In this paper, a new hybrid optimization approach for the pattern synthesis of linear antenna array is proposed. Hybrid approach (TAGAPSO) contains taguchi algorithm(TA), Genetic algorithm(GA) and Particle Swarm Optim...
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ISBN:
(纸本)9781538671320
In this paper, a new hybrid optimization approach for the pattern synthesis of linear antenna array is proposed. Hybrid approach (TAGAPSO) contains taguchi algorithm(TA), Genetic algorithm(GA) and Particle Swarm Optimization (PSO). The aim of the optimization is to obtain desired side lobe level and half power beam width of the linear antenna array. Optimization results obtained by TA, GA, PSO and TAGAPSO are compared. The results show that TAGAPSO is much better than TA, GA and PSO. Optimization goals satisfied via TAGAPSO are much better than the other methods. Results of TAGAPSO are also compared with the results obtained by High Frequency Structural Simulator (HFSS) in order to verify the results.
Characterization modules in electric machines and drives design optimization environments typically involve the use of electromagnetic finite element-state space models that require large number of iterations and comp...
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Characterization modules in electric machines and drives design optimization environments typically involve the use of electromagnetic finite element-state space models that require large number of iterations and computational time. It is shown in this work that the utilization of a taguchi orthogonal arrays method in conjunction with a particle swarm optimization (PSO), search algorithm in a design optimization case study of a synchronous reluctance motor (SynRM) drive, resulted in about 80% reduction of computational time.
Fouling formation in gas dehydration units is performed mainly by gradual accumulation of sulfur-containing compounds and its corrosion products in glycol streams. High concentrations of iron-sulfur species in glycol ...
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Fouling formation in gas dehydration units is performed mainly by gradual accumulation of sulfur-containing compounds and its corrosion products in glycol streams. High concentrations of iron-sulfur species in glycol media increase the fouling propensity on the tube surfaces of heat exchangers. Therefore, the factors affecting the fouling formation and their ranks were determined in a pilot plant gas dehydration unit. Then, the morphology and composition of the fouling layers were studied by qualitative and quantitative XRD patterns. The results revealed that among studied parameters, the concentration of dissolved iron in glycolic media is the main factor responsible for the formation of iron-sulfide deposits. Moreover, it was showed that non-stoichiometric pyrrhotite polytypes 4C, 5C and 6C are the base components of fouling scales deposited on the surface of heat exchangers. Distribution of iron-based species was also determined in the cross-section of a typical heat exchanger and the results showed that the deposited layers are consisted of hydrocarbon residues and pyrrhotite polytypes. Over the time, the pyrrhotite polytypes in deposited layers are covered by paraffin residues absorbed by TEG phase from the natural gas stream.
This paper develops a method of knowledge-aided clutter suppression for subsurface radar imaging by crafting the power spectrum of the transmit waveform. The power spectrum is optimized to enhance the signal-to-clutte...
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ISBN:
(纸本)9781728168135
This paper develops a method of knowledge-aided clutter suppression for subsurface radar imaging by crafting the power spectrum of the transmit waveform. The power spectrum is optimized to enhance the signal-to-clutter-ratio (SCR) by target matched illumination for suppressing transmit power in dominant clutter frequencies. This approach is extended to radar imaging for the enhancment of the overall 2-dimensional target reflectivity function. By modelling the received signal as the output of an LTI filter, the channel capacity can be maximized. An algorithm is developed using taguchi techniques to optimized the spectrum and thus reduce the clutter in radar images. Particle swarm optimization (PSO) is extended to waveform design for comparison. The optimization objective function is the mutual information between the received signal and the target response conditioned upon a transmit waveform. The PSO and taguchi algorithms are seen to converge quickly to a waveform that maximizes the SCR. The radar imagery is formed using the newly optimized waveforms to test the methodology by the coherent addition of simulated and distributed target and clutter responses. The SCR is used as a performance metric. The results show that transmitting a waveform tailored to the frequency response of the target and clutter improve the SCR and mutual information over a conventional linearly frequency modulated waveform.
design optimization environments are used for electric vehicles and other traction applications to arrive at efficient motor drives. Typically, the environment includes characterization modules that involve the use of...
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design optimization environments are used for electric vehicles and other traction applications to arrive at efficient motor drives. Typically, the environment includes characterization modules that involve the use of Electromagnetic Finite Element and State-Space models that require large number of iterations and computational time. This work proposes the utilization of a taguchi orthogonal arrays method in conjunction with a Particle Swarm Optimization search algorithm to reduce computational time needed in the design optimization of electric motors for traction applications. The effectiveness of the taguchi method in conjunction with the optimization environment is demonstrated in a case study involving a prototype of a Synchronous Reluctance Motor drive system.
In this research, the operating parameters of proton exchange membrane (PEM) electrolyzer are optimized in order to decrease the required input voltage using taguchi method. The considered parameters include the opera...
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In this research, the operating parameters of proton exchange membrane (PEM) electrolyzer are optimized in order to decrease the required input voltage using taguchi method. The considered parameters include the operating temperature, the pressure of cathode and anode, membrane water content, membrane thickness, and cathode and anode exchange current density. First, a thermodynamic model is developed for the PEM electrolyzer, and then the taguchi method is applied for optimization of the electrolyzer performance. The signal to noise ratio (SNR) and the analysis of variance (ANOVA) method are also performed to determine the contribution ratio of effective parameters. The results reveal that the optimal condition is achieved at maximum working temperature, membrane water content, and cathode and anode exchange current density and at minimum membrane thickness, cathode pressure, and anode pressure. The anode exchange current density has considerable effect on the electrolyzer voltage with contribution of 67.15% while the membrane water content and the anode pressure have a minor influence with contribution of 1.1% and 0.42%, respectively. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
This paper investigates the optimization problem in wideband cognitive radio networks. It focuses on jointly optimizing the decision threshold, sensing time and transmission power to maximize the aggregate throughput ...
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This paper investigates the optimization problem in wideband cognitive radio networks. It focuses on jointly optimizing the decision threshold, sensing time and transmission power to maximize the aggregate throughput under the constraints of local interference, false-alarm probability, missed detection probability and maximal total power of each secondary user. Sequential parameter optimization strategy is introduced to deal with different optimization parameters in the optimization problem. It starts with power allocation first, with the optimal power allocation vector obtained by adaptive power allocation strategy, the gold section search method combined with taguchi algorithm is proposed to find the optimal sensing time with the optimal power allocation vector, and the optimal decision threshold with the optimal power allocation vector and sensing time is optimized through iterative process. Simulation results show that the proposed algorithm can achieve a better performance and is effective in solving such optimization problems.
This paper built a finite element model of the Halbach permanent magnet motor, whose accuracy was verified by comparing the output phase back-electromotive force of the model with that of the prototype motor. Keeping ...
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This paper built a finite element model of the Halbach permanent magnet motor, whose accuracy was verified by comparing the output phase back-electromotive force of the model with that of the prototype motor. Keeping other parameters constant as far as possible, we investigated five variables one by one to find out the law how these variables affect air gap magnetic flux, which is a basis for further optimization research. After a new variable named Cost constructed to reflect the distortion ratio of air gap magnetic flux, this paper performed some optimization experiments by studying five parameters of the motor using taguchi algorithm, Genetic algorithm and Pattern Search algorithm. On the basis of summarizing the advantages and disadvantages of these algorithms, we proposed two kinds of novel hybrid optimization algorithms, which are named as taguchi-Pattern Search algorithm and Genetic-Pattern Search algorithm, and proved the validity and practicability by experiments and finite element calculations.
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