| INORGANIC MATERIALS AND CERAMIC MATRIX COMPOSITES |
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| Multisource Large-sample Model for Chloride Diffusion Coefficient of Fly Ash Concrete |
| YANG Lufeng1,2,*, ZHU En1,2
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1 School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China 2 Key Laboratory of Disaster Prevention and Structural Safety of the Ministry of Education, Guangxi University, Nanning 530004, China |
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Abstract A multi-factor computational model of chloride diffusion coefficient of fly ash concrete was developed with high accuracy, incorporating the influence of quality of cement and fly ash by means of the two-phase regression technique on basis of the multisource large-sample RCM test data to overcome the drawbacks of the conventional chloride diffusion coefficient models for fly ash concrete. Firstly, the linear function of the water-binder ratio and the quadratic function of fly ash were chosen to be most suitable for the development of the chloride diffusion coefficient model through regression analysis of the multisource large-sample RCM test data. Furthermore, the cement type factor and the fly ash quality factor were presented with their values determined by means of the two-phase regression method, based on which the chloride diffusion coefficient model of concrete was developed incorporating the quality of cementitious material. It is validated by comparing with different models and test data that the multisource large-sample model improves the prediction accuracy and stability of the chloride diffusion coefficient of fly ash concrete to some extent. However the improvement is sometimes limited when the quality of cementitious material is not considered. The weighted average error and the coefficient of variation of the proposed multisource large-sample model can be further reduced by 41.7% and 34.3%, respectively, thus greatly improving the prediction accuracy and adaptability of the chloride diffusion coefficient by introducing cement category factor and fly ash quality factor.
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Published: 10 November 2025
Online: 2025-11-10
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