Triple Diode Solar Cell Module (TDSCM) circuit with nine parameters for various environmental circumstances represents the behavior and practical performance of solar *** precise extraction of photovoltaic (PV) module...
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Triple Diode Solar Cell Module (TDSCM) circuit with nine parameters for various environmental circumstances represents the behavior and practical performance of solar *** precise extraction of photovoltaic (PV) module parameters is essential for optimising the energy conversion efficiency of PV systems. Usually the equations describing solar panels are implicit in nature, and parameter extraction has been very complicated. The solar cell is mathematically modelled with nonlinear I-V (Current -Voltage) characteristics behavior, and it cannot be directly determined from the PV's datasheet due to the lack of data offered by the PV manufacturers. On the basis of the technical datasheet of the photovoltaic module (PV), only four equations can be obtained in single diode, double diode, and triple diode parameters. To be implemented with fifth equation, many researchers have been done with multiple approximations and it becomes with low accuracy, complexity of computation, convergence problem. To resolve these issues, a new multi-objective optimization (GA) geneticalgorithm method is prescribed to frame the fifth equation using the Boole rules implemented with the curved area concept. The proposed Boole's rule based model offers superior non-linearity performance and high precision modelling, and the error shows a significant reduction when compared to the single and double diode approaches used in the existing approach. The effectiveness of the proposed I-V curve characteristics efficiency was improved by the implementation of the proposed Boole's rule with RMSE error 0.000034.
This work aims to present a new statistical optimization approach of artificial neural network modified by multi objective genetic algorithm to improve the pipe flow hydrodynamic and thermal properties such as pressur...
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This work aims to present a new statistical optimization approach of artificial neural network modified by multi objective genetic algorithm to improve the pipe flow hydrodynamic and thermal properties such as pressure drop and heat transfer coefficient for a non-Newtonian nanofluid composed of Fe3O4 nanoparticles dispersed in liquid paraffin. Hence the mixture pressure lose & convection coefficient are evaluated and then optimized so that to maximize the convection heat transfer and minimize the pressure drop. The results showed that the proposed model of multiobjective optimization of GA Pareto optimal front, quantified the trade-offs to handle 2 fitness functions of the considered non-Newtonian pipe flow. (C) 2019 Elsevier B.V. All rights reserved.
In this paper thermal and hydraulic optimization of water to water chevron type plate heat exchanger is presented. The optimization is performed using the multi objective genetic algorithm in MATLAB optimization envir...
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In this paper thermal and hydraulic optimization of water to water chevron type plate heat exchanger is presented. The optimization is performed using the multi objective genetic algorithm in MATLAB optimization environment. Constrain matrix is a set of different geometrical parameters of plate heat exchanger within the logical bounds. The two objective functions are pressure drop of hot side and heat transfer. Due to conflicting nature of these objective functions, no single solution can satisfy both of the objective function simultaneously. The increase in heat transfer will results in increase in pressure drop, therefore, optimization results are presented as Pareto Front. multi objective genetic algorithm tool was employed to find a set of optimum solution which was trade-off between pressure drop and heat transfer. M the end, sensitivity analysis was performed to analyse the effect of geometrical parameters of heat exchanger on thermal and hydraulic performance. The sensitivity results show that the heat transfer and pressure drop are greatly affected by the vertical port centre distance, plate spacing and number of thermal plates.
Energy consumption in agricultural products and its environmental damages has increased in recent *** cycle assessment(LCA)has been introduced as a suitable tool for evaluation environmental impacts related to a produ...
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Energy consumption in agricultural products and its environmental damages has increased in recent *** cycle assessment(LCA)has been introduced as a suitable tool for evaluation environmental impacts related to a product over its life *** this study,optimization of energy consumption and environmental impacts of chickpea production was conducted using data envelopment analysis(DEA)and multi objective genetic algorithm(MOGA)*** were collected from 110 chickpea production enterprises using a face to face questionnaire in the cropping season of *** results of optimization revealed that,when applying MOGA,optimum energy requirement for chickpea production was significantly lower compared to application of DEA technique;so that,total energy requirement in optimum situation was found to be 31511.72 and 27570.61 MJ ha^-1 by using DEA and MOGA techniques,respectively;showing a reduction by 5.11%and 17%relative to current situation of energy *** of environmental impacts by application of MOGA resulted in reduction of acidification potential(ACP),eutrophication potential(EUP),global warming potential(GWP),human toxicity potential(HTP)and terrestrial ecotoxicity potential(TEP)by 29%,23%,10%,6%and 36%,*** capable of reducing the energy consumption from machinery,farmyard manure(FYM)diesel fuel and nitrogen fertilizer(the mostly contributed inputs to the environmental emissions)by 59%,28.5%,24.58%and 11.24%,***,the MOGA technique showed a superior performance relative to DEA approach for optimizing energy inputs and reducing environmental impacts of chickpea production system.
In the era of sustainability, recycling of industrial waste material by using marble powder as filler in the Polypropylene matrix recommend an interesting opportunity. In this study, composites were fabricated by addi...
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ISBN:
(纸本)9781509028078
In the era of sustainability, recycling of industrial waste material by using marble powder as filler in the Polypropylene matrix recommend an interesting opportunity. In this study, composites were fabricated by adding different weight percentages of marble powder (5-15 wt.%) in the Polypropylene by injection molding process. To evaluate the contribution of marble powder in the PP-marble composite, Mechanical characterizations such as Shore hardness test, compressive strength and impact strength were performed. For surface morphological characterizations Scanning Electron Microscopy (SEM) was performed for the Polypropylene-marble composites. Taguchi technique and multi objective genetic algorithm were used to optimize the parameters.
Using extended finite state machines for test data generation can be a difficult process because we need to generate paths that are feasible and we also need to find input data that traverse a given path. This paper p...
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ISBN:
(纸本)9781538626269
Using extended finite state machines for test data generation can be a difficult process because we need to generate paths that are feasible and we also need to find input data that traverse a given path. This paper presents a test suite generation algorithm for extended finite state machines. The algorithm produces a set of feasible transition paths that cover all transitions using a modified multi-objectivegeneticalgorithm (deleting redundant paths and shortening the solutions). The multi-objective problem aims to optimize the transitions coverage and the path feasibility, based on dataflow dependencies. Having a set of paths resulted from this algorithm, we can easily find input parameters for each path.
This paper describes the application of an evolutionary optimization method to design satellite constellation for continuous regional coverage without intersatellite links. This configuration, called mutual coverage, ...
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This paper describes the application of an evolutionary optimization method to design satellite constellation for continuous regional coverage without intersatellite links. This configuration, called mutual coverage, is related to some technical limitations that exist on small satellite technology. The coverage of the north Algerian seismological network is taken as an example of application. A multi objective genetic algorithm (MOGA) is used to make a trade-off between the improvement of the coverage rate, the minimization of the total number of satellites and the reduction of the satellites' altitude. First, some experiments have been performed to find the weight distribution of the fitness function that shows the most significant improvement of the average fitness function. Then, some optimized constellation designs are given for different ranges of altitude and it is shown that the size of the MOGA constellation design is significantly reduced compared to the traditional geometrical design.
Power system stability enhancement via optimal simultaneous coordinated design of a power system stabilizer (PSS) and a thyristor-controlled series capacitor (TCSC) for electric power systems oscillations damping is i...
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Power system stability enhancement via optimal simultaneous coordinated design of a power system stabilizer (PSS) and a thyristor-controlled series capacitor (TCSC) for electric power systems oscillations damping is investigated in this paper. A SMIB system equipped with PSS and TCSC controllers is considered in this study. Although these controllers are used for stabilization of power system oscillations but the system must preserve its stability when subjected to sever disturbances. Therefore, the overall stability of the system should be considered. To do so, in the present paper the problem of controllers design is formulated as a multiobjective optimization problem. Then the multi objective genetic algorithm (MOGA) is explored to solve this optimization problem. Pareto method type of selection is used in the present MOGA approach.
A compact crossflow offset plate-fin heat exchanger (CPFHE) is widely used in many industrial applications. In this paper, a local sensitivity analysis was performed and a parametric analysis was used to validate the ...
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A compact crossflow offset plate-fin heat exchanger (CPFHE) is widely used in many industrial applications. In this paper, a local sensitivity analysis was performed and a parametric analysis was used to validate the results of the sensitivity analysis and locate the optimum by utilizing the unidirectional search. A new formula for the mass of the CPFHE that includes the masses of fans was introduced. A practical approach was used to formulate multi-objective optimization problems through which the total annual relative cost, heat rate, effectiveness, and mass of the CPFHE were optimized separately and simultaneously relative to 13 optimization design variables using a geneticalgorithm and the direct search method. The main optimization results showed that the effectiveness of the CPFHE could be increased by 9% through performing the optimization process relative to an additional influential variable, achieving a remarkable 0.9812. The actual value for the optimized mass of the CPFHE reported in the literature (a very small volume with huge pressure drops and massive fans) is many times greater than the optimized mass of this study. The distributions of the Pareto-optimal point solutions of multi-objective optimization results for three different conflict-objective functions were plotted and showed that all points are nondominated.
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