NOAH LAND SURFACE MODLE SOURCE CODE

umat abaqus plasticity

说明：  高质量的分子动力学建模学习入门，很有用的短期提升。(High quality molecular dynamics modeling learning introduction, very useful for short-term promotion.)

VUMAT子程序，做复合材料渐进损伤分析(VUMAT subroutine, do composite progressive damage analysis)

a program which analyzes a 2D fluid flow using the reduced basis method

说明：  forward处理程序，使用于煤炭、石油、天然气行业(forward processing procedures used in coal, oil, gas industry)

johnson-cook模型umat 适用于应变硬化，应变率硬化，温度硬化的材料，例如铝合金(johnson-cook model umat)

该程序用于瞬变电磁勘探近区场计算，只要输入不同参数便可以得到近区场的视电阻率(The procedure transient electromagnetic exploration for near field calculations, as long as the input parameters can be different near field apparent resistivity)

说明：  应用visual studio软件，将疲劳三个方向应力合成主应力(Used to stress stress synthesis in three directions as fatigue hot spot stress)

双线性插值FORTRAN计算程序,用于FORTRAN９０(Bilinear interpolation)

说明：  CUDA Fortran 高效编程实践_科学家和工程师特供 2007 年以来，以 nVidia GPU 为代表的加速器并行计算风起云涌，带有加速器的超级计 算机在 TOP500 中的份额逐年增加，支持加速器的主流应用软件也呈爆炸式增长，研究加速 器计算的技术人员数以百万计，世界范围内的大学、研究机构竞相开设相关课程。 目前流行的 GPU 通用编程语言是 CUDA C 和 OpenCL. 它们均是 C/C++语言的扩展，因 此可以方便地将 C/C++代码移植到 GPU 上。但对于科学与工程计算中的重要编程语言 Fortran，无法直接地改写为 CUDA C 或 OpenCL。很多久经考验的应用程序都是用 Fortran 开发，如果完全改写，工作量巨大，而且有不可估量的稳定性风险。 为使 Fortran 应用能够使用 GPU 加速，The Portland Group 设计了 CUDA Fortran 语言， 并在自家的 PGI 编译器中支持。气象、理论物理等领域的应用经过简单的改造，就能够利 用 GPU 的强大计算能力。(CUDA FORTRAN efficient programming practice Since 2007, with NVIDIA GPU as the representative of accelerator parallel computing, the share of supercomputers with accelerators in top 500 has increased year by year, and the mainstream application software supporting accelerators has also grown explosively. There are millions of technicians studying accelerator computing, and universities and research institutions around the world are competing to offer relevant courses. To enable FORTRAN applications to use GPU acceleration, the Portland group designed CUDA FORTRAN language, which is supported in its own PGI compiler. The application of meteorology, theoretical physics and other fields can make use of the powerful computing power of GPU after simple transformation.)