fluent湍流模型总结

总结是在项目、工作、时期后，对整个过程进行反思，以分析出有参考作用的报告，用于为以后工作的实施，提供明确的参考。所以，编写一份总结十分重要，以下是小编整理的关于《fluent湍流模型总结》，供大家阅读，更多内容可以运用本站顶部的搜索功能。

第一篇：fluent湍流模型总结

FLUENT软件的学习总结

通过这段时间对FLUENT软件的学习，我发现这个软件有庞大的参数设置和边界条件设置，同时要应用好这个软件也需要扎实的流体力学、传热学、导热学等基础知识。在逐步的学习和摸索的过程中我总结有以下几个核心问题需要面对和研究。

第一.GAMBIT软件中的边界设置错误问题

当在gambit中进行边界条件的设置时，路面上方十米处设置辐射源时，只要选择RADIATOR在网格输出时就会出现错误的提示，如选择WALL来作为边界，或者选择其它项时则不会出现这种情况。

请教一些人后，有人认为是网格划分的问题，认为对于网格的划分，要求控制网格的密度，可以遵循从线到面的原则，不能将所有边的网格点都定死，必须有一些边不定义网格，如四边形区域，一般只定义相邻两个边的网格，但是我在重新划分后还是不能解决。后来在gambit2.3.16版本下运行也出现同样的问题。所以现在对辐射面还是暂时设定为WALL，这直接影响到在msh文件导入fluent后的边界条件设置。

同时在导入FLUENT也会出现如下的错误提示。

第二.Fluent中辐射模型的选用

FLUENT 中可以用5 种模型计算辐射换热问题。这5 种模型分别是离散换热辐射模型(DTRM)、P-1 辐射模型、Rosseland 辐射模型、表面辐射(S2S)模型和离散坐标(DO)辐射模型。这五种模型究竟哪一种最适合路面对空气辐射的情况，由于没找到相关的算例，只能预估选择模型，根据看一些辐射算例和相关论坛，总结出要从以下几个方面去考虑：

(1)光学厚度：可以用光学厚度(optical thickness)作为选择辐射模型的一个指标，看到一些论坛上关于光学厚度选模型的文章，由于我的模型的介质是空气，而空气的光学厚度相对其他介质比较小，所以选用P-1 模型或DO 模型，DO 模型的计算范围更大，但是同时计算量也更大，对计算机要求更高。 (2)散射：P-

1、Rosseland 和DO 模型均可以计算散射问题，而DTRM 模型则忽略了散射的影响。考虑到本模型初步并不考虑路面上方空气的散射问题，所以这四种模型中选择DTRM模型或DO模型，只是还不知道如何在DO模型中消除散射的影响。

(3)局部热源：在带有局部热源的问题中，DO 模型是这种问题最合适的计算方法。如果采用足够多的射线，也可以用DTRM 模型进行计算。因为本模型初步把太阳考虑为局部热源，所以选用DO模型。

通过上面的分析，初步决定采用DO 模型来进行计算，但一些算例中指出，由于DO 模型对网格划分精度的要求比较高，在辐射计算时很难收敛，所以在网格划分上不能过分精细，由于还没有建模成功，这也只是一个潜在的问题。 第三.太阳加载模型的选用

在最初的建模思想中，主要是想把太阳模拟成一个平面的辐射源，来计算辐射源与路面之间的温度场，但随着深入的学习我发现高版本的FLUENT(如fluent6.3)软件中有太阳计算器，可以直接模拟太阳动态的对路面辐射，所以我找了一个较高版本的FLUENT软件，如下图

如图，在选择DO模型后，solar load(太阳照射量)下有两种模式solar ray tracing和do irradiation。因为我选择的是DO模型，所以考虑后一种模式Do Irradiation。关于太阳加载的算例不多，我只找到一个关于室内通风算例中有用到太阳加载模型，我想随着模型的逐步成型，在后期的模型建立中一定会用到太阳加载，也可以更真实的模拟现场的环境。 第四.壁面边界条件的输入

对于壁面的边界条件也是模型设置的关键，设置不当将直接影响到计算的结果，误差会很大，在求解能量方程时，可以定义的热力学条件有5 种： (1)固定热通量。 (Heat flux) (2)固定温度。 (Temperature) (3)对流热交换。 (Convection) (4)外部辐射热交换。 (Radiation) (5)外部辐射与对流混合热交换。(Mixed)

因为辐射和对流的混合热交换复杂的多，在初步的模型中我打算只考虑辐射热交换，也就是第四种条件情况，碰到困难的地方是参数该如何来进行设置，共有七个参数需要确定，如设定External Emissivity(外部辐射率)，查了相关的资料，测试太阳辐射下对乘客车厢的降温的ACC系统一般采用0.5左右的辐射率，而其它有些相近的算例有的辐射率却接近1。在我们自己的模型中，除路面外，其它壁面的辐射率应该考虑为多少，是一个要解决的重要问题，当然还有如热交换率、自由流温度、传热系数等等参数需要确定，由于没有相关的算例，只能逐渐的摸索和尝试。

总结：

在对于FLUENT软件的学习和认识过程中，基础知识的重要性凸现出来，也感觉到自己此前想直接应用软件的想法不是很现实，因为在软件中有大量的流体力学定理和方程的参数设定，只有真正懂了和了解这些定理和方程，才能灵活应用，所以想学通FLUENT，要掌握流体力学、热力学和传热学等多门课程。但我们课题毕竟是仅仅应用软件的辐射传热部分，我想如果有相关的算例和相关专家的指导应该会事半功倍。

在逐渐的发现问题和解决问题的过程中，我自己的思路也慢慢清晰起来，看到困难同时也看到希望，只要初步的模型建立好，后期的模型扩展和完善将相对容易很多。

第二篇：湍流怎么造句

湍流拼音【注音】： tuan liu

湍流解释

【意思】：(tuānliú)<书>流得很急的水。

湍流造句：

1、湍流将紧挨着球的曲面，从而减少足球的空气阻力。

2、我们认为一个中等或尾流结构可能存在，现在我们可以证明有大群结构位于湍流非常中心的位置。

3、虽然其结构，被称为壁结构，已经在湍流的边缘被找到，但是一个难以捉摸的中等或尾流结构至今从未被发现。

4、在汹涌的湍流中，每个人在他们内心都应该有指导他们做出决定的思想。

5、研究小组现正期找到类似的结构，如果它们存在于其它的湍流流动的案例中。

6、由于湍流而快速变化的折射在视线中会影响到光的不同颜色，这种影响也各不相同，一般会给恒星产生一种闪烁的效果。

7、这可能包括工作机械零件，涉及血液流动的医疗，和在空中，海上和公路旅行中的湍流各个方面。

8、当鲨鱼在水中游动时，水流从鳞屑的沟槽中流过有助于减少湍流，保持其流线型的泳姿。

9、《第十三个故事》情节跌宕起伏，就像湍流的河水，充满不可预知的漩涡和大浪，让读者无法逃避。

10、如果你踢球的力量足够大，使得球表面的气流形成湍流，则阻力会很小，你很可能踢成高射炮。

11、实际上，上周经历很多湍流的航班就是沿着该高压边缘。

12、然而，当气流为湍流时，边界层维持时间较长。

13、它将测定太阳磁场形成以及如何导致太阳剧烈活动，比如太阳风湍流。

14、但如果你能大力踢球使其获得一个足够快的速度，使它表面的气流形成湍流，足球将受到较小的制动力(见上图)。

15、当球在空中速度减慢时，周围的气流从湍流变为稳定的层流。

16、这架69磅重的飞行器由一位希腊奥林匹克自行车手所驱动，在靠近圣托里尼的海岸时还遭遇到了空中湍流的袭击。

17、这一新发现的湍流状态是由大量存在于一种湍拎干结构中的元素组成的，而且已经被该研究组描述为一块“打结的漩涡挂毯”。

18、球的表面流动的空气形成湍流，这使得球的阻力相对较低。

19、混沌理论先驱BenoitMandelbrot发现尼罗河每年的洪水泛滥程度符合这个性质，音乐和空气湍流中也有这个性质。

20、现在，我们确信我们所拥有的湍流经验可以帮助消费者克服困难，并能帮助商业的成功。

21、他们站在湍流的汹涌的河水中间，束手无策，天完全黑下来。他们离河岸还有25英尺之远。

22、对于大多数危险的湍流，我们花费了更多的时间来保障安全，但是只有少数情况下，这些措施才起到重大的作用。

23、从冰川包覆的山巅冲击而下的湍流携下一种具有很高价值的玉石，毛利人将这种硬质半透明的石头雕刻成为珠宝和刀刃，既是工具也可以作为武器。

24、然而，处女是简单化的，什么东西都显现在表面一目了然，天蝎却更加注重生活表象下的湍流。

25、在绵延湍流中，享受尼泊尔宁静、与世隔绝的乡间景观。

第三篇：FLUENT

FLENT ①快捷键：

缩放：中键选择要缩放区域----松开; ②

一、导入并检查网格

1、读入网格

2、网格按比例缩放

---在scaling中选择尺寸单位(建模时所用单位)---scale--- 会发现domain extent中数值变化;

Domain extent：当前模型的尺寸范围(我们需要的尺寸范围); Scale：缩放;unscale：撤销缩放(反缩放);

3、检查网格

Mesh---check:网格最小体积大于零即可; Minimum volume(m3):

4、光顺网格与交换单元面

5、网格显示

二、选择求解器及计算模型

1、选择求解器

①压力基和密度基：

分离方法(segregated)—压力基(pressure-based)--可压缩(分压)：

基于压力的算法;适用于低速流体; 耦合方法(coupled)—密度基(density-based)--不可压缩：

基于密度的算法;使用与高速流体;密度可变;密度，速度 ，压强都变化，采用耦合求解;

只有密度基的时候才有积分显式/隐式选择： Solution condition---formulation--- ②设置湍流模型：

Models---viscous-laminar--- ③选择能量方程： Models---energy-off

2、设置运行环境

①打开步骤：define---operating conditions 或cell zone conditions--- operating conditions

三、定义材料

1、创建新流体：Define---materials：

<1从database中找(常用与添加液体水water liquid); <2新定义名字，自己输入参数;

2、粘性系数：material—air—properties—viscosity 温度变化不大时，一般采用southerland模型;

四、设置边界条件

1、设置流体区域边界条件

①设置计算所用材料： ---cell zone condition---edit---material name---选择所需材料---

2、设置进口边界条件 ①设置压力入口：

入口压强定义了总压和静压，即可知道马赫数;

p121(1Ma) p02Cauge total pressure 总表压(相对压强) Initial cauge pressure 初始表压---静压

3、设置出口边界条件

4、

五、求解

1、求解参数设置:--Soulution Controls ①courant number：柯朗数;C2att 2axVmin

t:步长;Vmin：最小单元体积;

通过设置柯朗数来设置计算步长;柯朗数越小，步长越小，

越容易收敛;

②显式/隐式积分：

在选择density-based的时候在solution methods里面会出现;

显式积分(explict):C<1;一般先取0.1，如果收敛，可取0.5;

隐式积分(inplict)：先取0.1，接着可取0.5，1,5···

2、打开残差图：solution---monitors <1 <2设置收敛点(降低收敛值)：

residuals,statistic···--- residuals-plot(双击)---equations---convergence absolute criteria---将数值调小即可;

3、初始化

4、动画设置

5、保存文件

6、开始迭代

六、后处理

1、等值线

2、矢量图

3、检查质量流量连续性：

Report---result reports---fluxes---选择面(入出口)---compute;;

流入和流出质量会有误差，但误差应在一定范围内，例5%，超出范围时，应降低收敛点后继续计算;

4、显示迹线图：

---graphics and animation---pathlines---set up---选择release surface---display--- 显示迹线动画：单击pulse(display右侧)即可---stop停止;

第四篇：fluent学习心得

1. 分离式求解器和耦合式求解器：都适用于从不可压到高速可压的很大范围的流动，总得来说，计算高速可压时，耦合式求解器更有优势;分离式求解器中有几个模型耦合式求解器中没有，如VOF，多项混合模型等。

2. 对于绝大多数问题，选择1st-Order Implicit就已经足够了。精度要求高时，选择2st-Order Implicit.而Explicit选项只对耦合显式求解器有效。

3. 压力都是相对压力值，相对于参考压力而言。对于不可压流动，若边界条件中不包含有压力边界条件时，用户应设置一个参考压力位置。计算时，fluent强制这一点的相对压力值为0. 4. 选择什么样的求解器后，再选择什么样的计算模型，即通知fluent是否考虑传热，流动是无粘、层流还是湍流，是否多相流，是否包含相变等。默认情况，fluent只进行流场求解，不求解能量方程。

5. 多相流模型：其中vof模型通过单独的动量方程和处理穿过区域的每一流体的容积比来模拟两种或三种不能混合的流体。

6. 能量方程：选中表示计算过程中要考虑热交换。对于一般流动，如水利工程及水力机械流场分析，可不考虑传热;气流模拟时，往往要考虑。默认状态下，fluent在能量方程中忽略粘性生成热，而耦合式求解器包含有粘性生成热。

7. 粘性模型：inviscid无粘计算;Laminar模型，层流模型;k-epsilon(2 eqn)模型，目前常用模型。

8. 材料定义：比较简单 9. 边界条件：见P210-211 10. 给定湍流参数：在计算区域的进口、出口及远场边界，需给定输运的湍流参数。Turbulence specification Method项目，意为让用户指定使用哪种模型来输入湍流参数。用户可任选其一，然后按公式计算选定的湍流参数，并作为输入。 湍流强度，湍动能k，湍动耗散率e。 11. 常用的边界条件： 压力进口：适用于可压和不可压流动，用于进口的压力一直但流量或速度未知的情况。Fluent中各种压力都是相对压力值。

速度入口：用于不可压流，如果用于可压流可能导致非物理结果。 质量进口：规定进口的质量。

压力出口：需要在出口边界处设置静压。静压只用于亚音速流动。在fluent求解时，当压力出口边界上流动反向时，就是用这组回流条件。出口回流有三种方式：垂直与边界，给定方向矢量，来自相邻单元。 出流：用于模拟求解前流速和压力未知的出口边界。适用于出流面上的流动情况由区域内外推得到，且对上游没影响。不用于可压流动，也不能与压力进口边界条件一起是用。 压力远场：只适用于可压气体流动，气体的密度通过理想气体定律来计算。

12. 设置求解控制参数：为了更好的控制求解过程，需要在求解器中进行某些设置，内容包括选择离散格式、设置欠松弛因子、初始化场变量及激活监视变量等。

Fluent允许用户对流项选择不同的离散格式。默认情况下，当是用分离式求解器时，所有方程中的对流相一阶迎风格式离散;耦合式求解时，二阶精度格式，其他仍一阶。对于2D三角形和3D四面体网格，注意要是用二阶精度格式。一般，一阶容易收敛，精度差。

欠松弛因子：为了加速收敛，在迭代10次左右后，检查残差是增加还是减小，若增大，则减小欠松弛因子的值;反之，增大它。

Pressure-velocity coupling：包含压力速度耦合方式的列表。该项只在分离式求解器中出现。可选SIMPLE、SIMPLEC、PISO。多数选择simplec，piso算法主要用于瞬态问题的模拟，特别是希望使用大的时间步长的情况。

Courant Number;设置网格的Courant数，用于控制耦合求解时的时间步长。对于耦合显示求解器，该数值不要过大，一般<2。隐式求解器，可取较大值，一般取5，有时20，甚至100，也可收敛。

13. 设置监视参数，一般残差监视。

14. 初始化流场的解：向fluent提供流场的解的初始猜测值。 15. 流畅迭代计算，稳态问题求解和非稳态问题求解。

第五篇：Fluent的并行计算

Possibilities of Parallel Calculations in Solving Gas Dynamics Problems in the CFD Environment of FLUENT Software

N. Chebotarev Research Institute of Mathematics and Mechanics, Kazan State

University, Kazan, Russia Received August 25, 2008 Abstract ：The results of studying an incompressible gas flow field in a periodic element of the porous structure made up of the same radius spheres are presented; the studies were based on the solution of the Navier–Stokes equations using FLUENT software. The possibilities to accelerate the solution process with the use of parallel calculations are investigated and the calculation results under changes of pressure differential in the periodic element are given. DOI : 10.3103/S1068799809010103

Multiprocessor computers that make it possible to realize the parallel calculation algorithms are in recent use for scientific and engineering calculations. One of the fields in which application of parallel calculations must facilitate a considerable progress is the solution of three-dimensional problems of fluid mechanics. Many investigators use standard commercial CFD software that provide fast and convenient solutions of three-dimensional problems in complicated fields.

The present-day CFD packages intended to solve the Navier–Stokes equations describing flows in the arbitrary regions contain possibilities of parallel processing. The objective of this paper is to test the solutions of a three-dimensional problem of gas dynamics using FLUENT software [1] by a multiprocessor computer in the mode of parallel processing.

An incompressible gas flow in the porous structure made up of closely-arranged spheres is calculated. Structures of different sphere arrangement are widely used as models of porous media in the theory of filtration. Using the porous elements it is possible to realize the processes of filtration, phase separation, throttling, including those in aircraft engineering [2]. The hydrodynamic flows in porous structures in the domain of small Reynolds numbers are described, as a rule, under the Stokes approximation without regard for the inertia terms in the equations of fluid motion [3]. At the same time, the flow velocities in the porous media may be rather large, and the Stokes approximation will not describe a real flow pattern. In this case the solution of the complete Navier–Stokes equations should be invoked. The flow with regard for inertia terms in the equations of fluid motion in the structures of different sphere arrangement was theoretically studied in [6] and experimentally in [7].

PROBLEM STATEMENT

We consider an incompressible gas flow in the three-dimensional periodic element of the porous structure made up of closely-arranged spheres of the same diameter d , the centers of which are in the nodes of the ordered grid (Fig. 1a). The porosity of the structure under consideration determined as the ratio of the space occupied by the medium to the total volume is equal to 0.26. Taking into account symmetry and periodicity of the flow, we will separate in the space between spheres the least element of the region occupied by air (Fig. 1b). In connection with a difficulty in dividing the calculation domain, small cylindrical areas are excluded in the vicinity of points at which the element spheres are in contact.

Fig. 1. Scheme of sphere arrangement (a) and a periodic element in the air space between spheres

(b).

The gas flow velocities inside the porous structures are so small that it is possible to neglect gas compressibility and adopt a model of incompressible fluid. The laminar flow of the incompressible gas is described by the stationary Navier–Stokes equations:

where u are the gas velocity vector and its Cartesian components; p is the pressure; μ and

ρ are the dynamic viscosity coefficient and air density. At the end bounds of the periodic element we lay down the conditions of periodicity

where L = d is the periodic element length along the flow (along the y axis); at the lateral faces we lay down the conditions of symmetry. The pressure at the end element bounds is described by the formula

where Δp is the pressure differential in the element limits. The conditions of symmetry are taken not only at the lateral faces but also at the upper and lower faces. On the spherical surfaces the conditions of adhesion are specified.

System of equations (1)–(2) is solved with the aid of the SIMPLE algorithm in the finite volume method in FLUENT software environment (FLUENT 6.3.26 version). For the calculation domain the irregular tetrahedral grid division is used (Fig. 2).

Fig. 2. Division of the periodic element into finite volumes.

ANALYSIS OF CALCULATION RESULTS IN THE PARALLEL MODE The calculations were carried out on the computational cluster of Kazan State University consisting of eight servers. Each server includes two AMD Opteron 224 processors with the clock rate 1.6 GHz and 2 GB of main memory. The servers operate under the control of the Ubuntu 7.10 version of the Linux operating system. The communication between the servers is based on the Gigabit Enternet technology. In the calculations the HP Message Passing Interface library (HP-MPI) delivered together with the FLUENT program is used. At the moment of experiments four servers were accessible for operation. To analyze the efficiency of parallel processing of the numerical solutions of the Navier–Stokesequations in the FLUENT environment, the calculations were performed with three variants of the grid division of the solution domain 116895, 307946, and 510889 finite volumes (variants A , B , C ). The number of iterations in all cases was taken to be equal to 760 resulting in solution convergence to10. All computation experiments were performed in the package mode.

One of the basic moments in solving problem with the use of FLUENT software in the parallel processing mode is the division of the initial domain into subdomains. In this case, each computation unit, that is, a processor is responsible for its subdomain. In dividing into subdomains FLUENT software uses the method of bisection, that is, when it is necessary to divide into four subdomains, the initial domain is first divided into two and then recursively the daughter subdomains are divided into two. If it is necessary to divide into three subdomains, the initial domain is divided into two subdomains so that one subdomain is twice as large as the other and then the larger subdomain is divided into two. FLUENT software incorporates several algorithms of bisection, and the efficiency of each algorithm depends on the problem geometry.

We studied the acceleration factor that is determined as the ratio of the calculation time t

1 by one processor to the calculation time tn by n processors ka .To provide the experiment purity, the acceleration factor was calculated four times for each case, and the calculation time obtained in each case was somewhat different. The minimal time for four calculations was chosen for the analysis. For the variants A , B , C without paralleling it amounted to 747, 2234, and 3600 s, respectively.

The dependence of ka on the number of n processors being used is given in Fig. 3. If the number of processors is small ( n < 5), the acceleration factor is about the same for all variants of the grid division and is close to the number n . As n increases, the parameter ka becomes much less than the number of processors and becomes different for different variants of the grid division. As a whole, the acceleration factor behavior with changes in the number of processors is in conformity with the theoretical concepts, and k a tends to the final limiting value as n grows. For the variant A with a lesser number of finite volumes, the efficiency of paralleling is lower than for the variants B and C .

Fig. 3. Dependence of the acceleration factor on the number of processors.

For a more detailed analysis of the calculation time with the different number of processors, we study the time t of data exchange between the processors and the factor tn of unloaded state [8] that represents the share of exchange time in the total calculation time. The less is ku , the higher is the efficiency of paralleling. The time of data exchange is determined by a share of boundary finite volumes between subdomains in the total number of finite volumes. Tables 1 and 2 present a share of boundary cells between subdomains and the values of the factor of unloaded state. It is seen that as the number of processors grows, the share of boundary volumes between subdomains increases resulting in the growth of the relative exchange time tu , that is, the factor of unloaded state. In this case, it is clear that the variants B and C are close to each other in both variants. In the variant A , the ratio of the exchange time to the calculation time increases much faster.

The flow pattern in the element under study is mainly determined by the value of pressure differential along the fluid flow. Denoting by v0 the average velocity in the inlet cross-section, we will introduce the Reynolds number Re:

At low pressure differential (small Re) a symmetric flow that is periodic in all directions is formed. The typical vector field of velocities for this range is shown in Fig. 4a. As the Reynolds number increases (pressure differential grows), the inertia effects become apparent (Fig. 4b). The inertia flow regime is characterized by the presence of complex three-dimensional vortex structures in the region between the spheres being streamlined.

At low velocities the gas flow in the porous structure is described by the Darcy law:

where v is the filtration velocity (the volumetric air flowrate per unit of time through unit area in the porous medium); kd is the permeability factor. The Darcy law establishes proportionality of the filtration velocity to the pressure gradient. In the inertia flow regime the Darcy law is violated, and to express the dependence of the filtration velocity on the pressure differential, the well-known Forhheimer formula is widely used [9]:

Fig. 4. Vector field of velocities at the periodic element faces at x = 0 (a, c) and x = d /2 (b, d) for

Re = 0.05 (a, b) and Re = 140 (c, d).

The permeability factor kd and the coefficient β are usually found by approximation of experimental results. At the same time the numerical solution of the equations for gas flow in the periodic element of the porous structure can be used for their definition. Let us write the equation for momentum variation when gas passes through the periodic element in the form [6]:

where n is the unit vector that is exterior with respect to the boundary element surfaceAf ; τ is the vector of viscous stresses. The boundary surface of the element consists of the boundary “fluid–fluid”Aff， the boundary “fluid–solid” Afs：Af=Aff+Afs

Let us rewrite Eq. (8) with regard for symmetry in the form:

where A is the area of the inlet cross-section in the periodic element. Taking into account that in connection with flow periodicity the last integral is zero, we will write Eq. (9) in the dimensionless form:

where we introduced the dimensionless parameter λ= d2Δp/ρvL. The gas velocity distribution in the porous element found from the solution of the Navier–Stokes equations makes it possible to calculate the forces acting on the spherical surfaces in the element limits, that is, the integrals in the right-hand part of Eq. (10). The dimensionless force of resistance λRe includes the resistance that is due to the normal fp and viscous f τ stresses on the spheres. Figure 5 presents the dependence of Re λ on the Reynolds number obtained from the calculations of the gas flow field at different values of pressure differential (calculated points), and the curve found by linear approximation of the calculated values Re λ at Re 4 > . The linear approximation obtained corresponds to the Forchheimer formula and is in a good agreement with the calculated data thus confirming the feasibility of the formula mentioned for description of flow characteristics in the porous media at the large Reynolds numbers. Using formulas (7) and (10), we will obtain from the calculated data the

permeability factor kd/d2=6.1 × 10-4.

Fig. 5. Dependence of the dimensionless resistance force on the Reynolds number.

Thus, using FLUENT software in the parallel calculations mode by a multi-processor computer, we solved a problem of the incompressible gas flow in the periodic element of the porous structure made up of the closely-arranged spheres. It is shown that the calculation time is reduced as the number of processors grows, and the efficiency of paralleling is higher with a larger number of finite volumes in dividing the calculation domain. The results of studying a flow field under variation of the pressure differential in the periodic element are presented. When the pressure differential increases (the large Reynolds numbers), the inertia flow regime that is characterized by a complicated pattern of vortex structures is formed in the porous element.