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Optimization and Modeling of a Spatial CAM Mechanism for a Two-Dimensional Plunger Electro-Hydraulic Pump

IEEE ACCESS 2023年 11卷 128354-128368页

作者： Qiu, Xinguo Wang, Fucheng Li, Changlong Yi, Bida Ruan, Jian Jiang, Wei Zhejiang Univ Technol Coll Mech Engn Hangzhou 310023 Peoples R China Zhejiang Univ Technol Key Lab Special Purpose Equipment & Adv Proc Techn Minist Educ & Zhejiang Prov Hangzhou 310023 Peoples R China Zhejiang Univ Technol Key Lab Special Purpose Equipment & Adv Mfg Techno Minist Educ & Zhejiang Prov Hangzhou 310014 Peoples R China

Traditional cam movements in piston pumps follow a non-stopping motion law, resulting in insufficient smoothness in plunger stroke changes. Consequently, this directly impacts the theoretical flow rate of the pump. To address this issue, describes the transition curve of the non-stopping motion law is constructed in this study by using a fivefold B-spline curve. The maximum uncaused velocity and acceleration are considered optimization parameters. multi-objective optimization of the motion law is conducted using a genetic algorithm, resulting in the generation of a Pareto solution set. Compared to the modified equivalent acceleration (MEA) motion law, the B-spline combined motion law leads to a reduction of 1.39% and 0.86% in the maximum velocity and acceleration characteristic values, respectively. Furthermore, by employing the principle of a single-parameter surface envelope, a mathematical model of the cam surface is developed. The obtained data points are then solved using the double-three times B-spline cam surface interpolation algorithm. Subsequently, the interpolation result is translated into a cam surface model file based on the data structure of the IGES *** optimization results demonstrate that compared to equal acceleration and deceleration motion laws, the B-spline optimization curve achieves a seamless transition. Specifically, the maximum pressure angle decreases from 27.98(degrees) to 19.92(degrees), and the minimum radius of curvature decreases from 9.94 mm to 7.44 mm, validating the accuracy of the theoretical analysis. Experimental displacement tests are conducted on the spatial cam mechanism, revealing that the cam design process has been streamlined, and the designed spatial cam exhibits enhanced fitting performance.

关键词： Splines (mathematics) Shafts Pistons Mathematical models Couplers Motion segmentation Hydraulic systems Electrohydraulics genetic algorithms Space CAM mechanism two-dimensional plunger electro-hydraulic pump B-spline curve multi-objective genetic algorithm envelope principle of a single-parameter surface

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multi-objective fuzzy control of smart base isolated spatial structure

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INTERNATIONAL JOURNAL OF STEEL STRUCTURES 2014年第3期14卷 547-556页

作者： Kim, Hyun-Su Kang, Joo-Won Sunmoon Univ Div Architecture Asan South Korea Yeungnam Univ Sch Architecture Gyongsan South Korea

Base isolation systems are used widely to reduce the dynamic responses of structures subjected to a seismic load. Recently, research has been conducted actively on smart base isolation systems that can effectively reduce the dynamic responses of isolated structures without accompanying increases in the base drifts. On the other hand, control performance of smart base isolation systems for spatial structures has not attracted significant attention. This study examined the dynamic response reduction capacity of a smart base isolation system for a spatial structure subjected to seismic excitation. MR dampers and low damping elastomeric bearings were used to compose a smart base isolation system, and its vibration control performance was compared with that of the optimally-designed, lead-rubber bearing (LRB) isolation system. A fuzzy controller was used to effectively control the spatial structure with a smart base isolation system. The dynamic responses of the spatial structure with an isolation system conflicted with the base drift. Therefore, these two responses were selected as the objective functions to apply a multi-objective genetic algorithm to optimize a fuzzy controller. The numerical simulation results showed that the smart base isolation system proposed in this study can reduce drastically the base drifts and seismic responses of the example spatial structure compared to the optimally designed LRB isolation system.

关键词： smart base isolation system spatial structure seismic response reduction fuzzy logic control multi-objective genetic algorithm MR damper lead-rubber bearing

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On multi-objective optimization of geometry of staggered herringbone micromixer

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MICROFLUIDICS AND NANOFLUIDICS 2009年第1期7卷 29-43页

作者： Cortes-Quiroz, Cesar Augusto Zangeneh, Mehrdad Goto, Akira UCL Dept Mech Engn London England Ebara Res Co Ltd Fujisawa Kanagawa Japan

A design methodology for micromixers is presented which systematically integrates computational fluid dynamics (CFD) with an optimization methodology based on the use of design of experiments (DOE), function approximation technique (FA) and multi-objective genetic algorithm (MOGA). The methodology allows the simultaneous investigation of the effect of geometric parameters on the mixing performance of micromixers whose design strategy is based fundamentally on the generation of chaotic advection. The methodology has been applied on a Staggered Herringbone Micromixer (SHM) at several Reynolds numbers. The geometric features of the SHM are optimized and their effects on mixing are evaluated. The degree of mixing and the pressure drop are the performance criteria to define the efficiency of the micromixer for different design requirements.

关键词： Design of experiments multi-objective genetic algorithm multi-objective optimization Response surface Staggered Herringbone Micromixer

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Intelligent workload allocation in IoT-Fog-cloud architecture towards mobile edge computing

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COMPUTER COMMUNICATIONS 2021年 169卷 71-80页

作者： Abbasi, M. Mohammadi-Pasand, E. Khosravi, M. R. Bu Ali Sina Univ Fac Engn Dept Comp Engn Hamadan Hamadan Iran Persian Gulf Univ Dept Comp Engn Bushehr Iran Shiraz Univ Technol Dept Elect & Elect Engn Telecommun Grp Shiraz Iran

Because of the tremendous growth in the number of smart vehicular devices and 5G mobile technologies, the Internet of Things (IoT) has experienced rapid expansion. This has led to a considerable increase in the volume of sensory data produced from, but not limited to, monitoring devices, traffic congestion in cities, safety, and pollution control. Cloud computing can deal with the corresponding workload by providing virtually unlimited computational resources. But, given the importance of the quality of service and security in delay-sensitive requests, other solutions like fog computing have also been introduced to speed up processing and management of sensory data in real scenarios like smart grid and IoT. Processing workloads at the network edge reduces the delay in mobile edge computing, but it highly increases the consuming power. Therefore, there is an urgent need for the improvement of the energy model of fog devices at the network edge. This paper is an attempt to modify this model using the green energy concept and reduce both delay and power consumption in multi-sensorial frameworks in secure IoT systems. In the proposed method, a genetic algorithm (GA) is used for handling a large number of requests and the corresponding quality and security limitations. Simulation results show that the proposed method can simultaneously reduce the delay and the power consumption of edge devices compared to a baseline strategy.

关键词： Internet of Things (IoT) Mobile edge computing (MEC) multi-objective genetic algorithm Workload allocation

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multi-objective demand fulfillment problem for solar cell industry

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COMPUTERS & INDUSTRIAL ENGINEERING 2018年 125卷 688-694页

作者： Zheng, Jia-Nian Chien, Chen -Fu Wu, Jei-Zheng Asia Univ Dept Business Adm 500 Lioufeng Rd Taichung 41354 Taiwan Natl Tsing Hua Univ Dept Ind Engn & Engn Management Hsinchu Taiwan Soochow Univ Dept Business Adm 56 Sect 1Kuei Yang St Taipei 10048 Taiwan

With the growth of green energy market, there are many companies with vertical integration and outsourcing process. Their business models in the solar cell industry cause different influence on the business objectives including revenue, profit, and gross margin. The sales managers are hard to generate fast and reliable ATP (Available-to-promise) which covered all business objectives. Under the various products types with limited quantity, the loading of factory is uncertain and the quantity of order becomes huger. This study formulates multi-objective demand fulfillment problem in solar cell industry and applies a multi-objective genetic algorithm (moGA) to optimize the ATP. The model trade-offs objectives with by Pareto approach without sacrificing other benefits. The multi-population strategy used for stability of solutions. Results of empirical study show that the proposed moGA can improve gross margin while maintaining the desired revenue and profit. With effective solutions and reasonable computing time, the decision support system with proposed moGA has become a regular communication bridge between sales and production departments in the case company.

关键词： Demand fulfillment Solar cell multi-objective genetic algorithm Decision support system

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A Parasitic Layer-Based Reconfigurable Antenna Design by multi-objective Optimization

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2012年第6期60卷 2690-2701页

作者： Yuan, Xiaoyan Li, Zhouyuan Rodrigo, Daniel Mopidevi, Hema Swaroop Kaynar, Oguz Jofre, Lluis Cetiner, Bedri A. Utah State Univ Dept Elect & Comp Engn Logan UT 84322 USA Tech Univ Catalonia Dept Signal Theory & Commun Barcelona 08034 Spain

A parasitic layer-based multifunctional reconfigurable antenna (MRA) design based on multi-objective genetic algorithm optimization used in conjunction with full-wave EM analysis is presented. The MRA is capable of steering its beam into three different directions (theta(i) = -30 degrees, 0 degrees, 30 degrees) simultaneously with polarization reconfigurability (P-j = Linear, Circular) having six different modes of operation. The MRA consists of a driven microstrip-fed patch element and a reconfigurable parasitic layer, and is designed to be compatible with IEEE-802.11 WLAN standards (5-6 GHz range). The parasitic layer is placed on top of the driven patch. The upper surface of the parasitic layer has a grid of 5 x 5 electrically small rectangular-shaped metallic pixels, i.e., reconfigurable parasitic pixel surface. The EM energy from the driven patch element couples to the reconfigurable parasitic pixel surface by mutual coupling. The adjacent pixels are connected/disconnected by means of switching, thereby changing the geometry of pixel surface, which in turn changes the current distribution over the parasitic layer, results in the desired mode of operation in beam direction and polarization. A prototype of the designed MRA has been fabricated on quartz substrate. The results from simulations and measurements agree well indicating 8 dB gain in all modes of operation.

关键词： Beam steering full-wave analysis multi-objective genetic algorithm reconfigurable antenna

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An improved procedure to implement NSGA-III in coordinate waste management for urban agglomeration

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WASTE MANAGEMENT & RESEARCH 2019年第11期37卷 1161-1169页

作者： Qu, Lili Zhou, Zhihao Zhang, Tianzhu Zhang, Huanan Shi, Lei Tsinghua Univ Sch Environm State Key Joint Lab Environm Simulat & Pollut Con Beijing Peoples R China Columbia Univ Dept Earth & Environm Engn New York NY 10027 USA

With the growth of urbanization in countries globally, large cities have often formed clusters of urban agglomerations in metropolitan areas. The coordinated management of regional solid waste produced by such urban agglomeration poses a typical high-dimensional, multi-objective optimization issue. This paper aims to introduce a procedure to implement the third-generation genetic algorithm (NSGA-III), an established multi-objective genetic algorithm based on non-dominated sorting mechanisms, for the purpose of evaluating environmental and economic benefits simultaneously while seeking the optimal solutions for coordinated management among multiple recycling centres. In this study, two series of scenarios were abstracted from scrap tire recycling, representing linear calculation and nonlinear calculation cases separately. Several improvements were made to the originally published NSGA-III procedure that solve the problem of non-convergence for hypervolumes of the output. Through comparisons of calculation results, an improved procedure is suggested and shown to have improved performance.

关键词： Urban agglomeration waste management multi-objective genetic algorithm NSGA-III Jing-Jin-Ji

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An optimization-based design approach for a novel self-adjuster using shear thickening fluid

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STRUCTURAL AND multiDISCIPLINARY OPTIMIZATION 2021年第6期64卷 4161-4179页

作者： Nagy-Gyorgy, P. Bene, J. G. Hos, C. J. Budapest Univ Technol & Econ Dept Hydrodynam Syst Budapest Hungary

Recently, the increasingly strict safety and emission regulations in the automotive industry drove the interest towards automatic length compensating devices, e.g., hydraulic lash adjusters (lower emission) and slack adjuster in brake systems (faster brake response). These devices have two crucial requirements: (a) be stiff during high load, while (b) be flexible in the released state to compensate for environmental effects such as wear and temperature difference. This study aims to use the advantageous properties of shear thickening fluids to develop a less complicated, cost-efficient design. The proposed design is modeled by a system of ordinary differential equations in which the effect of the non-Newtonian fluid flow is taken into account with a novel, simplified, semi-analytical flow rate-pressure drop relationship suitable for handling arbitrary rheology. The adjuster's dimensions are determined with a multi-objective genetic algorithm based on the coupled solid-fluid mechanical model for six different shear thickening rheologies. The accuracy of the simplified flow model is verified by means of steady-state and transient CFD simulations for the optimal candidates. We have found that the dominating parameters of such devices are (a) the shear thickening region of the fluid rheology and (b) the gap sizes, while the piston diameters and the zero viscosity or the critical shear rate of the fluid have less effect. Based on the results, we give guidelines to design similar-length compensating devices.

关键词： multi-objective genetic algorithm Optimal design CFD shear thickening fluid Non-Newtonian fluid Self-adjuster

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multi-objective optimization of a road diet network design

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TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE 2011年第6期45卷 499-511页

作者： Sohn, Keemin Chung Ang Univ Dept Urban Engn Seoul 156756 South Korea

The present study focuses on the development of a model for the optimal design of a road diet plan within a transportation network, and is based on rigorous mathematical models. In most metropolitan areas, there is insufficient road space to dedicate a portion exclusively for cyclists without negatively affecting existing motorists. Thus, it is crucial to find an efficient way to implement a road diet plan that both maximizes the utility for cyclists and minimizes the negative effect on motorists. A network design problem (NDP), which is usually used to find the best option for providing extra road capacity, is adapted here to derive the best solution for limiting road capacity. The resultant NDP for a road diet (NDPRD) takes a bi-level form. The upper-level problem of the NDPRD is established as one of multi-objective optimization. The lower-level problem accommodates user equilibrium (UE) trip assignment with fixed and variable mode-shares. For the fixed mode-share model, the upper-level problem minimizes the total travel time of both cyclists and motorists. For the variable mode-share model, the upper-level problem includes minimization of both the automobile travel share and the average travel time per unit distance for motorists who keep using automobiles after the implementation of a road diet. A multi-objective genetic algorithm (MOGA) is mobilized to solve the proposed problem. The results of a case study, based on a test network, guarantee a robust approximate Pareto optimal front. The possibility that the proposed methodology could be adopted in the design of a road diet plan in a real transportation network is confirmed. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Road diet Network design multi-objective optimization multi-objective genetic algorithm

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Toward green container liner shipping: joint optimization of heterogeneous fleet deployment, speed optimization, and fuel bunkering

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2024年第0期

作者： Zhao, Yuzhe Peng, Zhongxiu Zhou, Jingmiao Notteboom, Theo Ma, Yiji Dalian Maritime Univ Collaborat Innovat Ctr Transport Studies Dalian 116026 Peoples R China Dalian Univ Foreign Languages Business Sch Dalian 116044 Peoples R China Univ Ghent Maritime Inst B-9000 Ghent Belgium Univ Antwerp Fac Business & Econ B-2000 Antwerp Belgium Antwerp Maritime Acad Fac Sci B-2030 Antwerp Belgium

Container liner shipping companies, under the international shipping carbon reduction indicators proposed by the International Maritime Organization, must transform two key aspects: technology and operations. This paper defines a green liner shipping problem (GLSP) that integrates the deployment of a heterogeneous fleet, speed determination, and fuel bunkering. The objective is to achieve low-carbon operations in liner shipping, taking into consideration the diversification of power systems, the use of alternative fuels in ships, and the continuous improvement of alternative fuel bunkering systems. For this purpose, we present a bi-objective mixed integer nonlinear programming model and develop two methodologies: an epsilon-constraint approach and a heuristic-based multi-objective genetic algorithm. We validate the effectiveness of our model and methods through a case study involving container ships of various sizes deployed on intra-Asian short sea routes by SITC International Holdings Co., Ltd. The experimental results highlight the crucial role of dual-fuel (DF) ships in the pursuit of low-carbon strategies by liner companies, with liquefied natural gas and ammonia DF ships being the most widely used. Additionally, fuel cell (FC) ships, particularly those powered by ammonia and hydrogen, demonstrate significant carbon reduction potential. Furthermore, ships with larger container capacities have a greater cost advantage. For the GLSP, speed determination is an auxiliary decision, and the lowest speed is not necessarily the optimal choice. Decision-makers must carefully balance competing economic and carbon emission reduction objectives, as deploying more alternative fuel ships may increase fuel bunkering and fuel consumption, resulting in a higher total operating cost.

关键词： liner shipping heterogeneous fleet deployment speed determination fuel bunkering carbon emission bi-objective mixed integer nonlinear programming multi-objective genetic algorithm

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