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Data-Driven Stochastic Averaging
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Stochastic averaging, as an effective technique for dimension reduction, is of great significance in stochastic dynamics and control. However, its practical applications in industrial and engineering fields are severely ...
Automatedly Distilling Canonical Equations From Random State Data
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Canonical equations play a pivotal role in various sub-fields of physics and mathematics. However, for complex systems and systems without first principles, deriving canonical equations analytically is quite laborious or ...
Automated Identification of Differential-Variational Equations for Static Systems
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Data-driven equation identification for dynamical systems has achieved great progress, which for static systems, however, has not kept pace. Unlike dynamical systems, static systems are time invariant, so we cannot capture ...
AI-Timoshenko: Automatedly Discovering Simplified Governing Equations for Applied Mechanics Problems From Simulated Data
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The simplified governing equations of applied mechanics play a pivotal role and were derived based on ingenious assumptions or hypotheses regarding the displacement fields for specific problems. In this paper, we introduce ...