Hongfei Cao, Bing Xiao, Fengjiang Qin, Qiuwei Yang
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Due to its minimal reliance on experimental data, the new model exhibits high practicality and convenience in real-world applications. To validate its superiority, a detailed comparison between the new model and existing models was conducted based on several sets of experimental data. The results demonstrate that the new model has significant advantages in terms of mean fitting error and standard deviation, making its predictions the most reliable. For most cases, the standard deviation of the new model is reduced by approximately 30% to 80% compared to the second-best model, underscoring its exceptional stability and consistency. Additionally, the predicted long-term compressive strength values of the new model are closer to the design strength grade of the concrete. This model can also be successfully applied to predict the tensile strength of concrete during its ultra-early age. 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Currently, widely adopted models such as polynomial, hyperbolic, and exponential models all possess limitations, particularly in terms of low fitting accuracy during the ultra-early-age stage. This paper innovatively introduces a mathematical model that utilizes a combined curve approach. This model boasts a simplified structure with only two fitting parameters. Compared to traditional models, when utilizing three or more sets of experimental data on compressive strength across different ages, the new model is capable of yielding more precise strength predictions. Due to its minimal reliance on experimental data, the new model exhibits high practicality and convenience in real-world applications. To validate its superiority, a detailed comparison between the new model and existing models was conducted based on several sets of experimental data. 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A Mathematical Model for Predicting the Ultra-Early-Age Strength of Concrete
To accurately quantify the time-varying pattern of concrete’s compressive strength, selecting an appropriate curve model is of paramount importance. Currently, widely adopted models such as polynomial, hyperbolic, and exponential models all possess limitations, particularly in terms of low fitting accuracy during the ultra-early-age stage. This paper innovatively introduces a mathematical model that utilizes a combined curve approach. This model boasts a simplified structure with only two fitting parameters. Compared to traditional models, when utilizing three or more sets of experimental data on compressive strength across different ages, the new model is capable of yielding more precise strength predictions. Due to its minimal reliance on experimental data, the new model exhibits high practicality and convenience in real-world applications. To validate its superiority, a detailed comparison between the new model and existing models was conducted based on several sets of experimental data. The results demonstrate that the new model has significant advantages in terms of mean fitting error and standard deviation, making its predictions the most reliable. For most cases, the standard deviation of the new model is reduced by approximately 30% to 80% compared to the second-best model, underscoring its exceptional stability and consistency. Additionally, the predicted long-term compressive strength values of the new model are closer to the design strength grade of the concrete. This model can also be successfully applied to predict the tensile strength of concrete during its ultra-early age. It has been demonstrated that the combined model proposed in this paper shows promising application prospects in evaluating the time-varying behavior of concrete strength.
CoatingsMaterials Science-Surfaces, Coatings and Films
CiteScore
5.00
自引率
11.80%
发文量
1657
审稿时长
1.4 months
期刊介绍:
Coatings is an international, peer-reviewed open access journal of coatings and surface engineering. It publishes reviews, research articles, communications and technical notes. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. Full experimental and/or methodical details must be provided. There are, in addition, unique features of this journal:
* manuscripts regarding research proposals and research ideas will be particularly welcomed
* electronic files or software regarding the full details of the calculation and experimental procedure - if unable to be published in a normal way - can be deposited as supplementary material