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Intelligent parameter optimization of sealed airbag vessels with preventing water hammer in cascaded pressurized water transmission system: Based on mopso algorithm

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JOURNAL OF WATER PROCESS ENGINEERING 2025年 70卷

作者： Li, Ran Gao, Yanqiang Jiang, Baiyi Lv, Mou Li, Hang Qingdao Univ Technol Sch Environm & Municipal Engn Qingdao 266555 Peoples R China Qingdao Municipal Engn Grp Co Ltd Qingdao 266409 Peoples R China Qingdao Huadu Architectural Design Co Ltd Qingdao 266000 Peoples R China

For long-distance water transmission projects utilizing cascade pressurized pump stations in mountainous regions, the configuration and optimization of water hammer protection equipment are indispensable. In practical engineering applications, the setup of water hammer protection equipment is not solely determined by the pipeline's ultimate pressure. Hence, a comprehensive evaluation of safety and cost factors should be conducted, while ensuring that the pipeline's carrying capacity is not exceeded. This paper opts for sealed airbag vessels as the water hammer protection equipment, aiming to optimize water transmission safety and equipment procurement costs. Utilizing the Bentley Hammer v10.08 and MATLAB R2023 software platforms, and incorporating the Latin Hypercube Sampling (LHS) method decomposed by Cholesky, stepwise regression analysis, Multiobjective Particle Swarm Optimization (mopso) algorithm, and fuzzy membership normalization evaluation method, a conceptual analysis module is developed. This module simulates the sampling of the optimization variables within the constraints to obtain a high-quality set of expected samples. A high-precision objective function formulation was derived by fitting the data with higher dispersion. A comprehensive evaluation of several Pareto optimal solutions was performed to identify a high-reliability water hammer protection scheme for the entire pipeline. It indicates that the optimal selection of water hammer protection equipment reduces transient positive pressure head and transient negative pressure head by 37.66 % and 63.74 % respectively, compared to the system without protection equipment. And compared to the equipment purchase cost before optimization, it can save 28.37%. This research will provide theoretical guidance for rational selection of sealed airbag air vessels.

关键词： Cascade pressurized pump stations Sealed airbag vessels LHS method decomposed by Cholesky mopso algorithm

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Multi-optimization of thermodynamic performance of an HT-PEM fuel cell based on mopso algorithm

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ARCHIVES OF THERMODYNAMICS 2024年第3期45卷 197-208页

作者： Wang, Yuting Ma, Zheshu Gu, Yongming Guo, Qilin Nanjing Forestry Univ Coll Automobile & Traff Engn Nanjing 210037 Peoples R China

In this study, an irreversible thermodynamic model for the high temperature proton exchange membrane fuel cell taking electrochemical and heat losses into account is developed. The power density, exergy destruction index, exergy sustainability index and ecological coefficient of performance is derived. The model was validated against experimental data. The influence of parameters on the irreversible thermodynamic performance of high temperature proton exchange membrane fuel cell are considered. The multi-objective particle swarm optimization algorithm is utilized to optimize the power, ecological coefficient of performance and efficiency. The population distribution of the optimization variables was analyzed using a threedimensional Pareto frontier analysis, and results show that the maximum power density, maximum efficiency and maximum ecological coefficient of performance being 6340 W/m 2 , 64.5% and 1.723 respectively, which are 43.28%, 3.7% and 17.8% higher than the preoptimized high temperature proton exchange membrane fuel cell. Moreover, the nondominated sorting genetic algorithm II and simulated annealing algorithm have been chosen versus multi-objective particle swarm optimization algorithm for making the optimization comparative analysis.

关键词： HT-PEMFC Irreversible thermodynamic Exergy Parameter optimization mopso algorithm

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Multi-Objective Placement of Capacitors Banks in Harmonic Contaminated Distribution Network Using mopso algorithm 21

Multi-Objective Placement of Capacitors Banks in Harmonic Co...

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21th Electrical Power Distribution Network Conference (EPDC)

作者： Zeinalzadeh, Arash Khorrami, Navid Islamic Azad Univ Borujerd Branch Young Researchers & Elites Club Borujerd Iran Univ Sci & Technol Faraz Sanat Airia Ctr Mashhad Iran

ISBN: (纸本)9781467390668

Parallel capacitors in distribution systems are usually used for reducing power wastes, improving voltage profile and releasing capacity and increasing in system voltage stability. For obtaining the mentioned objectives, this problem should be solved and defined as a multi-objective optimization issue, the benefits are related to how to install capacitor optimally also in this article network is considered with harmonic load because of harmonic load extensions. Capacitors allocation is a nonlinear problem with equality and inequality constraints;therefore in this article we have used particle mass multi-objective algorithm for solving the capacitor allocation issue. The problem has been implemented for 69 buses with nonlinear loads.

关键词： capaitor allocation harmonic distortion imbalance network mopso algorithm

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A mopso algorithm based on pareto dominance concept for comprehensive analysis of a conventional adsorption desiccant cooling system

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JOURNAL OF BUILDING ENGINEERING 2022年 60卷

作者： Bouchaala, Ahmed Merroun, Ossama Sakim, Anas Hassan II Univ Casablanca Lab Artificial Intelligence & Complex Syst Engn ENSAM Casablanca Casablanca Morocco

Multi-Objective Particle Swarm Optimization (mopso) algorithm based on the concept of Pareto optimality was used to efficiently evaluate the thermal performance of a conventional adsorption ventilated cooling system. A desiccant wheel numerical model was developed and then coupled to a thermodynamic one in order to predict the different states of airflow through the system components. Instead of the dehumidification performances of the desiccant wheel, the present study focused on optimizing simultaneously the COP and the cooling capacity of the system. The process and regeneration air velocity, the rotational speed of the desiccant wheel and the regeneration temperature were considered as the main initial working parameters to generate the particle swarm within the research space. The results showed that the developed mopso algo-rithm is suitable for this kind of complex optimization problem and allowed, with a minimum computational effort, to generate the Pareto front solutions considered as the best compromises between the objective functions. The use of a purge zone during the optimization process im-proves the cycle performance mainly by lowering the regeneration heat and the pre-cooling of the process air. The application of mopso seems to be useful for the cooling system operators, providing them with a wide choice of operating conditions that will meet the predefined cooling requirements with a better COP.

关键词： Desiccant cooling Simulation-optimization model mopso algorithm Pareto front

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Enhancing the performance of a parallel nitrogen expansion liquefaction process (NELP) using the multi-objective particle swarm optimization (mopso) algorithm

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ENERGY 2019年 172卷 286-303页

作者： Mofid, Hossein Jazayeri-Rad, Hooshang Shahbazian, Mehdi Fetanat, Abdolvahhab Petr Univ Technol Dept Instrumentat & Automat Ahvaz 63431 Iran Islamic Azad Univ Behbahan Branch Dept Elect Engn Behbahan Iran

Because of the complex relationship of the characteristics of the liquefied natural gas (LNG) processes, the use of multi-objective optimization algorithms seems rational, for the reason that these methods have the ability to tradeoff between different objectives. The unit energy consumption (UEC);the sizes of the LNG heat exchangers;and the liquefaction rate (LR) are chosen as the objective functions of the mopso algorithm. Optimizations were performed under two separate circumstances: initially, the optimization in the early stages of the plant design was considered;and consequently the optimization in the operational conditions was implemented. A fuzzy-based clustering method is then used to choose the optimum solution from the resulting points of the Pareto fronts derived from the mopso algorithm. The performance of this optimization is compared against the performances of a base case and the optimization performed on the same process using the genetic algorithm (GA). The utilized algorithm improves the objectives values, reduces the exergy destructions in the process and enriches the performance of the LNG heat exchangers. In addition, it is confirmed that the optimization performed at the early stages of the process design yields better results and cost savings. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Liquefaction process LNG heat exchangers Unit energy consumption Multi-objective optimization mopso algorithm

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Multi-objective optimization of a sustainable two echelon vehicle routing problem with simultaneous pickup and delivery in construction projects

JOURNAL OF ENGINEERING RESEARCH

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JOURNAL OF ENGINEERING RESEARCH 2025年第1期13卷 39-46页

作者： Sun, Jie Wang, Ruipu Shanghai Urban Construct Vocat Coll Sch Urban Operat & Management Shanghai 200438 Peoples R China

In many construction projects, the delivery of raw materials from the warehouse to the project place and the return of waste materials from the project place to the warehouse are planned simultaneously. This issue has many complexing assumptions. Accordingly, in this research, the multi-objective two-echelon vehicle routing with simultaneous pickup and delivery is investigated. For this purpose, a multi-objective mathematical model has been developed. Objective functions include economic, environmental and social criteria to achieve sustainability. Moreover, as the problem is known as a hard-NP problem, two meta-heuristic algorithms, NSGA-II and mopso, are proposed to solve this problem. In order to evaluate the performance of the proposed metaheuristic algorithms, 10 test problems of different sizes were generated. The solutions obtained with the proposed algorithms for each of these example problems were evaluated using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method in eight indicators. The achieved numerical results show that the proposed model and the applied algorithms have sufficient efficiency. Moreover, it is revealed that the NSGAII and mopso algorithms have a desirability weight of 0.4321 and0.5679, respectively. Therefore, it can be concluded that the mopso algorithm has higher efficiency for solving the model.

关键词： Two-echelon vehicle routing problem Multi-objective optimization Simultaneous pickup and delivery NSGA-II algorithm mopso algorithm

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Exergoeconomic analysis of an integrated electric power generation system based on biomass energy and Organic Rankine cycle

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AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING 2025年第1期23卷 149-160页

作者： Azish, Ehsan Assareh, Ehsanolah Azizimehr, Behzad Lee, Moonyong Islamic Azad Univ Dept Mech Engn Dezful Branch Dezful Iran Yeungnam Univ Sch Chem Engn Gyongsan South Korea Islamic Azad Univ Dept Mech Engn Tehran West Branch Tehran Iran

The present study investigates the thermodynamics analysis of a trigeneration system using a gasifier system. An Organic Rankine Cycle (ORC) system is used to heat recovery and consequently, supplying the cooling demand. The first and second laws of thermodynamics are used to energy and exergy analysis of the system. Some thermodynamic parameters which affect the system performance including combustion temperature, gasifier temperature, compressor isentropic efficiency, gas turbine isentropic efficiency, compressor pressure ratio, and ORC pressure are parametrically analysed and their contribution in improving the efficiency and economy of the system is investigated. To the sustainable performance of the combined system, we need an evolutionary algorithm to identify the optimum values of thermodynamic parameters that have an impact on system performance. Hence, the Multi-Objective Particle Swarm Optimization (mopso) algorithm is used to find the best values of decision variables. The most striking result to emerge from the *** is that implementing the mopso algorithm improves the exergy efficiency by 5.17% and reduces the total cost of the system by 1.9%.

关键词： Gasifier biomass energy Organic Rankine cycle mopso algorithm exergoeconomic analysis

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Optimization of water hammer protection against sudden pump stoppage using machine learning models and intelligent algorithms

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JOURNAL OF HYDRAULIC RESEARCH 2025年第2期63卷 265-277页

作者： Li, Hongyan Zhang, Yu Cui, Jianguo Zhang, Feng Yang, Xiaoyu Shi, Wentao Mao, Libo Luliang Univ Dept Architecture & Civil Engn Luliang Peoples R China Taiyuan Univ Technol Coll Environm Sci & Technol Jinzhong Peoples R China CNNC 7 Res & Design Inst Co Ltd Inst Architectural Engn Design Taiyuan Peoples R China Shanxi Dadi Environm Investment Holdings Co Ltd Taiyuan Peoples R China

Pump-stoppage-induced water hammer is very harmful, and there is usually a requirement for protective equipment to be installed. In order to guarantee the safety of pipelines while reducing engineering cost, a method was proposed to simulate hydraulic transients by using back propagation neural network (BPNN), random forest (RF) and support vector machine (SVM), while optimizing with the multi-objective particle swarm optimization (mopso) algorithm and making decisions with entropy weight-technique for order preference by similarity to an ideal solution (EW-TOPSIS). The machine learning model was used to fit the mapping associations between protective equipment parameters and optimization objectives. Taking the maximum and minimum water hammer pressure and costs as the objective functions, a multi-objective optimization model was constructed to determine the effective linkage between the hydraulic transient and the intelligent optimization algorithm, and a scheme with comprehensive benefits was obtained through optimization and decision-making. The case study showed that the proposed scheme can greatly improve the protection effect and reduce costs.

关键词： Machine learning method of characteristics (MOC) mopso algorithm water hammer water transmission pipeline

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Research on quarter wave shape control of cold rolled high strength steel based on BP-mopso

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2022年第9-10期122卷 3867-3880页

作者： Yuan, Tieheng Sun, Wenquan He, Anrui Chen, Luzhen Liu, Chao Yong, Shengyi Univ Sci & Technol Beijing Natl Engn Res Ctr Adv Rolling & Intelligent Mfg 30 Xueyuan Rd Beijing 100083 Peoples R China

The problem of quarter waves is more fundamental in the production of cold rolled high strength steel, which harms the quality of the strip shape. To reasonably and maximally exploit the quarter wave shape control capability of the cold rolling six-roller UCM mill, this paper establishes a BP-mopso-based shape optimization model for the 65MN strip produced by the 1720 UCM mill and makes a decision selection from the Pareto frontier according to the finished cold rolled strip shape requirements. To verify the validity of the model, an integrated static implicit model of the roll mill based on the initial mechanical properties and section profile is established based on ABAQUS software. The simulation results show that the appropriate increase in roll bending force can effectively reduce the regional depression at the quarter position of the strip, and the optimal bending force setting value found by the BP-mopso model can improve the strip shape to the maximum extent. The application shows that the optimized bending force setting value decreases the average shape high point from 16 to 8 IU in actual production, which can reduce the generation of quarter wave shapes of high-strength steel to a certain extent and improve the accuracy level of shape control in UCM mills.

关键词： BP neural network mopso algorithm Cold rolling bending force ABAQUS finite element Quarter wave

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Multi-objective control chart design optimization using NSGA-III and mopso enhanced with DEA and TOPSIS

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EXPERT SYSTEMS WITH APPLICATIONS 2016年 50卷 17-39页

作者： Tavana, Madjid Li, Zhaojun Mobin, Mohammadsadegh Komaki, Mohammad Teymourian, Ehsan La Salle Univ Distinguished Chair Business Analyt Business Syst & Analyt Dept Philadelphia PA 19141 USA Univ Paderborn Business Informat Syst Dept Fac Business Adm & Econ Warburger Str 100 D-33098 Paderborn Germany Western New England Univ Ind Engn & Engn Management Dept Springfield MA 01119 USA Case Western Reserve Univ Dept Elect Engn & Comp Sci Cleveland OH 44106 USA Oregon State Univ Sch Mech Ind & Mfg Engn Corvallis OR 97331 USA

X-bar control charts are widely used to monitor and control business and manufacturing processes. This study considers an X-bar control chart design problem with multiple and often conflicting objectives, including the expected time the process remains in statistical control status, the type-I error, and the detection power. An integrated multi-objective algorithm is proposed for optimizing economical control chart design. We applied multi-objective optimization methods founded on the reference-points-based non-dominated sorting genetic algorithm-II (NSGA-III) and a multi-objective particle swarm optimization (mopso) algorithm to efficiently solve the optimization problem. Then, two different multiple criteria decision making (MCDM) methods, including data envelopment analysis (DEA) and the technique for order of preference by similarity to ideal solution (TOPSIS), are used to reduce the number of Pareto optimal solutions to a manageable size. Four DEA methods compare the optimal solutions based on relative efficiency, and then the TOPSIS method ranks the efficient optimal solutions. Several metrics are used to compare the performance of the NSGA-III and mopso algorithms. In addition, the DEA and TOPSIS methods are used to compare the performance of NSGA-III and mopso. A well-known case study is formulated and solved to demonstrate the applicability and exhibit the efficacy of the proposed optimization algorithm. In addition, several numerical examples are developed to compare the NSGA-III and mopso algorithms. Results show that NSGA-III performs better in generating efficient optimal solutions. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Economical control chart design NSGA-III algorithm mopso algorithm Data envelopment analysis TOPSIS

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