Top-down metacomputing with algebraic dimensionality raising for automating theory-building to enable directly computable multiphysics models

Author:

Michopoulos J.G.ORCID,Apetre N.A.,Steuben J.C.,Iliopoulos A.P.

Publisher

Elsevier BV

Subject

Modeling and Simulation,General Computer Science,Theoretical Computer Science

Reference96 articles.

1. Bottom-up hierarchical and categorical metacomputing for automating composition and deployment of directly computable multiphysics models;Michopoulos;J. Comput. Sci.,2023

2. Modeling and simulation of multiphysics systems;Michopoulos;J. Comput. Inf. Sci. Eng.,2005

3. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations;Raissi;J. Comput. Phys.,2019

4. On a application of complex function theory to a plane problem of the mathematical theory of elasticity (in Russian);Kolosov,1909

5. Some Basic Problems of the Mathematical Theory of Elasticity;Muskhelishvili,1953

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Metacomputing for Directly Computable Multiphysics Models;Journal of Computing and Information Science in Engineering;2023-09-14

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