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Optimizing performance of water-cooled photovoltaic-thermal modules: A 3D numerical approach
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To evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and multi-objective optimizations are performed using the predictive model to optimize the thermal and electrical productivity under different scenarios. The findings indicate the significance of the thermal exergy effectiveness, as evidenced by its low P-value for all solar system responses, indicating its crucial role in the predictive model. For single-objective optimization, the desirability is equal to 1 in cases where only heat transfer efficiency, whole energy effectiveness, or thermal exergy efficiency is maximized or only destroyed exergy is minimized. The improvements in energy and exergy efficiencies range from 3.55% to 69.13%, with the amount of destroyed exergy reduced by 81.47% compared to the base case. For multi-objective optimization, desirability values exceeding 0.829 and 0.655 are obtained for single and multi-objective scenarios, respectively, indicating that the expected performance is within desirable limits. The findings provide valuable insights for designing high-efficiency photovoltaic/thermal systems and addressing their challenges and limitations.

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Mon Jan 08 2018
Journal Name
International Journal Of Science And Research
effect of steel fiber type on compressive strength and modules of rupture on reactive powder concrete
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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Effect of synthesis parameters on the formation 4A zeolite crystals: characterization analysis and heavy metals uptake performance study for water treatment
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Publication Date
Sun Mar 20 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
Numerical Modeling of Circular Tunnel Alignment Under Seismic Loading
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The continuous increase in population has led to the development of underground structures like tunnels to be of great importance due to several reasons. One of these reasons is that tunnels do not affect the living activities on the surface, nor they interfere with the existing traffic network. More importantly, they have a less environmental impact than conventional highways and railways. This paper focuses on using numerical analysis of circular tunnels in terms of their behavior during construction and the deformations that may occur due to overburden and seismic loads imposed on them. In this study, the input data are taken from an existing Cairo metro case study; results were found for the lateral and vertical displacements, the Peak

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
EXPERIMENTAL AND NUMERICAL STRESS ANALYSIS OF INVOLUTE SPLINED SHAFT
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In this study, the induced splined shaft teeth contact and bending stresses have been investigated numerically using finite element method(Ansys package version 11.0) with changing the most effecting design parameter,(pressure angle, teeth number, fillet radius and normal module), for internal and external splined shaft. Experimental work has been achieved using two dimensional photoelastic techniques to get the contact and bending stresses; the used material is Bakelite sheet type “PSM-4”.
The results of numerical stress analysis indicate that, the increasing of the pressure angle and fillet radius decrease the bending stress and increase the contact stress for both internal and external spline shaft teeth while the increasing of

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Publication Date
Fri Jul 01 2011
Journal Name
Energy
Experimental and numerical analysis of electrical metal foam heater
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A novel concept of air heater using a heating element made from Aluminum metal porous disc surrounded by a DC resistive electrical heater inserted in the mid-plane of a copper tube of (52.8 mm) diameter and (480 mm) length is presented herein. Study of the developed heater is conducted; using different porous disc thicknesses of (20, 40, 60 mm), heater wall temperatures (106 °C and 119 °C), and flow rates rare varied from (100–300 L/min). Al-metal foam disc has been made using the metal powder technology. Different resistive electrical heaters according to the type of porous disc used have been manufactured. A 2-D computational model is developed, using continuity, momentum, and energy equations for turbulent forced flow in plain tube,

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Publication Date
Fri Mar 20 2020
Journal Name
Remote Sensing
Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics
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The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
A Novel Approach to Improving Brain Image Classification Using Mutual Information-Accelerated Singular Value Decomposition
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Publication Date
Sat Feb 25 2017
Journal Name
International Journal On Advanced Science, Engineering And Information Technology
A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method
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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach
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