Predicting CBR Value from Index Properties of Soils using Expert System

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Ahmad Taha Abdulsadda
Ahmad Taha Abdulsadda
σ
Dhurgham Abdul Jaleel
Dhurgham Abdul Jaleel
α Al-Furat Al-Awsat Technical University

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Predicting CBR Value from Index Properties of Soils using Expert System

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Abstract

The sub grade gives an establishment to supporting the asphalt structure. The sub review regardless of whether in cut or fill ought to be all around compacted to use its full quality and to conserve consequently on the general thickness of asphalt required. For plan, the sub review quality is evaluated regarding the CBR of the sub review soil in both fill and cut areas. For deciding the CBR esteem, the static entrance test method ought to be entirely clung to. The test should dependably be performed on formed specimens of soils in the research center. CBR test is difficult and tedious; yet once in a while the outcomes are not precise due to the poor laboratory conditions. Advance if the accessible soil is of low quality, appropriate added substances are blended with soil and the subsequent quality of the dirt will be evaluated by CBR esteem, which is unwieldy. In this paper we proposed a new expert system (Multi Layer Perceptron (MLP) neural network) to be working as computer decision maker and predicate the precise CBR value based upon the data.

References

13 Cites in Article
  1. Abdul Karim,K,A,Afaf,H (2014). Best Fit Model to Estimate Relation Between (CBR) and the Dry Density of Fine Grains Soils.
  2. Astm (1992). Test Method for California Bearing Ratio (CBR) of Laboratory-Compacted Soils.
  3. J Bowles (1996). Foundation Analysis and Design.
  4. J Bowles,W (1984). Physical and Geotechnical Properties of Soil.
  5. Y Deepak,P Jain,K Rakesh,K (2013). prediction of soaked cbr of fine grained soils from classification and compaction parameters.
  6. K Dilip,T (2014). A Study of Correlation Between California Bearing Ratio (CBR) Value With Other Properties of Soil.
  7. K Head (1992). Manual of soil laboratory testing, Soil specification and compaction tests.
  8. F Kulhawy,H Mayne,P,H (1990). Manuel on Estimating Soil Properties for Foundation Design.
  9. (2001). Appendix CC-1: Correlation of CBR Values with Soil Index Guide for Mechanistic and Empirical Design for New and Rehabilitated Pavement Structures.
  10. B Naveen,S Santosh,G,H (2014). Establishing Relationship between CBR Value and Physical Properties of Soil.
  11. B Patel,S Gandhi,D Desai (2010). Clinico-epidemiological aspect of leptospirosis in South Gujarat.
  12. G Ramasubbarao,V,Siva,G (2013). Predicting Soaked CBR Value of Fine Grained Soils Using Index and Compaction Characteristics.
  13. C Venkatasubramanian,G Dhinakaran (2021). DEVELOPING CORRELATION OF CBR FROM INDEX PROPERTIES.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Ahmad Taha Abdulsadda. 2017. \u201cPredicting CBR Value from Index Properties of Soils using Expert System\u201d. Global Journal of Research in Engineering - E: Civil & Structural GJRE-E Volume 17 (GJRE Volume 17 Issue E1): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords
Classification
GJRE-E Classification: FOR Code: 290899
Version of record

v1.2

Issue date

August 11, 2017

Language
en
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Published Article

The sub grade gives an establishment to supporting the asphalt structure. The sub review regardless of whether in cut or fill ought to be all around compacted to use its full quality and to conserve consequently on the general thickness of asphalt required. For plan, the sub review quality is evaluated regarding the CBR of the sub review soil in both fill and cut areas. For deciding the CBR esteem, the static entrance test method ought to be entirely clung to. The test should dependably be performed on formed specimens of soils in the research center. CBR test is difficult and tedious; yet once in a while the outcomes are not precise due to the poor laboratory conditions. Advance if the accessible soil is of low quality, appropriate added substances are blended with soil and the subsequent quality of the dirt will be evaluated by CBR esteem, which is unwieldy. In this paper we proposed a new expert system (Multi Layer Perceptron (MLP) neural network) to be working as computer decision maker and predicate the precise CBR value based upon the data.

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Predicting CBR Value from Index Properties of Soils using Expert System

Ahmad Taha Abdulsadda
Ahmad Taha Abdulsadda Al-Furat Al-Awsat Technical University
Dhurgham Abdul Jaleel
Dhurgham Abdul Jaleel

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