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COMPARISON OF BLISS 2000 AND CO IN TURBINE BLADE MDO FOR AIRCRAFT ENGINE

机译:Bliss 2000与CO与飞机发动机涡轮叶片MDO的比较

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摘要

In this paper, the two methods of CO and BLISS 2000 are compared by using a classical numerical example firstly. The results show that the BLISS 2000 performs better in both computational accuracy and efficiency, because the scale of the optimization problem, such as the number of variables and constraints, in the BLISS 2000 is less than that in the CO. Moreover, the BLISS 2000 optimizes directly the system objectives while the CO focuses on decreasing the discrepancy between the coupled variables in different fields. The two methods are then applied to an aerodynamics-thermal-structure coupled design problem for the turbine blades of an aircraft engine. Based on the results of sensitivity analysis, the number of design variables is reduced from 34 to 12. To eliminate the impact of the surrogate models on the different MDO algorithms as much as possible, the same initial Kriging surrogate models are not refreshed during the MDO procedures. Without the high fidelity simulation such as CFD and FEM analysis in the MDO processes, the BLISS 2000 method shows the more powerful capability of the convergence than that of the CO method, as shown in the numerical example. The optimization steps of the system level for BLISS 2000 are approximate 1/5 of those for CO, and the iteration number of step in the sub-system level with BLISS 2000 is only about 1/8 of that with CO. Based on the weight sum of two objectives, the BLISS 2000 shows more robust than the CO because both weight reduction and aerodynamic efficiency are improved in the BLISS 2000 but only the blade weight reduction is gained in the CO. For other multi-objective optimization approaches, however, it still needs to be demonstrated through more studies.
机译:在本文中,通过首先使用经典的数值示例来比较CO和Bliss 2000的两种方法。结果表明,Bliss 2000以计算准确性和效率而言更好,因为优化问题的规模,例如变量和约束的数量,在Bliss 2000中的规模小于CO中的变量和约束。此外,幸福的2000直接优化系统目标,而CO专注于降低不同字段中耦合变量之间的差异。然后将这两种方法应用于飞机发动机的涡轮叶片的空气动力学 - 热结构耦合设计问题。基于灵敏度分析的结果,设计变量的数量从34到12减少。为了尽可能地消除代理模型对不同MDO算法的影响,在MDO期间不刷新相同的初始Kriging代理模型程序。如果在MDO工艺中的CFD和有限元分析如CFD和有限元分析,则Bliss 2000方法示出了比数值示例中所示的收敛性更强大的收敛能力。 Bliss 2000的系统级的优化步骤近似于CO的1/5,并且具有Bliss 2000的子系统级别中的步骤的迭代次数仅为CO的1/8。基于重量两个目标的总和,Bliss 2000示出了比CO更稳健,因为在Bliss 2000中重量减轻和空气动力学效率都得到了改善,但在CO中只获得了叶片重量。然而,对于其他多目标优化方法,它仍然需要通过更多的研究证明。

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