Multidisciplinary feasible method (MDF) is conventional method to multidisciplinary optimization (MDO) and well-understood by users. It reduces the dimensions of the multidisciplinary optimization problem by using the...Multidisciplinary feasible method (MDF) is conventional method to multidisciplinary optimization (MDO) and well-understood by users. It reduces the dimensions of the multidisciplinary optimization problem by using the design variables as independent optimization variables. However, at each iteration of the conventional optimization procedure, multidisciplinary analysis (MDA) is numerously performed that results in extreme expense and low optimization efficiency. The intrinsic weakness of MDF is due to the times that it loop fixed-point iterations in MDA, which drive us to improve MDF by building inexpensive approximations as surrogates for expensive MDA. An simple example is presented to demonstrate the usefulness of the improved MDF. Results show that a significant reduction in the number of multidisciplinary analysis required for optimization is obtained as compared with original MDF and the efficiency of optimization is increased.展开更多
A new reliability-based multidisciplinary design optimization （RBMDO） framework is proposed by combining the single-loop-based reliability analysis （SLBRA） method with multidisciplinary feasible （MDF） method. Th...A new reliability-based multidisciplinary design optimization （RBMDO） framework is proposed by combining the single-loop-based reliability analysis （SLBRA） method with multidisciplinary feasible （MDF） method. The Kriging approximate model with updating is introduced to reduce the computational cost of MDF caused by the complex structure. The computational efficiency is remarkably improved as the lack of iterative process during reliability analysis. Special attention is paid to a turbine blade design optimization by adopting the proposed method. Results show that the method is much more efficient than the commonly used double-loop based RBMDO method. It is feasible and efficient to apply the method to the engineering design.展开更多
指出准协同优化策略(Collaborative optimization,CO)存在的数值缺陷及其原因。针对系统级优化不满足Kuhn-Tucker条件所导致的计算困难,提出一种基于可行方向序列无约束极小化技术(Feasible direction sequential unconstrainedminimiza...指出准协同优化策略(Collaborative optimization,CO)存在的数值缺陷及其原因。针对系统级优化不满足Kuhn-Tucker条件所导致的计算困难,提出一种基于可行方向序列无约束极小化技术(Feasible direction sequential unconstrainedminimization technology,FD-SUMT)外点法的改进协同优化策略(Enhanced collaborative optimization with FD-SUMT method,ECO-FSM)。在系统级优化中使用FD-SUMT外点法,该方法不依赖Lagrange乘子并且能够将系统级设计变量限定在设计变量可行域内,避免传统SUMT外点法设计变量越界所导致的异常。利用学科间动态不一致信息更新系统级优化中的罚因子以加速学科间的协调。利用测试问题检验ECO-FSM的性能,并与其他的CO进行比较研究。研究结果表明ECO-FSM消除了系统级优化中设计变量越界的现象,收敛性、数值稳定性以及收敛速度得以显著提高。将ECO-FSM用于亚声速喷气式客机总体方案优化设计,优化结果表明ECO-FSM具有工程实用性。展开更多
文摘Multidisciplinary feasible method (MDF) is conventional method to multidisciplinary optimization (MDO) and well-understood by users. It reduces the dimensions of the multidisciplinary optimization problem by using the design variables as independent optimization variables. However, at each iteration of the conventional optimization procedure, multidisciplinary analysis (MDA) is numerously performed that results in extreme expense and low optimization efficiency. The intrinsic weakness of MDF is due to the times that it loop fixed-point iterations in MDA, which drive us to improve MDF by building inexpensive approximations as surrogates for expensive MDA. An simple example is presented to demonstrate the usefulness of the improved MDF. Results show that a significant reduction in the number of multidisciplinary analysis required for optimization is obtained as compared with original MDF and the efficiency of optimization is increased.
基金Supported by the National High Technology Research and Development Program of China("863" Program) (2009AA04Z418, 2007AA04Z404)the National "111" Project(B07050)~~
文摘A new reliability-based multidisciplinary design optimization （RBMDO） framework is proposed by combining the single-loop-based reliability analysis （SLBRA） method with multidisciplinary feasible （MDF） method. The Kriging approximate model with updating is introduced to reduce the computational cost of MDF caused by the complex structure. The computational efficiency is remarkably improved as the lack of iterative process during reliability analysis. Special attention is paid to a turbine blade design optimization by adopting the proposed method. Results show that the method is much more efficient than the commonly used double-loop based RBMDO method. It is feasible and efficient to apply the method to the engineering design.
