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因为安装的intel fortran或是vs的版本的差异,其他主机上编译的程序在另外的电脑运行时,常常会出现这种问题。此外,自己电脑安装多个版本软件时,也会时环境变量里的dll不是自己程序依赖的动态库,此时可以尝试找到自己程序依赖的动态库,将dll文件拷贝到程序路径下。
fortran可参考路经:C:\Program File(x86)\Common Files\Intel\Shared Libraries\redist\intel64\compiler
注意64位还是32位

Definition

  • CFM refers to the method of measuring the volume of air moving through a ventilation system or other space, also known as “Cubic Feet per Minute.”This is a standard unit of measurement found in many forms of ventilation, both in vehicle and in home heating, ventilation and air conditioning systems.https://www.reference.com/vehicles/cfm-airflow-20969775e326400d

  • Cubic feet per minute (CFM) is a measure used in Industrial hygiene and ventilation engineering. It describes the rate of flow of a gas or air volume into or out of a space.A standard measurement of airflow that indicates how many cubic feet of air pass by a stationary point in one minute. The higher the number, the more air is being forced through the system. The volumetric flow rate of a liquid or gas in cubic feet per minute. 1 CFM equals approximately 0.47 liter per second. https://www.convertunits.com/info/cfm

    Convert $Flux$ to $CFM$

    $1 kg / s=1 m^3 \cdot \rho/s=3.280839895^3 \cdot ft^3/s \cdot \rho= 2118.88 \cdot \rho/min$

连接远程服务器

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sudo apt install openssh-client
ssh user@192.168.1.111 -p 1234

图形化

  • 安装x11
    sudo apt install x11-common
  • 连接服务器
    ssh -X user@192.168.1.111 -p 1234

本地文件夹形式访问远程服务器

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Ctrl+Shirt+T打开终端
Ctrl+L查看当前文件夹路径

Kriging模型:Fortran代码,没有采用EI加点准则,目前挑选Pareto Front上的点进行校验和重新训练
modeFrontier:优化中可以利用代理模型预测,无法加点
Dace:Matlab中的代理模型工具,没有仔细研究,有一些参考文档

出发点

使用Nektar++开源软件必须导入其支持的.xml格式,当前Nektar++支持msh格式,但是用gmsh生成网格可能不太方便,自己也不熟悉。所以现在使用其他网格生成软件导出的unv格式网格,在gmsh中将网格转化成unv格式。

实现

虽说gmsh支持unv网格转化为msh网格,但是在转化过程中常常会出现边界信息丢失或是混乱的状况。gmsh是根据几何的编号来划分物理边界的。这里生成网格后,对边界分配color ID,然后编写简单的程序将color ID强制分配给physical IDmaterial ID,最后利用gmsh转化为msh网格。

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The discipline of acoustics is intimately related to fluid dynamics.Many sounds that are technologically important in industrial applications are generated by and propagated in fluid flows. The phenomena associated with sounds can therefore be understood and analyzed in the general framework of fluid dynamics. (The governing equations for acoustics are indeed the same as the ones governing fluid flows.)
The main challenge in numerically predicting sound waves stems from the well-recognized fact that sounds have much lower energy than fluid flows, typically by several orders of magnitude. This poses a great challenge to the computation of sounds in terms of difficulty of numerically resolving sound waves, especially when one is interested in predicting sound propagation to the far field. Another challenge comes from the difficulty of predicting the very flow phenomena (for example, turbulence) in the near field that are responsible for generating sounds.

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程序:python.scikit,matlab.DACE