Decreasing Risk in the Design of Large Coupled Systems via Co-Simulation-Based Optimization and Adaptive Stress Testing

Abstract

Optimization and stress testing are key aspects of thedesign and verification process for large, high-risksystems. Optimization is about improving the capabilitiesand performance of a system; stress testing is aboutuncovering its weaknesses and faults. Both require aquantitative representation of the system's behavior, andfor complex, multi-physical systems, co-simulation can be avery powerful method to create such a representation.However, co-simulation frequently involves the use ofblack-box subsystem models, which poses challenges totraditional optimization and stress testing methods. Here,we review the state of the art in co-simulation-basedoptimization and stress testing, focusing especially on\emph{adaptive stress testing} in the latter case, anddiscuss open research questions and promising researchdirections. In particular, we make the case that aco-simulation is not an entirely black box even when someor all of its subsystems are; it may be possible to exploitthe visible system structure, coupling variable values, andpartial subsystem information. We use examples from themaritime industry to motivate and illustrate thediscussion, centering on the highly contemporary designcase of an autonomous ferry.