谷中的拓扑流动功能,具有不均匀的建筑物高度。升压的平均速度场(即,低层建筑物的高层建筑物的高层建筑物)和降压(即,高层建筑的低层建筑物下风)街道峡谷评估了高 - 天空分辨率风隧道数据。每种方法代表不同水平的流量物理:一个题为快速城市和工业复杂风模型(QUIC-URB)的大规模保护模型,雷诺平均Navier-Stokes(RANS)模型以及大涡模拟(LES ) 模型。引入了一种新的指标,其代表了准确性和效率之间同样加权的权衡,以评估CFD方法的能力,以捕获不均匀的建筑物高度街道峡谷中的主要流动拓扑功能。对于升压街道峡谷,所有三种方法都定性地预测了主要拓扑特征,然而,没有同时捕获所有辅助特征。对于具有狭窄街道的升压街道峡谷和降压街道峡谷,QUIC-URB捕获了大部分主要流动拓扑功能,包括停滞和鞍点和屋顶再循环区域。 Rans捕捉到升级的街道峡谷和宽阔的街道峡谷的主要漩涡。 LES是计算的昂贵,但它是唯一成功预测宽阔街道的降压街道峡谷的二次流动拓扑特性的唯一方法。在检查我们的权衡指标时,Quic-URB的升级街道峡谷的得分最高,而Quic-URB和Rans在狭窄的街道峡谷和Quic-Urb的下坡街道峡谷具有同样高的权衡分数和宽阔的街道峡谷有几乎平等的权衡分数。

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