TE_PHC

基于FLUENT软件的一些常用UDF实例，比较有帮助(udf example)

针对多径效应的影响，提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号，采用单样本数信号矢量构造了一个前后向矩阵束，并利用两个酉矩阵对该矩阵束进行降维处理，最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵，可在低 信噪比和单样本数情况下，有效地克服多径效应，实现同时多目标低仰角估计，相比最大似然算法，避免了谱峰搜索，计算量小。仿真结果验证了该算法的有效性。(To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method)

用MRT-LBM计算顶盖驱动流的程序，比LBGK方法更加稳定。(Codes for lid-driven flow with MRT-LBM, which is more stable than LBGK.)

对加速度数据进行二次积分，最终得到位移数据。(Double integration of acceleration data and the final displacement data.)

潮流计算中的拉丁采样算法的源程序，可运用其进行概率潮流计算(Latin sampling flow calculation algorithm source, may, in its calculation of the probability trend)

python机器学习预测分析核心算法的例程(Python machine learning prediction and analysis of core algorithm routines)

自己在各个论坛上搜集的十大算法，Dijkstra算法，Floyd算法，动态规划，分治算法，概率算法，灰色预测，聚类算法，蒙特卡洛，模拟退火算法，神经网络等等，附有算法的原理，部分含有相关的程序源代码。(In various forums to collect the ten algorithms, Dijkstra algorithm, the Floyd algorithm, dynamic programming, divide and conquer algorithms, probabilistic algorithms, gray prediction, clustering algorithms, Monte Carlo, simulated annealing, neural networks, etc., accompanied by the algorithmthe principle, in part contain the source code.)

这是用于求解精确求解zoeppritz方程的程序，可用于AVO反演，合成地震记录等(This function computes the particle displacement reflection and transmission coefficients (the relative displacement amplitudes) for a solid-solid interface, a liquid-solid interface, a solid-liquid interface, and a liquid-liquid interface. The medium on each side of a given interface is perfectly elastic. The output is the value of the reflection or transmission coefficient, specified by the user at the incidence angle anginc (see input parameters). )

说明：  fluent数值计算中在指定单元坐标加入源项的udf(Add source term to cell coordinates in numerical analysis)

fitness,适应度函数，计算适应度函数，(fitness, fitness function, calculate the fitness function,)