Results 61 to 70 of about 1,081 (171)

CBR Predictive Models for Granular Bases Using Physical and Structural Properties

open access: yesApplied Sciences, 2020
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.
Mildred Estivaly Montes-Arvizu   +4 more
doaj   +1 more source

Comparison of field methods for evaluating subgrade bearing capacity based on the CBR index: analysis of test results obtained using the Panda penetrometer and the Dynamic Cone Penetrometer

open access: yesRoads and Bridges
The article presents a comprehensive analysis of two field methods for determining the California Bearing Ratio (CBR), namely the Panda cone penetrometer and the Dynamic Cone Penetrometer (DCP).
Agata Kowalewska, Tomasz Gajda
doaj   +1 more source

Modeling CBR Value using RF and M5P Techniques

open access: yesMendel, 2019
Two modeling techniques namely (i) Random forest (RF) and (ii) M5P model tree are used to model, soaked California bearing ratio (CBR) value of thermal power plant generated stabilized pond ash.
Manju Suthar, Praveen Aggarwal
doaj   +1 more source

The Effect of CKD and RAP on the Mechanical Properties of Subgrade Soils

open access: yesAnbar Journal of Engineering Sciences, 2022
This paper discusses the use of cement kiln dust and reclaimed asphalt pavement to improve poor subgrade soils. Unconfined compressive strength and California bearing ratio tests were conducted on natural and stabilized soils. The results showed that CKD
salman saeed   +2 more
doaj  

Regression Analysis of Index Properties of Soil as Strength Determinant for California Bearing Ratio (CBR)

open access: yes, 2017
Investigation of the variation in different soil types and origins is an essential task for Geotechnical engineers. To overcome the effects of this change, the Geotechnical engineers, as well as other professionals, attempted to develop empirical equations unique to a region and soil type to use the soil for its intended purpose.
Quezon, Emer Tucay   +2 more
openaire   +1 more source

California Bearing Ratio of Some Iraqi Dune Soils

open access: yesTikrit Journal of Engineering Sciences, 2015
   This paper contains the results of CBR tests that performed on compacted samples of real dune sand (cohesionless sand grains) and pseudo dune sand which is a mixture of sand sized  aggregate of  clay and silt.
Yousif Al-Shakarchi   +2 more
doaj  

Peningkatan Nilai CBR Laboratorium Rendaman Tanah dengan Campuran Kapur, Abu Sekam Padi dan Serat Karung Plastik

open access: yesSemesta Teknika, 2016
Bearing capacity of a subgrade is one of the parameters to design the thickness of road pavement. Beside the bearing capacity, swelling behavior of subgrade must be in a narrow range to avoid crack of the pavement.
Anita Widianti
doaj  

Forecasting California bearing ratio (CBR) of soil using machine learning algorithms: A review

open access: yesResearch on Engineering Structures and Materials
Traditionally California bearing ratio (CBR) is obtained by conducting laboratory testing, which is often time-consuming, laborious, and costly. This delays the design and construction processes of important structures. Recently, several researchers have predicted CBR using ML algorithms.
Nabam Tado, Salam Medhajit, Dibyendu Pal
openaire   +1 more source

Prediction of California Bearing Ratio (CBR) and Compaction Characteristics of granular soil

open access: yes, 2017
This research is an effort to correlate the index properties of granular soils with the California Bearing Ratio (CBR) and the compaction characteristics. Soil classification, modified proctor and CBR tests conforming to the relevant ASTM methods were performed on natural as well as composite sand samples.
Rehman, Attique ul   +2 more
openaire   +1 more source

Optimized deep learning framework for reliable prediction of pavement subgrade CBR

open access: yesTransportation Engineering
California Bearing Ratio (CBR) is a fundamental parameter determining the load-bearing capacity essential for pavement subgrade design. This study introduces a deep learning (DL) based predictive framework for estimating CBR of pavement subgrade soil ...
Adil A.M. Elhassasn   +5 more
doaj   +1 more source

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