Prediction of Compressive Strength of Lithium Slag-rubber Mortar Based on PSO-BP and GA-BP Neural Networks

Yan-xiang HU , Hao CHEN , Kai-xi XUE , Sheng-fu WANG , Xiao-ting YAN , Ming-dong LI

Science Technology and Engineering ›› 2026, Vol. 26 ›› Issue (5) : 2084 -2091.

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Science Technology and Engineering ›› 2026, Vol. 26 ›› Issue (5) : 2084-2091 DOI: 10.12404/j.issn.1671-1815.2501297
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Prediction of Compressive Strength of Lithium Slag-rubber Mortar Based on PSO-BP and GA-BP Neural Networks
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Abstract

In order to study the influence of the content of lithium slag and rubber on the strength of cement mortar, four groups of all-factor tests were designed to study the influence of the content of lithium slag and rubber particles on the compressive strength of cement mortar. The formulas for calculating peak stress and peak strain of compressive strength in the code for design of concrete structures were modified by introducing the content of lithium slag and rubber particles. Based on the damage constitutive model of concrete structure design code, the content of lithium slag and rubber particles was introduced to modify the parameters of the descending section of the constitutive model, and then the stress-strain constitutive equation of lithium slag-rubber cement mortar under uniaxial compression was obtained. Through model validation, it is concluded that the stress-strain curve obtained from this constitutive model fits well with the test curve and can better predict the changing trend of the stress-strain relationship of mortar under different dosages of lithium slag and rubber particles.

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lithium slag / rubber / solid waste utilization / mortar / compressive strength / constitutive model

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Yan-xiang HU, Hao CHEN, Kai-xi XUE, Sheng-fu WANG, Xiao-ting YAN, Ming-dong LI. Prediction of Compressive Strength of Lithium Slag-rubber Mortar Based on PSO-BP and GA-BP Neural Networks. Science Technology and Engineering, 2026, 26(5): 2084-2091 DOI:10.12404/j.issn.1671-1815.2501297

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