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首页> 外文期刊>American Journal of Mechanical Engineering >Alternative Equations to Compute the Network and the Thermal Efficiency of the Irreversible Diesel Cycle Using Genetic Algorithm
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Alternative Equations to Compute the Network and the Thermal Efficiency of the Irreversible Diesel Cycle Using Genetic Algorithm

机译：使用遗传算法计算不可逆柴油机循环网络和热效率的替代方程

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摘要

In the current study, the effect of specific heat ratio, compression ratio, and the maximum to minimum temperature ratio of cycle on the thermal efficiency and the Network of irreversible Diesel cycle have been investigated. For this purpose, numerical solution and multi-objective genetic algorithms with a Pareto optimization method are used to determine the optimum values of specific heat ratio, compression ratio, and the maximum to minimum temperature ratio of cycle. The optimized values of the objective functions (namely Network and thermal efficiency) are then determined by using these vales. The numerical solution shows that the maximum Network and thermal efficiency is obtained simultaneously when the values of specific heat ratio, compression ratio, and the maximum to minimum temperature ratio of cycle are 1.3, 17.7, and 6.0, respectively, and these parameters are obtained by multi-objective genetic algorithms with a Pareto optimization method as 1.3, 17.57, and 6.0. The results obtained from current work are presented in the form of optimal equations for Network thermal efficiency in term of compression efficiency, expansion efficiency and compression ratio of the cycle. The results of current research work can provide a significant insight for optimal design of internal combustion engines including irreversibility.
机译：在当前的研究中，研究了比热比，压缩比和循环的最大/最小温度比对热效率和不可逆柴油循环网络的影响。为此，使用数值解法和具有帕累托优化方法的多目标遗传算法来确定比热比，压缩比和循环的最大与最小温度比的最佳值。然后使用这些值确定目标函数的最佳值（即网络和热效率）。数值解表明，当比热比，压缩比和循环的最大与最小温度比分别为1.3、17.7和6.0时，可以同时获得最大网络效率和热效率，并且这些参数可以通过以下方式获得：多目标遗传算法，其中Pareto优化方法为1.3、17.57和6.0。从当前工作中获得的结果以网络热效率的最佳方程式的形式给出，即压缩效率，膨胀效率和循环的压缩比。当前研究工作的结果可以为内燃机的最佳设计（包括不可逆性）提供重要的见识。

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