dc.contributorTorres Acosta, Andrés Antonio
dc.contributorEscuela de Ingeniería y Ciencias
dc.contributorRangel Ramírez, José Guadalupe
dc.contributorHerrera Sosa, Eduardo Sadot
dc.contributorCrespo Sánchez, Saúl Enrique
dc.contributorCampus Monterrey
dc.contributordnbsrp
dc.creatorMedina Hernandez, Job Rigoberto
dc.date.accessioned2023-07-14T22:21:58Z
dc.date.accessioned2023-07-19T19:08:35Z
dc.date.available2023-07-14T22:21:58Z
dc.date.available2023-07-19T19:08:35Z
dc.date.created2023-07-14T22:21:58Z
dc.date.issued2023-06
dc.identifierMedina, J. (2023). Prognosis estructural en obras de infraestructura a partir de digital twins [Tesis de maestría, Tecnológico de Monterrey].
dc.identifierhttps://hdl.handle.net/11285/651040
dc.identifierhttps://orcid.org/0009-0005-1151-7130
dc.identifier1151881
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7715600
dc.description.abstractThe infrastructure industry plays a vital role in the development of society; however, its significant environmental impact often goes unnoticed. Designing and constructing infrastructure to be robust, effectively managing it, and securing its lifespan are essential strategic tasks. A methodology is presented that integrates structural health monitoring with a novel virtualization of infrastructure systems using LiDAR technology and digital twins—virtual models that replicate a system’s real-world behavior. Digital twins serve as a powerful tool in the prognosis of infrastructure, allowing for a comprehensive evaluation and analysis of infrastructure. Moreover, this digital twin can be created by using readily available automated tools. Results show that digital twins are an accessible and effective solution for smart infrastructure management, enabling informed decision-making and proactive maintenance strategies.
dc.languagespa
dc.publisherInstituto Tecnológico y de Estudios Superiores de Monterrey
dc.relationacceptedVersion
dc.rightshttp://creativecommons.org/licenses/by/4.0
dc.rightsopenAccess
dc.titlePrognosis estructural en obras de infraestructura a partir de digital twins
dc.typeTesis de Maestría / master Thesis


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