000125258 001__ 125258
000125258 005__ 20241125101136.0
000125258 0247_ $$2doi$$a10.1016/j.cma.2023.115912
000125258 0248_ $$2sideral$$a132991
000125258 037__ $$aART-2023-132991
000125258 041__ $$aeng
000125258 100__ $$aHernández, Quercus
000125258 245__ $$aThermodynamics-informed neural networks for physically realistic mixed reality
000125258 260__ $$c2023
000125258 5060_ $$aAccess copy available to the general public$$fUnrestricted
000125258 5203_ $$aThe imminent impact of immersive technologies in society urges for active research in real-time and interactive physics simulation for virtual worlds to be realistic. In this context, realistic means to be compliant to the laws of physics. In this paper we present a method for computing the dynamic response of (possibly non-linear and dissipative) deformable objects induced by real-time user interactions in mixed reality using deep learning. The graph-based architecture of the method ensures the thermodynamic consistency of the predictions, whereas the visualization pipeline allows a natural and realistic user experience.
Two examples of virtual solids interacting with virtual or physical solids in mixed reality scenarios are provided to prove the performance of the method.
000125258 536__ $$9info:eu-repo/grantAgreement/ES/MICINN-AEI/PID2020-113463RB-C31/AEI/10.13039/501100011033
000125258 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000125258 590__ $$a6.9$$b2023
000125258 592__ $$a2.397$$b2023
000125258 591__ $$aMECHANICS$$b7 / 170 = 0.041$$c2023$$dQ1$$eT1
000125258 593__ $$aComputational Mechanics$$c2023$$dQ1
000125258 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b4 / 135 = 0.03$$c2023$$dQ1$$eT1
000125258 593__ $$aComputer Science Applications$$c2023$$dQ1
000125258 591__ $$aENGINEERING, MULTIDISCIPLINARY$$b6 / 181 = 0.033$$c2023$$dQ1$$eT1
000125258 593__ $$aPhysics and Astronomy (miscellaneous)$$c2023$$dQ1
000125258 593__ $$aMechanics of Materials$$c2023$$dQ1
000125258 593__ $$aMechanical Engineering$$c2023$$dQ1
000125258 594__ $$a12.7$$b2023
000125258 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000125258 700__ $$0(orcid)0000-0001-7639-6767$$aBadías, Alberto
000125258 700__ $$aChinesta, Francisco
000125258 700__ $$0(orcid)0000-0003-1017-4381$$aCueto, Elías$$uUniversidad de Zaragoza
000125258 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000125258 773__ $$g407 (2023), 115912 [11 pp.]$$pComput. methods appl. mech. eng.$$tComputer Methods in Applied Mechanics and Engineering$$x0045-7825
000125258 8564_ $$s1237465$$uhttps://zaguan.unizar.es/record/125258/files/texto_completo.pdf$$yVersión publicada
000125258 8564_ $$s2051912$$uhttps://zaguan.unizar.es/record/125258/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000125258 909CO $$ooai:zaguan.unizar.es:125258$$particulos$$pdriver
000125258 951__ $$a2024-11-22-12:00:51
000125258 980__ $$aARTICLE