Reveal: An Extensible Reduced-Order Model Builder for Simulation and Modeling

Many science domains need to build computationally efficient and accurate representations of high fidelity, computationally expensive simulations known as reduced-order models (ROMs). This article presents the design and implementation of the Reveal toolset, a ROM builder that generates ROMs based on science- and engineering-domain-specific simulations executed on high-performance computing (HPC) platforms. The toolset encompasses a range of sampling and regression methods for ROM generation, automatically quantifies ROM accuracy, and supports an iterative approach to improve ROM accuracy. Reveal is designed to be extensible for any simulator that has published input and output formats. It also defines programmatic interfaces to include new sampling and regression techniques so users can mix and match mathematical techniques best suited to their model characteristics. The article describes the architecture of Reveal and demonstrates its use with a computational fluid dynamics model used in carbon capture.

Related Work in Reduced-Order Modeling

Reduced-order modeling has been studied in the context of various scientific problems, such as subsurface flow simulations, manufacturing technology, circuit models, water flood modeling, and computational fluid dynamics (CFD) models.^[1] However, to our knowledge, no tools exist that provide highly usable and generic, full life-cycle capabilities required for reduced-order modeling of scientific simulations.