数值模拟方法对NASA CRM模型阻力预测的影响

在复杂工程外形的数值模拟中，网格类型、规模和分布、湍流模型、数值格式等都会不同程度影响模拟结果。如何评估这些模拟方法对模拟结果的影响，并识别对模拟结果影响较显著的因素，对于CFD的发展方向有积极的借鉴指导意义。为了综合研究不同因素对商用运输机外形阻力预测的影响，以AIAA第六届阻力预测会议外形NASA CRM为研究对象，同时考虑了网格、湍流模型、无黏通量格式和体心梯度求解方法等因素对阻力预测的影响。分析中采用枚举法和正交试验设计两种方法，并使用了基于聚类分析的定性敏感性分析方法和基于Mckay主影响分析的定量方法，识别出对阻力预测影响较大的因素，这为数值模拟方法的发展指明了方向。

Effects of numerical simulation approaches on drag prediction of NASA CRM

In numerical simulations of industry relevant geometries, plenty of factors will more or less affect the final results, including grid type/amount/distribution, turbulence model, numerical schemes, etc. It has become meaningful to quantify the effects of factors mentioned before on the simulation results and identify important areas needing additional research and development of CFD. In order to comprehensively study the impacts of several simulation options on the drag prediction of commercial transports, numerical investigations of the NASA Common Research Model from the 6th AIAA CFD Drag Prediction Workshop are performed in this paper. The effects of grid refinement, turbulence model, inviscid flux scheme, and the gradient computation method on drag prediction are investigated. Enumeration and orthogonal design of experiment are used to provide sampling data for analysis. The factors that have important contributions are identified by the kmeans clustering analysis and Mckay main effect analysis. The gradient computation method is recognized to be a key factor for total drag prediction, and more attention is needed in simulations of similar configurations and conditions.