Determination of criteria for the exploration and for obtaining indicators in evolutional analysis of degradation in urban facades
Autor: | Gibert Armengol, Vicente, Serrat Piè, Carles, Casas Rius, Joan Ramon |
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Přispěvatelé: | Universitat Politècnica de Catalunya. Departament de Construccions Arquitectòniques II, Universitat Politècnica de Catalunya. Departament de Matemàtiques, Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental, Universitat Politècnica de Catalunya. GREiP - Grup de Recerca d'Edificació i Patrimoni, Universitat Politècnica de Catalunya. GRBIO - Grup de Recerca en Bioestadística i Bioinformàtica, Universitat Politècnica de Catalunya. EC - Enginyeria de la Construcció |
Jazyk: | angličtina |
Rok vydání: | 2014 |
Předmět: | |
Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya instname |
Popis: | The interest of this research is motivated by the huge constructive development in the building sector, which has led to an enormous volume of buildings worldwide over the last decades. This fact, as well as poor management in conservation of buildings, mainly in urban cities, has led to total degradation situations on the facades of building stocks. To infer on the evolutional process of degradation that occurs in the facade, during its service life and based on the information obtained from inspections, the method for the data analysis (e.g. survival analysis techniques) is as important as the truthfulness and usefulness of the data collected on the subjects (facades) under study. In this paper we propose a method based on the design of indicators for prospecting and global data collection on the injury state of the inspected facades. The method analyzes how to perform the identification, classification, methodology, resources and quality of the data in order to be reliable, testable and measurable. The proposed model enables the macro inspection and monitoring of large-scale urban zones and the data obtained allow the researcher to understand and manage the predictive degradation phenomenon and, in turn, eliminate potential risks in the urban front. |
Databáze: | OpenAIRE |
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