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

机译:航空发动机涡轮叶片MDO中BLISS 2000和CO的比较

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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:本文首先通过经典的数值例子对CO和BLISS 2000这两种方法进行了比较。结果表明,BLISS 2000在计算精度和效率上都表现更好,这是因为BLISS 2000中优化问题的规模(例如变量数和约束条件)小于CO中的问题。此外,BLISS 2000直接优化系统目标,而CO专注于减少不同领域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涡轮叶片的空气动力-热结构耦合设计问题。根据敏感性分析的结果,设计变量的数量从34个减少到12个。为了尽可能消除代理模型对不同MDO算法的影响,在MDO期间不会刷新相同的初始Kriging代理模型程序。如数值示例所示,如果没有MDO流程中的高保真度模拟(例如CFD和FEM分析),则BLISS 2000方法显示的收敛能力比CO方法更强大。 BLISS 2000的系统级优化步骤约为CO的1/5,而BLISS 2000的子系统级优化步骤的迭代数仅为CO的1/8。两个目标的总和,BLISS 2000比CO更坚固,因为在BLISS 2000中既减轻了重量,又提高了空气动力效率,但在CO中仅降低了叶片的重量。但是,对于其他多目标优化方法,它仍然需要通过更多的研究来证明。

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