Gaussian process regression as a surrogate model for the computation of dispersion relations

DOI10.1016/j.cma.2023.116661OpenAlexW4390600552MaRDI QIDQ6194136

Berthy T. Feng, Katherine L. Bouman, Alexander C. Ogren, Chiara Daraio

Publication date: 19 March 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2023.116661

zbMATH Keywords

wave propagationdispersion relationmachine learningGaussian process regressionsurrogate model

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Optics, electromagnetic theory (78-XX)

Cites Work

• Wave propagation in mechanical waveguide with curved members using wave finite element solution
• Generalized Bloch mode synthesis for accelerated calculation of elastic band structures
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Variational methods for phononic calculations
• Genetic algorithm optimization of phononic bandgap structures
• Reduced Bloch mode expansion for periodic media band structure calculations
• Adaptive sampling in hierarchical simulation
• Systematic design of phononic band–gap materials and structures by topology optimization

This page was built for publication: Gaussian process regression as a surrogate model for the computation of dispersion relations