Abstract
The issues of environmental degradation due to natural sand overextraction are becoming increasingly severe. In desert regions, utilizing aeolian sand as a substitute for natural sand in construction projects facilitates the resource economization and the effective management of desertification. The concrete industry is expected to significantly contribute to this objective, as high-performance concrete with full aeolian sand (FA-HPC) has demonstrated excellent mechanical properties. However, current researches have yet to establish a rational damage evolution law for uniaxial compression in FA-HPC from the perspective of damage characteristics. In this study, uniaxial compression tests were conducted on FA-HPC with different mixture proportions. Simultaneously, the stress-strain behavior was examined, and acoustic emission (AE) signals were collected and localized. Based on the Weibull distribution function-based stochastic damage evolution law for uniaxial compression, regression analyses of the stress-strain and AE cumulative ringing count for FA-HPC were performed. Damage evolution model for effective stress and damage variable were established and validated with experimental data to confirm their applicability. The scale and shape parameters of the model were predicted using the mixture proportions as independent variables. The results show that the rationality of the damage evolution law assumption was validated through AE source localization. The goodness of fit values for damage variable and effective stress equation range from 0.87 to 0.98, with the ascending segment and the vicinity of the peak point closely matching the experimental data, indicating that the Weibull distribution function-based stochastic damage model for uniaxial compression is applicable for FA-HPC. The predicted values of the damage evolution model parameters based on the mixture proportions align well with the measured values, achieving a goodness of fit of 0.99, thereby guiding the study of FA-HPC's compressive characteristics prior to the formation of primary cracks. Notably, there remains a need to propose corrective equations to enhance the correlation between regression curves and experimental data in the late failure stages of FA-HPC in future research, achieving precise predictions by considering the interactions of multiple factors.
Published Version
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