Optimizing the construction process: State‐of‐art, innovations, and potential benefits of temperature match curing

Abstract The temperature match curing (TMC) method significantly enhances the accuracy of concrete property assessments by replicating in situ curing conditions in test specimens. While this method has remained underutilized and relatively unknown in the industry due to its complexity, the advent of Internet of Things and wireless sensor technologies has mitigated practical barriers previously impeding TMC, facilitating its application in real construction settings. This paper aims to elucidate the scientific and practical advancements of TMC, focusing on its theoretical foundations and recent technological advancements. It highlights several key benefits, including improved accuracy and predictability of concrete mechanical properties: studies have proven that TMC can enhance the predictive reliability of concrete performance by up to 20% and potentially reduce construction project timelines by 15%. The paper also emphasizes the advantages of enhanced quality control through continuous monitoring and increased operational efficiency by optimizing resource usage and construction workflows. Additionally, it explores the potential of emerging IoT and wireless sensor technologies to further improve TMC's real‐time monitoring capabilities. Despite these advantages, the paper acknowledges several barriers to wider adoption, such as high operational costs and a lack of empirical studies comparing TMC with conventional methods, which may limit its broader implementation in the industry.

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Publication Details

Journal
Structural Concrete
Published
2025-06-19
DOI
https://doi.org/10.1002/suco.70199
Citations
1
Primary Topic
Concrete Properties and Behavior
Type
article
Field-Weighted Citation Impact
0.95

Funders

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article

Optimizing the construction process: State‐of‐art, innovations, and potential benefits of temperature match curing

Albert de la Fuente, David Boix‐Cots, Fidel Lozano‐Galant, Tai Ikumi
1 citations
Structural Concrete
Concrete Properties and Behavior
0.95
article

Optimizing the construction process: State‐of‐art, innovations, and potential benefits of temperature match curing

Albert de la Fuente, David Boix‐Cots, Fidel Lozano‐Galant, Tai Ikumi
article en
1 citations

Abstract

Abstract The temperature match curing (TMC) method significantly enhances the accuracy of concrete property assessments by replicating in situ curing conditions in test specimens. While this method has remained underutilized and relatively unknown in the industry due to its complexity, the advent of Internet of Things and wireless sensor technologies has mitigated practical barriers previously impeding TMC, facilitating its application in real construction settings. This paper aims to elucidate the scientific and practical advancements of TMC, focusing on its theoretical foundations and recent technological advancements. It highlights several key benefits, including improved accuracy and predictability of concrete mechanical properties: studies have proven that TMC can enhance the predictive reliability of concrete performance by up to 20% and potentially reduce construction project timelines by 15%. The paper also emphasizes the advantages of enhanced quality control through continuous monitoring and increased operational efficiency by optimizing resource usage and construction workflows. Additionally, it explores the potential of emerging IoT and wireless sensor technologies to further improve TMC's real‐time monitoring capabilities. Despite these advantages, the paper acknowledges several barriers to wider adoption, such as high operational costs and a lack of empirical studies comparing TMC with conventional methods, which may limit its broader implementation in the industry.

Structural ConcreteVol. 26(6)
University of Castilla-La Mancha (ES), Universitat Politècnica de Catalunya (ES)
Agència de Gestió d'Ajuts Universitaris i de Recerca
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
Concrete Properties and Behavior
0.95
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