文章基于Matlab GUI编程开发出应力状态分析平台,并引入力学类课程课堂教学中,通过交互方式,将抽象的单元体模型和复杂繁琐的公式计算以图形直观动态表达出来。实践表明,该平台解决了学生学习过程中的易错点和难点,提高了教师课堂讲授...文章基于Matlab GUI编程开发出应力状态分析平台,并引入力学类课程课堂教学中,通过交互方式,将抽象的单元体模型和复杂繁琐的公式计算以图形直观动态表达出来。实践表明,该平台解决了学生学习过程中的易错点和难点,提高了教师课堂讲授和学生学习的效率;同时,通过实践大作业的方式,帮助学生提升编程能力和计算机应用水平,锻炼和培养学生动手和创新能力,从而更好地达到复合型工科人才的需求。Based on Matlab GUI programming, an interactional software platform for analyzing plane-stress state is developed. By applying it through the teaching practices of mechanics courses, abstract conceptions of elements and complex mechanical formula are displayed and illustrated by graphical visualization through the teaching practices of mechanics courses. It shows that the platform can help the students understand the difficult knowledge and reduce the error-prone problems, and improves the efficiency of classroom teaching and student learning. At the same time, through the practice assignments, students’ programming ability is improved and their creative ability is also inspired, so as to meet the needs of composite engineering talents better.展开更多
航空发动机压气机内部流道气流特性复杂,叶片所处的涡状流场具有高压、高速、旋转和非定常等特点,因此,亟需高效、准确地计算和预测压气机叶片复杂流场的气动特性.该文针对航空发动机叶片复杂流场的研究,通过计算流体动力学(computation...航空发动机压气机内部流道气流特性复杂,叶片所处的涡状流场具有高压、高速、旋转和非定常等特点,因此,亟需高效、准确地计算和预测压气机叶片复杂流场的气动特性.该文针对航空发动机叶片复杂流场的研究,通过计算流体动力学(computational fluid dynamics,CFD)方法,生成不同工作状态下的叶片表面气动载荷分布.采用径向基函数(radial based function,RBF)神经网络建立压力面表面气动载荷预测模型,将神经网络建模方法与流场计算相结合,神经网络方法能够对基于CFD的数据集进行学习和训练,适当地弥补来自计算流体动力学的误差,为有效预测航空发动机压气机叶片复杂流场提供了参考渠道.展开更多
文摘文章基于Matlab GUI编程开发出应力状态分析平台,并引入力学类课程课堂教学中,通过交互方式,将抽象的单元体模型和复杂繁琐的公式计算以图形直观动态表达出来。实践表明,该平台解决了学生学习过程中的易错点和难点,提高了教师课堂讲授和学生学习的效率;同时,通过实践大作业的方式,帮助学生提升编程能力和计算机应用水平,锻炼和培养学生动手和创新能力,从而更好地达到复合型工科人才的需求。Based on Matlab GUI programming, an interactional software platform for analyzing plane-stress state is developed. By applying it through the teaching practices of mechanics courses, abstract conceptions of elements and complex mechanical formula are displayed and illustrated by graphical visualization through the teaching practices of mechanics courses. It shows that the platform can help the students understand the difficult knowledge and reduce the error-prone problems, and improves the efficiency of classroom teaching and student learning. At the same time, through the practice assignments, students’ programming ability is improved and their creative ability is also inspired, so as to meet the needs of composite engineering talents better.
文摘航空发动机压气机内部流道气流特性复杂,叶片所处的涡状流场具有高压、高速、旋转和非定常等特点,因此,亟需高效、准确地计算和预测压气机叶片复杂流场的气动特性.该文针对航空发动机叶片复杂流场的研究,通过计算流体动力学(computational fluid dynamics,CFD)方法,生成不同工作状态下的叶片表面气动载荷分布.采用径向基函数(radial based function,RBF)神经网络建立压力面表面气动载荷预测模型,将神经网络建模方法与流场计算相结合,神经网络方法能够对基于CFD的数据集进行学习和训练,适当地弥补来自计算流体动力学的误差,为有效预测航空发动机压气机叶片复杂流场提供了参考渠道.
