concrete – El blog de Víctor Yepes

Evaluación del ciclo de vida de un puente en ambiente marino con ayuda de métodos no destructivos de detección de daños

Acaban de publicarnos un artículo en el Journal of Marine Science and Engineering, revista indexada en el JCR. Se trata de la evaluación del coste del ciclo de vida con ayuda de métodos no destructivos de un puente de hormigón en ambiente costero. El trabajo se enmarca dentro del proyecto de investigación HYDELIFE que dirijo como investigador principal en la Universitat Politècnica de València.

El artículo evalúa el uso de métodos no destructivos de detección de daños, específicamente la técnica de densidad espectral de potencia (PSD), para reducir el impacto ambiental durante la reparación y el mantenimiento de un puente costero de hormigón. Los resultados muestran una reducción del 23% en los impactos ambientales cuando se utiliza el enfoque PSD durante la vida útil del puente.
La investigación evalúa las capacidades no destructivas y el enfoque dinámico de la técnica PSD para predecir la cantidad y la ubicación de los daños en la evaluación del ciclo de vida (LCA) del puente. Esta evaluación ayuda a los especialistas e ingenieros en el campo de la seguridad y el mantenimiento de los puentes.

Abstract:

Recently, using economic damage identification techniques to ensure the safety of bridges has become essential. But investigating the performance of those techniques for various conditions and environments and, in addition, a life cycle assessment (LCA) through these methods depending on the situation and during the life of a structure could help specialists and engineers in this field. In these regards, analyzing the implementation of a technique for the restoration and maintenance stages of costly structures such as bridges can illustrate the effect of each damage detection method on the LCA. This research assessed non-destructive abilities and a dynamic approach to predict the amount and location of damages in the LCA. For this purpose, the power spectral density (PSD) technique’s performance by different approaches in identifying corrosion damages for a coastal bridge and the effectiveness of using this technique on reducing the environmental impact compared with a conventional method were evaluated. The results demonstrate a reduction of the environmental impacts by approximately 23% when using the PSD during the bridge’s service life. In conclusion, the PSD approach does well in anticipating the damage quantity and location on a coastal bridge, which reduces the environmental impacts during the repair and maintenance.

Keywords:

Sustainability; non-destructive damage identification technique; life cycle assessment (LCA); environmental impacts assessment; concrete coastal bridge; corrosion; power spectral density method (PSD)

Reference:

HADIZADEH-BAZAZ, M.; NAVARRO, I.J.; YEPES, V. (2023). Life Cycle Assessment of a Coastal Concrete Bridge Aided by Non-Destructive Damage Detection Methods. Journal of Marine Science and Engineering, 11(9):1656. DOI:10.3390/jmse11091656

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Optimización de muros de contención mediante enfoques de aprendizaje por refuerzo y técnicas metaheurísticas

Acaban de publicarnos un artículo en Mathematics, revista indexada en el primer decil del JCR. Se trata de un nuevo método para optimizar el diseño de muros de contención mediante funciones de aprendizaje y transferencia por refuerzo. El trabajo se enmarca dentro del proyecto de investigación HYDELIFE que dirijo como investigador principal en la Universitat Politècnica de València. Es fruto de la colaboración de nuestro grupo de investigación con los profesores chilenos.

El artículo presenta un nuevo método para optimizar el diseño de muros de contención mediante funciones de aprendizaje y transferencia por refuerzo. El estudio compara el método propuesto con otros métodos metaheurísticos y de fuerza bruta, y muestra que las funciones de transferencia en forma de S arrojan consistentemente mejores resultados en términos de costes y emisiones de CO₂. El documento concluye que el método propuesto proporciona un enfoque prometedor para reducir los costos y las emisiones de CO₂ y, al mismo tiempo, mejorar la resistencia estructural en los proyectos de ingeniería civil.

Las contribuciones de este artículo son:

Introducir una nueva técnica de discretización basada en funciones de aprendizaje y transferencia por refuerzo para optimizar el diseño de los muros de contención en términos de costes y emisiones de CO₂.
Comparar el método propuesto con varios métodos metaheurísticos y de fuerza bruta, y demostrar que las funciones de transferencia en forma de S arrojan consistentemente resultados más sólidos.
Proporcionar un enfoque prometedor para reducir los costos y las emisiones de CO₂ y, al mismo tiempo, mejorar la resistencia estructural en los proyectos de ingeniería civil.

Abstract:

The structural design of civil works is closely tied to empirical knowledge and the design professional’s experience. Based on this, adequate designs are generated in terms of strength, operability, and durability. However, such designs can be optimized to reduce conditions associated with the structure’s design and execution, such as costs, CO₂ emissions, and related earthworks. In this study, a new discretization technique based on reinforcement learning and transfer functions is developed. The application of metaheuristic techniques to the retaining wall problem is examined, defining two objective functions: cost and CO₂ emissions. An extensive comparison is made with various metaheuristics and brute force methods, where the results show that the S-shaped transfer functions consistently yield more robust outcomes.

Keywords:

Metaheuristics; concrete retaining walls

Reference:

LEMUS-ROMANI, J.; OSSANDÓN, D.; SEPÚLVEDA, R.; CARRASCO-ASTUDILLO, N.; YEPES, V.; GARCÍA, J. (2023). Optimizing Retaining Walls through Reinforcement Learning Approaches and Metaheuristic Techniques. Mathematics 11(9): 2104. DOI:10.3390/math11092104

Os paso el artículo para su descarga, pues se ha publicado en abierto:

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Machine learning aplicado a la construcción: Un análisis de los avances científicos y del futuro próximo

Acaban de publicarnos un artículo en la revista Automation in Construction, que es la revista indexada de mayor impacto JCR en el ámbito de la ingeniería civil. En este caso se ha realizado un análisis bibliométrico del estado del arte y de las líneas de investigación futura del Machine Learning en el ámbito de la construcción. El trabajo se enmarca dentro del proyecto de investigación HYDELIFE que dirijo como investigador principal en la Universitat Politècnica de València. En este caso, se trata de una colaboración con grupos de investigación de Chile, Brasil y España.

El artículo lo puedes descargar GRATUITAMENTE hasta el 11 de octubre de 2022 en el siguiente enlace: https://authors.elsevier.com/c/1fdIq3IhXMtgv2

Los complejos problemas industriales, junto con la disponibilidad de una infraestructura informática más robusta, presentan muchos retos y oportunidades para el aprendizaje automático (Machine Learning, ML) en la industria de la construcción. Este artículo revisa las técnicas de ML aplicadas a la construcción, principalmente para identificar las áreas de aplicación y la proyección futura en esta industria. Se analizaron estudios desde 2015 hasta 2022 para evaluar las últimas aplicaciones de ML en la construcción. Se propuso una metodología que identifica automáticamente los temas a través del análisis de los resúmenes utilizando la técnica de Representaciones Codificadoras Bidireccionales a partir de Transformadores para posteriormente seleccionar manualmente los temas principales. Hemos identificado y analizado categorías relevantes de aplicaciones de aprendizaje automático en la construcción, incluyendo aplicaciones en tecnología del hormigón, diseño de muros de contención, ingeniería de pavimentos, construcción de túneles y gestión de la construcción. Se discutieron múltiples técnicas, incluyendo varios algoritmos de ML supervisado, profundo y evolutivo. Este estudio de revisión proporciona directrices futuras a los investigadores en relación con las aplicaciones de ML en la construcción.

Highlights:

State-of-the-art developed using natural language processing techniques.
Topics analyzed and validated by experts for consistency and relevance.
Topics deepened through application of bigram analysis and clustering in addition to traditional bibliographic analysis.
Identified five large areas, and detailed two to three groups of relevant lines of research.

Abstract:

Complex industrial problems coupled with the availability of a more robust computing infrastructure present many challenges and opportunities for machine learning (ML) in the construction industry. This paper reviews the ML techniques applied to the construction industry, mainly to identify areas of application and future projection in this industry. Studies from 2015 to 2022 were analyzed to assess the latest applications of ML techniques in construction. A methodology was proposed that automatically identifies topics through the analysis of abstracts using the Bidirectional Encoder Representations from Transformers technique to select main topics manually subsequently. Relevant categories of machine learning applications in construction were identified and analyzed, including applications in concrete technology, retaining wall design, pavement engineering, tunneling, and construction management. Multiple techniques were discussed, including various supervised, deep, and evolutionary ML algorithms. This review study provides future guidelines to researchers regarding ML applications in construction.

Keywords:

Machine learning; BERT; Construction; Concretes; Retaining walls; Tunnels; Pavements; Construction management

Reference:

GARCÍA, J.; VILLAVICENCIO, G.; ALTIMIRAS, F.; CRAWFORD, B.; SOTO, R.; MINTATOGAWA, V.; FRANCO, M.; MARTÍNEZ-MUÑOZ, D.; YEPES, V. (2022). Machine learning techniques applied to construction: A hybrid bibliometric analysis of advances and future directions. Automation in Construction, 142:104532. DOI:10.1016/j.autcon.2022.104532

Análisis del ciclo de vida de las medidas preventivas a la corrosión aplicadas a puentes pretensados

Acaban de publicarnos un artículo en la revista Environmental Impact Assessment Review (primer decil del JCR), de la editorial ELSEVIER, en el que se realiza una valoración de las medidas preventivas consideradas en el proyecto a lo largo del ciclo de vida de un puente de hormigón sometido a un ambiente costero, donde los clorhídricos suponen una agresión que supone un mantenimiento de la infraestructura. En el artículo se analizan 15 diseños diferentes y se comprueba que no siempre ejecutar un mantenimiento mínimo supone menores impactos ambientales. Además, los tratamientos superficiales y la adición de humo de sílice supone una reducción del 70% en los impactos.

Asimismo, podéis solicitar al autor una copia en la plataforma Researchgate: https://www.researchgate.net/publication/325690791_Life_cycle_impact_assessment_of_corrosion_preventive_designs_applied_to_prestressed_concrete_bridge_decks

Referencia:

NAVARRO, I.J.; YEPES, V.; MARTÍ, J.V.; GONZÁLEZ-VIDOSA, F. (2018). Life cycle impact assessment of corrosion preventive designs applied to prestressed concrete bridge decks. Journal of Cleaner Production, 196:698-713. https://doi.org/10.1016/j.jclepro.2018.06.110

Abstract:

Chloride corrosion of reinforcing steel in concrete structures is a major issue in the construction sector due to economic and environmental reasons. Assuming different prevention strategies in aggressive marine environments results in extending the service life of the exposed structures, reducing the maintenance actions required throughout their operation stage. The aim of the present study is to analyze the environmental implications of several prevention strategies through a life cycle assessment using a prestressed bridge deck as a case study.

The environmental impacts of 15 prevention alternatives have been evaluated when applied to a real case of study, namely a bridge deck exposed to a chloride laden surrounding. The Eco-indicator 99 methodology has been adopted for the evaluation of the impacts. As some of the alternatives involve the use of by-products such as fly ash and silica fume, economic allocation has been assumed to evaluate their environmental impacts.

Results from the life cycle analysis show that the environmental impacts of the chloride exposed structure can be reduced significantly by considering specific preventive designs, such as adding silica fume to concrete, reducing its water to cement ratio or applying hydrophobic or sealant treatments to its surface. In such scenarios, the damage caused to the environment mainly due to maintenance operations and material consumption can be reduced up to a 30–40% of the life cycle impacts associated to a conventional design. The study shows how the application of life cycle assessment methodologies can be of interest to reduce the environmental impacts derived from the maintenance operations required by bridge decks subjected to aggressive chloride laden environments.

Keywords:

Life cycle assessment; Chloride corrosion; Preventive measures; Eco-indicator 99; Bridge deck; Sustainable design; Concrete

Highlights:

Life cycle assessment of different design strategies for bridge decks in marine environments.
15 different design alternatives were studied and compared with the conventional design.
Less maintenance does not always result in lower environmental impacts.
Steel and maintenance are main contributors to environmental burdens.
Surface treatments and the addition of silica fume reduce impacts up to 70%.

Environmental impact shares of a reinforced concrete earth-retaining wall with buttresses

http://blog.360gradosenconcreto.com/tipos-muros-contencion-prefabricados-concreto/

Abstract: Structural engineers focus on the reduction of carbon emissions in reinforced concrete structures, while other impacts affecting ecosystems and human health become secondary or are left behind. The featured life cycle assessment shows the impacts corresponding to each construction stage of an earth-retaining wall with buttresses. In this study the contribution ratio of each input flow is analyzed. Accordingly, concrete, landfill, machinery, formwork, steel, and transport are considered. Results show that despite the concrete almost always accounts for the largest contribution to each impact, the impact shares of steel present noticeable sensitivity to the steel-manufacturing route. The parameter of study is the recycling rate, usually 75% reached in Spain. Noticeable variation is found when the recycling content increases. The relationship between the impacts of each material with the amount of material used discloses research interest.

Keywords: Life cycle assessment, Functional unit, Steel recycling rate, Concrete ratio, Photochemical oxidation, Ozone depletion, Global warming.

Reference:

MOLINA-MORENO, F.; MARTÍ, J.V.; YEPES, V.; CIROTH, A. (2017). Environmental impact shares of a reinforced concrete earth-retaining wall with buttresses. The Ninth International Structural Engineering and Construction Conference, Resilient Structures and Sustainable Construction ISEC-9, Valencia, Spain July 24-July 29.

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Environmental Assessment of Concrete Structures

In recent decades, with the objective of reaching a more sustainable development, worldwide society has increased its concern about environmental protection. Nevertheless, there are still economic sectors, such as the construction industry, which produce significant environmental impacts. Life Cycle Assessment (LCA) is a tool that enables identifying environmental issues related to both finished products and services, and allows focusing efforts to resolve them. The main objective of this paper is to asses LCA applicability on concrete structures so that construction’s environmental performance can be improved. For this purpose, an attempt is made to provide a decision-making tool for construction-sector stakeholders with reliable and accurate environmental data. The research methodologies used in this paper are based on a literature review and are applied to a case study. This review was performed to collect information on LCA methodologies currently in use and their practical application. The case study subsequently described in this paper involved identification of the most sustainable type of slab for a reinforced concrete structure in a residential building, using two different databases. It was observed that, depending on the database selected and inherent assumptions, results varied. Therefore it was concluded that in order to avoid producing incorrect results when applying LCA, it is highly recommended to develop a more constrained methodology and grant access to reliable construction-sector data. (link)