This paper deals with prediction the effect of soil re-moulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil re-moulding due to actual pile driving. The results of the tests exhibited that the pile might loss 14% of its ultimate capacity when it is loaded immediately after installation. Also, it was concluded that the pile may regain of about 9% of its original capacity after 30days of its installation.
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For
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Sheet piles are necessary with hydraulic structures as seepage cut-off to reduce the seepage. In this research, the computational work methodology was followed by building a numerical model using Geo-Studio program to check the efficiency of using concrete sheet piles as a cut-off or reducer for seepage with time if the sheet piles facing the drawdown technique. Al-Kifil regulator was chosen as a case study, an accurate model was built with a help of observed reading of the measuring devices, which was satisfactory and helped in checking the sheet piles efficiency. Through the study, three scenarios were adopted (with and without) drawdown technique, it was found that at the short time there's no effect of the drawdown technique on
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Newly acid hydrazide was synthesized from ethyl 2-(2,3-dimethoxyphenoxy) acetate (2), which is cyclized to the corresponding 4-amino-1,2,4-triazole (3). Five newly azo derivatives (4a-e) were synthesized from this 1,2,4-triazole by converting the amine group to diazonium salt then reacted with various substituent phenol,as well three newly imine derivatives (5a-c) were synthesized from reacting the amine group of compound (3) with three aryl aldehyde. The thermal electro conductivity of these compounds was tested at 30, 50, 75 and 100 áµ’C. compound 4a showed interesting electro conductivity at 75áµ’C as well 5a at 75áµ’C while 5b showed significant conductivity at 100 áµ’C
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Newly acid hydrazide was synthesized from ethyl 2-(2,3-dimethoxyphenoxy) acetate (2), which is cyclized to the corresponding 4-amino-1,2,4-triazole (3). Five newly azo derivatives (4a-e) were synthesized from this 1,2,4-triazole by converting the amine group to diazonium salt then reacted with various substituent phenol,as well three newly imine derivatives (5a-c) were synthesized from reacting the amine group of compound (3) with three aryl aldehyde. The thermal electro conductivity of these compounds was tested at 30, 50, 75 and 100 áµ’C. compound 4a showed interesting electro conductivity at 75áµ’C as well 5a
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
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The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u
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