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In this communication, the thermodynamic performance of an ideal Stirling cycle engine has been investigated. In this regard, the first law of thermodynamics has been employed to determine state of total heat addition, network output, and thermal efficiency with changes in dead volume percentage and regenerator effectiveness. Second law analysis is applied to obtain the trends for the total entropy generation of the cycle. Moreover, the entropy generation of each element involving the Stirling cycle processes is measured. Three objective functions including the output power per rate of mass of the ideal gas working fluid (wnet) and the thermal efficiency (ηt) have been considered simultaneously for maximisation, and the ratio of total entropy generation to rate of mass of the ideal gas working fluid of the Stirling engine is minimised at the same time. Multi-objective evolutionary algorithms based on the NSGA-II algorithm have been employed, while effectiveness of the regenerator, effectiveness of low- and high-temperature heat exchangers, effectiveness of high-temperature heat exchanger, temperatures of the hot side and cold side, and dead volume ratio are considered as decision variables. After the definition of the Pareto optimal frontier, the final optimal solution has been selected using different decision-making methods such as the fuzzy Bellman–Zadeh, LINMAP and TOPSIS.
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Ahmadi et al. (2014) studied this question.
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