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The Estimation of Vibrational Energy of Two Coupled (Welded) Plates Using Statistical Energy Analysis
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This paper deals with a method called Statistical Energy Analysis that can be applied to the mechanical and acoustical systems like buildings, bridges and aircrafts …etc. S.E.A as a tool can be applied to the resonant systems in the circumstances of high frequency or/and complex structure». The parameters of S.E.A such as coupling loss factor, internal loss factor, modal density and input power are clarified in this work ; coupled plate sub-systems and explanations are presented for these parameters. The developed system is assumed to be resonant, conservative, linear and there is an equipartition of energy between all the resonant modes within a given frequency band in a given sub-system. The aim of this work is to find the energy stored in the sub-systems for two coupled (welded) plates in rectangular angle systems and study the effect of changing sub-systems dimensions, the results shows that as surface area of directly driven plates A1 increases energy level of plate 1 increases while a reduction in the energy level of indirectly driven plate (plate 2) is noticed. This is because of the strength of coupling decreases towards the weak coupling condition and this leads to a reduction in the power transferred from plate 1 to plate 2 and consequently a lower energy level for plate 2. In addition the effect of changing the internal loss factor for a range of (0.00001-0.1) causes a reduction of the values of energy level in these sub-systems. because the increasing of internal loss factor values led to the increasing of the material resistance and that will dissipate the energy flow across those sub-systems. A comparison is made between S.E.A models built by FORTRAN program and Finite Element model solved by ANSYS package.

 

 

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data
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      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

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Publication Date
Wed May 01 1985
Journal Name
International Journal Of Mass Spectrometry And Ion Processes
Energy distributions of atmospheric ions drifting in rare gases
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Publication Date
Fri Feb 17 2012
Journal Name
Smart Materials And Structures
Frequency tuning of piezoelectric energy harvesters by magnetic force
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Publication Date
Tue Feb 28 2017
Journal Name
Journal Of Engineering
Design and Implementation of Enhanced Smart Energy Metering System
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In this work, the design and implementation of a smart energy metering system has been developed. This system consists of two parts: billing center and a set of distributed smart energy meters. The function of smart energy meter is measuring and calculating the cost of consumed energy according to a multi-tariff scheme. This can be effectively solving the problem of stressing the electrical grid and rising consumer awareness. Moreover, smart energy meter decreases technical losses by improving power factor. The function of the billing center is to issue a consumer bill and contributes in locating the irregularities on the electrical grid (non-technical losses). Moreover, it sends the switch off command in case of the consumer bill is not

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Buckling Analysis of Composite Plates under Thermal and Mechanical Loading
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Buckling analysis of composite laminates for critical thermal (uniform and linear) and mechanical loads is reported here. The objective of this work is to carry out theoretical investigation of buckling analysis of composite plates under thermomechanical loads, and experimental investigation under mechanical loads. The analytical investigation involved certain mathematical preliminaries, a study of equations of orthotropic elasticity for classical laminated plate theory (CLPT), higher order shear deformation plate theory (HSDT) , and numerical analysis (Finite element method), then the equation of motion are derived and solved using Navier method and Levy method for symmetric and anti-symmetric cross-ply and angle-ply laminated plates t

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Information Technology Management
The impact of social commerce determinants on social capital for energy sectors
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This study investigates the constructs and related theories that drive social capital in energy sector from the intention perspectives. This research uses theories of 'social support' and 'planned behaviour' alongside satisfaction and perceived value to propose a research model that drives social capital for energy sectors in Malaysia. The model reveals that the Theories of Planned Behaviour (TPB) and Social Support Theory (SST) alongside satisfaction and perceived value factors promote social capital development in energy sectors. Using PLS-SEM to analyse data gathered from energy sector employees in Malaysia, this research demonstrates that social capital is present when there is trust and loyalty among the users and positively effects en

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Publication Date
Tue Mar 30 2021
Journal Name
Scientific Review Engineering And Environmental Studies (srees)
Testing the performance of a solar energy cooling system in Baghdad city
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Renewable energy resources have become a promissory alternative to overcome the problems related to atmospheric pollution and limited sources of fossil fuel energy. The technologies in the field of renewable energy are used also to improve the ventilation and cooling in buildings by using the solar chimney and heat exchanger. This study addresses the design, construction and testing of a cooling system by using the above two techniques. The aim was to study the effects of weather conditions on the efficiency of this system which was installed in Baghdad for April and May 2020. The common weather in these months is hot in Baghdad. The test room of the design which has a size of 1 m3 was situated to face the geographical south. The te

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Publication Date
Mon Nov 01 2021
Journal Name
Energies
Solidification Enhancement in a Triple-Tube Latent Heat Energy Storage System Using Twisted Fins
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This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet tem

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Publication Date
Thu Jun 01 2017
Journal Name
International Journal Of Heat And Mass Transfer
Melting enhancement in triplex-tube latent thermal energy storage system using nanoparticles-fins combination
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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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