Results 261 to 270 of about 44,442 (295)

Application of hybrid modeling to predict California bearing ratio of soil

Vietnam Journal of Earth Sciences
California Bearing Ratio (CBR) is used to assess bearing capacity, deformation characteristics of roadbed soil, and base layer material in pavement structure. In general, CBR is often determined by laboratory or in-situ tests. However, it is time- and cost-consuming to conduct this experiment because this test requires cumbersome equipment such as a ...
Huong Thi Thanh Ngo, Quynh- Anh Thi Bui, Vi Nguyen Van, Thuy Nguyen Thi Bich   +3 more
openaire   +1 more source

Application of Machine-Learning Algorithms for Predicting California Bearing Ratio of Soil

Journal of Transportation Engineering Part B: Pavements, 2023
Vaishnavi Bherde, Umashankar Balunaini, Balunaini Umashankar   +2 more
exaly  

Machine learning approach for predicting and evaluating California bearing ratio of stabilized soil containing industrial waste

Journal of Cleaner Production, 2022
Lanh Si Ho, Van Quan Tran
exaly  

Effect of natural and synthetic fibers reinforcement on California bearing ratio and tensile strength of clay

Journal of Rock Mechanics and Geotechnical Engineering, 2021
Alireza Tabarsa, Nima Latifi
exaly  

Determination of CBR (California Bearing Ratio) Test

2023
openaire   +1 more source

Influence of cohesion on California bearing ratio of clay–gravel mixtures

International Journal of Sediment Research, 2023
Rajesh Jain, Ketan Timani, Manish Pandey
openaire   +1 more source

The California Bearing Ratio Test on Loess

Nature, 1966
openaire   +1 more source

The application of deep neural networks for the prediction of California Bearing Ratio of road subgrade soil

Ain Shams Engineering Journal, 2023
Kareem Othman
exaly  

Surrogate models to predict maximum dry unit weight, optimum moisture content and California bearing ratio form grain size distribution curve

Road Materials and Pavement Design, 2022
Saif Alzabeebee, Safaa A Mohamad, Rwayda Kh S Al-Hamd   +2 more
exaly  

An empirical predictive model for the dynamic resilient modulus based on the static resilient modulus and California bearing ratio of cement- and lime-stabilised subgrade soils

Road Materials and Pavement Design, 2021
Junyan Yi, Songqiang Chen, Decheng Feng   +2 more
exaly