RT Journal Article
T1 Integrating FMI and ML/AI models on the open-sourcedigital twin framework OpenTwins
A1 Infante, Sergio
A1 Martín-Fernández, Cristian
A1 Robles, Julia
A1 Rubio-Muñoz, Bartolomé
A1 Díaz-Rodríguez, Manuel
A1 González Perea, Rafael
A1 Montesinos, Pilar
A1 Camacho Poyato, Emilio
K1 Soporte lógico libre
K1 Industria - Simulación por ordenador
AB 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.
PB Wiley
YR 2024
FD 2024-03-24
LK https://hdl.handle.net/10630/30823
UL https://hdl.handle.net/10630/30823
LA eng
NO 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
NO Funding for open access charge: Universidad de Málaga/CBUA.This work is funded by the Spanish projects TSI-063000-2021-116 (“5G+TACTILE_2: Digital vertical twins for B5G/6G networks”), TED2021-130167B (“GEDIER: Application of Digital Twins to more sustainable irrigated farms”), PID2022-141705OB-C21 (“DiTaS: A framework for agnostic compositional and cognitive digital twin services”), and MIG-20221022 (“GEDERA: Intelligent Flexible Energy Demand Management in Coupled Hybrid Networks”).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026