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arXiv · 2407.03325

On the accuracy and efficiency of reduced order models: towards real-world applications

Pierfrancesco Siena·Paquale Claudio Africa·Michele Girfoglio·Gianluigi Rozza
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Abstract

This chapter provides an extended overview about Reduced Order Models (ROMs), with a focus on their features in terms of efficiency and accuracy. In particular, the aim is to browse the more common ROM frameworks, considering both intrusive and data-driven approaches. We present the validation of such techniques against several test cases. The first one is an academic benchmark, the thermal block problem, where a Poisson equation is considered. Here a classic intrusive ROM framework based on a Galerkin projection scheme is employed. The second and third test cases come from real-world applications, the one related to the investigation of the blood flow patterns in a patient specific coronary arteries configuration where the Navier Stokes equations are addressed and the other one concerning the granulation process within pharmaceutical industry where a fluid-particle system is considered. Here we employ two data-driven ROM approaches showing a very relevant trade-off between accuracy and efficiency. In the last part of the contribution, two novel technological platforms, ARGOS and ATLAS, are presented. They are designed to provide a user-friendly access to data-driven models for real-time predictions for complex biomedical and industrial problems.

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Pierfrancesco Siena, Paquale Claudio Africa, Michele Girfoglio, Gianluigi Rozza. 2024-09-02. On the accuracy and efficiency of reduced order models: towards real-world applications. https://arxiv.org/abs/2407.03325

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