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multi-objective optimization for shrinkage, mechanical, and shape-memory behavior in 4D printed polymer composites

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2025年第7-8期136卷 3345-3366页

作者： Dixit, Garima Pandey, Pulak Mohan Indian Inst Technol Dept Mech Engn New Delhi India

In the context of 4D printing, the term "fourth dimension" pertains to the capacity of materials to change their shape or form once they have been manufactured. This characteristic enables them to possess enhanced functional capabilities and enables the creation of applications that prioritize performance. Stimulus-responsive materials like shape memory polymers provide great opportunities to be used in 4D printing for a wide range of applications. Using polylactic acid (PLA) and bioactive glass (BG), this study demonstrates the developed material's potential for processing and experimentation for shape memory properties and 4D printing. Expanding our approach, a multi-objective optimization was done to minimize shrinkage and maximize strength along with shape recovery for 4D printed shape memory polymer composites (SMPCs) with the help of the central composite design (CCD) approach commonly referred to as response surface methodology (RSM). The model was validated by conducting confirmation tests using the best possible combination of parameters for the process, as determined utilizing the genetic algorithm multi-objective optimization method. In the end, different structures were developed by utilizing 4D printing at optimum parameters and the shape-changing behavior was recorded in the 4D printed parts by applying a thermal stimulus.

关键词： 4D printing Solvent cast 3D printing Shape memory polymer composites Bioactive glass design of experiment multi-objective optimization

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multi-objective optimization of a wet electromagnet-driven water hydraulic high-speed on/off valve for underwater manipulator in deep sea

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MEASUREMENT 2025年 239卷

作者： Meng, Lingkang Wu, Defa Gao, Heng Ye, Xujun Liu, Hanhui Liu, Yinshui Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430074 Peoples R China

Water hydraulic high-speed on/off valves (WHSVs) have the potential to replace the traditional oil hydraulic valves to be used in underwater hydraulic manipulators (UHMs) in the deep-sea environment due to their environmental friendliness, strong anti-pollution ability, and good sealing property. In this paper, we develop and optimize a novel wet electromagnet-driven WHSV to enhance its suitability for UHMs. Firstly, an accurate equivalent magnetic model of the WHSV is derived, considering the leakage flux and nonlinear characteristics. This magnetic model is combined with other physical field models to accurately describe the dynamic behavior of the WHSV and provide a comprehensive simulation framework. Then, the multi-objective optimization and decision-making methods are combined to optimize and determine the structural parameters of the WHSV, achieving a balance between rapid response and light mass. Finally, a WHSV prototype is manufactured and tested based on the optimized structural parameters. Experimental results indicate that the WHSV achieves opening and closing times of 1.63 ms and 1.22 ms, respectively, with the electromagnetic components weighing 75.5 g. These results show a maximum deviation of 7.4 % from the optimization results (1.52 ms, 1.31 ms, 71.6 g). Moreover, the deep-sea simulation test verifies the prototype functionality under a high-pressure condition (110 MPa).

关键词： Wet electromagnet High-speed on/off valve multi-objective optimization Dynamic characteristics Mathematical modeling Underwater manipulator

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multi-objective optimization of reinforced concrete columns considering long-term and second order effects: Constructability, cost, and environmental impact

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STRUCTURAL CONCRETE 2025年第0期

作者： Preuss, Arthur de C. Grotti, Ewerton de Almeida, Felipe Schaedler Gomes, Herbert M. Univ Fed Rio Grande do Sul Grad Program Civil Engn Ave Osvaldo Aranha 99 Porto Alegre Brazil Fed Univ Rio Grandedo Sul Grad Program Mech Engn Porto Alegre Brazil Fed Univ Fed Rio Grande do Sul Dept Civil Engn Porto Alegre Brazil

This work presents a methodology for the optimum design of reinforced concrete (RC) columns subjected to axial compression and bending end loads, considering long-term and second-order effects, designed according to the general method outlined in Eurocode 2 (EN 1992-1-1, 2004). The approach is applicable to columns of any slenderness, with arbitrary polygonal cross-section shape and subjected to any combination of axial compression and bending end loads. The multi-objective problem is formulated for the simultaneous improvement of cost, constructability, and environmental impact. The solution is obtained by the metaheuristic algorithms multi-objective quantum particle swarm optimization (MOQPSO), multi-objective particle swarm optimization (MOPSO) and the well-established non-dominated sorting genetic algorithm II (NSGA-II). Examples of the optimization of RC columns with rectangular cross-section and subjected to many load cases showed that cost and environmental impact can be minimized simultaneously at the expense of constructability, which is observed by the non-linear Pareto frontier obtained for each pair of these conflicting objectives.

关键词： constructability cost environmental impact multi-objective optimization reinforced concrete columns second-order effect

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multi-objective optimization in roll-to-roll UV embossing for manufacturing linear Fresnel lenses

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POLYMER ENGINEERING AND SCIENCE 2025年第0期 2624-2641页

作者： Yu, Cheng-Long Wu, Cheng-Hsien Natl Kaohsiung Univ Sci & Technol Dept Mold & Die Engn Kaohsiung 807 Taiwan

Linear Fresnel lenses are widely used in solar energy concentration, image processing, and optical imaging applications. Concentrated solar power technology offers a more efficient and economical solution by focusing sunlight onto a smaller receiver, thereby increasing energy conversion efficiency and reducing facility costs. This research aims to design and manufacture a concentrating lens that can achieve the most uniform illumination and the lowest energy loss percentage. The optical design of the linear Fresnel lens aims for maximum uniformity and minimal energy loss. The lens parameters include a lens area, a focal length, and a structure spacing. Roll-to-roll UV embossing was applied to produce the linear Fresnel lenses. Four embossing parameters: resin pressure, film speed, film-press pressure, and film tension, were optimized. The design optimization uses the Taguchi method and multi-objective response surface methodology (RSM), which are applied to the optical design and process parameter analysis. The results show that optimized parameter combinations can significantly improve the replication percentage of the lens structure and reduce surface bubble defects. In addition, the linear Fresnel lens was tested on solar cells. The highest quality lenses are manufactured under multi-objective optimization *** multi-objective optimization design using response surface methodology. Applying linear Fresnel lenses to solar cells increases output power. Optimized Fresnel lens design achieves uniform illumination and low energy loss. Roll-to-roll UV embossing makes Fresnel lenses with excellent light focus.

关键词： Fresnel lenses multi-objective optimization roll-to-roll Taguchi methods UV embossing

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multi-objective optimization of gasoline blending scheduling via NSGA-II algorithm with composite operators considering oil movement path planning

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 280卷

作者： He, Renchu Bian, Rui Hua, Junjie Zhao, Liang Xu, Feng Long, Jian China Univ Petr Coll Artificial Intelligence Dept Automat Beijing 102249 Peoples R China East China Univ Sci & Technol Key Lab Smart Mfg Energy Chem Proc Minist Educ Shanghai 200237 Peoples R China East China Univ Sci & Technol State Key Lab Ind Control Technol Shanghai 200237 Peoples R China

Gasoline blending is a complex process of mixing multiple components into refined oil, directly affecting the economic benefits and product quality of refineries. However, traditional gasoline blending scheduling optimization methods often overlook the movement paths of oils, leading to misunderstanding between scheduling schemes and actual operations. This paper conducts in-depth research on the tank area topology structure composed of key equipment, such as storage tanks, blending heads, pumps, etc., and constructs a gasoline blending and scheduling model considering oil movement paths. The model aims to maximize refined oil production and delivery volume, minimize excess octane number attributes, and reduce oil movement costs. Because of the complexity of solving the multi-path search problem, this paper introduces NSGA-II for solution, using chromosomes of evolutionary algorithms to represent oil movement paths and combining with a priority search algorithm to ensure path feasibility. Experimental results show this model can provide feasible gasoline blending and scheduling schemes for refinery production.

关键词： Gasoline blending scheduling Oil movement multi-objective optimization Path planning

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multi-objective optimization of the mixed-flow intelligent production line for automotive MEMS pressure sensors

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APPLIED INTELLIGENCE 2025年第1期55卷 1-14页

作者： Zhang, Quanyong Li, Hui Shen, Shengnan Cao, Wan Jiang, Jing Tang, Wen Hu, Yuanshun Wuhan Univ Inst Technol Sci Wuhan 430072 Peoples R China Wuhan Univ Sch Power & Mech Engn Wuhan 430072 Peoples R China Wuhan Univ Hubei Prov Engn Res Ctr Integrated Circuit Packagi Wuhan 430072 Peoples R China Wuhan Univ Hubei Key Lab Elect Mfg & Packaging Integrat Wuhan 430072 Peoples R China Wuhan Fine MEMS Inc Wuhan 430075 Peoples R China Wuhan Huagong Cyber Data Syst Co Ltd Wuhan 430074 Peoples R China

Intelligent manufacturing can provide powerful support for the digital transformation of manufacturing industry. Micro-electro-mechanical system (MEMS) sensors have been widely used in the automotive industry because of their small size, low cost, and high reliability. Aiming at the problems of low flexibility, poor adaptability, and high manufacturing cost in the mixed-flow intelligent production line of multi-variety automotive MEMS pressure sensors in this study, a multi-objective optimization model is established with takt time and balance rate as optimization objectives. The non-dominated sorting genetic algorithm-II (NSGA-II) is used to obtain the multi-objective optimization of the mixed-flow intelligent production line with the elite strategy, crowding degree, and crowded comparison operator. The accuracy of the NSGA-II is validated by comparing it with that of the ant colony optimization (ACO) algorithm, simulated annealing (SA) algorithm, and particle swarm optimization (PSO) algorithm. The NSGA-II achieves higher optimization accuracies for takt time and balance rate compared to ACO, SA, and PSO algorithms. Specifically, the NSGA-II achieves optimization accuracies of 2.73%, 2.44%, and 8.99% for the takt time, slightly surpassing those of the ACO, SA, and PSO algorithms respectively. Similarly, for the balance rate, the NSGA-II achieves optimization accuracies of 2.17%, 1.89%, and 2.48%, slightly higher than those of the ACO, SA, and PSO algorithms respectively. The takt time is optimized by NSGA-II to less than 10 s/piece, while the balance rate is optimized to over 90%. The multi-objective optimization of the mixed-flow intelligent production line for automotive MEMS pressure sensors is practical and instructive for improving production line efficiency.

关键词： multi-objective optimization Takt time Balance rate Non-dominated sorting genetic algorithm-II

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multi-objective optimization on combined heat pump and mechanical vapor recompression system for waste heat recovery of offshore wind power converter

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DESALINATION 2025年 601卷

作者： Hu, Xiaowei Shi, Chenyang Dong, Shengming Fu, Xingyu Ma, Tianya Chen, Qijing Tianjin Univ Commerce Sch Mech Engn Tianjin 300134 Peoples R China

Offshore wind power converter station generates a significant amount of low-temperature waste heat, requiring tremendous freshwater for discharge. Conventional waste heat utilization solutions are no longer effective because their products are unable to be reused in situ. Therefore, two types of seawater desalination systems combining heat pump and mechanical vapor recompression were proposed and investigated by multi-objective optimization and sensitivity analysis. From a view of thermodynamics and economics, the total heat transfer area and total power consumption were adopted as objective functions. An improved non-dominated sorting genetic algorithm was adopted to determine the key parameters, including the condensation temperature of the heat pump, the temperature of seawater after the electronic expansion valve, and the condensation temperature of water vapor in the seawater and water vapor heat exchanger. The Pareto front and approximate ideal solution sorting methods determined the optimal operational states of the two systems as [70.5, 20, 28.57] and [61.42, 40, 73.48], respectively. From the sensitivity analysis, the condensation temperature of the condenser is the most critical parameter. Moreover, HP-MVR-1 and HP-MVR-2 need 139.75 kW and 158.17 kW electric power if freshwater is fully utilized in situ. It may be an effective solution for waste heat in offshore wind power converters.

关键词： Mechanical vapor recompression Heat pump Seawater desalination multi-objective optimization Non-dominated sorting genetic algorithm Offshore power wind converter

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multi-objective optimization Design Framework and Flight Performance Prediction for Reentry Module Using a Rapid Analysis Program

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INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES 2025年第3期26卷 1341-1353页

作者： Yeo, Hoonjung Lee, Minsul Kim, Dohoon Kim, Kyu Hong Seoul Natl Univ Dept Aerosp Engn Seoul 08826 South Korea Seoul Natl Univ Inst Adv Aerosp Technol Seoul 08826 South Korea

In this study, we developed a multi-objective design optimization framework that integrates thermal, aerodynamic, trajectory, and structural analyses through the use of low-fidelity and rapid analysis tools. Using a sphere-cone-flare shape as the baseline, the optimization was aimed at minimizing the total heating load, maximizing the volumetric efficiency, and minimizing the ballistic coefficient, employing a genetic algorithm for optimization. The Pareto-front solutions revealed correlations between the total heating load, volumetric efficiency, and ballistic coefficient. Increasing the flare area effectively reduced the total heating load and ballistic coefficient by enhancing the drag and reducing the aerodynamic heating at through significant deceleration. However, this adjustment resulted in a reduction in volumetric efficiency. Conversely, reducing the flare and adopting a blunt hemispherical shape increased the volumetric efficiency yet resulted in higher ballistic coefficients and significant aerodynamic heating. Performance analysis of the proposed designs indicated improved thermal performance and ballistic coefficients compared to the baseline. Future research should focus on optimizing the entry modules for planetary exploration by considering diverse planetary characteristics.

关键词： multi-objective optimization High-speed vehicle design Genetic algorithm

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multi-objective optimization on thermal-hydraulic performance of symmetrical hierarchical microchannel heat sinks

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APPLIED THERMAL ENGINEERING 2025年 271卷

作者： Wang, Yuwei Qi, Cong China Univ Min & Technol Sch Low Carbon Energy & Power Engn Xuzhou 221116 Peoples R China Zhejiang Univ Inst Adv Equipment Hangzhou 310027 Peoples R China

The increasing integration of microelectronic devices will lead to hot spots and reduce service life. The micro-channel heat sink can effectively manage thermal loads, and its energy efficiency requires urgent enhancement amidst global energy constraints. This study investigated the effects of the secondary channel width and trapezoidal bottom angle on the thermohydraulic performance through numerical simulation and multi-objective optimization. Results showed that expanding the secondary channel width provides a larger flow space and increases the heat transfer area. The pressure drop is reduced, while maintaining effective cooling. The energy efficiency ratio of the cooling system is improved. Increasing the trapezoidal bottom angle can increase the velocity and takes away the heat quickly. The temperature uniformity is improved to avoid excessive local hot spot. Taking the minimization of pressure drop and thermal resistance as objectives, the Pareto optimal solution is obtained by Non-dominated Sorting Genetic Algorithm II. Using Technique for Order Preference by Similarity to Ideal Solution with entropy weight to get the optimal compromise solution. The secondary channel width is 0.216 mm, and the trapezoidal bottom angle is 56.93 degrees. Compared with the microchannel without fins, the pressure drop is reduced by 15.19 % and the thermal resistance is reduced by 23.79 %. A new method was provided to improve the efficiency of structural optimization and obtain microchannel structures with high temperature uniformity and energy efficiency ratio, which provides a very important reference value for the parameter optimization of microchannels.

关键词： Microchannels Heat sink multi-objective optimization Temperature uniformity

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multi-objective optimization evaluation of renewable and clean methanol synthesis

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INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES 2025年 20卷 443-452页

作者： Hai, Tao Rasheed, Rassol Hamed Sharma, Aman Dhawan, Aashim Sharma, Prabhat Rajab, Husam Becheikh, Nidhal Aich, Walid Kolsi, Lioua Singh, Narinderjit Singh Sawaran Ajman Univ Artificial Intelligence Res Ctr AIRC POB 346 Ajman U Arab Emirates INTI Int Univ Fac Data Sci & Informat Technol Nilai 71800 Malaysia Warith Al Anbiyaa Univ Fac Engn Air Conditioning Engn Dept Karbala Iraq GLA Univ Inst Engn & Technol Dept Mech Engn Mathura Uttar Pradesh India Chitkara Univ Ctr Res Impact & Outcome Rajpura 140417 Punjab India Chitkara Univ Chitkara Ctr Res & Dev Kalujhanda 174103 Himachal Prades India Najran Univ Coll Engn Dept Mech Engn POB 1988King Abdulaziz Rd Najran Saudi Arabia Northern Border Univ Min Res Ctr POB 1321 Ar Ar 91431 Saudi Arabia Univ Hail Coll Engn Dept Mech Engn Hail 81451 Saudi Arabia

This study examines the feasibility of establishing a power-to-fuel facility for synthesizing renewable methanol (e-methanol) through the integration of green hydrogen and captured carbon dioxide. Hydrogen is produced via water electrolysis using surplus renewable electricity, while carbon dioxide is captured from a conventional power plant's emissions through an amine-based absorption process. Despite the current economic constraints, with production costs exceeding current market prices for methanol, the study highlights potential future competitiveness, especially considering impending European regulatory frameworks. Furthermore, the study employs a hybrid Grey Wolf Optimizer-Particle Swarm optimization approach to balance the trade-offs between methanol production cost and energy efficiency.

关键词： Clean hydrogen CO2 capture Financial evaluation E-methanol multi-objective optimization

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