A BRIEF TUTORIAL ON VERIFICATION AND VALIDATION

This paper offers a brief overview of the technology developed at Los Alamos National Laboratory, among other places, in support of engineering verification and validation programs. The material presented is based to a large extent on a tutorial taught at the Los Alamos Dynamics Summer School [1]. The paper overviews the concepts and introduces methods useful to assess the predictive accuracy of numerical simulations. The technology available for code verification, solution verification, testanalysis correlation, meta-modeling, and calibration is discussed. The quantification of uncertainty, both in the forward mode (“What is the effect of uncertainty on predictions?”) and inverse mode (“Where is an observed variability coming from?”) is also addressed. Rather than providing a detailed account of the state-of-theart, techniques are illustrated using engineering applications.

[1]  F. Hemez,et al.  Title : Inversion of Structural Dynamics Simulations : State-ofthe-art and Orientations of the Research , 2000 .

[2]  P. Roache.  Perspective: A Method for Uniform Reporting of Grid Refinement Studies , 1994 .

[3]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[4]  J. Oden,et al.  A Posteriori Error Estimation in Finite Element Analysis , 2000 .

[5]  François M. Hemez,et al.  The Good , The Bad , and The Ugly of Predictive Science , 2005 .

[6]  Patrick J. Roache,et al.  Verification and Validation in Computational Science and Engineering , 1998 .

[7]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[8]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[9]  B. Carlin,et al.  Bayesian Model Choice Via Markov Chain Monte Carlo Methods , 1995 .

[10]  Scott W. Doebling,et al.  STRUCTURAL DYNAMICS MODEL VALIDATION: PUSHING THE ENVELOPE , 2002 .

[11]  J. Cadafalch,et al.  Verification of Finite Volume Computations on Steady-State Fluid Flow and Heat Transfer , 2002 .

[12]  C. F. Jeff Wu,et al.  Experiments: Planning, Analysis, and Parameter Design Optimization , 2000 .

[13]  R. Armstrong,et al.  Dislocation-mechanics-based constitutive relations for material dynamics calculations , 1987 .

[14]  T. M. Shih,et al.  A procedure to debug computer programs , 1985 .

[15]  François M. Hemez,et al.  From shock response spectrum to temporal moments and vice-versa , 2002 .

[16]  John E. Mottershead,et al.  Model Updating In Structural Dynamics: A Survey , 1993 .

[17]  William L. Oberkampf,et al.  Guide for the verification and validation of computational fluid dynamics simulations , 1998 .

[18]  Kenneth M. Hanson,et al.  A framework for assessing uncertainties in simulation predictions , 1999 .

[19]  Yakov Ben-Haim,et al.  Robust rationality and decisions under severe uncertainty , 2000, J. Frankl. Inst..

[20]  Patrick Knupp,et al.  Code Verification by the Method of Manufactured Solutions , 2000 .

[21]  J. N. Johnson,et al.  The effect of void growth on Taylor cylinder impact experiments , 1993 .

[22]  Brian E. Thompson,et al.  Assessment of Numerical Uncertainty Around Shocks and Corners on Blunt Trailing-Edge Supercritical Airfoils , 2002 .

[23]  Lesley F. Wright,et al.  Information Gap Decision Theory: Decisions under Severe Uncertainty , 2004 .

[24]  A. L. Cundy,et al.  Variable screening in metamodel design for a large structural dynamics simulation , 2002 .

[25]  Joseph A. C. Delaney.  Sensitivity analysis , 2018, The African Continental Free Trade Area: Economic and Distributional Effects.

[26]  Dolores R. Wallace,et al.  Reference information for the software verification and validation process , 1996 .

[27]  François M. Hemez,et al.  Design of Computer Experiments for Improving an Impact Test Simulation , 2000 .

[28]  Charles R. Farrar,et al.  THE LOS ALAMOS DYNAMICS SUMMER SCHOOL , 2000 .

[29]  Timothy J. Ross.  Possibility intervals in the characterization of dynamic model uncertainty , 2000, PeachFuzz 2000. 19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.00TH8500).

[30]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.