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bsj-7584
Performance Evaluation of a Triple Concentric Tube Heat Exchanger Using Deionized Water and Oil-40
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This study examines experimentally the performance of a horizontal triple concentric tube heat exchanger TCTHE made of copper metal using water as cooling fluid and oil-40 as hot fluid. Hot fluid enters the inner annular tube of the TCTHE in a direction at a temperature of 50, 60 and 70 oC and a flow rate of 20 l/hr. On the other hand, the cooling fluid enters the inner tube and the outer annular tube in the reverse direction (counter current flow) at a temperature of 25 oC and flow rates of 10, 15, 20, 25, 30 and 35 l/hr. The TCTHE is composed of three copper tubes with outer diameters of 34.925 mm, 22.25 mm, and 9.525 mm, and thicknesses of 1.27 mm, 1.143 mm, and 0.762 mm, respectively. TCTHE tube's length was 670 mm. Nusselt number, overall heat transfer coefficient, convective heat transfer coefficient (CHTC), friction factor and pressure drop were measured from the obtained experimental results and plotted in graphs against Reynold number and volumetric flow rate of water. These parameters appeared good results in the cooling process. Nusselt numbers increased linearly with DIW flow rate for both C1 and C2 reaching maximum values of 38.25 and 14.64 respectively. CHTC increased linearly with the DIW flow rate for both C1 and C2 reaching maximum values of 2934.3 and 871.7 respectively. Overall heat transfer coefficient of DIW reached maximum values of 296.36 and 251.4 at 35 l/hr for C1 and C2, respectively. Friction factor DIW in C1 and C2 decreased with the volumetric flow rate increases, reaching minimum values of 0.04 and 0.25 respectively. Pressure drop of DIW increased linearly with flow rate reaching maximum values of 81.4 and 4.31 for C1 and C2 respectively. This in turn leads to reduced TCTHE length and size leading to a decrease in the construction cost of the heat exchanger.

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

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Publication Date
Fri Feb 13 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Studying the effect of addition a composite of silanized Nano-Al2O3 and plasma treated polypropylene fibers on some physical and mechanical properties of heat cured PMMA denture base material
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Background: Polymethyl methacrylate (PMMA) is the most commonly used material in denture fabrication. The material is far from ideal in fulfilling the mechanical requirements, like low impact and transverse strength, poor thermal conductivity. The purpose of this study was to evaluate the effect of addition a composite of surface treated Nano Aluminum oxide (Al2O3) filler and plasma treated polypropylene fiber (PP) on some properties of denture base material. Materials and methods: One hundred fifty prepared specimens were divided into 5 groups according to the tests, each group consisted of 30 specimens and these were subdivided into 3 groups (unreinforced heat cured acrylic resin as control group),reinforced acrylic resin with( 0.5%wt Nan

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Improve operational performance by simulating the Holonic manufacturing system A case study at the rubber product plant in Al-Najaf Al-Ashraf
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The research aims to improve operational performance through the application of the Holonic Manufacturing System (HMS) in the rubber products factory in Najaf. The problem was diagnosed with the weakness of the manufacturing system in the factory to meet customers' demands on time within the available resources of machines and workers, which led to time delays of Processing and delivery, increased costs, and reduced flexibility in the factory, A case study methodology used to identify the reality of the manufacturing system and the actual operational performance in the factory. The simulation was used to represent the proposed (HMS) by using (Excel 2010) based on the actual data and calculate the operational performance measures

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Customers emotional blackmail and reduce it the new product- study of the opinions of a sample of customers who deal with peak economy for household items in najaf al Ashraf
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The challenges facing today's multi-customer and this is due to the multiplicity of products and speed in launching new products so search came to reveal the  reveal the of the new product classification standards through a relationship (good products, low interest products, useful products and products desired) and the customer emotionally blackmail through deportation (fear, obligation and guilt). dentified the problem of the research in several questions focused on the nature of the relationship between the variables of research, and for that outline supposedly to search it expresses the head of one hypothesis and branched out of which four hypotheses subset, but in order to ensure the validity of the ass

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Publication Date
Sun Jan 19 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Effect flexibility of the Strategic human resources in improvement operational performance: "Survey study of views of a sample of managers, engineers and technicians in the Baghdad south 2/Station directorate of Electricity"
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The research attempts to diagnose the level of the effect of human resources flexibility (employees skills flexibility, employees behaviors flexibility, and human resource practice flexibility) in the south al-rusafa directorate of a power  station one of the formations and the Ministry of Electricity, and impact of a range of variables related to the performance operational, namely, (efficiency, effectiveness)recognizing the importance of the subjects studied,& because of the importance of expected results of the field under consideration,researcher selected a sample of size (121) engineers and technicians of workers in the directorate. Was my hypotheses the major search of a relationship and impact between human resources flex

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Publication Date
Sun Jan 01 2023
Journal Name
Chemical Engineering And Processing - Process Intensification
Optimization of a combined electrocoagulation-electro-oxidation process for the treatment of Al-Basra Majnoon Oil field wastewater: Adopting a new strategy
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The performance of a synergistic combination of electrocoagulation (EC) and electro-oxidation (EO) for oilfield wastewater treatment has been studied. The effect of operative variables such as current density, pH, and electrolyte concentration on the reduction of chemical oxygen demand (COD) was studied and optimized based on Response Surface Methodology (RSM). The results showed that the current density had the highest impact on the COD removal with a contribution of 64.07% while pH, NaCl addition and other interactions affects account for only 34.67%. The optimized operating parameters were a current density of 26.77 mA/cm2 and a pH of 7.6 with no addition of NaCl which results in a COD removal efficiency of 93.43% and a specific energy c

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Scopus (41)
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Publication Date
Sun Jan 01 2023
Journal Name
Chemical Engineering And Processing - Process Intensification
Optimization of a combined electrocoagulation-electro-oxidation process for the treatment of Al-Basra Majnoon Oil field wastewater: Adopting a new strategy
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Crossref (33)
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Publication Date
Sat Oct 01 2022
Journal Name
Case Studies In Thermal Engineering
Comparative assessment of the performance and combustion attributes of a free piston linear generator fuelled with CNG and CNG-CO2
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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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