Improving Modulus of Elasticity Prediction in Cement-Based Composites: The Impact of Rubber Particle Incorporation, Nonlinear Regression Optimization, and Hybrid Voigt-Reuss/Reuss-Voigt Models
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Keywords:
Stiffness, Deformability, Reuss-Voigt Model, Voigt-Reuss Model, Nonlinear RegressionAbstract
This study investigates the influence of rubber particles on the stiffness and deformability of
cement-based composites, with a particular focus on predicting the modulus of elasticity based on the
incorporation rate of rubber particles. Accurate prediction of the modulus of elasticity for these
composites presents a challenge due to the tendency of conventional models to either overestimate or
underestimate this parameter. The Voigt-Reuss and Reuss-Voigt models, employed as predictive bases,
are reliable; however, they exhibit biases in estimating the modulus of elasticity. Nevertheless, these
models prove valuable when optimized using nonlinear regression factors derived from polynomial
equations of nth order. Despite their tendency to skew results, the Reuss-Voigt and Voigt-Reuss models
remain robust tools for predicting the modulus of elasticity of concrete. The optimization process utilizing
the calibration factor significantly enhances their predictive accuracy. This research highlights the
enhancement of predictive accuracy in models for cement-based composites, thereby contributing to a
better understanding and optimal utilization of these materials in structural applications.
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References
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