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Efficient Heat Transfer Augmentation in Channels with Semicircle Ribs and Hybrid Al2O3-Cu/Water Nanofluids
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Global technological advancements drive daily energy consumption, generating additional carbon-induced climate challenges. Modifying process parameters, optimizing design, and employing high-performance working fluids are among the techniques offered by researchers for improving the thermal efficiency of heating and cooling systems. This study investigates the heat transfer enhancement of hybrid “Al2O3-Cu/water” nanofluids flowing in a two-dimensional channel with semicircle ribs. The novelty of this research is in employing semicircle ribs combined with hybrid nanofluids in turbulent flow regimes. A computer modeling approach using a finite volume approach with k-ω shear stress transport turbulence model was used in these simulations. Six cases with varying rib step heights and pitch gaps, with Re numbers ranging from 10,000 to 25,000, were explored for various volume concentrations of hybrid nanofluids Al2O3-Cu/water (0.33%, 0.75%, 1%, and 2%). The simulation results showed that the presence of ribs enhanced the heat transfer in the passage. The Nusselt number increased when the solid volume fraction of “Al2O3-Cu/water” hybrid nanofluids and the Re number increased. The Nu number reached its maximum value at a 2 percent solid volume fraction for a Reynolds number of 25,000. The local pressure coefficient also improved as the Re number and volume concentration of “Al2O3-Cu/water” hybrid nanofluids increased. The creation of recirculation zones after and before each rib was observed in the velocity and temperature contours. A higher number of ribs was also shown to result in a larger number of recirculation zones, increasing the thermal performance.

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Physics: Conference Series
Gamma Irradiation Effects on Energy Transfer Parameters for Acrvlaven – Rhodamine19 Binary Laser Dye Mixtures
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Publication Date
Tue May 01 2018
Journal Name
Chemical Engineering And Processing - Process Intensification
Studies of mass transfer at a spiral-wound woven wire mesh rotating cylinder electrode
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Publication Date
Tue May 01 2018
Journal Name
Chemical Engineering And Processing - Process Intensification
Studies of mass transfer at a spiral-wound woven wire mesh rotating cylinder electrode
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Mass transfer has been studied at rotating cylinder electrodes fabricated with spiral-wound woven-wire meshes using reduction of copper as a test reaction. The experimental data were correlated by an empirical expression between the Sherwood number and the Reynolds number, both regarding the hydraulic diameter as a characteristic length. It was found that the Sherwood number was dependent upon the Reynolds number to the power of 0.521. An enhancement factor was adopted to compare the efficiency of the new rotating cylinder electrode with previous three-dimensional rotating cylinder electrodes. The results showed that the new type has a mass-transfer enhancement factor 2.3 times higher than those obtained with smooth rotating cylinder electr

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Design and Construction of Electrical Magnate to Study its Efficiency and the Optimum Parameters to Produce Alkaline Magnetic Water and Treating the Sea Water to be Suitable for Irrigation
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Abstract

Electrical magnate  was designed and constructed,  the optimum Magnetic flux  and the effect of time on the physical properties of the alkaline (magnetic water) produced from the bottled drinking water [the total dissolved solids (TDS) or the electrical conductivity, and pH] were studied, to simulate ZamZam water in Mekka Saudi Arabia. Also, the efficiency of magnetic field from this designed electrical magnate in decreasing the TDS of sea water (of 1500 ppm NaCl Content), to convert it to water suitable for irrigation (TDS<1000 ppm) was investigated in this work.The results show that the magnetic flux from our designed electrical magnate in the range of (0.013- 0.08) Tesla and 30 minut

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Fri Nov 21 2025
Journal Name
Journal Of Advances In Information Technology
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata
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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Fri May 01 2026
Journal Name
Statistics, Optimization &amp; Information Computing
Hybrid Modeling of Currency Circulation Volatility: Evidence from the Central Bank of Iraq
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The currency in circulation is a key element of the monetary supply system of the Iraqi economy because itreflects the level of economic activity and the liquidity level in the market. It can be expressed as an important tool when formulating monetary policy. This research aims to analyze and forecast the behavior of the currency in circulation in Iraq using the ARMA-GARCH model for monthly data from 2004 to 2025 to understand the dynamics of monetary liquidity, The sample was divided into two parts: approximately 80% for the training set (2004-2021), and approximately 20% for the testing set (2022-2025). Data were analyzed in Python using many packages. The results showed that the time series was initially non-stationary but became

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The study of the literature review of hybrid classification approaches to credit scoring
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