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Structural health monitoring data collected during construction of a mass-timber building with a data platform for analysis

The George W. Peavy Forest Science Complex, or “Peavy Hall,” is a mass-timber university building that is the subject of a structural health monitoring (SHM) program to create a comprehensive building performance dataset. The building substructure consists of cross-laminated timber (CLT)-concrete co...

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Detalles Bibliográficos
Autores principales: Baas, Esther J., Riggio, Mariapaola, Barbosa, André R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7903298/
https://www.ncbi.nlm.nih.gov/pubmed/33665247
http://dx.doi.org/10.1016/j.dib.2021.106845
Descripción
Sumario:The George W. Peavy Forest Science Complex, or “Peavy Hall,” is a mass-timber university building that is the subject of a structural health monitoring (SHM) program to create a comprehensive building performance dataset. The building substructure consists of cross-laminated timber (CLT)-concrete composite floors, a mass plywood panel (MPP) roof system, and the world's first application of CLT post-tensioned (PT) self-centering shear walls. This document reports on static and hygrothermal data collected during the final ten months of building construction that were used to validate a proposed methodological approach to SHM for mass-timber buildings under construction, described in A Methodological Approach for Structural Health Monitoring of Mass-Timber Buildings Under Construction[1]. These data, available in the repository at https://osf.io/jdz6y/, include wood moisture content of CLT, MPP, and glulam structural components, horizontal and vertical displacements of axially loaded CLT panels, tension loss of PT steel rods within CLT self-centering walls, and indoor and outdoor environmental conditions such as temperature, relative humidity, rain quantities, wind speeds, as well as wind directions. Additionally, data figures and analysis coding files are included in the repository to further define processes and allow for potential use of the analysis tools for similar projects.