Advances in thermal barrier coatings modeling, simulation, and analysis: A review
A Ashofteh, M Rajabzadeh - Journal of the European Ceramic Society, 2024 - Elsevier
This review presents an approach to traditional and advanced modeling, simulation, and
analysis techniques in the context of thermal barrier coatings (TBCs), augmented by AI …
analysis techniques in the context of thermal barrier coatings (TBCs), augmented by AI …
Review on the theories and applications of dynamic condensation and component mode synthesis methods in solving FEM-based structural dynamics
Y Sun, Y Lu, Z Song - Acta Mechanica Solida Sinica, 2023 - Springer
The rapid development of modern science, technology, and industrialization has promoted
the birth of more large and complex engineering structures. When the finite element (FE) …
the birth of more large and complex engineering structures. When the finite element (FE) …
[HTML][HTML] Machine learning of evolving physics-based material models for multiscale solid mechanics
In this work we present a hybrid physics-based and data-driven learning approach to
construct surrogate models for concurrent multiscale simulations of complex material …
construct surrogate models for concurrent multiscale simulations of complex material …
Trustworthy AI for human-centric smart manufacturing: A survey
Human-centric smart manufacturing (HCSM) envisions a symbiotic relationship between
humans and machines, leveraging human capability and Artificial Intelligence (AI)'s …
humans and machines, leveraging human capability and Artificial Intelligence (AI)'s …
A manifold learning approach to nonlinear model order reduction of quasi-static problems in solid mechanics
L Scheunemann, E Faust - arXiv preprint arXiv:2408.12415, 2024 - arxiv.org
The proper orthogonal decomposition (POD)--a popular projection-based model order
reduction (MOR) method--may require significant model dimensionalities to successfully …
reduction (MOR) method--may require significant model dimensionalities to successfully …
Learning Projection-Based Reduced-Order Models
In this chapter, we introduce the solution space for high-fidelity models based on partial
differential equations and the finite element model. The manifold learning approach to …
differential equations and the finite element model. The manifold learning approach to …
[PDF][PDF] BasicTools: a numerical simulation toolbox
Numerical simulations of physical phenomena can be computed by many (commercial/free)
software packages, but despite the apparent variety, all of them rely on a relatively small set …
software packages, but despite the apparent variety, all of them rely on a relatively small set …
Nonlinear model order reduction using local basis methods on RVEs: A parameter study and comparison of different variants
E Faust, L Scheunemann - PAMM, 2024 - Wiley Online Library
All possible solutions to a static representative volume element (RVE) problem lie on a
solution manifold, which is often quite low‐dimensional. Solutions of a hyperelastic 3D RVE …
solution manifold, which is often quite low‐dimensional. Solutions of a hyperelastic 3D RVE …
Industrial Application: Uncertainty Quantification in Lifetime Prediction of Turbine Blades
In this chapter, many of the concepts introduced in the previous chapters are applied to the
uncertainty quantification of the lifetime prediction of turbine blades, generated by the …
uncertainty quantification of the lifetime prediction of turbine blades, generated by the …
Muscat: Mesh manipulation and finite element engine for engineering and science
Résumé Numerical simulations of physical phenomena can be computed by many
(commercial/free) software packages, but despite the apparent variety, all of them rely on a …
(commercial/free) software packages, but despite the apparent variety, all of them rely on a …