2019
DOI: 10.1002/htj.21463
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A multiobjective thermodynamic optimization of a nanoscale Stirling engine operated with Maxwell‐Boltzmann gas

Abstract: Recent developments in nanotechnology provided an opportunity to solve many complex problems in the field of energy. Performance investigation of the nanoscale thermal cycles can prove crucial in the development of efficient and less polluting energy system. Due to the influence of boundary phenomenon and quantum degeneracy effects, a nanoscale engine performs according to statistical quantum thermodynamics instead of classical thermodynamics. In this study, a nanoscale Stirling engine operating on an ideal Ma… Show more

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Cited by 14 publications
(7 citation 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%
“…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%
“…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%
“…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%