Yuan-Zhuo Ma , Jia Wei , Wei-Dong Liu , Peng-Peng Zhi , Zhen-Zhou Zhao , Chang Xu , Hong-Shuang Li
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引用次数: 0
Abstract
Design
optimization of the large-scale composite wind turbine blade during conceptual design is one of the key processes of the cost decreasing and benefit increasing for current wind power industry. It however, still remains several key issues, such as lack of a fully parametric process, suffering from a huge computational burden and being easily trapped into local optimum. To remedy these issues, this paper proposes a design optimization method for composite wind turbine blade using Complete Constrained Expected Improvement-Subset Simulation Optimization (CCEI-SSO). A fully parametric Finite Element Analysis (FEA) coded by ANSYS parametric design language of the composite wind turbine blade is firstly proposed, which can be linked to an arbitrary optimization method to form a unified joint simulation framework. To enhance the performance of the optimization process, CCEI-SSO is further proposed, where an adaptive Kriging model leveraging CCEI infill strategy is deeply coupled into each simulation level of SSO to keep balance of optimality and feasibility within very limited number of real FEAs. Inheriting from the random nature within SSO, local optimum is well avoided as well. A case of the design optimization of a 10 MW wind turbine blade is considered to demonstrate the performance of the proposed method.
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