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  • 用fluent3DMeshToFoam转化网格的时候报错

    Meshy
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    bestucanB

    缺这个包:binutils

    或者路径没配置对,可以用echo $PATH看看有没有/usr/bin这一项

  • 环流强度

    Fluent
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    是的,老师,速度有的是0

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    Prometheus10P

    @李东岳 好的~谢谢东岳老师:xinxin:

  • 关于pimpleFoam的外循环和松弛因子

    OpenFOAM
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    N

    刚接触OpenFoam不就,疑问可能有点多
    请问在pimpleFoam对松弛因子和* Final的松弛因子进行设置,如果设置了残差控制,在满足跳出外循环的残差条件之后是不是才会采用* Final设置的松弛因子进行计算?
    如果达到设置的外循环次数后都没满足残差要求的话是不是最后一次循环还是用的原来的松弛因子计算?
    我在其他地方有看到说最后一次需要采用一次松弛因子为1.0计算才能获得正确的结果,松弛因子设置为1.0是不是就相当于不进行松弛设置?
    但是我在我自己写的一个求解器中,不在fvSolution中进行松弛设置和设置松弛因子为1.0得到的结果不一样,这又是为什么?

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    P

    英国谢菲尔德大学(The University of sheffield)Energy2050团队(http://energy2050.ac.uk)在招一个做CFD方向的全奖博士,做旋转填料床反应器捕捉二氧化碳的CFD仿真研究,对此职位感兴趣的研究生或者优秀本科毕业生可以申请(可直博),目前的申请截止日期是2022年7月22日(可能推迟),如来不及,入学时间可推迟到明年一月。

    谢菲尔德大学,世界百强名校,著名的CFD仿真软件Fluent的发源地,课题组学术氛围很好,适合静心搞科研。课题组在CFD领域有几十年的研究基础,在CCUS领域有丰富的研究资源,课题紧扣国内火热的"双碳"主题,该细分方向组里有7年的研究基础了,可以在前人的基础上接着做。

    具体招聘信息如下:
    We have a fully funded PhD studentship and look for applicants open to both UK and international students: Engineering doctorate (EngD): Predicting performance of intensified carbon capture inside rotating packed beds using CFD modelling

    If you know any good students from China, or the UK, please encourage them to apply.
    Any questions then let them to contact Professor Lin Ma: https://www.sheffield.ac.uk/mecheng/people/academic/lin-ma

    The advert is on findaphd.com: https://www.findaphd.com, search for the project 搜索 predicting performance of intensified carbon capture inside rotating packed beds using cfd modelling。

    或直接通过以下链接:https://www.findaphd.com/phds/project/engineering-doctorate-engd-predicting-performance-of-intensified-carbon-capture-inside-rotating-packed-beds-using-cfd-modelling/?p145128#opennewwindow

    Please make sure that they apply through the university of sheffield website: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying.

    课题介绍:

    Carbon capture is considered the only technology able to decarbonise the hard-to-abate industries. many of these industries utilise legacy sites with little space for large new unit operations required in conventional carbon capture. rotating packed beds (RPB) look to solve this problem by intensifying carbon capture and reducing the footprint required by up to ten times, while also significantly decreasing the capital cost of these units. when combined with proprietary solvents, it is believed the cost of capture can be reduced to $30/tonne CO2 in some cases, helping to enable the rapid uptake of carbon capture and progression towards net zero.

    RPB are a novel technology that utilise the principles of process intensification to enhance the performance of mass transfer processes between fluids. given the application of rpb to the field of CO2 capture is relatively new, there is uncertainty regarding the impact of different process variables on the performance of the rpb that would otherwise require a significant amount of practical experimentation to investigate. computational fluid dynamics can enable the process to be accurately modelled, allowing for quick and inexpensive prediction of performance under various conditions.

    In this project a rotating packed bed absorber will be modelled in ansys fluent, with validation of the model’s outputs through use of the 1 tonnes of co2 per day (TPD) pilot-scale rotating packed bed absorber at the university of sheffield’s translational energy research centre. Initial research will involve investigating the impact of operational conditions and physical properties of the solvent on capture performance. As the project continues, the scope will widen to include sensitivity analysis of design parameters and the impact of scaling the RPB absorber on the existing project outputs and learnings. Additionally, further rotating unit operations could also be investigated.

    This project will utilise and develop your knowledge surrounding CFD modelling, mass and heat transfer, reaction kinetics and chemical equilibria. You will work closely with carbon clean, a global leader in the development of carbon capture technology and pioneers in the use of RPB for industrial decarbonisation. Your findings could directly impact the design and operation of commercial working carbon capture facilities, supporting the pathway to net zero.

    We are seeking applicants to start in september 2022.

    The project will be part of the EPSRC-supported centre for doctoral training in resilient decarbonised fuel energy systems. The student who undertakes it will be one of a cohort of over 50 students in a broad range of disciplines across the universities of sheffield, nottingham and cardiff.

    The research work will be based in the energy research group within the department of mechanical engineering and the translational energy research centre (TERC) at sheffield which is a brand new, high profile, innovation focused national research facility. You will be working within an exciting and dynamic group with approximately over 60 researchers undertaking a broad area of energy research with approximately three years' extensive research time in industry, preparing for high-level careers in the energy sector.

    Funding notes
    The studentship will cover full university fees and a tax-free, enhanced annual stipend of £20,352, including £16,062 (2022/2023) a year for four years and a stipend enhancement of £3,750 per annum.

    英国的全奖机会非常少,机会难得,欢迎各位优秀的CFDer申请!

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    李东岳

    @肖艺 只是看过相关的影片.. :zoule:

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    Z

    @chenboyao 天哪,膜拜大佬,成功解决了TAT

  • 粒子穿过可变形界面的问题

    CFD彩虹条
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    凤雏岂能消逝

    @bestucan 真的非常感谢您的建议。对于二维的case尝试了一下,我设置一个不变形的界面,进入filter区域的粒子数量大约是等同于流通量。但我手上的计算资源和代码的优化方面并不乐观,耗时久。如果界面变成可变形的情况,计算时间应该会加倍,时间上等不起。

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    bestucanB

    @李东岳 我就记得我之前搞过,后来坑太深了,就没搞了。

    这些涉及到图形处理的各个层,又是平台不同,又是商业公司夹私货,那些个组件的名字本来就乱七八糟,缩写规则还不一样。想短时间了解就更乱。

    大概就是,可以软件渲染(OSMesa),可以硬件渲染(EGL)。
    其实都是基于Open GL,就这三个英语词空格隔开一起搜都一大堆讲更多术语关系的文章。

    paraview 默认用软件渲染,想要硬件渲染把 EGL 编译选项打开就行了,这就有个忘了打开报错的:
    https://discourse.paraview.org/t/build-paraview-for-nvidia-gpu/8309
    但这个是单GPU的,不知道多GPU的怎么搞,

    我的GPU是当显卡用的,一开paraview就调用GPU,当然是为“图形界面渲染"的,不是为“paraview渲染”的,这俩还都是opengl下面的,那些名词太乱了。

    我试着编了一下 pvserver能多线程跑在GPU上,
    Screenshot from 2022-06-11 15-52-46.png
    就是这个方法:
    https://github.com/Kitware/ParaView/blob/master/Documentation/dev/build.md

    当然编译之前已经安装好nvidia自带的驱动了。

    nvidia 早些年自己出过 paraview 的插件:
    https://www.nvidia.com/en-us/data-center/index-paraview-plugin/
    不过是针对 paraview 5 的

  • 发现虚拟机上openfoam12的一个bug

    OpenFOAM
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    V

    虚拟机上openfoam10和11没有问题

  • Fluent meshing totorials

    Meshy
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    这个主要看cfd之道公众号流沙的教程就可以学会了(哈哈哈哈,你是我拿到注册码之后回复的第一个人)

  • kvm也挺奇葩的

    CFD彩虹条
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    李东岳

    买了个迈拓维矩的,这个可以切换,并且用起来目前来看还可以

  • OpenFOAM并行计算

    OpenFOAM
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    D

    大佬们,想请教下为什么OpenFOAM自定义并行计算时,初始化(这边初始化是指下述的代码)有时候很快2-3s,有时候需要很久1-2min(测试的时候没有其他程序运行)。
    下述是我自定义的并行计算初始化代码:

    scalarField MyField(5*N,0); List<scalarField> AllMyField_List(Pstream::nProcs()); AllMyField_List[Pstream::myProcNo()] = MyField; Pstream::gatherList(AllMyField_List); Pstream::scatterList(AllMyField_List); scalarField AllMyField(ListListOps::combine<scalarField>(AllMyField_List, accessOp<scalarField>()));

    其中,N为所有网格单元的数量,N=86400。程序是有个变量,我将其分配到各个线程进行计算,在总线程中进行收集。
    此外,程序中不止这一个变量,有五六个需要同样操作的变量。之前测试过,如果N很小的时候,初始化过程很快,但是当N增大时,初始化时间就完全不一样了。想请教下如何解决这个bug。

  • fluent中使用的是同位网格吗?

    Fluent
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    L

    fluent使用的是交错网格加重叠网格技术

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    @bestucan 在别人电脑上是正常的 ,很奇怪,我最后重装电脑解决了

  • 在流场内部加一个速度场

    OpenFOAM
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    A

    @coolhhh 谢谢老师!

  • CFD和LBM的优劣势

    CFD彩虹条
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    C

    @leo_chou 大批量的工业算例(本身可能不复杂,但就是工况多),LBM是不是也需要大规模网格和较长时间?工业应用CFD对时间的要求基本上是小时级别的。

    另外好奇问下,复杂几何下的LBM如何,需要湍流的LBM呢?我觉得大部分案例,复杂几何+湍流模型是标配,没有湍流的话可能有多相或者化学反应啥的,这些LBM是不是会更强一些?

  • 如何求整个流体域的y+

    Algorithm
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    李东岳

    整个域中的摩擦速度用的是当地的还是壁面的呢?

    壁面的,我刚刚验证过,确定

    替代文字

  • 大家发朋友圈越来越少了

    CFD彩虹条
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    @李东岳 这两年的学生真的是过的没劲。。

  • 非定常CFL数相关问题

    OpenFOAM
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    东方白杨

    @李东岳 在 非定常CFL数相关问题 中说:

    就是简单的一个传输的标量,附加一个s的传输方程

    哦哦,谢谢老师!!