The WiseCFD Platform for CFD Credibility Analysis
This paper presents a summary for WiseCFD platform, which is one of important outputs of an ongoing project at ACTRI to establish a software platform for studying the credibility of CFD solvers and performing credible CFD simulations. Within the platform,several crux techniques are overcome. These techniques include data management technique for CFD credibility analysis, data analysis and comparison technique, and distributed computing technique for parameters sensitivity. Via these techniques, the WiseCFD platform completes a streamline aerodynamic process of case selection, computational parameter definition, computing job management, distributed computing, and data analysis and comparison, which greatly enhances computing efficiency and effectively reduces uncertainty in simulation. The main components of WiseCFD include test cases, candidate solvers, graphical user interface (GUI), tools for parameter sensitivity study, tools for data extract, analysis and comparison, and an applied job scheduler. The test cases are organized as three distinct classes called verification case, validation case and application challenge case respectively. Under each specific test case, the so-called study cases can be established to perform various analysis activities related to parameter sensitivity study. The platform is delivered with built-in test cases. User can also establish his own test cases through interactive operations. The platform is also delivered with built-in CFD solvers. Currently five solvers are integrated into the platform as referenced computing engines, including a multi-block structured grid RANS solver and a hybrid grid RANS solver developed by ACTRI, two multi-block structured grid RANS solvers by CARDC, and a single block structured grid RANS solver by National Laboratory of CFD. Besides, Statistic analysis tools, grid convergence analysis tools, flow topology analysis tools, 2-D curve drawing and 3-D flow field visualization tools are all together integrated into the platform. Critical parameters can be varied in different ways to check the sensitivity of the computational results. In order to deal with the vast computational tasks, a job scheduler for distributed computational environment is developed and integrated into the platform.
Yi-hua Liang Li Li
Aeronautics Computing Technique Research Institute,Xian,P.R.China,710068
国际会议
西安
英文
233-240
2006-08-19（万方平台首次上网日期，不代表论文的发表时间）