Prediction Dry Density of Soil from Some Physical and Chemical Properties

Prediction Dry Density of Soil from Some Physical and Chemical Properties

Dhurgham Abdul-Jaleel Rasool Al-Hamdani

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Hana Mahmoud Amer Al-Kasaar

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Hussain Ali Muhammad Zani

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Al-Furat Al-Awsat Technical University

Prediction Dry Density of Soil from Some Physical and Chemical Properties

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Abstract

The prediction of dry density play important role in projects or major or laboratory tests which required to estimates the value of dry density for cohesion less soils to decision of the solution of these soils or conducting tests. In this paper, an attempt utilized to predict the value cohesion less soil form known some physical and chemical properties of soil such as technical institute Laboratory which conducted for ninety nine cohesion less soil samples. These tests may classify aseasier, cheaper and low time consume when compared with laboratory dry density tests. The results show many correlation models depending on the independent variables constricted to estimate the dry density of soil. The highest coefficient of determination resulted from this study is 0.92 for multiple regression analysis. In this case nine soil property correlated to gathers to estimate the dry density. This value may decrease when the independent variable are decrease than nine soil property.

References

8 Cites in Article

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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

Dhurgham Abdul-Jaleel Rasool Al-Hamdani. 2018. \u201cPrediction Dry Density of Soil from Some Physical and Chemical Properties\u201d. Global Journal of Research in Engineering - E: Civil & Structural GJRE-E Volume 18 (GJRE Volume 18 Issue E2).

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GJRE Volume 18 Issue E2

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

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Classification

GJRE-E Classification FOR Code: 290899

Submission ReceivedDecember 14, 2017
Peer Review Double Blind
Handling Editor
Accepted January 1, 2018
Published January 15, 2018

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v1.2

Issue date

November 17, 2018

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Article Matrices

Total Score: 103

Country: Iraq

Subject: Global Journal of Research in Engineering - E: Civil & Structural

Authors: Dhurgham Abdul-Jaleel Rasool Al-Hamdani, Hana Mahmoud Amer Al-Kasaar, Hussain Ali Muhammad Zani (PhD/Dr. count: 0)

View Count (all-time): 188

Total Views (Real + Logic): 3071

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Publish Date: 2018 11, Sat

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Total Views: 3071

Total Downloads: 1506

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