检索结果-内蒙古大学图书馆

multi-objective optimization of electro-pneumatic braking process with fuzzy logic control for heavy haul railway applications

引用

INTERNATIONAL JOURNAL OF RAIL TRANSPORTATION 2025年第2期13卷 332-351页

作者： Eckert, Jony Javorski Teodoro, Icaro Pavani Lopes, Matheus Valente Wu, Qing Santos, Auteliano A. Univ Estadual Campinas Sch Mech Engn Integrated Syst Dept UNICAMP Mendeleyev St 200 BR-13083860 Campinas SP Brazil Cent Queensland Univ Ctr Railway Engn Rockhampton Australia

This paper presents a novel approach to multi-objective optimization in heavy haul trains' electro-pneumatic braking systems using optimizable fuzzy control. Initial findings indicate that a straightforward replacement of pneumatically controlled valves with electro-pneumatic ones, without significant control schedule modifications, fails to substantially improve the dynamics behaviour of rolling-stock. Consequently, a more sophisticated strategy based on optimizable fuzzy logic control for the electro-pneumatic valves was developed. This approach utilizes multi-objective optimization to simultaneously minimize energy dissipation during braking and reduce force peaks in freight car draft gears. The optimal solution achieved demonstrates a 13.41% reduction in kinetic energy dissipation during downhill sections, along with a concurrent decrease in draft gear peak forces by 14.22% in traction and 3.16% in buff regimes compared to standard rolling-stock with pneumatically controlled valves. This optimized fuzzy braking controller outperforms standard procedures, highlighting its potential to enhance heavy haul train efficiency while adhering to safety standards.

关键词： Air brake freight railway train dynamics fuzzy logic control multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization of ventilation in pharmaceutical cleanrooms based on response surface methodology and AHP-entropy weight method

引用

ENERGY AND BUILDINGS 2025年 329卷

作者： Wu, Zhaofan Li, Yongcun Hunan Univ Sci & Technol Sch Civil Engn Xiangtan 411201 Peoples R China

optimization of ventilation is essential for achieving efficient production in pharmaceutical cleanrooms. Workspace satisfaction, energy utilization coefficient, and clean ventilation index are three important performance indicators for evaluating cleanroom ventilation, and they are influenced by the interaction among multiple factors. This paper adopts the response surface methodology to investigate the effects of Air changes per hour (ACH), air supply outlet size and air supply outlet distribution ratio on ventilation performance. An evaluation system is established using the AHP-entropy weight method and a comprehensive score is obtained to predict optimal ventilation performance. The results show that increasing ACH significantly optimizes workspace satisfaction, the air supply outlet distribution ratio has a significant impact on the energy utilization coefficient, and the ACH and the air supply outlet distribution ratio have a positive interaction effect on the clean ventilation index. Furthermore, the energy-saving optimal solution is determined to be an ACH of 26 h- 1 , an air supply outlet size of 608 mm, and an air supply outlet distribution ratio of 0.3732. The comprehensive score of the energy-saving optimal solution is 87.9734, which is only 2.9 % lower than the global optimal solution but achieves a 10 % saving in ACH. This study provides a novel perspective and practical guidance for ventilation optimization in pharmaceutical cleanrooms.

关键词： Pharmaceutical cleanrooms Ventilation multi-objective optimization Response surface methodology AHP-entropy weight method

来源：评论

学校读者我要写书评

暂无评论

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

JOURNAL OF ENGINEERING RESEARCH

引用

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

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization of hybrid energy systems using gravitational search algorithm

引用

SCIENTIFIC REPORTS 2025年第1期15卷 1-20页

作者： Mahmoudi, Sayyed Mostafa Maleki, Akbar Ochbelagh, Dariush Rezaei Amirkabir Univ Technol Tehran Polytech Dept Energy Engn & Phys Tehran Iran Shahrood Univ Technol Fac Mech Engn Shahrood Iran

The depletion of fossil fuel reserves, increasing environmental concerns, and energy demands of remote communities have increased the acceptance of using hybrid renewable energy systems (HRES). However, choosing an optimal HRES from economic, environmental, reliability, and sustainability aspects is still challenging. To solve this challenge, this study introduces a novel multi-objective optimization approach using the Gravitational Search Algorithm (GSA) and non-dominated sorting techniques. The proposed framework addresses four objectives: minimizing the loss of power supply probability, reducing total costs, increasing renewable energy fraction, and lowering CO2 emissions. A carbon tax sensitivity analysis evaluates the system's economic performance under varying scenarios. Also, the amount of damage caused by the release of carbon dioxide on human health and the ecosystem is examined. In this way, an optimal configuration consisting of wind turbines, photovoltaic panels, and diesel generators is introduced to satisfy the above objectives. Results demonstrate that the GSA outperforms established methods, such as multi-objective particle swarm optimization and non-dominated sorting genetic algorithm II in Pareto front diversity and convergence. In this work, the optimal system achieves an 18.4% increase in renewable energy share, reducing ecosystem and human health damage by 14.2%. Notably, with a 20% increase in the carbon tax, system costs increased by 3%. These findings underscore the potential of multi-objective optimization combined with carbon tax policies to enhance energy system sustainability and affordability.

关键词： Hybrid renewable energy system multi-objective optimization Gravitational search algorithm Sustainable energy Carbon tax

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization and Performance Analysis of a Hybrid Thermal Photovoltaic and Membrane-based Reverse Osmosis Desalination System for Efficient Renewable-powered Water Production in Arid Regions

引用

WATER CONSERVATION SCIENCE AND ENGINEERING 2025年第1期10卷 1-16页

作者： Babaelahi, Mojtaba Shadin, Alireza Univ Qom Dept Mech Engn Qom Iran

This study investigates an integrated photovoltaic-thermal (PV/T) and reverse osmosis (RO) desalination system designed to address water scarcity in arid regions, with a focus on Iran. The research aims to optimize freshwater production and energy efficiency through the integration of solar energy harvesting with desalination technology. A comprehensive numerical model was developed using the COMSOL multiphysics, which incorporates heat transfer, fluid flow, and mass transport phenomena. The Nelder-Mead optimization algorithm was utilized to maximize system performance. Key operating parameters, such as inlet water temperature, solar irradiance, and flow rates, were analyzed to assess their impact on efficiency. The optimized system achieved a 33.33% improvement in overall efficiency (from 45 to 60%) and a 40% increase in freshwater production (from 50 to 70 L/day). An optimal feed water temperature of 46 degrees C was identified for the desalination unit, which balances thermal gain and efficiency. The study revealed that PV/T panel efficiency decreases by 0.55% for every 1 degrees C increase above 64.3 degrees C, emphasizing the importance of temperature control in system design and operation.

关键词： Thermal photovoltaic Reverse osmosis Desalination Numerical modeling multi-objective optimization Renewable-powered water production

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization of railway construction under carbon trading mechanism based on improved NSGA-II algorithm

ENGINEERING RESEARCH EXPRESS

引用

ENGINEERING RESEARCH EXPRESS 2025年第2期7卷

作者： Xu, Xizhen Liu, Yuming Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China

Railway engineering projects exhibit complex internal structures and extensive external interconnections, making it difficult to establish definitive control objectives for duration and cost during construction. With the increasing severity of environmental pollution and energy consumption, carbon emissions have gradually become a critical factor that cannot be ignored in the construction process. This study proposes a multi-objective optimization method for construction based on cost-duration-carbon emissions under the carbon trading mechanism, employing an improved NSGA-II algorithm to solve the multi-objective optimization model and deriving the optimal construction solution based on projection characteristic values. An empirical study of a railway engineering project demonstrates the following results: (1) Compared to the baseline solution, the optimized construction solution achieves reductions of 1.87 million yuan in cost, 3 days in duration, and 137 tons in carbon emissions, with all optimization results being statistically significant;(2) Quantitative analysis using spacing metrics and one-sample t-tests confirms that the improved NSGA-II algorithm exhibits high solution stability and solution set uniformity in solving construction multi-objective optimization problems, along with good scalability;(3) The optimal projection vector [Duration, Cost, Carbon Emission] = [0.0120, 0.9821, 0.9958] indicates that carbon emissions are the most critical factor influencing the selection of the optimal construction solution. This study provides theoretical foundations and technical support for multi-objective optimization in railway engineering construction, offering significant value for promoting green and sustainable development in the industry.

关键词： engineering construction multi-objective optimization carbon trading mechanism NSGA-II algorithm

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization of laser spot welding parameters for enhancing mechanical properties of hard disk components using response surface methodology

引用

RESULTS IN ENGINEERING 2025年 25卷

作者： Chimklin, K. Phuangkaew, S. Deeying, J. King Mongkuts Univ Technol North Bangkok Fac Tech Educ Dept Teacher Training Mech Engn Bangkok 10800 Thailand Rajamangala Univ Technol Krungthep Fac Tech Educ Dept Ind Engn Bangkok 10120 Thailand King Mongkuts Univ Technol North Bangkok Sci & Technol Res Inst Logist & Supply Chain Management Res Ctr Bangkok 10800 Thailand

This study investigates the optimization of laser welding parameters for stainless-steel components using response surface methodology. The aim is to achieve robust joints and sufficient contact between components by employing a laser spot preheating technique followed by subsequent laser spot application for joining. The parameters considered include outer diameter (OD), inner diameter (ID), penetration, and tip height. Through a central composite design matrix experiment and quadratic modeling, empirical mathematical models were established to predict the response variables. The study reveals significant relationships between power flash ramps, time flash ramps, and N2 flow rate, particularly influencing tip height and ID. multi-objective optimization using a desirability function was employed to determine the optimal process parameters. The optimal process parameters were determined to be power flash ramp 1 at 2.15 kW, time flash ramp 1 at 0.5 ms, power flash ramp 2 at 2.83 kW, time flash ramp 2 at 1.2 ms and N2 flow rate at 18l/min Finally, empirical model validation was performed, resulting in slight differences between the predicted and actual values of OD, ID, penetration and tip height which were 6.614.00%, 4.60%, 8.398% and 15.42% respectively. The validation test results indicated that the proposed models showed good agreement between the actual values and the predicted values from the optimization.

关键词： multi-objective optimization Response surface methodology Laser spot welding Preheating technique Melt pool

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization for Data Collection in UAV-Assisted Agricultural IoT

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第4期74卷 6488-6503页

作者： Liu, Lingling Wang, Aimin Sun, Geng Li, Jiahui Pan, Hongyang Quek, Tony Q. S. Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Singapore Univ Technol & Design Informat Syst Technol & Design ISTD Pillar Singapore 487372 Singapore Hainan Univ Sch Informat & Commun Engn Haikou 570228 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engn Minist Educ Changchun 130012 Peoples R China Nanyang Technol Univ Data Sci Singapore 639798 Singapore Singapore Univ Technol & Design Pillar Engn Syst & Design ESD Singapore 487372 Singapore Dalian Maritime Univ Informat Sci & Technol Coll Dalian 116026 Peoples R China Singapore Univ Technol & Design Singapore 487372 Singapore

To enhance the observation and management of agricultural plants, it is critical to collect data from Internet of Things (IoT) devices in agriculture. However, the use of fixed ground-based stations (BSs) often results in inflexible deployment, high overhead costs, and increased vulnerability to damage from natural disasters, which can impede continuous data collection. To address these challenges, this work explores the use of Unmanned Aerial Vehicles (UAVs) as aerial BSs to gather data from IoT devices. First, we formulate a UAV-assisted data collection multi-objective optimization problem (UDCMOP) to efficiently collect agricultural data. Specifically, we aim to collaboratively optimize the hovering positions of UAV, visit sequence of UAV, speed of UAV, and the transmit power of devices, to simultaneously maximize the minimum transmit rate of devices, minimize the total energy consumption of devices and UAV. Second, the proposed UDCMOP is characterized as a non-convex mixed integer nonlinear optimization problem, containing both continuous and discrete variables, which presents considerable challenges in terms of solvability. Therefore, we solve it by proposing an improved multi-objective artificial hummingbird algorithm (IMOAHA) with several specific improvement factors, including the hybrid initialization operator, Cauchy mutation foraging operator, and the discrete mutation operator. Simulations are carried out to testify that the proposed IMOAHA can effectively improve the system performance in comparison to existing benchmarks. Additionally, to verify the effective working time of the UAV system, we investigate both random and uniform UAV deployment strategies and consider the impact of varying farm topology on the system model. Finally, practical implementation experiments using a Raspberry Pi confirm the feasibility and effectiveness of the proposed UAV-assisted communication system in real-world environment.

关键词： Autonomous aerial vehicles Internet of Things Data collection Sensors Wireless sensor networks Agriculture optimization Wireless communication Energy consumption Transportation UAV agricultural Internet of Things data collection multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization of a cascaded supercritical CO2 brayton cycle with ejector-enhanced transcritical CO2 and flash tank absorption refrigeration cycles

引用

ENERGY CONVERSION AND MANAGEMENT-X 2025年 26卷

作者： Khan, Tausif Elahi Sakib, Sakibul Haque Sakib, Nazmus Hossain, Tanvir Ehsan, M. Monjurul Khan, Yasin Islamic Univ Technol IUT Dept Mech & Prod Engn MPE Gazipur 1704 Bangladesh

The research introduces a novel system that combines power generation and cooling system by integrating an ejector-assisted transcritical CO2 refrigeration (ETCR) subsystem and a flash tank installed compression absorption refrigeration (FCAR) subsystem, cascaded with a supercritical CO2 recompression Brayton cycle. The FCAR subsystem contributes additional cooling capacity, while the ETCR subsystem enhances the chiller load by minimizing waste heat from the cooler. These added loads significantly enhance the system's overall power output, leading to higher thermal and exergy efficiencies. The thermal performance of the integrated system is evaluated through extensive parametric analyses implemented in Python, considering variables such as turbine and compressor inlet temperatures, minimum pressure, pressure ratio, evaporator temperature, and the generator's hot and cold-end pinch temperatures. multi-objective optimization (MOO) is used to identify the ideal operational parameters for maximizing thermal and exergy efficiencies. For MOO and multi-Criteria Decision Making (MCDM), the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and TOPSIS methods are used, respectively. The optimization results indicate that the system achieves peak performance when the compressor entry temperature is set at 33.03 degrees C, and the pressure ratio is 3.52. Under these optimal conditions, the system attains thermal and exergy efficiencies of 61.8 % and 65.76 %, respectively. With a 100 MW input power, the system delivers a net output of 40.52 MW, along with a chiller load of 10.96 MW and a cooling load of 10.32 MW, leading to 16.14 % greater thermal efficiency and 4.4 % improved exergy efficiency over a conventional system. Additionally, exergy analysis identified a total exergy destruction of 26 MW, with significant losses observed in the reactor and R41 evaporator (10.24 % and 5.48 %, respectively). Under optimal conditions, the system can produce 40.52 MW of total work, a 10

关键词： Ejector refrigeration multi-objective optimization multi-Criteria Decision Making Non-dominated Sorting Genetic Algorithm Exergy destruction Supercritical CO2

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization OF LIQUID COLD PLATE WITH V-SHAPED RIBS FOR LITHIUM-ION BATTERIES

引用

THERMAL SCIENCE 2025年第1期29卷 489-507页

作者： Wang, Yan Liang, Shaozhong Fu, Jian Zheng, Jian Wang, Ya Lanzhou Univ Technol Sch Energy & Power Engn Lanzhou Peoples R China Sinohydro Engn Bur 4 Co Ltd Power China Xining Peoples R China

The performance of lithium-ion batteries is affected by the operational temperature significantly for the new energy vehicles, and should be below 338 K and 5 K, respectively, in the actual project. An efficient thermal management system is essential for the battery, as it would ensure the safe operation and increase the battery life. In this study, the liquid cold plate with V-shaped ribs is applied to improve the heat transfer characteristics for guaranteeing the safe operational temperature of the battery. Based on the battery thermal models, the accuracy of numerical simulation through classical experimental correlation is verified, and is adopted to investigate the effects of different design factors on the heat dissipation of the battery, including the ribbed shaped, the distance between adjacent ribs and the inlet velocity of the coolant. The maximum temperature and the temperature difference of the battery and the pressure drop of the channel are taken as the design objectives. An orthogonal test and an entropy weighted-TOPSIS method are used to optimize the results with multi-objective analysis, then the optimal case of design parameters is obtained. The optimal case for the liquid cold plate is the ribbed shape of Model 2, the distance between the adjacent ribs of 30 mm and the inlet velocity of 0.3 m/s. A good balance is achieved between the heat dissipation of the battery pack and the pressure drop of the channel. The optimal case can reduce the maximum temperature and the temperature difference of the battery by 7.41 K and 4.94 K compared with the unoptimized cases, meanwhile the pressure drop is also effectively controlled.

关键词： lithium-ion batteries liquid cold plate V-shaped ribs heat dissipation multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：