Digital twins that learn and correct themselves

Moya, Beatriz (Universidad de Zaragoza) ; Badías, Alberto ; Alfaro, Icíar (Universidad de Zaragoza) ; Chinesta, Francisco ; Cueto, Elías (Universidad de Zaragoza)

Resumen: Digital twins can be defined as digital representations of physical entities that employ real‐time data to enable understanding of the operating conditions of these entities. Here we present a particular type of digital twin that involves a combination of computer vision, scientific machine learning, and augmented reality. This novel digital twin is able, therefore, to see, to interpret what it sees—and, if necessary, to correct the model it is equipped with—and presents the resulting information in the form of augmented reality. The computer vision capabilities allow the twin to receive data continuously. As any other digital twin, it is equipped with one or more models so as to assimilate data. However, if persistent deviations from the predicted values are found, the proposed methodology is able to correct on the fly the existing models, so as to accommodate them to the measured reality. Finally, the suggested methodology is completed with augmented reality capabilities so as to render a completely new type of digital twin. These concepts are tested against a proof‐of‐concept model consisting on a nonlinear, hyperelastic beam subjected to moving loads whose exact position is to be determined.

Idioma: Inglés

DOI: 10.1002/nme.6535

Año: 2022

Publicado en: International Journal for Numerical Methods in Engineering 123, 13 (2022), 3034-3044
ISSN: 0029-5981

Factor impacto JCR: 2.9 (2022)

Categ. JCR: MATHEMATICS, INTERDISCIPLINARY APPLICATIONS rank: 27 / 107 = 0.252 (2022) - Q2 - T1
Categ. JCR: ENGINEERING, MULTIDISCIPLINARY rank: 39 / 90 = 0.433 (2022) - Q2 - T2

Factor impacto CITESCORE: 5.2 - Mathematics (Q1) - Engineering (Q2)

Factor impacto SCIMAGO: 1.043 - Applied Mathematics (Q1) - Numerical Analysis (Q1) - Engineering (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2017-85139-C2-1-R

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)