Prognosis estructural en obras de infraestructura a partir de digital twins
| dc.audience.educationlevel | Investigadores/Researchers | es_MX |
| dc.contributor.advisor | Torres Acosta, Andrés Antonio | |
| dc.contributor.author | Medina Hernandez, Job Rigoberto | |
| dc.contributor.cataloger | dnbsrp | es_MX |
| dc.contributor.committeemember | Rangel Ramírez, José Guadalupe | |
| dc.contributor.committeemember | Herrera Sosa, Eduardo Sadot | |
| dc.contributor.department | Escuela de Ingeniería y Ciencias | es_MX |
| dc.contributor.institution | Campus Monterrey | es_MX |
| dc.contributor.mentor | Crespo Sánchez, Saúl Enrique | |
| dc.date.accepted | 2023-06-15 | |
| dc.date.accessioned | 2023-07-14T22:21:58Z | |
| dc.date.available | 2023-07-14T22:21:58Z | |
| dc.date.issued | 2023-06 | |
| dc.description | https://orcid.org/0000-0003-0058-9903 | es_MX |
| dc.description.abstract | The 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. | es_MX |
| dc.description.degree | Maestro en Ciencias de la Ingeniería | es_MX |
| dc.format.medium | Texto | es_MX |
| dc.identificator | 7 | es_MX |
| dc.identifier.citation | Medina, J. (2023). Prognosis estructural en obras de infraestructura a partir de digital twins [Tesis de maestría, Tecnológico de Monterrey]. | es_MX |
| dc.identifier.cvu | 1151881 | es_MX |
| dc.identifier.orcid | https://orcid.org/0009-0005-1151-7130 | es_MX |
| dc.identifier.uri | https://hdl.handle.net/11285/651040 | |
| dc.language.iso | spa | es_MX |
| dc.publisher | Instituto Tecnológico y de Estudios Superiores de Monterrey | es_MX |
| dc.relation.isFormatOf | acceptedVersion | es_MX |
| dc.rights | openAccess | es_MX |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0 | es_MX |
| dc.subject.classification | INGENIERÍA Y TECNOLOGÍA | es_MX |
| dc.subject.keyword | SHM | es_MX |
| dc.subject.keyword | Digital twin | es_MX |
| dc.subject.keyword | LiDAR | es_MX |
| dc.subject.keyword | Photogrammetry | es_MX |
| dc.subject.keyword | Resistencia de estructuras | es_MX |
| dc.subject.lcsh | Technology | es_MX |
| dc.title | Prognosis estructural en obras de infraestructura a partir de digital twins | es_MX |
| dc.type | Tesis de maestría |
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