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Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
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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.

150 sets of data were generated in different days by the reference heat exchanger model to training the network. Regression between desired target and prediction ANN output for training , validation, testing and all samples show reasonably values are equal to one (R=1) . 50 sets of data were generated to test the network and compare between desired and predicated exit temperature (water temp. and air temp.) show a good agreement ( ).

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Publication Date
Fri Mar 05 2021
Journal Name
Materials
Optimum Placement of Heating Tubes in a Multi-Tube Latent Heat Thermal Energy Storage
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Utilizing phase change materials in thermal energy storage systems is commonly considered as an alternative solution for the effective use of energy. This study presents numerical simulations of the charging process for a multitube latent heat thermal energy storage system. A thermal energy storage model, consisting of five tubes of heat transfer fluids, was investigated using Rubitherm phase change material (RT35) as the. The locations of the tubes were optimized by applying the Taguchi method. The thermal behavior of the unit was evaluated by considering the liquid fraction graphs, streamlines, and isotherm contours. The numerical model was first verified compared with existed experimental data from the literature. The outcomes re

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Some Estimation Methods Of GM(1,1) Model With Missing Data and Practical Application
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This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

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Publication Date
Tue Sep 04 2018
Journal Name
Al-khwarizmi Engineering Journal
Effect of Carburization Parameters on Hardness of Carburized Steel Using MOORA Approach
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In this research, (MOORA) approach based– Taguchi design was used to convert the multi-performance problem into a single-performance problem for nine experiments which built (Taguchi (L9) orthogonal array) for carburization operation. The main variables that had a great effect on carburizing operation are carburization temperature (oC), carburization time (hrs.) and tempering temperature (oC). This study was also focused on calculating the amount of carbon penetration, the value of hardness and optimal values obtained during the optimization by Taguchi approach and MOORA method for multiple parameters. In this study, the carburization process was done in temperature between (850 to 950 ᵒC) for 2 to 6

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Reflection of the application TD-ABC approach on profits persistence Applied study in the General State of Hydraulic Industries Factory of Plastic*
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The interest of many companies has become dealing with the tools and methods that reduce the costs as one of the most important factors of successful companies, and became the subject of the attention of many economic units because of the impact on the profits of company, and since the nineties of the last century the researchers and writers gave great attention to this subject, especially in light of the large competition and rapid developments in cost management techniques, as well as the wide and significant change in production methods that have been directed towards achieving customer satisfaction, all this and more driven by economic units in all sectors whether it is service or productivity to find methods that would reduc

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Publication Date
Thu Jan 22 2026
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
The Effect of Duration of Stress Urinary Incontinence on developing Signs of Bladder Outlet Obstruction in Urodynamic Study
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Background: Stress urinary incontinence is a frequent urological disease in women; it has a great influence on an individual’s wellbeing and places a significant economic strain on any health service. The placement of urodynamic diagnostic tests in the evaluation route is an important clinical research concern in this field.

Objective: to find out whether the duration of stress urinary incontinence is associated with the finding of bladder outlet obstruction in urodynamic study or not.

Subjects and Methods: A descriptive study. With enrolled female patients had symptomatic Stress urinary incontinence as their primary complain. All the included patients w

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Publication Date
Fri Aug 20 2021
Journal Name
Iraqi Journal Of Laser
Design of Tunable Optical Band Pass Filter based on in-Line PM-Mach Zehnder Interferometer
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In this paper, tunable optical band-pass filters based on Polarization Maintaining Fiber –Mach Zehnder Interferometer presented. Tunability of the band-pass filter implemented by applying different mechanical forces N on the micro-cavities splicing regions (MCSRs). The micro-cavity formed by using three variable-lengths of single-mode polarization-maintaining fiber with (8, 16, 24) cm lengths, splice between two segments of (SMF-28) with (26, 13) cm lengths, using the fusion splicing technique.  Ellipsoidal shape micro-cavities experimentally achieved parallel to the propagation axis having dimensions between (12-24) μm of width and   (4-12) μm of length. A micro-cavity with width and length as high as 24 μm and 12 μ

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Publication Date
Thu Aug 01 2019
Journal Name
The Journal Of Solid Waste Technology And Management
Recycling of Waste Compact Discs in Concrete Mix: Lab Investigations and Artificial Neural Networks Modeling
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This study aimed to investigate the incorporation of recycled waste compact discs (WCDs) powder in concrete mixes to replace the fine aggregate by 5%, 10%, 15% and 20%. Compared to the reference concrete mix, results revealed that using WCDs powder in concrete mixes improved the workability and the dry density. The results demonstrated that the compressive, flexural, and split tensile strengths values for the WCDs-modified concrete mixes showed tendency to increase above the reference mix. However, at 28 days curing age, the strengths values for WCDs-modified concrete mixes were comparable to those for the reference mix. The leaching test revealed that none of the WCDs constituents was detected in the leachant after 180 days. The

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