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Using genetic algorithms to improve the thermodynamic efficiency of gas turbines designed by traditional methods

机译:使用遗传算法提高传统方法设计的燃气轮机的热力学效率

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摘要

A method for optimizing the thermodynamic efficiency of aeronautical gas turbines designed by classical methods is presented. This method is based in the transformation of the original constrained optimization problem into a new constrained free optimization problem which is solved by a genetic algorithm. Basically, a set of geometric, aerodynamic and acoustic noise constraints must be fulfilled during the optimization process. As a case study, the thermodynamic efficiency of an already optimized by traditional methods real aeronautical low pressure turbine design of 13 rows has been successfully improved, increasing the turbine efficiency by 0.047% and reducing the total number of airfoils by 1.61%. In addition, experimental evidence of a strong correlation between the total number of airfoils and the turbine efficiency has been observed. This result would allow us to use the total number of airfoils as a cheap substitute of the turbine efficiency for a coarse optimization at the first design steps.
机译:提出了一种通过经典方法设计的优化航空燃气轮机热力学效率的方法。该方法基于将原始约束优化问题转换为新的约束自由优化问题,并通过遗传算法对其进行求解。基本上,在优化过程中必须满足一组几何,空气动力学和声学噪声约束。作为一个案例研究,已经成功地改进了已经通过传统方法优化的13排航空低压涡轮实际设计的热力学效率,涡轮效率提高了0.047%,翼型总数减少了1.61%。另外,已经观察到翼型总数与涡轮效率之间有很强相关性的实验证据。这一结果将使我们能够将机翼的总数用作涡轮效率的廉价替代品,以便在最初的设计步骤中进行粗略优化。

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