PREDICTION OF CALIFORNIA BEARING RATIO OF SUBBASE LAYER USING MULTIPLE LINEAR REGRESSION MODEL

摘要

A method for predicting the California Bearing Ratio of a pavement subbase layer, wherein samples are collected from different regions of the subbase layer, the samples are tested to determine at least moisture content and density. Each sample is prepared at optimum moisture content and at different densities and tested to determine the California Bearing Ratio for each density and to obtain a dataset of variables. A multiple linear regression model is applied to selected variables from the dataset to relate the determined California Bearing Ratio value to the selected variables from the dataset to obtain a predicted value of the California Bearing Ratio of a subbase having comparable variables.

主权项

1. A method for predicting the California Bearing Ratio of a pavement subbase layer, comprising:
collecting samples from different regions of the subbase layer; testing the samples to obtain a dataset of variables including at least moisture content and density; preparing each sample at optimum moisture content and at different densities; testing each sample to determine the California Bearing Ratio for each density; and applying a multiple linear regression model to relate the determined California Bearing Ratio value to selected variables from the dataset to obtain a predicted value of the California Bearing Ratio of a subbase having comparable variables.