2026-06-01T16:37:35Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/308232026-02-03T11:24:43Zcom_10630_2254col_10630_37953

Integrating FMI and ML/AI models on the open-sourcedigital twin framework OpenTwins Infante, Sergio Martín-Fernández, Cristian Robles, Julia Rubio-Muñoz, Bartolomé Díaz-Rodríguez, Manuel González Perea, Rafael Montesinos, Pilar Camacho Poyato, Emilio Soporte lógico libre Industria - Simulación por ordenador The realm of digital twins is experiencing rapid growth and presents a wealth ofopportunities for Industry 4.0. In conjunction with traditional simulation meth-ods, digital twins offer a diverse range of possibilities. However, many existingtoolsinthedomainofopen-sourcedigitaltwinsconcentrateonspecificusecasesand do not provide a versatile framework. In contrast, the open-source digitaltwin framework, OpenTwins, aims to provide a versatile framework that can beappliedtoawiderangeofdigitaltwinapplications.Inthisarticle,weintroduceare-definition of the original OpenTwins platform that enables the managementof custom simulation services and the management of FMI simulation services,whichisoneofthemostwidelyusedsimulationstandardsintheindustryanditscoexistence with machine learning models, which enables the definition of thenext-gendigitaltwins.Thankstothisintegration,digitaltwinsthatreflectrealitybetter can be developed, through hybrid models, where simulation data can feedthe scarcity of machine learning data and so forth. As part of this project, a sim-ulation model developed through the hydraulic software Epanet was validatedin OpenTwins, in addition to an FMI simulation service. The hydraulic modelwas implementedandtestedinanagricultural usecaseincollaboration withtheUniversity of Córdoba, Spain. A machine learning model has been developed toassess the behavior of an FMI simulation through machine learning. 2024-03-13T11:22:31Z 2024-03-13T11:22:31Z 2024-03-13T11:22:31Z 2024-03-24 journal article Infante S., Martín C., Robles J., et al. Integrating FMI and ML/AI models on the open-source digital twin framework OpenTwins. Softw: Pract Exper. 2024;1-21. doi: 10.1002/spe.3322 https://hdl.handle.net/10630/30823 10.1002/spe.3322 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional Wiley