Preferred Language
Articles
/
WBbrHYcBVTCNdQwCKjjR
Prediction of Ultimate Soil Bearing Capacity for Shallow Strip Foundation on Sandy Soils by Using (ANN) Techniqu
...Show More Authors

Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that using ANN gave a very high correlation factor associated with the results obtained from Terzagih’s equation, besides little computation time needed compared with computation time needed when applying Terzagih’s equation.

Publication Date
Fri Jan 01 2016
Journal Name
Iraqi Journal Of Science
Effect of growth media components and growth condition on indole - 3 - acetic acid (IAA) production by Pseudomonas putida isolated from soil
...Show More Authors

Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
...Show More Authors

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

... Show More
Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method
...Show More Authors

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

... Show More
View Publication Preview PDF
Crossref (5)
Crossref
Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
...Show More Authors

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

... Show More
View Publication Preview PDF
Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
An Experimental Study of Compaction and Strength of Stabilized Cohesive Soil by Stone Powder
...Show More Authors

The In this experimental study, natural stone powder was utilized to improve a cohesive soil’s compaction and strength properties. According to the significant availability of limestone in the globe, it has been chosen for the purpose of the study, in addition to considering the existing rock industry massive waste. Stone powder was used in percentages of 4, 8, 12, 16% replaced from the soil weight in dry state. Some of cohesive soil’s consistency, shear, and compaction properties were depicted after improvement. The outcomes yielded in significant amendments in the experimented geotechnical properties after stone powder addition considering 60 days curing period. Cohesion and friction angle were notably increased by

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Wed Jun 09 2021
Journal Name
International Journal Of Pavement Research And Technology
Influence of Mellowing Periods on Short- and Long-Term Performance of Lime-Treated Clay Subgrade Soils
...Show More Authors

View Publication
Scopus (1)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Wed Aug 09 2023
Journal Name
Applied Sciences
Effect of Crude Oil on the Geotechnical Properties of Various Soils and the Developed Remediation Methods
...Show More Authors

Crude oil still affects many countries because it is one of the essential fuel sources. It makes life more manageable in modern communities and cannot be overstated because it is easy to use and find. However, the pollution caused by its use in industries such as mining, transportation, and the oil and gas business, especially soil pollution, cannot be ignored. Soil pollution is an issue in most communities because it influences people and ecology. Accidental infusions and spills of ore oils are prevalent occurrences leading to the entire or fractional exchange of the soil pore fluid by oil-contaminated soils that have affected the geotechnical engineering properties. The liquid limitations for polluted soil grades silty loam and sa

... Show More
View Publication
Scopus (11)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Wed Aug 09 2023
Journal Name
Applied Sciences
Effect of Crude Oil on the Geotechnical Properties of Various Soils and the Developed Remediation Methods
...Show More Authors

Crude oil still affects many countries because it is one of the essential fuel sources. It makes life more manageable in modern communities and cannot be overstated because it is easy to use and find. However, the pollution caused by its use in industries such as mining, transportation, and the oil and gas business, especially soil pollution, cannot be ignored. Soil pollution is an issue in most communities because it influences people and ecology. Accidental infusions and spills of ore oils are prevalent occurrences leading to the entire or fractional exchange of the soil pore fluid by oil-contaminated soils that have affected the geotechnical engineering properties. The liquid limitations for polluted soil grades silty loam and sa

... Show More
Scopus (11)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering Science And Technology
Using sustainable material in improvement the geotechnical properties of soft clayey soil
...Show More Authors

Preview PDF
Scopus (46)
Scopus
Publication Date
Mon Jul 01 2013
Journal Name
Http://www.i-csrs.org/volumes/gisars/vol.3/vol.3.1.1.july.12.pdf
Remote sensing technique to monitoring the risk of soil degradation using NDVI
...Show More Authors

In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

... Show More
View Publication