Simulation Accuracy, Uncertainty, and Predictive Capability: A Physical Sciences Perspective

Abstract

Most computational analysts, as well as most governmental policy-makers and the public, view computational simulation accuracyAccuracyas a good agreementAgreementof simulation results with empirical measurements. However, decision-makers, such as business managers and safety regulators who rely on simulation for decision support, view computational simulation accuracy as much more than agreement of simulation results with experimental dataExperimental data. Decision-makers' concept of accuracy is better captured by the term predictive capability of the simulation. Predictive capability meaning the use of a computational modelComputational modelto foretell or forecastBenchmark forecastthe response of a system to conditions without availableExperimental dataexperimental dataData, even for system responses that have never occurred in nature. This chapter makes this important distinction by discussing the crucial ingredients needed for predictive capabilityPredictive capability: code verificationCode verification, solution (or calculation) verification, model validation, model calibrationCalibration, and predictive uncertaintyUncertaintyestimation. Each of these ingredients is required, whether the simulation results are used in the generation of new knowledgeKnowledge, or for decision support by business managers, government policy-makers, or safety regulators.