Progress Toward a Complete Set of Errors for Modeling and Simulation

Abstract

Abstract To develop a fully complete set of errors associated with modeling and simulation, it is necessary to express every error that could impact the accuracy of a computational model's prediction of the real world system (i.e., a set of errors that is theoretically complete) and to develop a means to assess each error (i.e., making the set practically complete). As a first step toward this goal, this paper focuses on developing a theoretically complete set of errors that, if accounted for, would result in the correct prediction of reality. In order to derive this theoretically complete set of errors, a three-step process is followed. First, a generic scenario is introduced which is defined by a set of functions and inputs common to many, if not most, applications in modeling and simulation. Second, using only these functions and inputs, an equation for the total error is defined such that correcting the model's prediction to account for the error would result in a correct prediction of reality. Finally, the equation for total error is expanded by introducing terms from the generic scenario. This results in a decomposition of the total error into a set of thirteen distinct difference terms, each of which is defined as an error and many of which are closely related to current practices in verification, validation, and uncertainty quantification. These thirteen errors represent a theoretically complete set.