upwind

《高等计算力学》教材的源程序,非线性有限元计算程序(" Advanced Computational Mechanics" of the source material)

三次样条插值函数实现 运行后画出曲线图，并得到插值函数表达式。(spline3)

说明：  用于三维条件下的推板造波法udf,冲程与周期可修改，附带消波udf和cas文件(generating waves with pushboard under 3D condition)

matlab中实现箭头的程序，直接作为函数使用。(matlab realize the arrow in the procedure)

说明：  常用于分析降水、径流、气温等要素时间序列的趋势变化，其优点在于样本不需要遵循某一特定的分布，而且很少受到异常值的的干扰，计算简便。(It is often used to analyze the trend change of time series of factors such as precipitation, runoff and air temperature. Its advantage is that the sample does not need to follow a specific distribution, and is rarely disturbed by outliers, so it is easy to calculate.)

说明：  Galileo单频定位程序，能基于rinex文件实现高精度定位，供编写时参考(Galileo single-frequency positioning program can achieve high-precision positioning based on RINEX file for reference when writing.)

地球物理偏移相关程序包，能实现时间偏移、深度偏移、及逆时偏移等，编写语言：Matlab。(Geophysical migration coding package, time migration, depth migration, reverse time migration, the writing language: Matlab.)

abaqus三维8节点实体单元Fortran子程序，里面有详细的注释，有单元开发兴趣的同学可以下载学习(The fortran subroutine of the 8 node solid element of ABAQUS, with detailed comments in the unit development interest students can download learning)

适合于稀薄流动计算的气体动力学格式源码，该源码为xukun老是JCP论文中的算例一致(UGKS1D- shock structure calculation using Unified Gas-Kinetic Scheme)

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.)