000119961 001__ 119961
000119961 005__ 20230914083712.0
000119961 0247_ $$2doi$$a10.1186/s40323-022-00234-8
000119961 0248_ $$2sideral$$a130667
000119961 037__ $$aART-2022-130667
000119961 041__ $$aeng
000119961 100__ $$aChinesta, Francisco
000119961 245__ $$aEmpowering engineering with data, machine learning and artificial intelligence: a short introductive review
000119961 260__ $$c2022
000119961 5060_ $$aAccess copy available to the general public$$fUnrestricted
000119961 5203_ $$aSimulation-based engineering has been a major protagonist of the technology of the last century. However, models based on well established physics fail sometimes to describe the observed reality. They often exhibit noticeable differences between physics-based model predictions and measurements. This difference is due to several reasons: practical (uncertainty and variability of the parameters involved in the models) and epistemic (the models themselves are in many cases a crude approximation of a rich reality). On the other side, approaching the reality from experimental data represents a valuable approach because of its generality. However, this approach embraces many difficulties: model and experimental variability; the need of a large number of measurements to accurately represent rich solutions (extremely nonlinear or fluctuating), the associate cost and technical difficulties to perform them; and finally, the difficulty to explain and certify, both constituting key aspects in most engineering applications. This work overviews some of the most remarkable progress in the field in recent years.
000119961 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000119961 592__ $$a0.656$$b2022
000119961 593__ $$aEngineering (miscellaneous)$$c2022$$dQ1
000119961 593__ $$aModeling and Simulation$$c2022$$dQ2
000119961 593__ $$aApplied Mathematics$$c2022$$dQ2
000119961 593__ $$aComputer Science Applications$$c2022$$dQ2
000119961 594__ $$a4.5$$b2022
000119961 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000119961 700__ $$0(orcid)0000-0003-1017-4381$$aCueto, Elias$$uUniversidad de Zaragoza
000119961 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000119961 773__ $$g9 (2022), 1-24$$pAdv. model. simul. eng. sci.$$tAdvanced modeling and simulation in engineering sciences$$x2213-7467
000119961 8564_ $$s395872$$uhttps://zaguan.unizar.es/record/119961/files/texto_completo.pdf$$yVersión publicada
000119961 8564_ $$s2110067$$uhttps://zaguan.unizar.es/record/119961/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000119961 909CO $$ooai:zaguan.unizar.es:119961$$particulos$$pdriver
000119961 951__ $$a2023-09-13-14:35:49
000119961 980__ $$aARTICLE