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Data-driven modeling and simulation ...

... via physicsinformed machine learning on the example of a double spring-damper-mass-system

€25.00

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Product Details
Description

For the double spring mass damper system, there are only measurement data for the mass 1 and partial differential equation and initial conditions for mass 2. From these imperfect data and physics, the system response can be modeled and simulated in real-time based on the physic-informed machine learning. The simulation and measurement of the system response coincides totally. This novel technology show case presents the new way, how to model the system from any mix of data and physical components as partial differential equation, initial conditions and constraints.

Reference: NumSim-2025-481

Author(s): T.Q. Pham
DOI: 10.48447/NumSim-2025-481
Year of publication: 2025
Publication type: conference paper (PDF)
Language: German
Keywords: Hilbert space, simulation, physics-informed machine learning, double-spring-mass-damper

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