Simulation Model Refinement for Decision Making Via a Value-of-Information Based Metric

Abstract

Since no simulation model is perfect, any simulation model for modeling a system’s physical behavior can be refined further. Hence, the question faced by a designer is — “How much refinement of a simulation model is adequate for a particular design problem?” To answer this question, we present a value-of-information based approach for determining the appropriate extent of refinement of simulation models. The value of additional information obtained via refinement of simulation models is measured as the difference between the maximum payoff that could possibly be achieved throughout the design space and the minimum possible payoff at the point in the design space selected using the simple model. The approach is presented using two examples — design of a pressure vessel and the design of a material.

Uncertainty Management in the Design of Multiscale Systems

“…However, if the improvement potential is low, then the possibility of improving the design solution is low. The advantages of the metric have been shown for uncertainty mitigation in individual models 72,73 .…”