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multi-objective optimization of high-temperature PEMFC considering gas distribution quality via surrogate models

APPLIED THERMAL ENGINEERING 2025年 269卷

作者： Zhang, Caizhi Cao, Xu Deng, Shutong Gao, Xin Gavrailov, Dilyan Cai, Lang Li, Fuli Liu, Peng Chongqing Univ Chongqing Automot Collaborat Innovat Ctr Sch Mech & Vehicle Engn Chongqing 400044 Peoples R China Tech Univ Carolo Wilhelmina Braunschweig Inst Internal Combust Engines & Fuel Cells ivb D-38108 Braunschweig Germany Tech Univ Sofia Dept Thermal & Nucl Power Engn 8Kl OhridskyBlvd Sofia 1000 Bulgaria

This study presents a multi-objective optimization approach for high-temperature proton exchange membrane fuel cells (HT-PEMFC), focusing on the simultaneous enhancement of gas distribution quality and output performance. The relationship between gas distribution quality and performance metrics, such as output power density, is thoroughly analyzed using surrogate models integrated with optimization algorithms. By incorporating power loss constraints, the analysis also accounts for the practical trade-offs between gas distribution and output performance. Through the analysis of 2000 selected sample points, the trade-offs between output power density, gas distribution uniformity, and oxygen concentration are quantified. The results demonstrate that optimizing gas distribution can yield up to a 15% increase in output power density while limiting the performance loss to less than 5%. This work emphasizes the practical feasibility of improving HT-PEMFC performance by considering both gas distribution quality and output power density, offering a comprehensive framework for optimizing HT-PEMFC operational parameters in future applications. To further enhance the efficiency of optimization and decision-making, surrogate models are integrated with the optimization algorithm to achieve a more comprehensive optimization of HT-PEMFC.

关键词： High-temperature proton exchange membrane fuel cell (HT-PEMFC) Gas distribution quality Surrogate model multi-objective optimization

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multi-objective optimization for the sightseeing bus problem: Trade-off between tourists and operator

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 269卷

作者： Jia, Zhou Huang, Di Liu, Zhiyuan Hu, Zhitao Liu, Ronghui Yu, Wenwu Southeast Univ Sch Transportat Nanjing Peoples R China Minist Transport Key Lab Transport Ind Comprehens Transport Theory Nanjing Modern Multimodal Transportat Lab Beijing Peoples R China Univ Leeds Inst Transport Studies Leeds England Southeast Univ Sch Math Nanjing Peoples R China

The sightseeing bus plays a crucial role in catering to the needs of urban tourist groups. In crafting operational plans, operators aim to make trade-offs between maximizing tourist benefits and minimizing operational costs. This study introduces the multi-objective sightseeing bus problem, encompassing decisions related to bus fleet scheduling, route planning, and tourist assignment. A two-stage multi-objective Adaptive Large Neighborhood Search (MO-ALNS) algorithm is proposed to tackle this multi-objective integer programming model. Customized operators for assignment and routing are devised to augment the algorithm. Numerical experiments demonstrate the algorithm's effectiveness, offering valuable insights to aid operators in formulating cost-effective sightseeing bus operational plans. Sensitivity analysis underscores a notable correlation between the formulation of the operational plan and the distribution of tourist preferences, spatial distribution of points of interest, and vehicle capacity.

关键词： Sightseeing bus planning Tourist trip planning multi-objective optimization Adaptive large neighborhood search (ALNS)

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multi-objective optimization of thermochemical energy storage systems with configuration planning for different applications

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APPLIED THERMAL ENGINEERING 2025年 274卷

作者： Wang, Yihan Xu, Zhiqi Liu, Shuli Shen, Yongliang Ji, Wenjie Chen, Tingsen Li, Yongliang Beijing Inst Technol Sch Mech Engn Dept Energy & Power Engn Beijing 100081 Peoples R China Beijing Inst Technol Sch Mech Engn Nonsilicon Micronano Mfg Key Lab Beijing 100081 Peoples R China Beijing Inst Technol Sch Mat Sci & Engn Beijing 100081 Peoples R China Univ Birmingham Bitmingham Ctr Energy Storage Sch Chem Engn Birmingham B15 2TT England

Due to the lack of effective operation configuration planning strategy, the promotion and efficient operation of thermochemical energy storage systems, which are seriously affected by parameter changes, are hindered. Based on the mathematical model developed from experimental data, this study proposes a configuration planning strategy combining non-dominated sorting genetic algorithm and TOPSIS algorithm. The minimum heating temperature, available heating energy and available heating time are used as the optimization targets of the discharging process, while the energy storage temperature, energy storage efficiency and total stored energy are the optimization targets of the charging process. Higher supplied heating temperature is only suitable for shortterm heating scenarios after storing excess energy. Lowering the heating temperature increases the available heating energy by 2.58 times, and the reactor discharging efficiency is increased to 85.68%. The inlet air moisture is the key factor in increasing the air temperature rise. There is an optimal reaction point inside the reactor that reaches the saturation state first. For the charging process, the scenario with lower energy storage temperature requires a larger air mass flow rate. Increasing the energy storage temperature increases the total stored energy by 16.05%, but it will reduce the energy storage efficiency.

关键词： Thermochemical energy storage system multi-objective optimization Thermodynamic performance analysis Heat and mass transfer analysis

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multi-objective optimization of sustainable aviation fuel production pathways in the US Corn Belt

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BIOMASS & BIOENERGY 2025年 193卷

作者： Akdemir, Ece Ari Kern, Jordan Smith, Jack P. Limb, Braden J. Quinn, Jason C. Field, John L. Pack, Taylor NC State Univ Dept Civil Construct & Environm Engn Raleigh NC 27606 USA NC State Univ Dept Ind & Syst Engn Raleigh NC 27606 USA Colorado State Univ Dept Mech Engn Ft Collins CO 80521 USA Oak Ridge Natl Lab Oak Ridge TN 37830 USA NC State Univ Dept Forestry & Environm Resources Raleigh NC 27695 USA

As a potential source of low-carbon transportation energy, biofuels offer certain advantages over vehicle electrification (e.g., lower societal vulnerability to grid failures, and improved range of sustainable aviation), but also several challenges, including cost, carbon intensity, and land usage. There are also well-founded concerns that biofuel supply chains could be disrupted if extreme weather events impact feedstock yields. In this paper, we explore the use of multi-objective optimization to identify biofuel production pathways that balance cost, greenhouse gas emissions, and supply vulnerability to extreme weather. We compare the use of three different many-objective evolutionary algorithms and linear programming in optimizing biomass cultivation decisions in the U.S. Corn Belt under weather uncertainty using historical, modeled, and synthetic yield data. We consider four feedstock choices (corn, soy, switchgrass, and algae) with two land types (agricultural and marginal lands) and evaluate decisions using three alternative spatial resolutions (ranging from the USDA agricultural district level to the state level). Results show that feedstock choice is the primary driver of objective performance (i.e., the position and shape of 3D, approximate Pareto frontiers). Spatial diversification is a less effective tool in reducing exposure to weather-caused drops in crop yield.

关键词： Biofuel supply chains Weather risk multi-objective optimization Linear programming

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multi-objective optimization design of NPR protection shell for hydrogen storage tank

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MECHANICS OF ADVANCED MATERIALS AND STRUCTURES 2025年第11期32卷 2560-2573页

作者： Zhou, Guan Niu, Yuankui Zhao, Jiale Wang, Yuanlong Nanjing Univ Aeronaut & Astronaut Dept Vehicle Engn Nanjing Peoples R China

In order to improve the safety of on-board hydrogen storage tanks during collision, a protective shell based on a negative Poisson's ratio (NPR) core is designed in this paper. After analyzing and comparing the crashworthiness of three typical honeycomb structures, the concave hexagonal negative Poisson's ratio honeycomb is selected as the energy-absorbing inner core of the hydrogen storage tank protection structure. The sensitivity analysis of the structural parameters of the NPR shell is conducted through orthogonal tests to identify parameters with a significant impact on crash performance. These parameters are then used as experimental variables for subsequent optimization design. Subsequently, a response surface approximation model between the optimization objective and the structural parameters is established based on the response surface method. Finally, the adaptive simulated annealing algorithm (ASA), neighborhood cultivation genetic algorithm (NCGA), and non-dominated sorting genetic algorithm-II (NSGA-II) are used to optimize the structural parameters, and the optimization results are verified by the whole-vehicle crash simulation. The simulation results demonstrate that all three algorithms achieve better optimization results, among which NCGA is more advantageous in improving the overall performance of the protective shell. After NCGA optimization, the specific energy absorption of the protective shell increases by 19.75%, the maximum collision force of the rigid wall decreases by 23.63%, and the maximum stress of the hydrogen storage tank body decreases by 22.77%. These findings indicate that the designed protection shell effectively improves the crashworthiness of the hydrogen storage tank during collisions.

关键词： multi-objective optimization NPR structure crash box hydrogen storage tank sensitivity analysis

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multi-objective optimization of cooling capacity and input power of precooled JT cryocooler working at liquid helium temperature

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INTERNATIONAL JOURNAL OF REFRIGERATION 2025年 173卷 18-28页

作者： Qiu, Changxu Shen, Yunwei Li, Ruize Wu, Tongfei Wang, Bo Zhao, Qinyu Gan, Zhihua Zhejiang Univ Inst Refrigerat & Cryogen Key Lab Refrigerat & Cryogen Technol Zhejiang Prov Hangzhou 310027 Peoples R China Hangzhou City Univ Cryogen Ctr Hangzhou 310015 Peoples R China

The precooled JT cryocooler has become the mainstream mechanical refrigeration technology at liquid helium temperature with the advantages of low vibration, high reliability and high efficiency. The efficient matching of the precooler, JT compressor and JT side cryocooler is the key to improving the cooling capacity and reducing input power. Input power and cooling capacity of JT cryocooler are key parameters related to thermodynamics and economic performance that deserve equal attention in most industrial and research applications. In this study, a thermodynamic model of the precooled JT cryocooler working at liquid helium temperature incorporating the heat exchangers, the JT compressor and the precooler is developed. Characteristics of cooling capacity, input power and efficiency of JT cryocooler under different working conditions are analyzed. A multi-objective optimization method is employed to holistically optimize both input power and cooling capacity. The Pareto frontier consisting of a series of non-dominated solutions is obtained. The linear programming technology of multidimensional analysis preference (LINMAP) method is utilized to choose the final optimal solution from the Pareto frontier. The multi-objective optimization results of input power and cooling capacity of the cryocooler are 10,991.3 W and 7.60 W, respectively.

关键词： JT cryocooler Liquid helium temperature Input power Cooling capacity multi-objective optimization

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multi-objective optimization of volume in a compressed carbon dioxide energy storage system coupled with auxiliary energy storage device based on NSGA-II

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JOURNAL OF ENERGY STORAGE 2025年 118卷

作者： Liu, Aijie Zhao, Pan Sun, Jiahong Xu, Wenpan Ma, Ning Wang, Jiangfeng Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

Nowadays, there is a growing focus on renewable energy due to escalating environmental issues. The energy storage system plays a crucial role in maintaining a balance between renewable energy sources and the power grid. This paper proposes an integrated system that includes a wind farm, a thermal power unit, and an energy storage system. The energy storage system includes a compressed CO2 energy storage (CCES) system and two alternative auxiliary energy storage devices (electric heater and power-to-gas device). The Non-dominated Sorting Genetic Algorithm-II is adopted to optimize the volume of the energy storage system. A comparison between three systems (System A: CCES;System B: CCES with electric heater;System C: CCES with power-to-gas device) is conducted. The result reveals that the wind curtailment cost and the power insufficient cost account for a large proportion of the total cost. System B has the lowest cost per unit generation of 0.974 $/kWh, 22.51 %, and 28.91 % lower than that of System C and System A, respectively. Compared to the addition of a Proton Exchange Membrane Electrolyzer, the addition of an electric heater has better performance. Moreover, the value and distribution of unbalanced power impact wind curtailment energy and result in insufficient energy generation. The duration time of unbalanced power determines the charge time, while the operating time affects the cost per unit generation.

关键词： Compressed carbon dioxide energy storage Electric heater Power-to-gas device Case study multi-objective optimization

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multi-objective optimization of urban logistics land: a gradient-based method approach with Wuhan city as an example

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INTERNATIONAL JOURNAL OF DIGITAL EARTH 2025年第1期18卷

作者： Jiao, Hongzan Zhang, Shuaikang Wuhan Univ Sch Urban Design Dept Urban Planning Wuhan 430072 Peoples R China

Effective planning of logistics land is crucial for mitigating urban freight congestion, fostering economic activities, and achieving environmental equilibrium. However, the dual challenge of mismatched logistics supply and demand, along with conflicts in land use functions, can lead to inefficiencies in resource allocation and urban freight system performance. To tackle this issue, our study integrates truck GPS trajectory data with urban land use datasets to formulate a multi-objective optimization model. By utilizing the gradient descent algorithm, which effectively handles large-scale datasets, we can navigate the complexities of logistics land planning with precision. The application of this model in the Wuhan Urban Development Area reveals that: (1) across various scenarios, the model balances the utilization of multiple optimization objectives and demonstrates high solution efficiency;(2) in both the equal weight scenario and the economic preference scenario, the areas of logistics land change are characterized by high economic output, relatively good traffic conditions, greater distance from residential zones, and comparatively low land prices;and (3) based on urban development goals, the model can determine the upper bounds of the optimization objectives through manual supervision of the selection of ideal points.

关键词： Logistics land multi-objective optimization gradient descent method truck GPS trajectory data Wuhan urban development zone

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multi-objective optimization of Blockage Design Parameters Affecting the Performance of PEMFC by OEM-AHP-EWM Analysis

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ENERGIES 2025年第6期18卷 1407-1407页

作者： Ji, Hongbo Yuan, Quan Zhu, Xiaoyong Jankovic, Nenad Chen, Xiaoping Ningbo Univ Technol Dept Mech Engn Vehicle Energy & Safety Lab Ningbo 315336 Peoples R China CATARC Automot Test Ctr Ningbo Co Ltd Ningbo 315336 Peoples R China Univ Kragujevac Inst Informat Technol Kragujevac Dept Sci Jovana Cvijica Bb Kragujevac 34000 Serbia

Adding blockages to the gas flow channels in the bipolar plates has a significant effect on the performance of the proton exchange membrane fuel cell (PEMFC). The design parameters of the gas flow channels with blockages mainly include the blockage shape (S), blockage number (N), blockage height (H), and channel-rib width ratio (CRWR) value. This paper systematically examines the combined effects of S, N, H, and CRWR value on current density (I), pressure drop (Delta P), net output power (Wnet), and non-uniformity of oxygen distribution (NU) of PEMFC through the application of the orthogonal experimental method (OEM). To provide a comprehensive optimization strategy, a novel multi-criteria decision framework is introduced, which integrates the analytic hierarchy process (AHP) and entropy weight method (EWM) to balance different evaluation objectives. Results from the AHP-EWM analysis reveal that the weight values of I, Delta P, Wnet, and NU are 0.415, 0.08, 0.325, and 0.18, respectively. The CRWR value exhibits the greatest effect on the comprehensive performance of PEMFC, followed by H, N, and S. The optimal design parameter combination identified in this paper is a triangular blockage with nine blockages, a height of 0.8 mm, and a CRWR value of 0.25, corresponding to the highest comprehensive score of 31.8306 among the 25 groups of orthogonal experiments. This paper provides a new optimization perspective and certain guidance for the performance optimization direction of PEMFC.

关键词： multi-objective optimization PEMFC orthogonal experimental method (OEM) analytic hierarchy process (AHP) entropy weight method (EWM)

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multi-objective optimization of thermochromic glazing: Evaluating useful daylight illuminance, circadian stimulus, and energy performance with implications for sleep quality improvement☆

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ENERGY AND BUILDINGS 2025年 333卷

作者： Fan, Lai Xie, Liang Zhong, Qikang Beijing Univ Civil Engn & Architecture Sch Architecture & Urban Planning Beijing 100044 Peoples R China Natl Univ Singapore Coll Design & Engn Singapore 117566 Singapore

This study explores the application of thermochromic (TC) glazing to improve energy efficiency, Useful Daylight Illuminance (UDI), and Circadian Stimulus (CS) in a typical slab-style elderly apartment in Changsha. A multiobjective optimization approach was utilized, integrating GA-BP neural networks for predictive modeling and the multi-objective Grey Wolf Optimizer (MOGWO) to evaluate and balance the impacts of different outcomes on the indoor environment. The results demonstrate that TC glazing reduces energy consumption by up to 40 % compared to conventional glazing while stabilizing indoor temperatures and enhancing daylighting conditions, with a 27 % increase in UDI and a 15 % improvement in CS alignment. These enhancements support circadian rhythm regulation and contribute to a more comfortable indoor environment, ultimately improving sleep quality. These findings underscore the effectiveness of TC glazing in retrofitting elderly apartments, offering significant energy savings and health-related benefits, providing a scalable framework for developing sustainable, healthsupportive indoor environments applicable to similar climates and residential building types.

关键词： Senior apartment multi-objective optimization Energy consumption Useful Day Illuminance Circadian Stimulus Improve sleep quality

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