Unsteady Heat Transfer Numerical Methods Development

这建立在最近完成的博士论文（“混合LES-RANS有效冷却预测”）的基础上，其目的是进一步扩展并可能包括（i）共轭传热和/或（ii）数据集的产生，这些数据集将用于优化/训练具有额外各向异性应力项的非线性（EARSM）RANS模型。该项目预计将在其过程中进行基础研究，但其最终结果旨在提高工业规模的建模“能力”。

This builds on a recently completed PhD thesis ('Hybrid LES-RANS for Effusion Cooling Prediction') and the intention is to extend further and potentially include (i) conjugate heat transfer and/or (ii) the production of data sets that will be used to optimise/train a nonlinear (EARSM) RANS model with additional anisotropy stress terms. The project is expected to have a strong flavour of fundamental research during its course, but its end result is targeted at increasing the modelling "capability" at an industrial scale.