The Mechanical Properties Of Cement Stabilized Laterite And Neural Network Model

This paper based on the problem of comprehensively analysis of soil reinforce,reinforcement mechanism,micro- structure,and neural network model, combining with the mechanical characteristics of laterite which is widely used in Yunnan can't completely satisfied engineering requirements, the problem "study on mechanical characteristics and neural network model of laterite-cement" was presented. Aiming at the typical laterite in Yunnan, this paper choosed cement as reinforced agent, and confirmed the mechanical characteristics and the microstructure characteristics of the laterite-cement through comparative study of the macro and micro test; Extracted the microstructure characteristic parameters of the laterite-cement by using image processing techniques; Illuminated that reinforcement mechanism of laterite-cement from the perspective of microstructure, combining with mechanical characteristics, microstructure characteristics and microstructure characteristic parameters; At last, the neural network model of shear strength of the laterite-cement was established by using neural network theory.The mechanical characteristics of compaction,shear strength compression and permeability of the laterite-cement was confirmed through the contrastive analysis of compaction test,shear strength test,compression test and penetproportionn test, considering the cement proportion and the sample curing time. The macroscopic experiment result indicated:For the laterite-cement, the maximum dry density increased and the optimum moisture content decreased, the shearing strength and it's parameters increased, the compressibility coefficient and the permeability coefficient decreased. With increasing the cement proportion and extended the curing time, shear strength and it's parameters increased gradually, the compressibility coefficient and the permeability coefficient decreased gradually, but the extent will slow down gradually, the increased extend of cohesion force is greater than the extend of internal friction angle. For all kinds of mechanics feature of laterite, the incidence of cement proportion is greater than the incidence of the sample curing time.The microstructure characteristic of the laterite-cement will be obtained by SEM, measuring and analyzing the microstructure images of different magnification factor before and after the condition of compaction reinforcement,curing,shear and compression. The SEM experiment result indicated:the the laterite-cement have the characteristic microstructure of close-grained,agglutinating,filling,enwrapping and porosity; Extracted the porosity rate and granular rate atc microstructure characteristic parameter through digitize image digital processing the microstructure of reinforced laterite. The extract result indicated:For the laterite-cement, the porosity rate decreased and the granular rate increased after compaction,reinforcement,curing and compression; With increasing the cement proportion and extended the curing time, the porosity rate decreased gradually, the granular rate decreased gradually; After shearing, the porosity rate increased and the granular rate decreased.For the laterite-cement, the change of mechanical characteristics rest with the change of microstructure, and the change of microstructure rest with the interaction between cement and laterite granule. The reinforcement mechanism of laterite-cement was explained from the perspective of microstructure combining with mechanical characteristics, microstructure characteristics and microstructure characteristic parameters and through agglutinating,filling,enwrapping, the change of mechanical characteristics is the result of the combined influence of the three effects. For the laterite-cement, the increase of maximum dry density and the decrease of optimum moisture content rest with enwrapping and filling; the increase of the shearing strength and it's indicators and the decrease of compressibility rest with agglutinating; The decrease of permeability rest with enwrapping and filling.Using the neural network theory, this paper established the neural network model according to the direct shear test's data which obtained through control cement different proportion and the sample different curing time. Make sure the cement proportion and curing time two factors as the input layer's vector quantity of model, make sure the cohesion force and internal friction angle two shear strength parameters as the output layer's vector quantity of model, and to make unitary processing for the selected specimen. The transfer function of hidden layer of the model is tangent function tansig and the transfer function of output layer of the model is log function logsin, the number of the hidden layer neuron of the model is 5. According to the arrangement of the model, the neural network model of shear strength of the laterite-cement is established, on the whole, the model's forecast result turn up trumps.