基于叶片角度和厚度分布的反应水轮机模型停留叶片优化设计

U. Shrestha, Jungwan Park, Young-Do Choi
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引用次数: 1

摘要

优化是工程领域的新兴技术,其目的是提高机械部件的性能。同样,即将到来的涡轮机械设计需要更高效,更具成本效益和易于制造。许多优化技术已经实现了高效涡轮的发展。在本研究中,优化主要局限于混流式、泵式水轮机等反应式水轮机的停留叶片。在反应式水轮机(法兰式水轮机、泵式水轮机)中,停留叶片主要用于引导水流流向导叶和转轮。螺旋机匣的三维流场高度畸变,产生二次流。然而,停留叶片保持了均匀的流场。由于停留叶片的流场稳定,提高了流道的性能。因此,为了改善流道周围的流场,需要更好地设计停留叶片。停留叶片的设计参数是叶片从前缘到后缘的角度分布和厚度分布。叶片的角度分布控制着流向流道的流场方向和动量的稳定性。同样,厚度分布将保持停留叶片的轮廓。停留叶片的优化改善了涡轮效率、流动均匀性和压力损失。由于多目标遗传算法不受任何特定解的支配,满足所有目标函数,因此选择多目标遗传算法(MOGA)进行导风标优化。MOGA是一种更现实的优化方法。进行了性能验证试验,比较了实验方法和数值方法的结果。优化后的停留叶片改善了停留叶片周围的流动均匀性。
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Optimal Design of Reaction Hydro Turbine Model Stay Vane by Vane Angle and Thickness Distribution
Optimization is uprising technology in the engineering field, which enhance the performance of mechanical components. Likewise, upcoming turbomachinery designs need to be more efficient, cost-effective and easy manufacturing. Many optimization techniques have implemented for the development of efficient turbomachines. In this study, the optimization has mostly confined to the stay vane of reaction turbine like Francis, Pump Turbine etc. Stay vanes are mainly used to direct the flow towards guide vane and runner in the reaction type turbine (Francis, Pump Turbine). The three-dimensional flow field from the spiral casing is highly distorted, which causes secondary flow. However, the uniform flow field has maintained by stay vane. Due to steady flow field from stay vane, the performance of the runner has improved. Therefore, the better design of stay vane has been required for the improvement of the flow field around the runner passage. The design parameters of the stay vane are vane angle distribution and thickness distribution from leading edge to trailing edge. The vane angle distribution controls the stability of flow field direction and momentum towards the runner. Similarly, the thickness distribution will maintain the profile of the stay vane. The optimization of stay vane has improved turbine efficiency, flow uniformity, and pressure loss. The multi-objective genetic algorithm (MOGA) was selected for the optimization of stay vane because it satisfies all the objective functions without being dominated by any specific solution. MOGA is a more realistic approach to optimization. The validation test of performance is conducted to compare the result of experimental and numerical methods. The optimized stay vane has improved the flow uniformity around the stay vane.
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