国家数值风洞(NNW)验证与确认系统关键技术研究进展

赵炜; 陈江涛; 肖维; 杨福军; 吴晓军; 陈坚强

doi:10.7638/kqdlxxb-2020.0138

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

国家数值风洞(NNW)验证与确认系统关键技术研究进展

专栏——国家数值风洞自主可控关键技术 | 更新时间：2026-05-28

- 国家数值风洞(NNW)验证与确认系统关键技术研究进展
- Advances in the key technologies of verification and validation system of National Numerical Windtunnel project
- 空气动力学学报 2020年38卷第6期页码：1165-1172
- 作者机构：
  
  1. 中国空气动力研究与发展中心空气动力学国家重点实验室,绵阳,621000
  2. 中国空气动力研究与发展中心计算空气动力研究所,绵阳,621000
- 作者简介：
  
  赵炜(1986-), 男, 湖北钟祥人, 工程师, 研究方向:CFD验证与确认.E-mail:ethnuaa@163.com
  陈坚强(1966-), 男, 浙江上虞人, 研究员, 研究方向:高超声速湍流, CFD验证与确认.E-mail:chenjq@cardc.cn
- 基金信息：
  
  国家数值风洞工程
- DOI：10.7638/kqdlxxb-2020.0138
  中图分类号： TP311
- 纸质出版：2020
- 稿件说明：
移动端阅览
赵炜, 陈江涛, 肖维, 杨福军, 吴晓军, 陈坚强. 国家数值风洞(NNW)验证与确认系统关键技术研究进展[J]. 空气动力学学报, 2020, 38(6): 1165-1172.

ZHAO Wei, CHEN Jiangtao, XIAO Wei, et al. Advances in the key technologies of verification and validation system of National Numerical Windtunnel project[J]. 2020, 38(6): 1165-1172.
赵炜, 陈江涛, 肖维, 杨福军, 吴晓军, 陈坚强. 国家数值风洞(NNW)验证与确认系统关键技术研究进展[J]. 空气动力学学报, 2020, 38(6): 1165-1172. DOI： 10.7638/kqdlxxb-2020.0138.

ZHAO Wei, CHEN Jiangtao, XIAO Wei, et al. Advances in the key technologies of verification and validation system of National Numerical Windtunnel project[J]. 2020, 38(6): 1165-1172. DOI： 10.7638/kqdlxxb-2020.0138.

摘要

系统、科学、严格的验证与确认是计算流体力学软件可信度评价和保证的必经途径。验证与确认系统是在软件的全生命周期，包括开发、测试、应用和更新阶段，从科学计算的角度为软件质量提供全方位的保证。本文从方法、数据和工具三个方面详细介绍了NNW工程验证与确认系统的关键技术研究进展。在方法方面，从误差和不确定度来源的数学特征出发，发展了相应的估计和量化手段，初步构建了可信度评价体系，这为如何进行验证与确认、可信度评价提供了技术基础。在数据方面，从流动现象层次分析出发，建立了多维度的从简单到复杂物理现象耦合的标模算例体系，为验证与确认活动提供了可靠的基准数据。在实验工具方面，数据库和可信度平台开发为方便实施验证与确认提供了高度自动化工具。文章最后对下一步工作进行了展望。

Abstract

Verification and validation (V V) activities which are systematic

scientific and rigorous

are essential approaches for credibility assessment and assurance of computational fluid dynamics software. V V are able to provide guarantee for software quality assurance and improvement from the perspective of scientific computing during the full life-cycles of software

including development

testing

application and updating stages. The advances in the key technologies of V V

including methodology

data and tools

are introduced in this paper. Error estimation and uncertainty quantification

from their respective mathematical characteristics

together with credibility assessment system

provide technical foundation to perform verification

validation and credibility assessment. The construction of multi-dimensional calibration model system

which starts from level analysis of flow phenomena and ranges from simple flows to complex flows

and standard case collection provide reliable benchmark data for V V. The development of database and credibility assessment platform provides highly automated tools for performing V V. The paper prospects further work at the end.

关键词

Keywords

references

SCHLESINGER S. Terminology for model credibility[J]. Simulation, 1979, 32(3):103-104. DOI:10.1177/003754977903200304

ANSI/IEEE Std 100-1984. IEEE Standard dictionary of electrical and electronics terms[S]. 1984-08-10.

AIAA G-077-1998. Guide for the verification and validation of computational fluid dynamics simulations[S]. 1998-05-06.

AIAA S-071A-1999. Assessment of experimental uncertainty with application to wind tunnel testing[S]. 1999-01-01.

ASME V V 10-2006. Guide for verification and validation in computational solid mechanics[S]. 2006-12-29.

ASME V V 20-2009. Standard for verification and validation in computational fluid dynamics and heat transfer[S]. 2009-11-30.

ASME V V 10.1-2012. An illustration of the concepts of verification and validation in computational solid mechanics[S]. 2012-04-16.

DoD Directive 5000.59. Modeling and simulation (M S) managemet[S].1994-02-04.

DoD Instruction 5000.61. Modeling and simulation (M S) verification, validation, and accreditation (VV A)[S]. 1996-04-26.

DoD 5000.59-M. DoD modeling and simulation glossary[S]. 1998-01-15.

MIL-STD-961E. Department of defense standard practice: documentation of verification, validation, and accreditation (VV A) for models and simulations[S]. 2008-04-02.

NASA-STD-7009. Standard for models and simulations[S]. 2016-12-07.

CASEY M, WINTERGERSTE T, INNOTEC S. ERCOFTAC special interest group on quality and trust in industrial CFD:Best practice guidelines[M]. Brussels:European Research Community on Flow, Tutbulence and Combusion, 2000.

HIRSCH C. The development of a framework for CFD validation and best practice:the QNET-CFD knowledge base[J]. Chinese Journal of Aeronautics, 2006, 19(2):105-113. DOI:10.1016/s1000-9361(11)60290-2

VIDANOVIC N, RASUO B, DAMLJANOVIC D, et al. Validation of the CFD code used for determination of aerodynamic characteristics of nonstandard AGARD-B calibration model[J]. Thermal Science, 2014, 18(4):1223-1233. DOI:10.2298/tsci130409104v

MARINI M, PAOLI R, GRASSO F, et al. Advanced fluid information. verification and validation in computational fluid dynamics:the FLOWNET database experience[J]. JSME International Journal Series B, 2002, 45(1):15-22. DOI:10.1299/jsmeb.45.15

OBARA C J, LAMAR J E. Overview of the cranked-arrow wing aerodynamics project international[J]. Journal of Aircraft, 2009, 46(2):355-368. DOI:10.2514/1.34957

LEVY D W, ZICKUHR T, VASSBERG J, et al. Data summary from the first AIAA computational fluid dynamics drag prediction workshop[J]. Journal of Aircraft, 2003, 40(5):875-882. DOI:10.2514/2.6877

LAFLIN K R, KLAUSMEYER S M, ZICKUHR T, et al. Data summary from second AIAA computational fluid dynamics drag prediction workshop[J]. Journal of Aircraft, 2005, 42(5):1165-1178. DOI:10.2514/1.10771

VASSBERG J C, TINOCO E N, MANI M, et al. Abridged summary of the third AIAA computational fluid dynamics drag prediction workshop[J]. Journal of Aircraft, 2008, 45(3):781-798. DOI:10.2514/1.30572

VASSBERG J C, TINOCO E N, MANI M R, et al. Summary of the fourth AIAA computational fluid dynamics drag prediction workshop[J]. Journal of Aircraft, 2014, 51(4):1070-1089. DOI:10.2514/1.c032418

LEVY D W, LAFLIN K R, TINOCO E N, et al. Summary of data from the fifth computational fluid dynamics drag prediction workshop[J]. Journal of Aircraft, 2014, 51(4):1194-1213. DOI:10.2514/1.c032389

DERLAGA J M, MORRISON J H. Statistical analysis of the sixth AIAA drag prediction workshop solutions[J]. Journal of Aircraft, 2018, 55(4):1388-1400. DOI:10.2514/1.c034938

RUMSEY C L, SLOTNICK J P, LONG M, et al. Summary of the first AIAA CFD high-lift prediction workshop[J]. Journal of Aircraft, 2011, 48(6):2068-2079. DOI:10.2514/1.c031447

RUMSEY C L, SLOTNICK J P. Overview and summary of the second AIAA high-lift prediction workshop[J]. Journal of Aircraft, 2015, 52(4):1006-1025. DOI:10.2514/1.c032864

RUMSEY C L, SLOTNICK J P, SCLAFANI A J. Overview and summary of the third AIAA high lift prediction workshop[J]. Journal of Aircraft, 2019, 56(2):621-644. DOI:10.2514/1.c034940

SCHUSTER D, CHWALOWSKI P, HEEG J, et al. A summary of data and findings form the first aeroelastic prediction workshop[C]//7th International Conference on Computational Fluid Dynamics. Hawaii: Big Island, 2012.

HEEG J, CHWALOWSKI P, RAVEH D E, et al. Plans and example results for the 2nd AIAA Aeroelastic Prediction Workshop[C ] //Proc of the 56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Kissimmee, Florida. Reston, Virginia: AIAA, 2015. DOI: 10.2514/6.2015-0437

ZHANG H X. On the uncertainty about CFD results[J]. Acta Aerodynamica Sinica, 2008, 26(1):47-49, 90.(in Chinese) DOI:10.3969/j.issn.0258-1825.2008.01.009

CHEN J Q, ZHANG Y R. Verification and validation in CFD based on the Richardson extrapolation method[J]. Acta Aerodynamica Sinica, 2012, 30(2):176-183.(in Chinese) DOI:10.3969/j.issn.0258-1825.2012.02.007

WANG R L, WEN W Z. Verification and validation of modeling and simulation of complex engineering[J]. Computer Aided Engineering, 2014, 23(4):61-68.(in Chinese) DOI:10.13340/j.cae.2014.04.013

DENG X G, ZONG W G, ZHANG L P, et al. Verification and validation in computational fluid dynamics[J]. Advances in Mechanics, 2007, 37(2):279-288.(in Chinese) DOI:10.3321/j.issn:1000-0992.2007.02.011

WANG Y T, LIU G, CHEN Z B. Summary of the first aeronautical computational fluid dynamics credibility workshop[J]. Acta Aerodynamica Sinica, 2019, 37(2):247-261, 246.(in Chinese)

陈坚强.国家数值风洞(NNW)工程关键技术研究进展[J].中国科学:技术科学, 2020(在线发表).

SLOTNICK J, KHODADOUST A, ALONSO J, et al. CFD vision 2030 study: A path to revolutionary computational aerosciences[R]. NASA CR-20414-218178, 2014.

郭亚军.综合评价理论与方法[M].北京:科学出版社, 2002.

JESPERSEN D C, PULLIAM T H, CHILDS M L. OVERFLOW turbulence modeling resource validation results[R]. NASA-2016-01, 2016.

CODER J G. Standard test cases for CFD-based laminar-transition model verification and validation[C ] //Proc of the 2018 AIAA Aerospace Sciences Meeting, Kissimmee, Florida. Reston, Virginia: AIAA, 2018. DOI: 10.2514/6.2018-0029

CHU J, LUCKRING J M. Experimental surface pressure data obtained on 65 #176; delta wing across Reynolds number and Mach number ranges[R]. NASA TM-4645, 1996.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

CFD软件可信度评估平台研制与应用

Menter SST湍流模型系数在高速流动模拟中的不确定度量化研究

低声爆超声速客机声爆预测及不确定度量化分析

考虑二次本构关系的湍流模型对翼身组合体阻力预测的影响分析

CFD不确定度量化方法研究综述