登录
首页 » C# » udf-fluent

udf-fluent

于 2020-12-29 发布
0 349
下载积分: 1 下载次数: 1
我要下载

代码说明：

说明：  fluent 二次开发，udf编程参考，c语言编程(Fluent udf coding c language multiphase flow)

文件列表：

udf-fluent\01-udf-porous.pdf, 255833 , 2018-01-09
udf-fluent\02-udf-sinu.pdf, 207654 , 2018-01-09
udf-fluent\03-udf-temp.pdf, 232975 , 2018-01-09
udf-fluent\04-udf-scalar.pdf, 395645 , 2018-09-26
udf-fluent\05-udf-fbed.pdf, 343871 , 2018-09-27
udf-fluent\06-udf-flow.pdf, 326592 , 2018-09-27
udf-fluent\07-udf-clarifier.pdf, 516784 , 2018-01-09
udf-fluent\08-udf-flex.pdf, 267363 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\libudf.dll, 65536 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\libudf.exp, 725 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\libudf.lib, 2040 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\log, 286 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\makefile, 5095 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\porous_plug.obj, 1163 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\udf_names.c, 593 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\udf_names.obj, 829 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\ud_io1.h, 155 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\ntx86\2ddp\user_nt.udf, 71 , 2018-01-09
udf-fluent\tut-01-udf-porous\libudf\src\porous_plug.c, 685 , 2018-01-09
udf-fluent\tut-01-udf-porous\porous_plug.c, 685 , 2018-01-09
udf-fluent\tut-01-udf-porous\porous_plug.cas.gz, 37758 , 2018-01-09
udf-fluent\tut-01-udf-porous\porous_plug.dat.gz, 52050 , 2018-01-09
udf-fluent\tut-01-udf-porous\porous_plug.msh.gz, 12381 , 2018-01-09
udf-fluent\tut-02-udf-sinu\channel.cas.gz, 36917 , 2018-01-09
udf-fluent\tut-02-udf-sinu\channel.dat.gz, 47938 , 2018-01-09
udf-fluent\tut-02-udf-sinu\channel.msh.gz, 11988 , 2018-01-09
udf-fluent\tut-02-udf-sinu\udfconfig.h, 3717 , 2018-01-09
udf-fluent\tut-02-udf-sinu\wallprof.c, 937 , 2018-01-09
udf-fluent\tut-03-udf-temp\udfconfig.h, 3717 , 2018-01-09
udf-fluent\tut-03-udf-temp\user-vis.cas.gz, 63098 , 2018-01-09
udf-fluent\tut-03-udf-temp\user-vis.dat.gz, 185976 , 2018-01-09
udf-fluent\tut-03-udf-temp\user-vis.msh, 143650 , 2018-01-09
udf-fluent\tut-03-udf-temp\viscosity.c, 978 , 2018-01-09
udf-fluent\tut-04-udf-scalar\laplace-1-00010.dat, 184902 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00020.dat, 223532 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00030.dat, 214162 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00040.dat, 204792 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00050.dat, 243426 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00060.dat, 234052 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00070.dat, 224682 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00080.dat, 215312 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00090.dat, 205942 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00100.dat, 244580 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00110.dat, 235208 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00120.dat, 225840 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00130.dat, 216472 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00140.dat, 207105 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00150.dat, 245741 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00160.dat, 236369 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00170.dat, 227001 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00180.dat, 217633 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00190.dat, 208265 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-00200.dat, 246901 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace-1-final.cas.gz, 40309 , 2018-01-09
udf-fluent\tut-04-udf-scalar\laplace-1-final.dat.gz, 31796 , 2018-01-09
udf-fluent\tut-04-udf-scalar\laplace-1.cas, 256310 , 2018-03-11
udf-fluent\tut-04-udf-scalar\laplace.cas.gz, 40099 , 2018-01-09
udf-fluent\tut-04-udf-scalar\laplace.dat.gz, 9610 , 2018-01-09
udf-fluent\tut-04-udf-scalar\laplace.msh, 67659 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\libudf.dll, 69632 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\libudf.exp, 725 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\libudf.lib, 2040 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\log, 286 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\makefile, 5095 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\mixedbc.obj, 1631 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\udf_names.c, 590 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\udf_names.obj, 861 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\ud_io1.h, 155 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\ntx86\2ddp\user_nt.udf, 67 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\libudf.dll, 58368 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\libudf.exp, 825 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\libudf.lib, 2032 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\log, 268 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\makefile, 7742 , 2016-12-05
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\mixedbc.obj, 2225 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\udf_names.c, 594 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\udf_names.obj, 848 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\ud_io1.h, 155 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf\win64\2ddp\user_nt.udf, 89 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\libudf.dll, 69632 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\libudf.exp, 725 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\libudf.lib, 2040 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\log, 286 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\makefile, 5095 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\transientMixedBC.obj, 2907 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\udf_names.c, 848 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\udf_names.obj, 1058 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\ud_io1.h, 155 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\ntx86\2ddp\user_nt.udf, 76 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\src\transientMixedBC.c, 3788 , 2018-01-09
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\libudf.dll, 59392 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\libudf.exp, 826 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\libudf.lib, 2032 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\log, 268 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\makefile, 7742 , 2016-12-05
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\transientMixedBC.obj, 4172 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\udf_names.c, 860 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\udf_names.obj, 1070 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\ud_io1.h, 155 , 2018-03-11
udf-fluent\tut-04-udf-scalar\libudf1\win64\2ddp\user_nt.udf, 98 , 2018-03-11

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • 3_1-D_CFD_scheme_ver2.zip
    The solver was mdae to solve the teat tansfrer fields with cooling and hot zone. The Gauss-seidial, ADI, Laasonnen, and Crank-Nicolson schemes are present in the code. You can handle the method you want, iteration and the level of tolerance. The code was made at the LINUX platform. Let me know if you need assistance.
    2017-09-28 19:06:51下载
    积分：1
  • isaacsrc.4_2.tar
    ISAAC采用多块网格技术求解二维或三维的Euler或者NS方程，并且提供了大量的湍流模型供使用，为相关研究人员提供了很好的参考。(ISAAC solves 2D or 3D Euler or NS equatioon based on a multiblock grid technique, also lots of turbulence models is included in the code. ISAAC provides a good reference for relative researches.)
    2009-11-17 10:05:26下载
    积分：1
  • gauss-seidel
    二维热传导扩散方程的高斯-赛德尔迭代方法。(A two-dimensional thermal diffusion problem using Gauss-Seidel iteration method.)
    2021-01-18 14:28:44下载
    积分：1
  • calte-QT
    QT编写功能及界面，实现功能：加、减、乘、除、连加、连减、连乘、连除、加减乘除混合运算、除零报错等功能，代码简单清晰，适用于刚刚接触QT的人(QT write functions and interface functionality: add, subtract, multiply, divide, even increase, even less, and even multiply, even in addition, subtraction, multiplication and division mixed operations, in addition to the zero error function, the code is simple and clear, suitable for just contact The QT)
    2013-01-11 10:26:50下载
    积分：1
  • SVD-QR-method
    svd分解，使用qr方法，编译即可运行，需要文件输入(SVD QR method，the program can run successfully, you need a file for input)
    2020-08-16 10:08:26下载
    积分：1
  • Conjugate-Gradient-Method
    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.)
    2017-03-14 15:48:15下载
    积分：1
  • 数据提取W-E-xian-2015
    说明：  通过面积加权在abaqus程序中提取温度作用数据，计算极值(The temperature action data was extracted by area weighting in abAQUs program and the extreme value was calculated)
    2020-12-23 11:49:07下载
    积分：1
  • residues
    该文件含残差点数目计算、均方差计算、信噪比计算、边缘等效视数计算(The document containing terms of the number of residues are calculated variance, SNR calculation, calculation of equivalent number of edges)
    2010-06-19 09:47:40下载
    积分：1
  • Density_Estimation
    分别采用GMM和KDE对Iris数据集进行密度建模，并进行对比。通过EM算法来确定GMM参数，通过交叉验证来确定K值(GMM and KDE respectively Iris data set of density modeling, and compared. GMM by EM algorithm to determine the parameters of K determined by the value of cross-validation)
    2011-05-05 10:37:48下载
    积分：1
  • nihe
    最小二乘法拟合进行n次多项式拟合，N用来控制拟合的次数，例如N=5时进行4次多项式拟合，还回的是拟合系数(Least squares fit polynomial n times, N is used to fit the number of control, e.g., N = 5 When quartic polynomial fitting, further back are fitting coefficients)
    2021-02-14 15:39:49下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！