A multiobjective thermodynamic optimization of a nanoscale Stirling engine operated with Maxwell‐Boltzmann gas

Shah, Priyank; Saliya, Pankaj; Raja, Bansi D.; Patel, Vivek

doi:10.1002/htj.21463

Cited by 14 publications

(7 citation statements)

References 70 publications

(72 reference statements)

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“…A multiobjective heat transfer search (MOHTS) is a multiobjective variant of the HTS algorithm capable to handle two or more objectives simultaneously. [36][37][38][39][40][41][42][43][44][45] The MOHTS algorithm works on the nondominating principle. The algorithm produces a set of solutions for each objective, from which the dominating solutions are eliminated and nondominating solutions are stored in external archives.…”

Section: E Modeling Of Power Cycle and Objective Function Formulationmentioning

confidence: 99%

Energy, economy, and ecological (3E)‐based performance evaluation of a steam cycle power plant through optimization investigation

et al. 2021

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Energy, economy, and ecological (3E)-based analysis of steam cycle power plant evaluated through multiobjective investigation. The Montazer Ghaem steambased power plant situated in Iran is considered for investigation. Cycle efficiency, total cost, and ecological function of steam power cycle are treated as the 3E objective in the analysis. Simultaneous optimization of this performance parameter is executed through a heat transfer search algorithm. Fifteen operating variables of the steam power cycle, which includes different pressure, temperature, and isentropic efficiency are

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Section: E Modeling Of Power Cycle and Objective Function Formulationmentioning

confidence: 99%

Energy, economy, and ecological (3E)‐based performance evaluation of a steam cycle power plant through optimization investigation

et al. 2021

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“…Multiobjective heat transfer search (MOHTS) is a multiobjective variant of the HTS algorithm, which is capable of processing two or more objectives simultaneously 34–38 . The MOHTS algorithm works on the nondominating principle.…”

Section: Hts Algorithm and Its Multiobjective Variantmentioning

confidence: 99%

Thermodynamic optimization of Stirling heat engine with methane gas using finite speed thermodynamic model

et al. 2021

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With the daily rise in environmental issues due to the use of conventional fuels, researchers are motivated to use renewable energy sources. One of such waste heat and low‐temperature differential driven energy sources is the Stirling engine. The performance of the Stirling engine can be improved by finding out the optimum operating and geometrical parameters with suitable working gas and thermal model. Based on this motivation, the current work focuses on the multiobjective optimization of the Stirling engine using the finite speed thermodynamic model and methane gas as the working fluid. Considering output power and pressure drop as two objective functions, the system is optimized using 11 geometrical and thermal design parameters. The optimization results are obtained in the form of the Pareto frontier. A sensitivity assessment is carried out to observe the decision variables, which are having a more sensitive effect on the optimization objectives. Optimization results reveal that 99.83% change in power output and 78% change in total pressure drop can take place in the two‐dimensional optimization space. The optimal solution closest to the ideal solution has output power and pressure drop values as 12.31 kW and 22.76 kPa, respectively.

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“…Therefore, the multi-objective optimization (MOO) not only adapts to the engineering design requirements but also promotes the update and replacement of the heat dissipation design strategy of electronic devices. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) [ 57 ] with an elite strategy has been successfully applied to many engineering designs [ 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 ]. In particular, some scholars apply the NSGA-II algorithm to the study of constructal design with different optimization objectives.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Constructal Design for Quadrilateral Heat Generation Body with Vein-Shaped High Thermal Conductivity Channel

Zhu

Chen

et al. 2022

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Based on the quadrilateral heat generation body (HGB) proposed by previous literature, the multi-objective constructal design is performed. Firstly, the constructal design is performed by minimizing the complex function composed of the maximum temperature difference (MTD) and entropy generation rate (EGR), and the influence of the weighting coefficient (a0) on the optimal constructal is studied. Secondly, the multi-objective optimization (MOO) with the MTD and EGR as optimization objectives is performed, and the Pareto frontier with an optimal set is obtained by using NSGA-II. The optimization results are selected from the Pareto frontier through LINMAP, TOPSIS, and Shannon Entropy decision methods, and the deviation indexes of different objectives and decision methods are compared. The research of the quadrilateral HGB shows that the optimal constructal can be gained by minimizing the complex function with the objectives of the MTD and the EGR, the complex function after the constructal design is reduced by up to 2% compared with its initial value, and the complex function of the two reflects the compromise between the maximum thermal resistance and the irreversible loss of heat transfer. The Pareto frontier includes the optimization results of different objectives, and when the weighting coefficient of a complex function changes, the optimization results obtained by minimizing the complex function will also be distributed in the Pareto frontier. The deviation index of the TOPSIS decision method is 0.127, which is the lowest one among the discussed decision methods.

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A multiobjective thermodynamic optimization of a nanoscale Stirling engine operated with Maxwell‐Boltzmann gas

Cited by 14 publications

References 70 publications

Energy, economy, and ecological (3E)‐based performance evaluation of a steam cycle power plant through optimization investigation

Energy, economy, and ecological (3E)‐based performance evaluation of a steam cycle power plant through optimization investigation

Thermodynamic optimization of Stirling heat engine with methane gas using finite speed thermodynamic model

Multi-Objective Constructal Design for Quadrilateral Heat Generation Body with Vein-Shaped High Thermal Conductivity Channel

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