Empowered decision-making in simulation-based engineering: Advanced Model Reduction for real-time, inverse and optimization in industrial problems
Computational Mechanics tools are well integrated in the technological industrial practice. However, the global effort (pre-process, solve and post-process) is a major overhead for real industrial problems.
Thus, simulation-based engineering are not extensively used in real-time for decision-making. Real-time (fast-queries) is critical for control of manufacturing processes, non-destructive-testing and fast decision-making at production phases.
This is also the case for multiple-queries: optimization and parameter identification with uncertainty quantification. These problems are pivotal for exploring the large parametric spaces; that is, for solving a large number of problems selected among a parametric family.
Addressing multiple-queries in an efficient and reasonably accurate manner is crucial in applications of major industrial interest (independently of the manufactured product: engines, cars, planes, helicopters, rockets, medical devices). The actual bottleneck lies in the computational effort to be furnished in solving each of the queries with the desired accuracy.