The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

     Investigation of geotechnical vulnerability (liquefaction) and Zonation of the southern region of the Caspian Sea is my most important aim in terms of destructive earthquakes hazard potential. Past geologic events on the south coast of Caspian Sea indicates that destructive earthquakes lead to the death of numbers in this area. Remained evidence of seismic events happening indicates extensive landslides, liquefaction and soil subsidence in the residential and even natural area. Therefore, in this study determination of geotechnical vulnerability (liquefaction) intensity in southern coast of Caspian Sea against natural forces resulting from earthquakes and coastal construction via geographical information system e

The study has used Geographic Information Systems (GIS) data and Arc GIS software, to produce a new map. This map contains a spatial database of the newly constructed buildings, in the area of water resources engineering college, and using the above tool for updating contains the college in any time, also the map and browse all buildings individually or in clustered, for example, browsing geometric data,  statistical data and the plans of drawings, and make any necessary changes to these sectors immediately, or in the future, like the expansion of the study halls by constructed a new floor, or add supplements, prepare any electrical to any building, and  anything else.  The paper also, updates the old Google Earth image, f

Kirchhoff Time migration was applied in Pre and Post-Stack for 2D seismic survey for line AJ-99N, that is located in Ajeel oilfield in Salah Al-Din Governorate, Central Iraq. The process follows several accurate steps to reach the final time migration stage. The results of applied time migration give an accurate image for the Ajeel anticline reservoir and to improve the signal to noise ratio. Pre-Stack shows a clearer image for the structure in the study area, and the time-frequency analysis insure the result.

     Well log rock physics and seismic facies analysis was carried out with a view to enhancing reservoir sand characterization of Mafe Field of Niger Delta. Lithofacies were identified using suites of well logs and correlated across the block. Rock properties were estimated from wireline logs using empirical methods. Vp-porosity crossplot was used to characterize the delineated sandstone reservoirs by comparing observed clusters and trends with various rock physics models. Seismic attribute analysis was employed to detect lateral changes in lithology across the field. Reservoir A is a relatively clean sand, with low average volume of shale of 0.4, average thickness of 55m, good average porosity of 0.

     In this study, lateral groundwater inflow was examined, according to the phenomena of groundwater mixing, groundwater flow and groundwater chemistry. The study region is composed of different aquifer systems; including karst-fracture media (Rattga-Jeed carbonates aquifer), fissure–porous media (Mullusi, Mullusi-Ubaid, Hartha-Rutba, and Digma-Tayarat aquifers) and porous media (Permo-carboniferous clastics rocks of Ga’ra aquifer).The aquifers are vertically super-imposed or of lateral contacts make open hydraulic connection between aquifers system. There is a severe shortage of water resources in the region because of rare precipitation and strong evapotranspiration. These conditions have hampered eco-environm

Flavonoids were extracted from Zizyphus spina-christi leaves by Ethyl acetate after acid digested and used as antioxidant. The dried extract was added separately to each sample of fat extracted from hallow cow and sheep bones as follows: T1 cow fat, T2 control for cow fat, T3 sheep fat and T4 control for sheep fat (the control T2 and T4 reffered to samples without added antioxidant).
Samples were stored at -18, 5, 25 and 55 °C for 28 days. The storage trials were conducted at -18, 5 and 25 °C for 28 days for T1, T2, T3 and T4. The chemical indices examined initially and at the end of storage period. PVs was 1.46, 1.46, 1.8 and 1.8 meq/ Kg oil respectively, FFA values were 0.245, 0.245, 0.244 and 0.244% respectively and TBA va

Noor oil field is one of smallest fields in Missan province. Twelve well penetrates the Mishrif Formation in Noor field and eight of them were selected for this study. Mishrif formation is one of the most important reservoirs in Noor field and it consists of one anticline dome and bounded by the Khasib formation at the top and the Rumaila formation at the bottom. The reservoir was divided into eight units separated by isolated units according to partition taken by a rounding fields.

In this paper histograms frequency distribution of the porosity, permeability, and water saturation were plotted for MA unit of Mishrif formation in Noor field, and then transformed to the normal distribution by applying the Box-Cox transformation alg

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big