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Seismic retrofit of MRF buildings using decentralized semi-active control for multi-target performances

EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS 2017年第3期46卷 409-424页

作者： Cha, Young-Jin Agrawal, Anil K. Univ Manitoba Dept Civil Engn Winnipeg MB R3T 5V6 Canada CUNY City Coll Dept Civil Engn New York NY 10034 USA

Numerous structures have been designed and built without taking earthquake ground motions or outdated seismic design codes into account. In order to improve the seismic performance of existing structures, many retrofit approaches based on performance-based design have been developed. However, some of these approaches are inapplicable due to structural limitations or because they were developed with the assumption of single-degree-of-freedom, which does not take higher modes into account. To overcome the limitations of these traditional methods, a multi-performance-based control design (MPBCD) methodology has been proposed by integrating a decentralized semi-active control algorithm, magnetorheological dampers, and an advanced multi-objective optimization method to provide various sets of retrofit control designs to satisfy multiple target performances under multiple seismic intensities without changing structural cross-section sizes or material properties. This MPBCD method provides engineers with numerous sets of control designs (i.e., control device layouts with control design parameters) to help them select proper control designs to retrofit existing building structures and improve seismic performance. Copyright (C) 2016 John Wiley & Sons, Ltd.

关键词： multi-target performances semi-active control magnetorheological damper multi-objective genetic algorithm nonlinear model nonlinear time-history analysis

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Thermo-economic optimization of gasification process with coal water slurry preheating technology

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ENERGY 2020年 199卷

作者： Xiao, Juan Wang, Simin Ye, Shupei Dong, Jiayu Wen, Jian Zhang, Zaoxiao Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

The energy efficiency of coal water slurry (CWS) gasification is less than that of pulverized coal gasification, a preheating technology using shell-and-tube heat exchangers (STHXs) with ladder-type fold baffles is introduced to improve energy efficiency of CWS gasification. The effect of structural parameters (folding angle, folding ratio and relative height) on cold gas efficiency and total cost is discussed coupling system design and unit equipment optimization, and multi-objective genetic algorithm combining response surface method is used to accomplish thermo-economic optimization. The results show that oxygen consumption decreases by 7.6% and cold gas efficiency increases by 6.5% than that without preheating technology. The local sensitivity illustrates that folding angle and folding ratio has a negative effect on cold gas efficiency and total cost, while relative height positively relates to cold gas efficiency and total cost. Moreover, structural parameters are regarded as optimization variables, maximizing cold gas efficiency and minimizing total cost are optimization functions. The optimization results indicate that the saving cost is the highest when folding angle, folding ratio and relative height are 30 degrees, 0.6 and 0.562, respectively. And a Pareto with multi-group of structural parameters obtained provides for design selections of CWS preheaters. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Thermo-economic optimization Coal water slurry Heat exchangers Gasification Preheating technology multi-objective genetic algorithm

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multi-objective optimization of a dual mass flywheel with centrifugal pendulum vibration absorbers in a single-shaft parallel hybrid electric vehicle powertrain for torsional vibration reduction

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2022年 163卷

作者： Lee, Hyung Joon Shim, Jae Kyung Korea Univ Dept Automot Convergence Engn Seoul 02841 South Korea Korea Univ Sch Mech Engn Seoul 02841 South Korea

This research deals with an optimization of a dual mass flywheel (DMF) with centrifugal pendulum vibration absorbers (CPVAs) used in a single-shaft parallel hybrid electric vehicle (HEV) powertrain for the reduction of the torsional vibration at the rotor of the electric motor and the total moment of inertia of the DMF and CPVAs. Unlike the previous studies, this research considers the overall behavior of an entire powertrain with an in-line four-cylinder engine and a five-speed automatic transmission for the optimization of the DMF with CPVAs. For this purpose, the multibody dynamics model of the HEV powertrain is constructed and used to analyze the transient response of the system for a given gas pressure map and acceleration condition of the vehicle. Then, a multi-objective genetic algorithm is applied to determine the Pareto optimal front that yields the design parameter values of the DMF and CPVAs effective in the torsional vibration reduction and inertia minimization. The result of the optimization is compared with the HEV powertrain system with a flywheel only, and shows that the vibrations transmitted to the motor are significantly reduced in all the solutions of the Pareto front. By using the method proposed in this research, various parameter combinations of the DMF and CPVAs can be considered in the early design process.

关键词： Dual mass flywheel (DMF) Single-shaft parallel hybrid electric vehicle (HEV) powertrain multibody dynamics Transient analysis multi-objective genetic algorithm Centrifugal pendulum vibration absorber (CPVA)

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Application of smart system to textile industry: Preliminary design of a smart hanger for garment inspection

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JOURNAL OF THE TEXTILE INSTITUTE 2008年第6期99卷 569-580页

作者： Yuen, C. W. M. Fung, E. H. K. Wong, W. K. Hau, L. C. Chan, L. K. Hong Kong Polytech Univ Dept Mech Engn Kowloon Hong Kong Peoples R China Hong Kong Polytech Univ Inst Text & Clothing Kowloon Hong Kong Peoples R China

A smart inspection system, comprising three components, namely a smart hanger, a stitching-workmanship defect classification unit as well as a shade variation detection unit, is introduced for the textile industry. The preliminary design and optimization results of the smart hanger which stretches garments to provide enough tension to facilitate the inspection are presented. The hanger, with a Proportional and Derivative (PD) controller, is modeled as a four-link robot consisting of three revolute joints and one prismatic joint. The design objectives include (1) maximizing the link portions within effective regions at the final state, (2) minimizing the force or torque required to finish the stretching process, and (3) minimizing the settling time of the stretching process. In addition to control gains, the lengths of the four links as well as the desired movements of the joints are taken as design variables. The required transient behavior of the hanger is defined by the constraints on settling time and maximum overshoot. In order to prevent the clothes from being damaged by the links during the stretching process, geometrical constraints are imposed on the motions of the links. Optimization results, obtained by using the multi-objective genetic algorithm (MOGA), are presented in the form of Pareto solutions. After analysis, optimal parameters are selected and computer simulations are performed to investigate the transient behavior of the hanger. Satisfactory results are obtained, which provide a good foundation for the on going development of the smart inspection system.

关键词： Smart hanger design optimization multi-objective genetic algorithm garment inspection textile industry

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Analysis of the effect of roughness and concentration of Fe₃O₄/water nanofluid on the boiling heat transfer using the artificial neural network: An experimental and numerical study

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2021年 163卷

作者： Peng, Yeping Ghahnaviyeh, Milad Boroumand Ahmad, Mohammad Nazir Abdollahi, Ali Bagherzadeh, Seyed Amin Azimy, Hamidreza Mosavi, Amirhosein Karimipour, Aliakbar Shenzhen Univ Coll Mech & Control Engn Guangdong Key Lab Electromagnet Control & Intelli Shenzhen 518060 Peoples R China Islamic Azad Univ Najafabad Branch Dept Mech Engn Najafabad Iran Univ Kebangsaan Malaysia Inst IR 4 0 Bangi 43600 Selangor Malaysia Ton Duc Thang Univ Environm Qual Atmospher Sci & Climate Change Res Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Environm & Labour Safety Ho Chi Minh City Vietnam Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam

Since experimental studies in the field of nanofluid pool boiling requires costly and time-consuming tests, numerical methods such as artificial neural networks with higher predictability and nonlinear features are suitable for prediction and modeling of problem parameters. In this paper, 180 pool boiling laboratory data of Fe3O4/water nanofluid are employed as datasets used for network training to determine the effect of different parameters of nanofluid pool boiling on Boiling Heat Transfer Coefficient (BHTC) and wall superheat. The concerned input parameters for the neural network include concentration, roughness, and heat flux, while the network outputs are the BHTC and wall superheat. Finally, it becomes clear that the trainbr training algorithm with the optimal quantity of 41 neurons within the hidden layer shows the best performance. In addition, the present model can accurately predict the BHTC and wall superheat with correlation coefficients (R) of 0.99936 and 0.9986 and the mean square error (mse) of 0.103 and 0.013, respectively. Also, given the optimization objectives considered in this research, including maximizing the heat transfer coefficient and minimizing the wall superheat in the nanofluid pool boiling process, the multi-objective genetic algorithm has been used to optimize the two objective functions concerned.

关键词： Artificial neural network multi-objective genetic algorithm Pool boiling Fe3O4/Water nanofluid BHTC Surface roughness

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Experimental investigation on the optimal control of vortex shedding of a circular cylinder with rotating rods at moderate Reynolds numbers

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JOURNAL OF FLUIDS AND STRUCTURES 2024年 124卷

作者： Silva, Paulo H. N. Assi, Gustavo R. S. Univ Sao Paulo Dept Naval Architecture & Ocean Engn Escola Politecn Sao Paulo Brazil

This paper presents an experimental study of fluid-structure interaction conducted at Reynolds numbers around 104 with scale models in a water channel. A circular cylinder was equipped with eight control rods positioned around its perimeter to interact with the external flow. Each rod could be driven independently to rotate about its axis. The controlled rotation of the rods interfered with the vortex generation mechanism mitigating the formation of a coherent wake. The results showed that it is possible to simultaneously reduce the mean drag and fluctuating lift forces when the rods rotate at a uniform speed or with each rod set at a different rate. A multi-objective genetic algorithm was employed to find the optimum rotation speeds. The optimum rotation produced a more significant reduction in both objectives and also consumed less energy. The contribution of each rod depends significantly on its angular position around the body and the flow conditions resulting from the upstream control rods. The present work clarifies the physical principles of the phenomenon and paves the way for the development of technological applications.

关键词： Bluff body Flow control Vortex shedding Control rods multi-objective genetic algorithm

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multi-objective optimization of the refrigerant-direct convective-radiant cooling system considering the thermal and economic performances

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ENERGY AND BUILDINGS 2022年 254卷

作者： Jiang, Tingting You, Shijun Wu, Zhangxiang Zhang, Huan Wang, Yaran Wei, Shen Tianjin Univ Sch Environm Sci & Engn Tianjin 300350 Peoples R China Tianjin Univ Minist Educ China Key Lab Efficient Utilizat Low & Medium Grade Ene Tianjin 300350 Peoples R China Univ Coll London UCL Bartlett Sch Sustainable Construct 1-19 Torrington Pl London WC1E 7HB England

The refrigerant-direct convective-radiant cooling (RCC) system is attracting widespread concern due to its advantages of good thermal comfort, high energy efficiency and simple structure. However, researches on thermal and economic optimization of this system are rare. In this study, a novel heuristic approach is proposed to optimize the aluminum column-wing type refrigerant-direct convective-radiant cooling (ACT-RCC) system, which adopts artificial neural network (ANN) integrated with multi-objective genetic algorithm (MOGA). The numerical and economic models of the ACT-RCC terminal are developed and the numerical model is validated by the experimental data. Besides, the ANN model is adopted to accelerate the prediction of the thermal and economic performances of this system. Results show that the training values of the ANN model are fitted well with simulated results and the ANN model can greatly improve the runtime in comparison with original numerical and economic models. Based on the heuristic optimization approach, the optimal structure of the ACT-RCC terminal is the copper pipe diameter with 8.7 mm, the copper pipe spacing with 25.5 mm and the rib height with 30.3 mm. Compared with the original structure, the cooling capacity of the improved ACT-RCC system is enhanced by 16.0% and the initial cost is reduced by 10.0%. The appearance area equals to the direct product of the length and width, and results show that the appearance area of the improved ACT-RCC terminal is decreased from 1.04 m(2) to 0.78 m(2). Therefore, the proposed heuristic approach provides guidance for improving the thermal and economic performances of the RCC systems. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Refrigerant-direct convective-radiant cooling system Thermal and economic optimization Artificial neural network multi-objective genetic algorithm

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Optimal Design of Intermittent Water Distribution Network Considering Network Resilience and Equity in Water Supply

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WATER 2023年第18期15卷

作者： Ramani, Katineni Rudraswamy, G. K. Umamahesh, Nanduri V. Natl Inst Technol Warangal Dept Civil Engn Hanamkonda 506004 Telangana India

In urban areas of developing countries, due to industrialization and population growth, water demand has been increasing significantly, thereby increasing stress on the existing water distribution systems (WDSs). Under these circumstances, maintaining equity in the allocation of water becomes a significant challenge. When building an intermittent water distribution system, it is important to provide a minimum level of supply that is acceptable as well as water supply equity. A non-dominated sorting genetic algorithm (NSGA-II) is employed for the optimal design of an intermittent water distribution network (WDN). Network resilience is taken as a measure of reliability (In), while the uniformity coefficient (CU) is taken as a measure of equity in the water supply. Maximizing network resilience, uniformity coefficient, and minimization of cost of the network are considered as the objectives in the multi-objective optimization model. Pressure-driven analysis (PDA) is used for the hydraulic simulation of the network. The NSGA-II model is applied and demonstrated over two water distribution networks taken from the literature. The results indicate that reliability and equity in WDNs can be accomplished to a reasonable extent with minimal cost.

关键词： water distribution networks intermittent supply uniformity coefficient network resilience reliability pressure driven analysis multi-objective genetic algorithm

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BI-CRITERIA SCHEDULING ON A BATCHING MACHINE WITH NON-IDENTICAL JOB SIZES

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IFAC Proceedings Volumes 2006年第3期39卷 727-732页

作者： Ali Husseinzadeh Kashan Behrooz Karimi Fariborz Jolai Department of Industrial Engineering Amirkabir University of Technology P.O.Box: 15875-4413 Tehran Iran Department of Industrial Engineering Faculty of Engineering University of Tehran P.O.Box: 11365-4563 Tehran Iran

This paper addresses scheduling jobs with non-identical sizes on a single batch-processing machine. Two different multi-objective genetic algorithms (MOGA) have been proposed. The first one is a sequence based MOGA (SMOGA) that generates random sequences of jobs and applies the batch first fit heuristic to group the jobs. The second one is a batch based hybrid MOGA (BHMOGA) that generates random batches of jobs and ensures feasibility through using knowledge of the problem. Computational results show that non-dominated solutions obtained by BHMOGA are superior in closeness to the true Pareto-optimal solutions and to keep diversity in the obtained Pareto-set, as the problem size increases.

关键词： Scheduling Batch processing machine multi-objective genetic algorithm Makespan Maximum tardiness

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Proportional integral controller gain tuning using real time digital simulation models and multi-objective optimization based co-simulation

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IFAC-PapersOnLine 2015年第30期48卷 473-478页

作者： Kumaraguru Prabakar Fangxing Li The University of Tennessee Knoxville

Proportional integral (PI) controller is a widely used controller strategy. It has two gain constants: proportional(k p ) and integral(k i ) gain constant. The dynamics of the PI controller depends on the values of the gain constant used. If gains of these control terms are not selected properly, instability will occur. Gain tuning methodologies are available to tune these controllers to avoid instability. But, these gain tuning strategies and algorithms utilize simplified mathematical model of the plant in order to obtain gain values. This approach might not provide optimal gain values for models used in real time digital simulator. In the proposed approach, the algorithm utilizes the step response of the system to obtain optimal gain constants. The plant is modeled using the real time digital simulator (RTDS). A multi-objective optimization formulation is used to find the optimal gain constants. Results are presented here to support the effectiveness of proposed multi-objective gain tuning strategy.

关键词： Proportional integral control Gain tuning multi-objective optimization multi-objective genetic algorithm

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