Shrutakeerti Mallikarjun, V. Casseau, W. Habashi, Song Gao, A. Karchani
{"title":"Hybrid Navier–Stokes–Direct Simulation Monte Carlo Automatic Mesh Optimization for Hypersonics","authors":"Shrutakeerti Mallikarjun, V. Casseau, W. Habashi, Song Gao, A. Karchani","doi":"10.2514/1.t6770","DOIUrl":null,"url":null,"abstract":"This paper describes the development of an unstructured hybrid finite element Navier–Stokes (NS)–direct simulation Monte Carlo (DSMC) framework for hypersonic flows. State-based coupling is employed and simulations of varying thermochemical complexity demonstrate the accuracy, robustness, and computational efficiency of the hybrid all-Mach algorithm. An automatic mesh optimization process using a posteriori error estimates based on the Hessian of the solution goes much further than traditional mesh adaptation processes by equidistributing the error estimator and producing a “single optimal hybrid mesh” with no increase in mesh size and with much higher accuracy. The DSMC region cells of the resulting optimal mesh are smaller than in NS regions and are sized to the local mean free path. Mesh optimization is also shown to greatly improve the quality of the hybrid interfaces from those of the initial mesh. Unstructured meshes are found to represent the hybrid interfaces smoothly, while structured meshes showcase a castellated pattern in the interfaces. The optimal hybrid meshes are found to be statistically similar to optimal full DSMC meshes, thus highlighting the solver independence of the optimizer. Such a coupled hybrid mesh optimization strategy can therefore tackle hypersonic flows with multiscale flow features at any degree of rarefaction.","PeriodicalId":17482,"journal":{"name":"Journal of Thermophysics and Heat Transfer","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Thermophysics and Heat Transfer","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.2514/1.t6770","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 1
Abstract
This paper describes the development of an unstructured hybrid finite element Navier–Stokes (NS)–direct simulation Monte Carlo (DSMC) framework for hypersonic flows. State-based coupling is employed and simulations of varying thermochemical complexity demonstrate the accuracy, robustness, and computational efficiency of the hybrid all-Mach algorithm. An automatic mesh optimization process using a posteriori error estimates based on the Hessian of the solution goes much further than traditional mesh adaptation processes by equidistributing the error estimator and producing a “single optimal hybrid mesh” with no increase in mesh size and with much higher accuracy. The DSMC region cells of the resulting optimal mesh are smaller than in NS regions and are sized to the local mean free path. Mesh optimization is also shown to greatly improve the quality of the hybrid interfaces from those of the initial mesh. Unstructured meshes are found to represent the hybrid interfaces smoothly, while structured meshes showcase a castellated pattern in the interfaces. The optimal hybrid meshes are found to be statistically similar to optimal full DSMC meshes, thus highlighting the solver independence of the optimizer. Such a coupled hybrid mesh optimization strategy can therefore tackle hypersonic flows with multiscale flow features at any degree of rarefaction.
本文介绍了一种用于高超声速流动的非结构化混合有限元Navier-Stokes (NS) -直接模拟Monte Carlo (DSMC)框架的发展。采用了基于状态的耦合,并对不同热化学复杂性的模拟验证了混合全马赫算法的准确性、鲁棒性和计算效率。一种基于Hessian解的后验误差估计的自动网格优化过程比传统的网格自适应过程走得更远,通过均匀分布误差估计器并产生“单一最优混合网格”,网格尺寸不增加,精度更高。得到的最优网格的DSMC区域单元比NS区域小,并且被调整到局部平均自由路径。网格优化也表明混合界面的质量比初始网格的质量有了很大的提高。发现非结构化网格平滑地表示混合界面,而结构化网格在界面中显示出城堡状模式。发现最优混合网格在统计上与最优全DSMC网格相似,从而突出了优化器的求解器独立性。因此,这种耦合混合网格优化策略可以处理具有任何稀疏度的多尺度流动特征的高超声速流动。
期刊介绍:
This Journal is devoted to the advancement of the science and technology of thermophysics and heat transfer through the dissemination of original research papers disclosing new technical knowledge and exploratory developments and applications based on new knowledge. The Journal publishes qualified papers that deal with the properties and mechanisms involved in thermal energy transfer and storage in gases, liquids, and solids or combinations thereof. These studies include aerothermodynamics; conductive, convective, radiative, and multiphase modes of heat transfer; micro- and nano-scale heat transfer; nonintrusive diagnostics; numerical and experimental techniques; plasma excitation and flow interactions; thermal systems; and thermophysical properties. Papers that review recent research developments in any of the prior topics are also solicited.