Výsledky vyhľadávania - "data-driven computational mechanics"

Data-driven identification-free approach for nonlinear structural dynamics

Autori: Paixão, Jessé Platzer, Auriane Rodriguez, Jonathan a ďalší

Prispievatelia: Paixão, Jessé Platzer, Auriane Rodriguez, Jonathan a ďalší

Zdroj: Nonlinear Dynamics. 113:18999-19021

Predmety: Hybrid Nonlinear Energy Sink, Data-driven solver, [NLIN] Nonlinear Sciences [physics], Data-driven computational mechanics, [PHYS.MECA] Physics [physics]/Mechanics [physics], Restoring force

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.science/hal-05044054v1
https://doi.org/10.1007/s11071-025-11163-7
https://hal.science/hal-05044054v1/document

Non intrusive interpolation and low rank approximation methods for nonlinear parametric models. Application to mechanical engineering.

Autori: Cloarec, Rémi Dongmo, Guissel Guevel, Y a ďalší

Prispievatelia: Cloarec, Rémi Dongmo, Guissel Guevel, Y a ďalší

Zdroj: DTE & AICOMAS 2025 3rd IACM Digital Twins in Engineering Conference (DTE 2025) & 1st ECCOMAS Artificial Intelligence and Computational Methods in Applied Science (AICOMAS 2025) ; https://cnrs.hal.science/hal-04958139 ; DTE & AICOMAS 2025 3rd IACM Digital Twins in Engineering Conference (DTE 2025) & 1st ECCOMAS Artificial Intelligence and Computational Methods in Applied Science (AICOMAS 2025), Feb 2025, Paris, France

Predmety: Digital twin, Data driven computational mechanics, Composite, Marine engineering, real-time, Applied mechanics, Singular value decomposition SVD, Sparse regression, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]

Geografické téma: Paris, France

Dostupnosť: https://cnrs.hal.science/hal-04958139

Some experiences in mixed finite element formulations for (model-free) data-driven computational mechanics

Autori: Figueredo Rocha, Felipe Quinelato, Thiago Stainier, Laurent

Prispievatelia: Figueredo Rocha, Felipe Quinelato, Thiago Stainier, Laurent

Predmety: Raviart-Thomas space, Brezzi-Douglas-Marini space, Darcy-forchheimer flow, [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], [SPI.MECA] Engineering Sciences [physics]/Mechanics [physics.med-ph], Nonlinear Poisson problem, Mixed Finite Element, (Model-free) Data-driven computational mechanics

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.science/hal-04611046v1

Some experiences in mixed finite element formulations for (model-free) data-driven computational mechanics ; Quelques expériences avec des formulations d'éléments finis mixtes pour la mécanique numérique pilotée par les données

Autori: Figueredo Rocha, Felipe, Figueredo Quinelato, Thiago Stainier, Laurent a ďalší

Prispievatelia: Figueredo Rocha, Felipe, Figueredo Quinelato, Thiago Stainier, Laurent a ďalší

Zdroj: 16ème Colloque National en Calcul de Structures (CSMA 2024)
https://hal.science/hal-04611046
16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS
CSMA
ENS Paris-Saclay
CentraleSupélec, May 2024, Hyères, France

Predmety: Mixed Finite Element, Nonlinear Poisson problem, Raviart-Thomas space, Brezzi-Douglas-Marini space, Darcy-forchheimer flow, (Model-free) Data-driven computational mechanics, [SPI.MECA]Engineering Sciences [physics]/Mechanics [physics.med-ph], [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]

Geografické téma: Hyères, France

Dostupnosť: https://hal.science/hal-04611046
https://hal.science/hal-04611046v1/document
https://hal.science/hal-04611046v1/file/508086.pdf

Algorithme prédicteur-correcteur pour la simulation de comportements élastoplastiques sans modèle de comportement

Autori: Dandin, Héloïse Leygue, Adrien Stainier, Laurent a ďalší

Prispievatelia: Dandin, Héloïse Leygue, Adrien Stainier, Laurent a ďalší

Zdroj: 16ème Colloque National en Calcul de Structures (CSMA 2024)
https://hal.science/hal-04610886
16ème Colloque National en Calcul de Structures (CSMA 2024), CNRS
CSMA
ENS Paris-Saclay
CentraleSupélec, May 2024, Hyères, France

Predmety: Data Driven Computational Mechanics, plasticité computationelle, théorie des graphes, prédicteur correcteur, [SPI]Engineering Sciences [physics]

Geografické téma: Hyères, France

Dostupnosť: https://hal.science/hal-04610886
https://hal.science/hal-04610886v1/document
https://hal.science/hal-04610886v1/file/csma2024_resume_DandinLeygueStainier.pdf

Data-driven methods for computational mechanics: A fair comparison between neural networks based and model-free approaches

Autori: Zlatić, Martin Rocha, Felipe Stainier, Laurent a ďalší

Prispievatelia: Zlatić, Martin Rocha, Felipe Stainier, Laurent a ďalší

Zdroj: ISSN: 0045-7825.

Predmety: Neural-Networks, Hyperelasticity, (Model-free) Data-driven Computational Mechanics, [SPI]Engineering Sciences [physics]

Relation: https://doi.org/10.5281/zenodo.12725683; info:eu-repo/semantics/altIdentifier/arxiv/2409.06727; ARXIV: 2409.06727

Dostupnosť: https://hal.science/hal-04701419
https://hal.science/hal-04701419v1/document
https://hal.science/hal-04701419v1/file/2024-Zlatic_etal-arXiv.pdf
https://doi.org/10.1016/j.cma.2024.117289

Graph-based representation of history-dependent material response in the Data-Driven Computational Mechanics framework

Autori: Dandin, Héloïse Leygue, Adrien Stainier, Laurent a ďalší

Prispievatelia: Dandin, Héloïse Leygue, Adrien Stainier, Laurent a ďalší

Zdroj: ISSN: 0045-7825.

Predmety: Data-Driven Computational Mechanics, computational plasticity, graph theory, I-GAIA, [SPI]Engineering Sciences [physics]

Dostupnosť: https://hal.science/hal-04259707
https://hal.science/hal-04259707v3/document
https://hal.science/hal-04259707v3/file/Dandin_Leygue_Stainier_v3.pdf
https://doi.org/10.1016/j.cma.2023.116694

A Data-Driven Model for the Analysis of Geometrically Nonlinear One-Dimensional Structures

Autori: Gjerde, Viljar Helgestad

Predmety: GO-ADM, Nonlinear Strain Measure, Nonlinear Structures, Finite Element Method, Alternating Direction Method (ADM), Mixed-Integer Nonlinear Programming (MINLP), Data-Driven Computational Mechanics (DDCM)

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/11250/3206838

A hybrid MGA-MSGD ANN training approach for approximate solution of linear elliptic PDEs

Autori: Hamidreza Dehghani Andreas Zilian Fonds National de la Recherche - FnR (PRIDE17/12252781) [sponsor] a ďalší

Prispievatelia: Hamidreza Dehghani Andreas Zilian Fonds National de la Recherche - FnR (PRIDE17/12252781) [sponsor] a ďalší

Zdroj: Mathematics and Computers in Simulation. 190:398-417

Predmety: Artificial Neural Network, Computer science [C05] [Engineering, computing & technology], FOS: Computer and information sciences, Modified Genetic Algorithm, Computer Science - Artificial Intelligence, Physics Informed ANN, Multidisciplinary, general & others [C99] [Engineering, computing & technology], Hybrid training algorithm, Mechanical engineering [C10] [Engineering, computing & technology], Data-driven computational mechanics, Numerical Analysis (math.NA), 02 engineering and technology, Sciences informatiques [C05] [Ingénierie, informatique & technologie], 01 natural sciences, Multidisciplinaire, généralités & autres [C99] [Ingénierie, informatique & technologie], Multilevel Stochastic Gradient Descent, Ingénierie mécanique [C10] [Ingénierie, informatique & technologie], Artificial Intelligence (cs.AI), FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Mathematics - Numerical Analysis, 0101 mathematics, Civil engineering [C04] [Engineering, computing & technology], Ingénierie civile [C04] [Ingénierie, informatique & technologie]

Prístupová URL adresa: http://arxiv.org/abs/2012.11517
https://dblp.uni-trier.de/db/journals/corr/corr2012.html#abs-2012-11517
https://www.sciencedirect.com/science/article/abs/pii/S0378475421002196
https://orbilu.uni.lu/bitstream/10993/45257/1/2012.11517.pdf
https://www.sciencedirect.com/science/article/pii/S0378475421002196
https://orbilu.uni.lu/handle/10993/45257
https://doi.org/10.1016/j.matcom.2021.05.036
http://orbilu.uni.lu/handle/10993/45257

ANN-aided incremental multiscale-remodelling-based finite strain poroelasticity

Autori: Hamidreza Dehghani Andreas Zilian Fonds National de la Recherche - FnR (PRIDE17/12252781) [sponsor] a ďalší

Prispievatelia: Hamidreza Dehghani Andreas Zilian Fonds National de la Recherche - FnR (PRIDE17/12252781) [sponsor] a ďalší

Zdroj: Computational Mechanics. 68:131-154

Predmety: FOS: Computer and information sciences, Remodelling of multiscale and multiphysics problems, ANN for homogenisation and localisation, Materials science & engineering [C09] [Engineering, computing & technology], Data-driven computational mechanics, Deviation from Darcy's law, 02 engineering and technology, 01 natural sciences, Computational Engineering, Finance, and Science (cs.CE), Science des matériaux & ingénierie [C09] [Ingénierie, informatique & technologie], 0203 mechanical engineering, Incremental finite strain poroelasticity, Brain tissue modelling, 0101 mathematics, Computer Science - Computational Engineering, Finance, and Science, Civil engineering [C04] [Engineering, computing & technology], Ingénierie civile [C04] [Ingénierie, informatique & technologie]

Prístupová URL adresa: https://link.springer.com/content/pdf/10.1007/s00466-021-02023-3.pdf
http://arxiv.org/abs/2103.06569
https://dblp.uni-trier.de/db/journals/corr/corr2103.html#abs-2103-06569
https://arxiv.org/abs/2103.06569
http://ui.adsabs.harvard.edu/abs/2021CompM.tmp...86D/abstract
https://link.springer.com/content/pdf/10.1007/s00466-021-02023-3.pdf
https://link.springer.com/article/10.1007/s00466-021-02023-3
http://export.arxiv.org/pdf/2103.06569
https://arxiv.org/abs/2103.06569
https://arxiv.org/pdf/2103.06569.pdf
http://orbilu.uni.lu/handle/10993/47065

Polymorphic Uncertain Structural Analysis: Challenges in Data-Driven Inelasticity

Autori: Zschocke, Selina Graf, Wolfgang Kaliske, Michael

Predmety: Polymorphic Uncertainty Quantification, Data-Driven Computational Mechanics, Multiscale Modelling, Inelastic Material Behaviour, Numerical Homogenization Methods, info:eu-repo/classification/ddc/510, ddc:510

Relation: e202200023

Dostupnosť: https://tud.qucosa.de/id/qucosa%3A95190
https://tud.qucosa.de/api/qucosa%3A95190/attachment/ATT-0/

Incorporating uncertainty in stress-strain data acquisition: extended model-free data-driven identification

Autori: Zschocke, Selina Graf, Wolfgang Kaliske, Michael

Predmety: Data-Driven Computational Mechanics (DDCM), Constitutive Material Description, Stress-Strain Relations, Polymorphic Uncertainty Models, Data-Driven Identification (DDI) Du, info:eu-repo/classification/ddc/510, ddc:510

Relation: e202300008; info:eu-repo/grantAgreement/Deutsche Forschungsgemeinschaft/SP 1886/273721697//Polymorphic Uncertainty Modelling for the Numerical Design of Structures/Structural Design of Reinforced Concrete based on Multiscale Modelling and Polymorphic Uncertainty

Dostupnosť: https://tud.qucosa.de/id/qucosa%3A95162
https://tud.qucosa.de/api/qucosa%3A95162/attachment/ATT-0/

Data-driven finite element method: Theory and applications

Autori: Siddiq, Amir University of Aberdeen.Engineering

Prispievatelia: Siddiq, Amir University of Aberdeen.Engineering

Zdroj: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 235:3329-3339

Predmety: Condensed Matter - Materials Science, carbon nanotubes, Mechanical Engineering, oriented strand board, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, data driven computational mechanics, data driven finite element method, TA Engineering (General). Civil engineering (General), 02 engineering and technology, Computational Physics (physics.comp-ph), 01 natural sciences, TA, 0203 mechanical engineering, nanocomposites, 0101 mathematics, Physics - Computational Physics, nanomaterials, biomaterials, bone scaffolds

Popis súboru: application/pdf

Prístupová URL adresa: https://aura.abdn.ac.uk/bitstream/2164/16657/1/Siddiq_JMES_DataDrivenFinite_AAM.pdf
http://arxiv.org/abs/2002.04446
https://journals.sagepub.com/doi/full/10.1177/0954406220938805
https://abdn.pure.elsevier.com/en/publications/data-driven-finite-element-method-theory-and-applications
http://aura.abdn.ac.uk/bitstream/2164/16657/1/Siddiq_JMES_DataDrivenFinite_AAM.pdf
https://aura.abdn.ac.uk/handle/2164/16657
http://journals.sagepub.com/doi/10.1177/0954406220938805

Poroelastic model parameter identification using artificial neural networks: on the effects of heterogeneous porosity and solid matrix Poisson ratio

Autori: Hamidreza Dehghani Andreas Zilian Fonds National de la Recherche - FnR (PRIDE17/12252781) [sponsor] a ďalší

Prispievatelia: Hamidreza Dehghani Andreas Zilian Fonds National de la Recherche - FnR (PRIDE17/12252781) [sponsor] a ďalší

Zdroj: Computational Mechanics. 66:625-649

Predmety: Artificial neural network, Computer science [C05] [Engineering, computing & technology], 0301 basic medicine, Géologie, ingénierie du pétrole & des mines [C08] [Ingénierie, informatique & technologie], Multidisciplinary, general & others [C99] [Engineering, computing & technology], Mechanical engineering [C10] [Engineering, computing & technology], Poroelastic media, Data-driven computational mechanics, Multiscale and multiphysics problems, Sciences informatiques [C05] [Ingénierie, informatique & technologie], 01 natural sciences, Multidisciplinaire, généralités & autres [C99] [Ingénierie, informatique & technologie], 03 medical and health sciences, Ingénierie mécanique [C10] [Ingénierie, informatique & technologie], Material characterisation, 0101 mathematics, Civil engineering [C04] [Engineering, computing & technology], Ingénierie civile [C04] [Ingénierie, informatique & technologie], Geological, petroleum & mining engineering [C08] [Engineering, computing & technology]

Prístupová URL adresa: https://link.springer.com/content/pdf/10.1007/s00466-020-01868-4.pdf
https://link.springer.com/article/10.1007/s00466-020-01868-4
https://orbilu.uni.lu/bitstream/10993/45256/1/Dehghani-Zilian2020_Article_PoroelasticModelParameterIdent.pdf
https://ui.adsabs.harvard.edu/abs/2020CompM..66..625D/abstract
https://orbilu.uni.lu/handle/10993/45256
https://link.springer.com/article/10.1007/s00466-020-01868-4?error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&error=cookies_not_supported&code=ea107973-f685-4ed0-abf3-0749d44ff620&code=2d5b55cd-5ba8-4065-8a12-6f0aeaa23099&code=c2b0cc7b-a812-4a14-8168-ca03665b666a&code=7a29bd38-836d-442d-a460-6befe4140633&code=550da320-0e09-4fce-8dab-c22122e68a8e&code=3b9cc66b-a821-4688-b6d8-63fdfc87c449&code=af4fad28-a31a-4d85-906c-cdad6b4e8b03&code=eba30d6a-4998-4860-879f-f13679536d9a&code=1bd8ceef-11f0-4aae-b944-c407af8d6c06&code=c3a76c9c-b79e-42fe-81d7-777509d1997d
https://link.springer.com/content/pdf/10.1007/s00466-020-01868-4.pdf
http://orbilu.uni.lu/handle/10993/45256

Deformation and failure in nanomaterials via a data driven modelling approach

Autori: Siddiq, Amir University of Aberdeen.Engineering

Prispievatelia: Siddiq, Amir University of Aberdeen.Engineering

Zdroj: Theoretical and Applied Mechanics Letters, Vol 10, Iss 4, Pp 249-252 (2020)

Predmety: Condensed Matter - Materials Science, Environmental Engineering, Statistical Mechanics (cond-mat.stat-mech), Mechanical Engineering, Biomedical Engineering, Computational Mechanics, Carbon nanotubes, Aerospace Engineering, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, TA Engineering (General). Civil engineering (General), Ocean Engineering, 02 engineering and technology, Engineering (General). Civil engineering (General), 01 natural sciences, Nanocomposites, Data driven computational mechanics, TA, 0203 mechanical engineering, Mechanics of Materials, TA1-2040, 0101 mathematics, Condensed Matter - Statistical Mechanics, Civil and Structural Engineering, Nanomaterials

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/abs/1910.00966
https://doaj.org/article/be2176d37a154c9ba1b3bc5f53187136
https://www.sciencedirect.com/science/article/pii/S2095034920300416
https://dblp.uni-trier.de/db/journals/corr/corr1910.html#abs-1910-00966
https://ui.adsabs.harvard.edu/abs/2019arXiv191000966S/abstract
https://aura.abdn.ac.uk/handle/2164/14851
https://abdn.pure.elsevier.com/en/publications/deformation-and-failure-in-nanomaterials-via-a-data-driven-modell
http://dblp.uni-trier.de/db/journals/corr/corr1910.html#abs-1910-00966

Wear across scales

Autori: Wattel, Sacha Zenon

Predmety: Data-Driven Computational Mechanics, Tribology, Ductile-to-brittle transition, Wear, Surrogate models, Molecular Dynamics, Neural networks

Model-free data-driven methods in mechanics: material data identification and solvers

Autori: Stainier, Laurent Leygue, Adrien Ortiz, Michael a ďalší

Prispievatelia: Stainier, Laurent Leygue, Adrien Ortiz, Michael a ďalší

Zdroj: Computational Mechanics. 64:381-393

Predmety: Computational Engineering, Finance, and Science (cs.CE), FOS: Computer and information sciences, Importance sampling, Material data identification, [SPI.MECA.MSMECA] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Materials and structures in mechanics [physics.class-ph], [SPI.MECA.MSMECA]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Materials and structures in mechanics [physics.class-ph], Data-driven computational mechanics, Computer Science - Computational Engineering, Finance, and Science, Field measures

Popis súboru: application/pdf

Prístupová URL adresa: https://authors.library.caltech.edu/96127/3/1903.07983.pdf
http://arxiv.org/abs/1903.07983
https://hal.archives-ouvertes.fr/hal-02159717/document
https://ui.adsabs.harvard.edu/abs/2019CompM..64..381S/abstract
https://arxiv.org/pdf/1903.07983.pdf
https://link.springer.com/article/10.1007/s00466-019-01731-1
https://arxiv.org/abs/1903.07983
http://dblp.uni-trier.de/db/journals/corr/corr1903.html#abs-1903-07983
https://arxiv.org/pdf/1903.07983
https://arxiv.org/abs/1903.07983

Graph-based representation of history-dependent material response in the Data-Driven Computational Mechanics framework

Autori: Dandin, Héloïse Leygue, Adrien Stainier, Laurent a ďalší

Prispievatelia: Dandin, Héloïse Leygue, Adrien Stainier, Laurent a ďalší

Zdroj: https://hal.science/hal-04259707 ; 2023.

Predmety: Data-Driven Computational Mechanics, computational plasticity, graph theory, I-GAIA, [SPI]Engineering Sciences [physics]

Relation: hal-04259707; https://hal.science/hal-04259707; https://hal.science/hal-04259707v2/document; https://hal.science/hal-04259707v2/file/Dandin_Leygue_Stainier_preprint_v2.pdf

Dostupnosť: https://hal.science/hal-04259707
https://hal.science/hal-04259707v2/document
https://hal.science/hal-04259707v2/file/Dandin_Leygue_Stainier_preprint_v2.pdf

Data driven approach in multiphysics framework: application to coupled electro-mechanical problems

Autori: Marenić, Eduard Seychal, Guillem Passieux, Jean-Charles a ďalší

Prispievatelia: Marenić, Eduard Seychal, Guillem Passieux, Jean-Charles a ďalší

Zdroj: ISSN: 0045-7825.

Predmety: Data driven approach, model-free, data driven computational mechanics, multiphysics, coupled problem, piezoelectricity, [SPI.MECA.SOLID]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Solid mechanics [physics.class-ph]

Dostupnosť: https://hal.science/hal-03626061
https://hal.science/hal-03626061v1/document
https://hal.science/hal-03626061v1/file/PaperDDCM_piezo_preprint.pdf
https://doi.org/10.1016/j.cma.2022.114959

Phase distribution and properties identification of heterogeneous materials: a data-driven approach

Autori: Valdés Alonzo, Gabriel Rolando Binetruy, Christophe Eck, Benedikt a ďalší

Prispievatelia: Valdés Alonzo, Gabriel Rolando Binetruy, Christophe Eck, Benedikt a ďalší

Predmety: Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències, Elasticity, Strength of materials, Data-driven computational mechanics, Data-driven identification, Correspondence analysis, Digital image correlation, Composites, Elasticitat, Resistència de materials, Classificació AMS::74 Mechanics of deformable solids::74B Elastic materials, Classificació AMS::74 Mechanics of deformable solids::74S Numerical methods

Popis súboru: application/pdf

Relation: https://www.sciencedirect.com/science/article/abs/pii/S0045782521006290?via%3Dihub; info:eu-repo/grantAgreement/EC/H2020/764636/EU/Industrial decision-making on complex production technologies supported by simulation-based engineering/ProTechTion; http://hdl.handle.net/2117/367374

Dostupnosť: http://hdl.handle.net/2117/367374
https://doi.org/10.1016/j.cma.2021.114354