Internal structural optimization of hollow fan blade based on sequential quadratic programming algorithm
Internal structural optimization of hollow fan blade based on sequential quadratic programming algorithm
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摘要: Several structural design parameters for the description of the geometric features of a hollow fan blade were determined. A structural design optimization model of a hollow fan blade which based on the strength constraint and minimum mass was established based on the finite element method through these parameters. Then, the sequential quadratic programming algorithm was employed to search the optimal solutions. Several groups of value for initial design variables were chosen, for the purpose of not only finding much more local optimal results but also analyzing which discipline that the variables according to could be benefit for the convergence and robustness. Response surface method and Monte Carlo simulations were used to analyze whether the objective function and constraint function are sensitive to the variation of variables or not. Then the robust results could be found among a group of different local optimal solutions.Abstract: Several structural design parameters for the description of the geometric features of a hollow fan blade were determined. A structural design optimization model of a hollow fan blade which based on the strength constraint and minimum mass was established based on the finite element method through these parameters. Then, the sequential quadratic programming algorithm was employed to search the optimal solutions. Several groups of value for initial design variables were chosen, for the purpose of not only finding much more local optimal results but also analyzing which discipline that the variables according to could be benefit for the convergence and robustness. Response surface method and Monte Carlo simulations were used to analyze whether the objective function and constraint function are sensitive to the variation of variables or not. Then the robust results could be found among a group of different local optimal solutions.
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