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Sustainable H2 production/separation by integration of solid oxide electrolyzer, biomass gasifier and H2 separation membrane: A techno-economic/environmental evaluation and multi-objective optimization

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PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2023年 177卷 909-920页

作者： Zhongjie Fei Su Zhanguo Jianbo Lu Singh, Pradeep Kumar Dahari, Mahidzal Majdi, Hasan Sh. Ali, H. Elhosiny Bouzgarrou, Souhail Mohamed Nanjing Agr Univ Coll Vet Med Key Lab Anim Dis Diagnost & Immunol Minist Agr Nanjing Peoples R China Huainan Normal Univ Huainan 232038 Anhui Peoples R China Krirk Univ Int Coll Bangkok 10220 Thailand Nanning Normal Univ Guangxi Key Lab Human Machine Interact & Intellig Nanning 530001 Peoples R China GLA Univ Inst Engn & Technol Dept Mech Engn Mathura 281406 UP India Univ Malaya Fac Engn Deparment Elect Engn Kuala Lumpur 50603 Malaysia Mustaqbal Univ Coll Dept Chem Engn & Petr Ind Hilla 51001 Iraq King Khalid Univ Fac Sci Dept Phys POB 9004 Abha Saudi Arabia Jazan Univ Coll Engn Civil Engn Dept Jazan Saudi Arabia Sousse Univ Higher Inst Appl Sci & Technol Sousse Sousse Tunisia

Hydrogen as a clean fuel can simultaneously respond to the challenges of energy shortage and environmental issues, provided that it is produced in a clean and cheap way. In this research, a hydrogen production system based on the combination of a solid oxide electrolyzer with a gasifier and a hydrogen separation membrane has been studied from a techno-economic outlook. In order to achieve a proper approximation of the levelized cost of hydrogen (LCOH), an elaborated economic analysis has been performed considering all aspects, where the life of the hydrogen separation membrane (HSM) and the solid oxide electrolyzer (SOE) has been taken into account. Finally, the minimization of the levelized cost of hydrogen and the levelized carbon dioxide emission (LCE) was carried out through multi-objective optimization. The cost of selling hydrogen was determined according to the various payback times. According to the conducted optimization, it is possible to obtain the minimum levelized cost of hydrogen of 3.63 $/kg. This condition leads to the levelized emission of 10.17 kg CO2/kg H2. Also, the system has the ability to bear levelized CO2 emissions up to 2.92 kg CO2/kg H2, so that the levelized cost of H2 production is 6.45 $/kg. In the four optimal conditions obtained from the optimization, considering the payback time of 5 years, the cost of selling the produced H2 can be 3.64 $/kg, 6.45 $/kg, 5.98 $/kg, and 5.29 $/kg.

关键词： Gasification Hydrogen separation membrane Levelized cost of hydrogen multi objective optimization Solid oxide electrolyzer

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multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill

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MEASUREMENT 2013年第6期46卷 1849-1864页

作者： Kuram, Emel Ozcelik, Babur Gebze Inst Technol Dept Mech Engn TR-41400 Gebze Turkey

This study was carried out to understand micro-milling of aluminum material with ball nose end mill and consisted of four stages: experimental work, modelling, mono and multi objective optimization. In the first stage (experimental work), micro-milling experiments were carried out using Taguchi method. The effects of spindle speed, feed per tooth and depth of cut on tool wear, force and surface roughness were investigated. Cutting tools and workpiece surfaces were also inspected via scanning electron microscope. Adhesion and abrasion wear mechanisms during micro-milling of aluminum were observed: Workpiece surfaces had the accumulations of plastically deformed workpiece material due to the high ductility of aluminum. In the second stage (modelling), all data gathered in the experimental works were utilized to formulate first-order models with interaction. These first-order models with interaction could be used to predict responses in micro-milling of aluminum with a minor error. In the third stage (mono-objective optimization), responses were used alone in optimization study as an objective function. To minimize all responses, Taguchi's signal to noise ratio was used. The effect of control factors on responses was determined by analysis of variance. In the fourth stage (multi objective optimization), responses were optimized simultaneously using grey relational analysis. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Micro-milling Grey relational analysis Tool wear Cutting force Surface roughness multi objective optimization

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multi-objective optimization for the geometry of trapezoidal corrugated morphing skins

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STRUCTURAL AND multiDISCIPLINARY optimization 2017年第1期55卷 331-345页

作者： Dayyani, Iman Friswell, Michael I. Cranfield Univ Sch Aerosp Transport & Mfg Ctr Struct Assembly & Intelligent Automat Cranfield MK43 0AL Beds England Swansea Univ Bay Campus Coll Engn Swansea SA1 8EN W Glam Wales

Morphing concepts have great importance for the design of future aircraft as they provide the opportunity for the aircraft to adapt their shape in flight so as to always match the optimal configuration. This enables the aircraft to have a better performance, such as reducing fuel consumption, toxic emissions and noise pollution or increasing the maneuverability of the aircraft. However the requirements of morphing aircraft are conflicting from the structural perspective. For instance the design of a morphing skin is a key issue since it must be stiff to withstand the aerodynamic loads, but flexible to enable the large shape changes. Corrugated sheets have remarkable anisotropic characteristics. As a candidate skin for a morphing wing, they are stiff to withstand the aerodynamic loads and flexible to enable the morphing deformations. This work presents novel insights into the multi-objective optimization of a trapezoidal corrugated core with elastomer coating. The geometric parameters of the coated composite corrugated panels are optimized to minimize the in-plane stiffness and the weight of the skin and to maximize the flexural out-of-plane stiffness of the skin. These objective functions were calculated by use of an equivalent finite element code. The gradient-based aggregate method is selected to solve the optimization problem and is validated by comparing to the GA multi-objective optimization technique. The trend of the optimized objectives and parameters are discussed in detail;for example the optimum corrugation often has the maximum corrugation height. The obtained results provide important insights into the design of morphing corrugated skins.

关键词： multi objective optimization Corrugated Morphing

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Evolution strategies and multi-objective optimization of permanent magnet motor

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APPLIED SOFT COMPUTING 2012年第2期12卷 778-792页

作者： Andersen, Soren B. Santos, Ilmar F. Tech Univ Denmark Dept Mech Engn DK-2800 Lyngby Denmark

When designing a permanent magnet motor, several geometry and material parameters are to be defined. This is not an easy task, as material properties and magnetic fields are highly non-linear and the design of a motor is therefore often an iterative process. From an engineering point of view, we usually want to maximize the efficiency of the motor and from an economic point of view we want to minimize the cost of the motor. As these two things seldom go hand in hand, the goal is to find the best efficiency per cost. The scope of this paper is therefore to investigate the applicability of evolution strategies, ES to effectively design and optimize parameters of permanent magnet motors. Single as well as multi-objective optimization procedures are carried out. A modified way of creating the strategy parameters for the ES algorithm is also proposed and has together with the standard ES algorithm undergone a comprehensive parameter study for the parameters rho and lambda. The results of this parameter study show a significant improvement in stability and speed with the use of the modified ES version. To find the most effective selector for a multi-objective optimization, MOO, of the motor a performance examination of 4 different selectors from the group of programs called PISA has been made and compared for MOO of the efficiency and cost of the motor. This performance examination showed that the indicator based evolutionary algorithm, IBEA, and hypervolume estimation algorithm, HypE, selectors performed almost equally good on this MOO problem where the HypE selector only had a slightly better performance indicator. (C) 2011 Elsevier B. V. All rights reserved.

关键词： Metaheuristic Permanent magnet motor optimization Evolution strategies multi objective optimization

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Modeling and Pareto based multi-objective optimization of wavy fin-and-elliptical tube heat exchangers using CFD and NSGA-II algorithm

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APPLIED THERMAL ENGINEERING 2017年 111卷 325-339页

作者： Damavandi, Mohammad Darvish Forouzanmehr, Mostafa Safikhani, Hamed Univ Tehran Coll Engn Sch Mech Engn Tehran Iran Arak Univ Fac Engn Dept Mech Engn Arak *** Iran

In this paper, a multi-objective optimization (MOO) of wavy fin-and-elliptical tube heat exchangers has been performed by using Computational Fluid Dynamics (CFD), Artificial Neural Network (ANN) of Group Method of Data Handling (GMDH) type, and Non-Dominated Sorting Genetic Algorithm II (NSGA-II). This multi-objective optimization is aimed at achieving maximum heat transfer and minimum pressure drop. For this purpose, the considered objective functions, Colbum factor (j) and friction factor (f) are optimized with regards to the design variables (four variables). The CFD results are validated by means of experimental findings. Polynomials of the GMDH type neural network are formed based on the CFD results. These polynomials relate the objective functions to the design variables. Ultimately, the NSGA-II algorithm obtains the Pareto optimal points by using the input data from the neural network. From among the optimal points, several points with unique features are introduced and explained. The investigation of optimal points indicates that with a slight reduction in heat transfer, pressure drop can be reduced considerably. By combining and simultaneously using the CFD, neural network and NSGA-II optimization algorithm, very useful and valuable results are obtained;which otherwise couldn't be achieved without the mutual use of these techniques. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： multi objective optimization Wavy fin Elliptical tube GMDH NSGA-II

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Deterministic and Stochastic Model in the Structuring of Batch Within an Arc Furnace for multi objective optimization

Deterministic and Stochastic Model in the Structuring of Bat...

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第三届机电一体化与工业信息学国际学术研讨会(ISMII 2017)

作者： Natalia S.Sibileva Oksana S.Logunova Julia B.Kuhta Nosov Magnitogorsk State Technical University

The traditional technology of preparation of charge materials does not include an intellectual component and is conducted only on the basis of an evaluation of the results of an industrial *** study has the following purpose:increasing the efficiency of the steelmaking process in large capacity arc furnace on the basis of implementation a new decision-making system about the composition of charge *** proposed a diagram of an interactive intelligent builder which is capable to solve problems of optimizing the composition of charge materials in the presence of several different targets.

关键词： technical preparation of steel multi objective optimization electric arc furnace preparation of materials charge composition intelligent support interactive builder

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A novel method for overlapping community detection using multi-objective optimization

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2018年 505卷 825-835页

作者： Ebrahimi, Morteza Shahmoradi, Mohammad Reza Heshmati, Zainabolhoda Salehi, Mostafa Univ Tehran Fac New Sci & Technol North Kargar StPOB 14395-1561 Tehran *** Iran

The problem of community detection as one of the most important applications of network science can be addressed effectively by multi-objective optimization. In this paper, we aim to present a novel efficient method based on this approach. Also, in this study the idea of using all Pareto fronts to detect overlapping communities is introduced. The proposed method has two main advantages compared to other multi-objective optimization based approaches. The first advantage is scalability, and the second is the ability to find overlapping communities. Despite most of the works, the proposed method is able to find overlapping communities effectively. The new algorithm works by extracting appropriate communities from all the Pareto optimal solutions, instead of choosing the one optimal solution. Empirical experiments on different features of separated and overlapping communities, on both synthetic and real networks show that the proposed method performs better in comparison with other methods. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Community detection Complex networks multi objective optimization Overlapping communities Pareto fronts

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multi-objective optimization analysis of construction management site layout based on improved genetic algorithm

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SYSTEMS AND SOFT COMPUTING 2024年 6卷

作者： Yin, Hui Xinjiang Inst Engn Sch Civil Engn Urumqi 830000 Peoples R China

In construction management, the rationality of on-site layout is crucial for project progress, cost, and safety. In order to improve the rationality of on-site layout, a multi-objective optimization model combining ant colony algorithm and Pareto optimal solution was constructed based on genetic algorithm, and this model was applied to practical engineering cases. The results show that in terms of computational time, the genetic algorithm takes an average of 1702.0 s, while the improved algorithm takes an average of 421.0 s, which is 1281s less and 85.9% more than before the improvement. The performance of the improved algorithm is the best, and the optimal solution can be obtained through multiple iterations. The improved algorithm has improved the efficiency of onsite layout optimization, and possesses practical application value for the layout of construction management sites. It offers a certain reference for the reasonable setting of construction management sites.

关键词： Construction management Site layout multi objective optimization Genetic algorithm Ant colony

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multi-objective optimization of Process Parameters in Wire Electric Discharge Machining of Ti-6-2-4-2 Alloy

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2014年第2期39卷 1465-1476页

作者： Garg, M. P. Jain, Ajai Bhushan, Gian MMEC Mullana Dept Mech Engn Ambala Haryana India NIT Dept Mech Engn Kurukshetra Haryana India

The present paper identifies the different process parameters that effect the cutting speed and surface roughness in wire electrical discharge machining of Titanium-6-2-4-2 (HSTR aerospace alloy), which is so far not reported in the literature. It also identifies optimal process parameter combination for simultaneous optimization of cutting speed and surface roughness to be presented as a guideline for machining of Titanium-6-2-4-2. Box-Behnken design and response surface methodology are used to plan and analyse the experiments. Six control factors viz. Pulse on time, pulse off time, peak current, spark gap set voltage, wire feed, and wire tension are chosen as process parameters to study the performance of the process in terms of cutting speed and surface roughness. The recommended optimal parameter combinations have been verified by conducting confirmation experiments.

关键词： WEDM Ti 6-2-4-2 alloy Box-Behnken designs Response surface methodology multi objective optimization

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multi-objective optimization and numerical modelling of helical coil spring for automotive application

Multi-objective optimization and numerical modelling of heli...

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4th International Conference on Advances in Materials and Manufacturing Applications (IConAMMA)

作者： Rahul, M. S. Rameshkumar, K. Amrita Vishwa Vidyapeetham Dept Mech Engn Amrita Sch Engn Coimbatore 641112 Tamil Nadu India

In this paper, a helical compression spring used in commercial transport three-wheeler has been modelled as a multi-objective optimisation problem. The objective functions considered in this study are reducing the volume of the spring and increasing the strain energy of the spring used in the light automotive. Minimizing the volume of the spring leads to reducing the cost of the spring. The utility and functionality of the spring can be improved by increasing the strain energy of the helical spring. Design parameters such as diameter of the spring wire, diameter of the coil spring and number of active turns of the spring are optimized in this study by using multi-objective optimisation formulation. Heuristic techniques such as Genetic Algorithms are used to find Pareto optimal solutions for a wide variety of engineering problems with multiple objectives. In this work, non-dominated solutions are generated using Non-Dominated Sorting GA-II approach. The Pareto-optimal solutions obtained in this study are validated using a numerical approach using ANSYS workbench. (c) 2020 Elsevier Ltd. Selection and peer-review under responsibility of the scientific committee of the International Conference on Advances in Materials and Manufacturing Applications.

关键词： Helical coil spring multi objective optimization Weighted sum approach Finite element method Pareto optimal solution

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