Prediction of the mechanical properties of structural recycled concrete using multivariable regression and genetic programming

González-Taboada, Iris; Martínez-Abella, Fernando; Ordóñez, Juan Luis Pérez

doi:10.1016/j.conbuildmat.2015.12.136

Cited by 106 publications

(39 citation statements)

References 83 publications

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“…In order to confirm this result, the ratio f cyl to f cu was calculated using the database of González-Taboada et al (9) with some researcher works that provide both results. Applying regression analysis, and analysing the results taking into account different replacement ratios, 0-20% and 50-100%, the ratio was found to be 0.810 and 0.861 respectively (Figure 4).…”

Section: Compressive Strength (F C )mentioning

confidence: 86%

“…Therefore, one of the best procedures to define the recycled aggregate's quality is to measure its water absorption capacity. In this regard, coarse RCA presents a water absorption capacity under 8.5% (9). This value increases when recycled fine aggregate is analysed.…”

Section: Introduction and Objectivesmentioning

confidence: 92%

“…However, the extent of this decrease mainly depends on the recycled aggregate's content, concrete production method (9) and recycled aggregates' type, size and origin (22).…”

Section: Compressive Strength (F C )mentioning

confidence: 99%

“…Using the database of González-Taboada et al (9), Figure 2 analyses the relationship "RC's compressive strength vs conventional concrete's compressive strength" taking into account different ratios of coarse RCA. 229, 80 and 75 mixes were used in the case of 100%, 50% and 20% replacements ratios, respectively.…”

Section: Compressive Strength (F C )mentioning

confidence: 99%

“…In order to produce RC, it is necessary to know the influence of the recycled aggregate's content and quality, which is usually determined by the aggregate's composition, water absorption capacity and attached mortar content (made of the source concrete) (9)(10)(11)(12)(13)(14)(15). These parameters lead to different sorts of recycled aggregates: recycled concrete aggregates (RCA), recycled ceramic aggregates or mixed recycled aggregates.…”

Section: Introduction and Objectivesmentioning

confidence: 99%

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Recycled concrete with coarse recycled aggregate. An overview and analysis

González-Fonteboa

Seara-Paz

Brito³

et al. 2018

Mater. construcc.

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ABSTRACT:The construction field has contributed to environmental degradation, producing a high amount of construction and demolition waste (C&D waste) and consuming large volumes of natural resources. In this context, recycled concrete (RC) has been recognised as a means to preserve natural resources and reduce space for waste storage. During the last decades, many researchers have developed works studying different recycled concrete properties.This review focuses on structural RC made with coarse recycled aggregate from concrete waste. The main objective is to provide a state of the art report on RC's properties and an analysis on how to predict them taking into account relevant research works. Moreover, the study tries to collect and update RC findings, proposing equations to define RC's performance, in terms of mechanical strength, modulus of elasticity, stress-strain, creep and shrinkage. RESUMEN:Hormigón reciclado con árido grueso reciclado. Una visión general y análisis. El campo de la construcción ha contribuido a la degradación del medio ambiente, produciendo gran cantidad de residuos de construcción y demolición y consumiendo grandes volúmenes de recursos naturales. En este contexto, el hormigón reciclado se ha presentado como una opción para preservar los recursos naturales y reducir el espacio destinado a vertedero. Así, durante las últimas décadas, muchos investigadores han desarrollado trabajos para estudiar las propiedades del hormigón reciclado.Este artículo se centra en el hormigón estructural fabricado con árido reciclado grueso procedente de residuos de hormigón. El principal objetivo es desarrollar un estado del arte que recoja las principales propiedades del hormigón reciclado y un análisis de cómo calcularlas teniendo en cuenta un gran número de trabajos relevantes en este ámbito. Adicionalmente, el estudio recopila y actualiza el conocimiento sobre estos hormigones, proponiendo ecuaciones que permitan definir sus resistencias mecánicas, módulo de elasticidad, tensión-deformación, fluencia y retracción.

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Section: Compressive Strength (F C )mentioning

confidence: 86%

Section: Introduction and Objectivesmentioning

confidence: 92%

“…However, the extent of this decrease mainly depends on the recycled aggregate's content, concrete production method (9) and recycled aggregates' type, size and origin (22).…”

Section: Compressive Strength (F C )mentioning

confidence: 99%

Section: Compressive Strength (F C )mentioning

confidence: 99%

Section: Introduction and Objectivesmentioning

confidence: 99%

See 3 more Smart Citations

Recycled concrete with coarse recycled aggregate. An overview and analysis

González-Fonteboa

Seara-Paz

Brito³

et al. 2018

Mater. construcc.

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Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend

Kazemi

2023

Engineering Reports

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Advanced concrete technology is the science of efficient, cost‐effective, and safe design in civil engineering projects. Engineers and concrete designers are generally faced with the slightest change in the conditions or objectives of the project, which makes it challenging to choose the optimal design among several ones. Besides, the experimental examination of all of them requires time and high costs. Hence, an efficient approach is to utilize artificial intelligence (AI) techniques to predict and optimize real‐world problems in concrete technology. Despite the large body of publications in this field, there are few comprehensive surveys that conduct scientometric analysis. This paper provides a state‐of‐the‐art review that lists, summarizes, and categorizes the most widely used machine learning methods, meta‐heuristic algorithms, and hybrid approaches to concrete issues. To this end, 457 publications are considered during the recent decade with a scientometric approach to highlight the annual trend/active journals/top researchers/co‐occurrence of key title words/countries' participation/research hotspots. In addition, AI techniques are classified into distinct clusters using VOSviewer clustering visualization to identify the application scope and their relationship through the link strength. The findings can be a beacon to help researchers utilize AI techniques in future research on advanced concrete technology.

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Retracted: Prediction of the elastic modulus of recycled aggregate concrete applying hybrid artificial intelligence and machine learning algorithms

Zhou

Afzal

2021

Structural Concrete

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Recycled aggregates (RAGs) usage in concrete is surging, inspired by environmental and economic concerns. Regarding predicting various models designed the values of modulus of elasticity (MOE) of concrete with natural aggregates and, in conclusion, they would probably be unreliable when used to concrete with RAG. In the present study, two new gray wolf multi‐layer perceptron neural networks (GWMLP) and gray wolf support vector regression (GWSVR) algorithms were proposed to predict RAG concrete's elastic modulus. About 400 records were gathered from published articles to develop these models. The results show that among the GWMLP models with different hidden layers, GWM3L with three hidden layers could get the highest score (TRS) at 39. Simultaneously, in the testing phase, the GWSVR was the first‐rank model because of the lower RMSE (0.6381), MAE (0.1541), and a larger R2 (0.9707) compared with GWMLP models. Therefore, it can result that the GWSVR model could predict the elastic modulus of RAG concrete precisely even better than GWM3L, which is well over the accuracy of the developed models.

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Prediction of the mechanical properties of structural recycled concrete using multivariable regression and genetic programming

Cited by 106 publications

References 83 publications

Recycled concrete with coarse recycled aggregate. An overview and analysis

Recycled concrete with coarse recycled aggregate. An overview and analysis

Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend

Retracted: Prediction of the elastic modulus of recycled aggregate concrete applying hybrid artificial intelligence and machine learning algorithms

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