Use of Multifidelity and Surrogate Models in the Design and Development of Physics‐Based Systems

Building a complex system in a time and cost effective manner, that performs well, meets diverse user needs, and has no inimical emergent behaviors is a challenge. The solution is to model before building. End‐to‐end high fidelity (HF) computational modeling and simulation (M&S) of a complex system, while attractive, is often too time consuming and expensive and may preclude the use of traditional systems engineering (SE) development tools. Missing are practicable approaches to reduce this computational time and cost by segmenting M&S performance and behaviors, keeping the model chain coherent, and only modeling what is necessary. An efficient framework is presented that couples mixed fidelity and surrogate models to reduce M&S computational time and cost for analysis of component‐level and system‐level performance of complex physics‐based problems. This framework is used in an example to modify a Nuclear Electromagnetic Pulse (NEMP) Bounded Wave Simulator (BWS). The framework is flexible and potentially extensible; it may provide systems engineers with a cost‐effective alternative to current approaches for modeling physics‐based engineering systems (e.g., radar, communications systems).