Indicador de daños que afectan a la durabilidad de las estructuras en entornos BIM

El Building Information Modelling (BIM) se está adoptando cada vez más en empresas privadas del sector de Arquitectura, Ingeniería, Construcción y Operación (AECO), y con ello surgen nuevas herramientas y funcionalidades. En el mercado español, los proyectos de reforma son cada vez más solicitados debido al envejecimiento del stock de viviendas y la necesidad de analizar la durabilidad de las estructuras existentes.

Este nuevo estudio presenta una herramienta integrada en BIM que permite evaluar el índice de durabilidad en elementos estructurales específicos a través de una inspección visual automatizada, lo que mejora la sostenibilidad del sector y determina el momento crítico para rehabilitar la estructura.

El trabajo se enmarca dentro del proyecto de investigación HYDELIFE que dirijo como investigador principal en la Universitat Politècnica de València.

Abstract:

As Building Information Modelling (BIM) is increasingly adopted through private businesses in the Architecture, Engineering, Construction, and Operation (AECO) Industries, new tools, procedures, and functionalities appear. In the last years, BIM has proven its advantages by providing benefits to professionals and guiding them towards a new horizon. Currently, the industry is changing in the Spanish market, and refurbishment projects are more demanded than construction projects involving the design of buildings from scratch. As Spanish housing stock grows older, durability and damage in existing structures need to be analyzed during the refurbishment project’s early stages. Structural durability is a critical factor in extending the life span of a building and improving the industry’s sustainability. This paper presents a tool integrated into BIM environments that can evaluate the durability index in a specific structural element based on data from a visual inspection. This automated analysis shows if any damage is caused by durability factors, such as steel rebar corrosion, and how much time is left until the damage is critical. This tool enables new functionality in BIM environments to control durability and determine when it is critical to rehabilitating the structure.

Referencia:

FERNÁNDEZ-MORA, V.; YEPES, V.; NAVARRO, I.J. (2022). Durability damage indicator in BIM environments. Proceedings of 3rd Valencia International Biennial of Research in Architecture. Changing priorities. 9-11 November 2022, Valencia, Spain. https://doi.org/10.4995/VIBRArch2022.2022.15191

Os paso, para su descarga, el artículo completo, pues está publicado en abierto.

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Redes neuronales aplicadas al diseño multiobjetivo de puentes postesados

Nos acaban de publicar en línea en la revista Structural and Multidisciplinary Optimization (revista indexada en JCR en el primer cuartil) un trabajo de investigación en el que utilizamos las redes neuronales artificiales junto para el diseño multiobjetivo de puentes postesados de carreteras. Os paso a continuación el resumen y el enlace al artículo por si os resulta de interés. El enlace del artículo es el siguiente: http://link.springer.com/article/10.1007%2Fs00158-017-1653-0

Referencia:

García-Segura, T.; Yepes, V.; Frangopol, D.M. (2017). Multi-objective design of post-tensioned concrete road bridges using artificial neural networks. Structural and Multidisciplinary Optimization, doi:10.1007/s00158-017-1653-0

Abstract:

In order to minimize the total expected cost, bridges have to be designed for safety and durability. This paper considers the cost, the safety, and the corrosion initiation time to design post-tensioned concrete box-girder road bridges. The deck is modeled by finite elements based on problem variables such as the cross-section geometry, the concrete grade, and the reinforcing and post-tensioning steel. An integrated multi-objective harmony search with artificial neural networks (ANNs) is proposed to reduce the high computing time required for the finite-element analysis and the increment in conflicting objectives. ANNs are trained through the results of previous bridge performance evaluations. Then, ANNs are used to evaluate the constraints and provide a direction towards the Pareto front. Finally, exact methods actualize and improve the Pareto set. The results show that the harmony search parameters should be progressively changed in a diversification-intensification strategy. This methodology provides trade-off solutions that are the cheapest ones for the safety and durability levels considered. Therefore, it is possible to choose an alternative that can be easily adjusted to each need.

Keywords:

Multi-objective harmony search; Artificial neural networks; Post-tensioned concrete bridges; Durability; Safety.

Os dejo a continuación la versión autor del artículo.

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Life cycle greenhouse gas emissions of blended cement concrete including carbonation and durability

Esta es la versión post-print de autor. La publicación se encuentra en: https://riunet.upv.es/handle/10251/49057, siendo el Copyright de Springer Verlag (Germany).

El artículo debe ser citado de la siguiente forma:

GARCÍA-SEGURA, T.; YEPES, V.; ALCALÁ, J. (2014). Life-cycle greenhouse gas emissions of blended cement concrete including carbonation and durability. The International Journal of Life Cycle Assessment, 19(1):3-12. DOI 10.1007/s11367-013-0614-0

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