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Optimal design of an indoor environment using an adjoint RNG k-ε turbulence model

机译:使用伴随RNGk-ε湍流模型的室内环境优化设计

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The computational fluid dynamics (CFD)-based adjoint method can determine design variables of an indoor environment according to the optimal design objective, such as minimal predicted mean vote (PMV) for thermal comfort. The method calculates the gradient of the objective function over the design variables so that the objective function can be minimized along the fastest direction using an optimization algorithm. Since the RNG k-ε model is the most popular model used in CFD, the corresponding adjoint equations of the turbulence model should be solved during the design process, rather than the “frozen turbulence” assumption used in the existing approach. This investigation developed adjoint equations for the RNG k-ε turbulence model and applied it to a two-dimensional ventilated cavity. Design processes with the adjoint RNG k-ε turbulence model led to a near-zero design function for the cavity case, while that one with the RNG k-ε turbulence model did not.
机译:基于计算流体动力学(CFD)的伴随方法可以根据最佳设计目标确定室内环境的设计变量,例如用于热舒适性的最小预测平均投票(PMV)。该方法计算目标函数在设计变量上的梯度,以便可以使用优化算法沿最快方向最小化目标函数。由于RNGk-ε模型是CFD中使用最广泛的模型,因此在设计过程中应解决湍流模型的相应伴随方程,而不是现有方法中使用的“冻结湍流”假设。这项研究开发了RNGk-ε湍流模型的伴随方程,并将其应用于二维通风腔。伴随RNGk-ε湍流模型的设计过程导致型腔的设计函数几乎为零,而使用RNGk-ε湍流模型的设计过程则没有。

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