CBR Predictive Models for Granular Bases Using Physical and Structural Properties
Source abstract
Abstract
The California bearing ratio (CBR) test evaluates the structure of the layers of pavements. Such a test is laborious, time-consuming, and its results are generally affected by sample disturbance and tests conditions. The main objective of this research was to build a numerical model for the prediction of CBR tests that might substitute laboratory tests. The model was based on structural and physical parameters of granular bases. Four different materials from the central region (Querétaro) and north (Mexicali) of Mexico were used for the experimental work. Using the above-mentioned materials, 36 samples were fabricated, and six of them were used for the evaluation of the model presented in this research. Numerical and experimental comparisons demonstrated the adequacy of the model to predict the result of CBR tests from soil parameters.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Asphalt Pavement Performance Evaluation · Infrastructure Maintenance and Monitoring · Geotechnical and construction materials studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil Engineering, Autonomous University of Queretaro, 76010 Queretaro, Mexico
Department of Civil Engineering, Autonomous University of Sinaloa, 80020 Culiacan, Mexico
Department of Physics and Mathematics, Autonomous University of Sinaloa, 80020 Culiacan, Mexico
Funding
Consejo Nacional de Ciencia y Tecnología
References (21)
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