nei-ba43

1.5MW风力机的载荷计算：摆振力矩、挥舞力矩、俯仰力矩等(The load calculations of the 1.5MW wind turbine: Flapwise moment, edgewise moment, tilt moment.)

abaqus有限元软件umat（damage）(abaqus finite element software umat (damage))

根据极限状态方程，计算结构的可靠度和敏感度程序(According to limit state equation, the calculation of structural reliability and sensitivity procedures)

求解二阶变系数常微分方程,主要用于涡激振动中频率响应的计算(Solving second-order ordinary differential equations with variable coefficients)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method between the method and Newton' s method, it takes only a first derivative information, but to overcome the steepest descent method convergence slow shortcomings, but also to avoid the Newton method needs to be stored Hesse and disadvantages of computing inverse matrix and the conjugate gradient method is not only one of the most useful methods to solve large linear equations, solution of large-scale nonlinear optimization is one of the most effective algorithm. In various optimization algorithm, conjugate gradient method is a very important one. The advantage is that a small amount of memory required, with step convergence, high stability, and does not require any external parameters.)

说明：  实现快速离散傅里叶变换，即FFT,很有用的程序(Fast discrete Fourier transform, namely, FFT, very useful program)

一个简单的网格生成程序，操作方便，易学，类似于easymesh！(A simple grid generation program, easy to operate, easy to learn, like easymesh!)

此程序用最小二乘法拟合椭圆图像，模拟地球的形状(This program fit ellipse images using the least squares method to simulate the Earth' s shape)

音频信号通过LM386放大，计算两个矩阵之间的欧氏距离，电力系统暂态稳定程序，可以进行暂态稳定计算。( LM386 audio signal amplification, Calculation of the Euclidean distance between the two matrices, Power System Transient Stability Program, can be transient stability.)

说明：  求任意一点到任意点的距离的最小值！ 对于求解一些最短距离的问题可以提供一些帮助！(seek any point to any point of the minimum distance! For some of the shortest distance to solve the problem, it can provide some help!)