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Optimization design with an advanced genetic algorithm for a compact air-air heat exchanger applied in aero engine

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2020年 158卷 119952-119952页

作者： Xu, Guoqiang Zhuang, Laihe Dong, Bensi Liu, Qihang Wen, Jie Beihang Univ Collaborat Innovat Ctr Adv Aeroengine Sch Energy & Power Engn Natl Key Lab Sci & Technol Aeroengine Aerothermod Beijing 100191 Peoples R China

This work presents an optimal design method for a compact air-air serpentine tube heat exchanger (STHE), which is applied as the core component of the bearing sealing cooling system in the aero engine. A new optimization tool, coupling with the Logarithmic Mean Temperature Difference (LMTD) method and an advanced genetic algorithm (AGA) using Gray code, is proposed to optimize the STHE with unknown outlet parameters under variable working conditions. Under the given performance and structural constraints, six optimization design variables, including tube outer diameter, the transverse tube pitch, the longitudinal tube pitch, the transverse tube rows, the height and the number of elbows, are selected to obtain the maximum heat transfer capability KA per total weight. The optimization results show that, by using AGA, the target parameter distribution is narrowed from 88.3193.86 kW/(***) to 91.9093.92 kW/(***), and the proportion of the optimal solutions higher than 93 kW/(***) increases from 22.62% to 94.32%. The optimization also improves the heat transfer capability KA per total weight to 93.92 kW/(***), comparing with the original value of 70.08 kW/(***). As the key limiting factors, the hot side maximum outlet temperature and pressure drop in the optimized STHE do not appear at the same operation mode and both of them are quite close to the given limits. It well demonstrates the validity and applicability of the proposed optimization design method using under multiple restrictions and conditions. (C) 2020 Published by Elsevier Ltd.

关键词： Serpentine tube heat exchanger advanced genetic algorithm Optimal design method Aero engine

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Implementation of advanced genetic algorithm to modern power system stabilization control

Implementation of advanced genetic algorithm to modern power...

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IEEE PES Power Systems Conference and Exposition

作者： Hongesombut, K Mitani, Y Kyushu Inst Technol Dept Elect Engn Kitakyushu Fukuoka 8048550 Japan

ISBN: (纸本)078038718X

This paper focuses on the use of advanced techniques in genetic algorithm for solving power system stabilization control problems. At the outset, the proposed hierarchical genetic algorithm (HGA) and parallel micro genetic algorithm (parallel micro-GA) are proposed and then they win be extended to solve two example problems. In the first example, these techniques are applied to simultaneously tune power system stabilizers (PSSs). The PSSs are optimally tuned to simultaneously shift the lightly damped and undamped oscillation modes to a stable zone in the s-plane and to self identify the appropriate PSS locations. In second example, parallel micro-GA is used to design the fuzzy logic controller (FLC) of STATCOM. The applied technique for designing a FLC helps us save time and does not require experts for designing. From these results, we can see that these advanced techniques provide enhanced versatility for solving problems in power system stabilization control.

关键词： power system stabilization advanced genetic algorithm hierarchical genetic algorithm parallel micro genetic algorithm

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advanced genetic algorithm for optimal models for gas production composition of gas field development programming

Xinan Shiyou Xueyuan Xuebao/Journal of Southwestern Petroleu...

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Xinan Shiyou Xueyuan Xuebao/Journal of Southwestern Petroleum Institute 2006年第3期28卷 1-4页

作者： Liu, Zhi-Bin Deng, Yong Fan, Zhe-Yuan Southwest Petroleum University Chengdu 610500 China

This paper introduces an advanced genetic algorithm for single-objective optimal models on the basis of optimal models for production composition of natural gas development programming. It takes Powell method as an arithmetic operator paralleled with the operators such as selection, crossover and mutation into the elementary genetic algorithm, and makes use of a new anneal accurate punishment function method to deal with the restriction conditions, then compiles the algorithm program with MATLAB, selects the maximal yield on the restriction of fixed cost, and analyze the actual application of the algorithm for optimal models for production composition of natural gas development programming with the example. And a better effect has been got.

关键词： advanced genetic algorithm Development programming Powell method Production composition

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Application of genetic algorithm and Annealing genetic algorithm in Short-term Optimal Operation and Economical Operation of Three Gorges Cascade

Application of Genetic Algorithm and Annealing Genetic Algor...

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International Conference on Modern Hydraulic Engineering (CMHE)

作者： Liu Guoshuai Yang Kan Zhou Ran Zheng Jiao Hohai Univ Coll Hydrol & Water Resources Nanjing 210098 Jiangsu Peoples R China

Considering the problems of convergence and prematurity occurred in simple genetic algorithm (SGA), an advanced genetic algorithm was proposed. Parent individuals were replaced by the elitist under certain proportion during the operation of selecting. The advanced genetic algorithm was introduced to solve the problem of optimization operation of Three Gorges cascade. Then advanced genetic algorithm and simulated annealing are combined together to solve the economical operation of The Three Gorges. The simulation results show that the advanced simple genetic algorithm and annealing genetic algorithm has greater converge speed and larger probability of getting the best solution compared to simple genetic algorithm. (C) 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Society for Resources, Environment and Engineering

关键词： Optimal operation economical operation SGA advanced genetic algorithm annealing genetic algorithm

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Multi-objective optimization strategy for distribution network considering V2Genabled electric vehicles in building integrated energy system

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Protection and Control of Modern Power Systems 2020年第1期5卷 48-55页

作者： Zhao Huang Baling Fang Jin Deng Hunan college of information ChangshaChina College of electric and information engineering Hunan university of technologyZhuzhouChina

Based on the large-scale penetration of electric vehicles(EV)into the building cluster,a multi-objective optimal strategy considering the coordinated dispatch of EV is proposed,for improving the safe and economical operation problems of distribution *** system power loss and node voltage excursion can be effectively reduced,by taking measures of time-of-use(TOU)price mechanism bonded with the reactive compensation of energy storage ***,the coordinate charging/discharging load model for EV has been established,to obtain a narrowed gap between load peak and ***,a multi-objective optimization model of the distribution grid is also defined,and the active power loss and node voltage fluctuation are chosen to be the objective *** improving the efficiency of optimization process,an advanced genetic algorithm associated with elite preservation policy is ***,reactive compensation capacity supplied by capacitor banks is dynamically determined according to the varying building *** proposed strategy is demonstrated on the IEEE 33-node test case,and the simulation results show that the power supply pressure can be obviously relieved by introducing the coordinated charging/discharging behavior of EV;in the meantime,via reasonable planning of the compensation capacitor,the remarkably lower active power loss and voltage excursion can be realized,ensuring the safe and economical operation of the distribution system.

关键词： Distribution network Electric vehicles Multi-objective optimization Coordinated dispatch advanced genetic algorithm

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Multi-objective parameter identification and optimization for dislocation-dynamics-based constitutive modeling of Ti-6Al-4V alloy

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JOURNAL OF ALLOYS AND COMPOUNDS 2020年第0期821卷 153460-000页

作者： Wang, Yuntian Zeng, Xiangguo Sheng, Ying Yang, Xin Wang, Fang Sichuan Univ Coll Architecture & Environm MOE Key Lab Deep Earth Sci & Engn Chengdu 610065 Peoples R China Southwest Univ Sci & Technol Sch Civil Engn & Architecture Mianyang 621010 Sichuan Peoples R China Southwest Univ Sch Mat & Energy Chongqing 400715 Peoples R China

Based on the plastic deformation mechanism and dislocation dynamics theory, a constitutive model to describe the mechanical behavior of the Ti-6Al-4V alloy over a wide range of strain rates and temperatures is proposed. The relationships between the constitutive model parameters and microstructural characteristics, as well as their physical significance, were described. The constitutive model contains 12 parameters. A new hybrid approach was developed to obtain the constitutive parameters from the existing experimental data. There were two main parts of the approach. First, to analyze the overall constitutive parameter sensitivity, the Latin hypercube sampling (LHS) and Spearman rank correlation (SRC) methods were applied. The effectiveness and accuracy of the parameter identification and sensitivity analysis results were improved significantly. Second, the parameter optimization was developed using an advanced genetic algorithm including the enhanced niche genetic algorithm, suspicious peak point judgment strategy, and local accuracy searching technology. Finally, the flow stress-plastic strain curve of the Ti-6Al-4V alloy over a wide range of strain rates and temperatures was reproduced through the proposed method. It was shown that the predicted results agreed reasonably well with the existing experimental data. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Ti-6Al-4V alloy Dislocation dynamics Constitutive model Parameter optimization advanced genetic algorithm

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Application of genetic algorithm and Annealing genetic algorithm in Short-term Optimal Operation and Economical Operation of Three Gorges Cascade

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Procedia Engineering 2012年 28卷 81-84页

作者： LIU Guoshuai YANG Kan ZHOU Ran ZHENG Jiao College of Hydrology and Water Resources Hohai University Xikang Road No.1 Nanjing 210098 China

关键词： Optimal operation economical operation SGA advanced genetic algorithm annealing genetic algorithm

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Optimization of system reliability for multi-level RAPs in intuitionistic fuzzy atmosphere using genetic algorithm

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RESULTS IN CONTROL AND OPTIMIZATION 2022年 9卷

作者： Paramanik, Rajesh Mahato, Sanat Kumar Kumar, Nirmal Bhattacharyee, Nabaranjan Gupta, Ranjan Kumar Sidho Kanho Birsha Univ Sainik Sch Dept Math Purulia 723104 India Univ Burdwan Dept Math Purba Barddhaman 713104 India West Bengal State Univ Dept Management North 24 Parganas Berunanpukuria 700126 India

Modular redundancy plays a significant role for designing a reliable system. This study examines the optimization of system reliability in a modular redundancy allocation problem in crisp and intuitionistic fuzzy atmospheres with the goal of maximizing total system reliability while adhering to resource restrictions. On applying modular technique on a redundancy allocation problem, one can increase the fault tolerance to the optimum design of the system, making it very effective in terms of component redundancy. So, modular redundancy should be seen as a proper replacement for the old technique of component level redundancy for improving the reliability, efficiency, and maintainability of a working system. The multi -level redundancy allocation problem is being addressed and solved comprehensively in this study using an advanced genetic algorithm (GA) and a penalty function approach in both crisp and intuitionistic fuzzy settings Finally, numerical examples are solved and sensitivity studies are carried out visually to evaluate the consequences of changing key parameters involved in GA.

关键词： Redundancy allocation problems Intuitionistic fuzzy number Center of area-defuzzification technique advanced genetic algorithm

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