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.

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

The aim of research is to show the effect of Ferric Oxide (Fe2O3) on the electricity production and wastewater treatment, since 2.5% of Ferric Oxide (Fe2O3) (heated and non heated) nanoparticles has been used. Characterization of nanoparticles was done using X-ray Diffraction (XRD) and Scan Electron Microscopy (SEM). The influence of acidity was also studied on both wastewater treatmenton the Chemical Oxygen demand (COD) and Biological Oxygen Demand (BOD) and voltage output was studied. From the results, it was infused that the dosage of 0.025 g/l and an initial pH 7 were founded to be optimum for the effective degradation of effluents. The results concluded that the treatment of anaerobic sludge wastewater using Ferric Oxide (Fe2O3) in

Sustainable crop production in a coarse soil texture is challenging due to high water permeability and low soil water holding capacity. In this paper, subsurface water retention technology (SWRT) through impermeable polyethylene membranes was placed at depth 35 cm below ground surface and within the root zone to evaluate and compare the impact of these membranes and control treatment (without using the membranes) on yield and water use efficiency of eggplant inside the greenhouse. The study was conducted in Al-Fahamah Township, Baghdad, Iraq during spring growing season 2017. Results demonstrated the yield and water use efficiencies were 3.483 kg/m² and 5.653 kg/m³, respectively for SWRT treatment p