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密度，比热，热导率，粘性系数随压力、温度变化的UDF(UDF of density, specific heat, thermal conductivity, viscosity coefficient with pressure and temperature.)

用C++编写的一维和二维快速傅里叶变换程序(Prepared with C++ one-dimensional and two-dimensional fast Fourier transform procedure)

非圆形离散元程序，通过采用非圆形颗粒实现康转动性能(Non-circular discrete element program, through the use of non-spherical particles achieve Kang rotation capability)

程序是关于计算两相黎曼问题的一个求解器。可以直接设置。(The code is a solver about the two-phase Riemann problem. the user can use it directly.)

％ 奇异值分解 (sigular value decomposition,SVD) 是另一种正交矩阵分解法；SVD是最可靠的分解法， ％ 但是它比QR 分解法要花上近十倍的计算时间。[U,S,V]=svd(A)，其中U和V代表二个相互正交矩阵， ％ 而S代表一对角矩阵。 和QR分解法相同者， 原矩阵A不必为正方矩阵。 ％ 使用SVD分解法的用途是解最小平方误差法和数据压缩。用svd分解法解线性方程组，在Quke2中就用这个来计算图形信息，性能相当的好。在计算线性方程组时，一些不能分解的矩阵或者严重病态矩阵的线性方程都能很好的得到解( Singular value decomposition (sigular value decomposition, SVD) is another orthogonal matrix decomposition method SVD decomposition is the most reliable method, but it takes more than QR decomposition near ten times the computing time. [U, S, V] = svd (A), in which U and V on behalf of two mutually orthogonal matrix, and the S on behalf of a diagonal matrix. And QR decomposition are the same, the original matrix A is no need for the square matrix. The use of SVD decomposition method are used as a solution of least squares error method and data compression. Using SVD decomposition solution of linear equations, in Quke2 on to use this information to calculate the graphics performance quite good. In the calculation of linear equations, some indecomposable matrix or serious pathological matrix of linear equations can be a very good solution)

数值计算各算法的程序,包括:牛顿迭代法,超松驰迭代法,微分法等.对于初学数值分析这门课程的人有很大的帮助.(Numerical calculation procedure of the algorithm, including: Newton iteration, ultra-relaxation iteration method, differential method and so on. Beginner numerical analysis for this course were very helpful.)

数值分析实验1.明确插值多项式和分段插值多项式各自的优缺点； 编程实现拉格朗日插值算法，分析实验结果体会高次插值产生的龙格现象；(Experiments of numerical analysis 1. Define the advantages and disadvantages of interpolation polynomials and piecewise interpolation polynomials. The Lagrange interpolation algorithm is programmed, and the Runge phenomenon produced by high-order interpolation is analyzed.)

the structure of the DG-FEM is very similar to that of the finite element method (FEM), there are several fundamental differences. In particular, the mass matrix is local rather than global and thus can be inverted at very little cost, yielding a semidiscrete scheme that is explicit. Furthermore, by carefully designing the numerical flux to reflect the underlying dynamics, one has more flexibility than in the classic FEM to ensure stability for wavedominated problems. Compared with the FVM, the DG-FEM overcomes the key limitation on achieving high-order accuracy on general grids by enabling this through the local element-based basis

最优潮流计算程序（使用电力系统专业，属于非线性规划问题）．(optimal power flow calculation procedure (using power systems professional, is Nonlinear Programming).)

复数矩阵的运算、包括乘、除、加、减、求逆等(Including all operations of the matrix)