Data-Driven Acceleration of Multi-Physics Simulations
arxiv(2024)
Abstract
Multi-physics simulations play a crucial role in understanding complex
systems. However, their computational demands are often prohibitive due to high
dimensionality and complex interactions, such that actual calculations often
rely on approximations. To address this, we introduce a data-driven approach to
approximate interactions among degrees of freedom of no direct interest and
thus significantly reduce computational costs. Focusing on a semiconductor
laser as a case study, we demonstrate the superiority of this method over
traditional analytical approximations in both accuracy and efficiency. Our
approach streamlines simulations, offering promise for complex multi-physics
systems, especially for scenarios requiring a large number of individual
simulations.
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