基于人工神经网络的静子叶片优化设计

Stator optimization using artificial neural network

关键词:  航空发动机  风扇  叶片  最优设计,人工神经元网络

Key words:  Aircraft engine  Fan  Blade  Optimum design  Artificial neural network

摘要:

采用NURBS参数化构型技术以及人工神经网络技术,对某两级风扇的第二级静子根部叶型进行优化改型。优化后,非设计点处该静子根部至中部流动得到较大改善,总压恢复系数有一定的提高。风扇总压比有较大增加,绝热效率基本不变。优化结果表明,该方法能够对静子叶片进行较好的优化改善,能够提高优化效率,减少优化时间,具有一定的实用价值。

Abstract:

The second stage stator which was parameterized applying NURBS(Non-Uniform Rational B-Spline)in a two stage fan was optimized by using artificial neural network.The flow field of the optimized stator was improved at the off-design condition from hub to mid.The total pressure recovery coefficient of the stator increased.Total pressure ratio of the fan was improved and adiabatic efficiency kept the same.The result shows that this method could improve stator blade efficiently and can be used in stator design as a new optimization method.