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Research Portal of the TU Dresden

Computational Mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity

ISSNs: 0178-7675

Additional searchable ISSN (electronic): 1432-0924

Springer Verlag, Germany

Scopus rating (2024): CiteScore 7.9 SJR 1.256 SNIP 1.36

Journal

Titles	Computational Mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity Computational Mechanics Computational mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity
Additional searchable titles	Computational mechanics : research journal
ISSNs	0178-7675
Additional searchable ISSN (electronic)	1432-0924
Publisher	Springer Verlag
Country/Territory	Germany
ZDB-ID	1458937-0
ZDB-ID	799787-5

Keywords

ASJC Scopus subject areas

Computational Mechanics
Ocean Engineering
Mechanical Engineering
Computational Theory and Mathematics
Computational Mathematics
Applied Mathematics

Library keywords

530 Physics
004 Computer science

Related content

Research output

A nonlocally-informed locally-scaled method for fracture: numerical implementation to model fragmentation of tempered glass

Kanan, A., Storm, J. & Kaliske, M., Sept 2025, In: Computational Mechanics. 76, 3, p. 745-767 23 p.

Research output: Contribution to journal › Research article › Contributed › peer-review

Inverse design of spinodoid structures using Bayesian optimization

Raßloff, A., Seibert, P., Kalina, K. A. & Kästner, M., 19 Feb 2025, In: Computational mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity. (2025), 22 p., 104726.

Research output: Contribution to journal › Research article › Contributed › peer-review

Enforcement of non-conforming dirichlet boundary conditions in the implicit material point method using the direct elimination method

Meyer, J. & Kaliske, M., 2025, (Accepted/In press) In: Computational Mechanics. 76, 3, p. 1-22

Research output: Contribution to journal › Research article › Contributed › peer-review

Learning solutions of thermodynamics-based nonlinear constitutive material models using physics-informed neural networks

Rezaei, S., Moeineddin, A. & Harandi, A., Aug 2024, In: Computational Mechanics. 74, 2, p. 333-366 34 p.

Research output: Contribution to journal › Research article › Contributed › peer-review

Viscoelasticty with physics-augmented neural networks: model formulation and training methods without prescribed internal variables

Rosenkranz, M., Kalina, K. A., Brummund, J., Sun, W. & Kästner, M., 6 May 2024, In: Computational Mechanics : solids, fluids, engineered materials, aging infrastructure, molecular dynamics, heat transfer, manufacturing processes, optimization, fracture & integrity. 74, 6, p. 1279-1301 23 p.

Research output: Contribution to journal › Research article › Contributed › peer-review

View all research output (38)