UNCONFINED COMPRESSIVE STRENGTH ANALYSIS FOR CYLINDRICAL SPECIMEN USING RANDOM FINITE ELEMENT METHOD

Abstract

 Unconfined compression test is generally used in the field of geotechnical engineering to evaluate the strength and deformation characteristics of cement-mixed soil in addition to rock and soil. However, there are several influential factors on the deformation and strength characteristics of cement-mixed soil, such as the specimen size and the spatial variations of cement content and water content caused by mixing quality, curing time, etc. This study develops random finite element method to evaluate the unconfined compressive strength of cylindrical specimens, compares the results of two-dimensional analysis and three-dimensional analysis, and discusses the effects of the specimen size, strength parameters, and spatial variability parameters on the unconfined compressive strength. It can be characterized that the unconfined compressive strength decreases with increasing spatial variability, which is more pronounced for larger specimens. To improve computational efficiency, a prediction model for unconfined compressive strength is constructed successfully by combining random finite element method with Convolutional Neural Network.