水利水电工程专业外文翻译、英汉互译、中英对照.doc

毕业设计（论文）外文翻译题 目 姚家河水电站 溢流坝及消能工优化设计专 业 水利水电工程 使用CFD模型分析规模和粗糙度对反弧泄洪洞的影响 作者 Dae Geun Kim1and Jae Hyun Park2摘 要在这项研究中，利用CFD模型、FLOW-3D模型详细调查流量特性如流量、水面、反弧溢洪道上的峰值压力，并考虑到模型规模和表面粗糙度对速度和压力的垂直分布特征的影响，因此，在领域中被广泛验证和使用。由于表面粗糙度数值的误差是微不足道的，对于流量，水面平稳，波峰压力影响较小。但是我们只是使用长度比例小于100或200在可接受的误差范围的建筑材料一般粗糙度高度和规模效应的模型，最大速度在垂直的坐标堰发生更严重的粗糙度和规模效应。原型的速度比缩尺比模型的更大，但现却相反的。在任何一节的最大速度略有降低或者表面粗糙度和长度的比例增加。最大速度出现在上游水头的增加几乎呈线性增加溢洪道前的距离和位置较低的垂直位置位上。关键词：FLOW-3D，反弧溢洪道，粗糙度效应，规模效应1.简介工程师在大多数情况下都选着设计建造具有过流高效、安全地反弧溢洪道，并且它在使用过程中具有良好的测量能力。反弧溢洪道的形状是从较高顶堰的直线段流到半径R的网弧形段，在反弧附近的大气压力超过设计水头。在低于设计水头时波峰阻力减少。在高水头的时候，顶堰的大气压较高产生负压使水流变得更缓。虽然这是关于一般反弧的形状和其流动特性的理解，但是从上游流量条件下的变化、修改的波峰形状或改变航道由于局部几何性质等的标准设计参数的偏差都会改变的水流的流动性，影响的分析结果。物理模型被广泛的用来确定溢洪道非常重要的大坝安全。物理模型的缺点是成本高，它可能需要相当长的时间得到的结果。此外，由于规模效应的误差的严重程度增加原型模型的大小比例。因此在指导以正确的模型细节时，计算成本相对较低物理建模、数值模拟，即使它不能被用于为最终确定的设计也是非常宝贵的资料。在过去的几年中，一些研究人员试着解决各种数学模型和计算方法的流量超过溢洪道的问题，主要困难是从亚临界流到超临界流过渡。此外，速度是未知的也必须作为解决方案的一部分，速度水头是上游泄洪时上游水头的重要组成部分。泄洪流量建模最早被试用在卡西迪（1965）复杂的平面势流理论和映射中。一个更好的解决卡西迪的问题的利用非线性有限元和变分原理方案被贝茨（1979年），李等提出 。这个方案能够自由表面和波峰压力并且发现现实与实验数据的相似性。然后，郭（1998）扩大了对势流理论的运用与分析，对边界值理论推导出边界积分方程的变量代换，此方法已成功应用到了自由下落的溢洪道中。艾斯（2000）采用流函数分析对溢洪道波峰无旋流动。有限差分法的方法给边界点上的问题提供了积极的成果。结果与实验的方式获得这些关系。1990年，开发了一个采用有限元和有限体积方法为二维自由表面流动方程，包括空气夹带的决议，并将其应用到在泄洪流量计算数值模型。实验证明该模型是有效的溢洪道水力设计作为主要分析工具。宋和周（1999）开发了一个数值模型可能被用来分析隧道或槽溢洪道，特别是进口水流条件几何效应的三维流模式。奥尔森（1988年），通过求解雷诺数方程来解释标准方程模型湍流粘性的影响。他们表现出优秀的水面和流量系数的相似。最近，在反弧溢洪道水流进行调查中发现，使用计算二维流体力学，三维流体学。他们还发现有相当不错的物理模型和数值模型之间的相似压力。尤其是金（2003）使用FLOW-3D物理模型的规模效应发现一系列比例模型、数值模拟结果：不同水流排放和规模较大模型的流速比规模较小的模型价值比更大。现有的研究大多使用CFD模型处理模型的适用性，以估算泄洪流量、水面和峰值压力对原型的影响。在这项研究中，利用CFD模型、FLOW-3D模型通过流量、水面、溢洪道坝顶上的压力、模型规模和表面粗糙度等流量特性对的速度和压力的垂直分布的影响。泄洪流量分析方法在溢流坝设计领域中被广泛验证和使用，本研究的目的是调查、定量分析的计算结果对流动特性的规模和粗糙度的影响。2.缩放和粗糙度一个采用在许多自然流系统和水工结构性能评估缩尺模型的的水力模型的缺点，通常被称为实验室效果的规模效应。规模效应的严重程度增加，比例模型的大小增加或物理过程的数量增加同时增加。实验室在空间、施工性模型、仪器仪表、或测量的限制，一般来说，水工结构的明渠流量恒定非均匀流动特性可以解释为以下关系（ASCE，2000）。Sw是水面坡度，S0所以渠道底坡，h是水深，k为固体边界的粗糙度高度，V为流速，g是重力加速度，和V， ，分别是动态粘度厘泊，密度，水的表面张力。方程（1）水面线为底坡，相对粗糙度高度、弗劳德数、雷诺数和韦伯数表示式中的变量的相似性。方程（1）之间保持正确复制功能复杂的原型流动情况的水工模型缩尺模型和原型。一般来说，几何相似并进行了实验用液压表1中的弗劳德数相似。粗糙高度，K的近似值明渠流量和水工结构模型中水是用来分析缩尺模型的流动特性。当建模精度受到损害，水的特性是不进行缩放，一个小规模的模型可能导致失败的模拟失败，如粘度和表面张力的流体性质，比原型表现出不同的流态。此外，因为实验材料有限缩尺模型的相对粗糙度高度不能完全复制。先前由于研究水力模型的规模限制导致一些误差。Lr的尺度比率为 30100型号的大型水坝溢洪道。和模型流深度超过溢洪道的设计水头工作范围至少为75毫米。对于一个给定的表面平均粗糙度高度可通过试验确定。为了确定规模和粗糙度如何影响模型结果的，实验中使用不同的表面粗糙度和一系列与原型成比例的模型，但水工模型试验费用昂贵而且在测量数中还有许多困难。随着计算机技术和更有效的CFD模型的进步，在一个合理的时间和金钱条件下进行反弧溢洪道的流态模型进行模拟实验。3.方程应用通过CFD模型、三维流动模型，采用有限体积方法来解决RANS方程的分数面积/体积的方程表示方法来定义一个流量的实施过程。由一般平均雷诺连续性方程和不可压缩流、包括其他变量可得：其中ui代表的是X，Y，Xi方向的速度，z方向; t是时间;Ai是小数区开放流标方向; VF是在每个单元的流体体积分数;密度; p是静水压力; gi是在标方向的引力;fi代表一个需要封闭湍流模型的雷诺应力。通过数值FLOW-3D模型求解水流经过反弧段的流速变化准确地追踪流体体积（VOF模型）函数代表了流体占据的比例量的自由表面。 两方程的整理总结的理论模型（RNG模型）用于湍流闭合。 RNG模型来描述更准确的低强度的湍流流动和流具有较强的剪切区域。流区域被细分成固定的矩形单元网格。每个单元有关联的当地所有相关的变量的平均值。所有变量都位于网格中面孔（交错网格布置）。弯曲的障碍、壁面边界或其他几何特征是嵌入在网状定义分区和分开流动的变量。4.结论在这项研究中,流动特性如流量、水的表面,堰顶S形的泄洪道承受了巨大的压力,和垂直速度及压力分布在考虑模型规模和表面粗糙度的影响利用商业CFD模型进行详细的研究,验证了FLOW-3D被广泛用于溢洪道流分析领域。探讨了尺度和表面粗糙度的影响,六例被采用。也就是对数值模拟液压平滑(PR00),k = 0.5毫米(PR05)和k = 3.0毫米(PR30)进行了调查研究和对原型粗糙度影响(PR05)、1/50模型(M50)、1/00模型(M100)、1/200模型(M200)的调查进行的尺度效应。在建模过程中按比例改变后的模型、网格分辨率、表面粗糙度、上游边界条件和几何相似度调整来排除不同的数值误差。重要的仿真结果包括以下几点:1)流量略微减少排放做为该模型表面粗糙度的高度和长度尺度的增加标准。水面波动是可以忽略不计的，和一些由于发生改变的表面粗糙度和模型的规模引起的波峰压力变化。由于数值误差表面粗糙度是渺小的,如果我们仅仅使用一般的建筑材料和粗糙高度的尺度效应，如长度尺度比小于100年或200年，模型就会出现在一个可接受的误差范围内。2)建模结果表明,增加的比率引起长度尺度相似现象，是由于日益增长的表面粗糙度造成的。如果hm选中作为参考点,速度的模型比在模型参考点以下,但速度的原型是低于按比例改变后的模型参考点。表面粗糙度和尺度效应的更为严重低于参考点。3)溢洪道顶的压力会有所不同。在改变表面粗糙度和模型的规模后，垂直压力分布几乎还是一样上网。4)最高速度稍微减少，任何部分的表面粗糙度和长度尺度比例增加。出现最大速度的垂直位置位于较低位置处作为上层水源，并且在溢洪道正前方很远处成直线增加。文章出处：土木工程研究所KSCE.第2/2005年3月9日，第161169外文原文：Analysis of Flow Structure over Ogee-Spillway in Consideration of Scale and Roughness Effects by Using CFD Model By Dae Geun Kim* and Jae Hyun Park* AbstractIn this study, flow characteristics such as flowrate, water surfaces, crest pressures on the ogee-spillway, and vertical distributions of velocity and pressure in consideration of model scale and surface roughness effects are investigated in detail by using the commercial CFD model, FLOW-3D, which is widely verified and used in the field of spillway flow analysis. Numerical errors in the discharge flowrate, water surfaces, and crest pressures due to the surface roughness are insignificant if we just use a general roughness height of construction materials, and the scale effects of the model are in an acceptable error range if the length scale ratio is less than 100 or 200. The roughness and scale effects are more severe below hm, where the maximum velocity occurs in perpendicular coordinate to the weir crest. The velocity of the prototype is larger than that of the scaled model below but the phenomena are contrary above hm. Maximum velocity at any section slightly decreases as the surface roughness and the length scale ratio increase. The vertical location where maximum velocity occurs is located on a lower position as the upstream water head increases and the location almost linearly increases with the distance from the front of the spillway. Keywords: FLOW-3D, ogee-spillway, roughness effect, scale effect1. IntroductionThe ogee-crested spillways ability to pass flows efficiently and safely, when properly designed and constructed, with relatively good flow measuring capabilities, has enabled engineers to use it in a wide variety of situations as a water discharge structure (USACE, 1988; USBR, 1973).The ogee-crested spillways performance attributes are due to its shape being derived from the lower surface of an aerated nappe flowing over a sharp-crested weir. The ogee shape results in near-atmospheric pressure over the crest section for a design head. At heads lower than the design head, the discharge is less because of crest resistance. At higher heads, the discharge is greater than an aerated sharp-crested weir because the negative crest pressure suctions more flow. Although much is understood about the general ogee shape and its flow characteristics, it is also understood that a deviation from the standard design parameters such as a change in upstream flow conditions, modified crest shape, or change in approach channel owing to local geometric properties can change the flow properties. For the analysis of the effects, physical models have been used extensively because a spillway is very important for the safety of dams. The disadvantages with the physical models are high costs and that it can take fairly long time to get the results. Also, errors due to scale effects may increases in severity as the ratio of prototype to model size increases. So, numerical modeling, even if it cannot be used for the final determination of the design, is valuable for obtaining a guide to correct details because computational cost is low relative to physical modeling.In the past few years, several researchers have attempted to solve the flow over spillway with a variety of mathematical models and computational methods. The main difficulty of the problem is the flow transition from subcritical to supercritical flow. In addition, the discharge is unknown and must be solved as part of the solution. This is especially critical when the velocity head upstream from the spillway is a significant part of the total upstream head.An early attempt of modeling spillway flow have used potential flow theory and mapping into the complex potential plane (Cassidy, 1965). A better convergence of Cassidys solution was obtained by Ikegawa and Washizu (1973), Betts (1979), and Li et al. (1989) using linear finite elements and the variation principle. They were able to produce answers for the free surface and crest pressures and found agreement with experimental data. Guo et al. (1998) expanded on the potential flow theory by applying the analytical functional boundary value theory with the substitution of variables to derive nonsingular boundary integral equations. This method was applied successfully to spillways with a free drop. Assy (2000) used a stream function to analyze the irrotational flow over spillway crests. The approach is based on the finite difference method with a new representation of Neumanns problem on boundary points, and it gives positive results. The results are in agreement with those obtained by way of experiments. Unami et al. (1999) developed a numerical model using the finite element and finite-volume methods for the resolution of two dimensional free surface flow equations including air entrainment and applied it to the calculation of the flow in a spillway. The results prove that the model is valid as a primary analysis tool for the hydraulic design of spillways. Song and Zhou (1999) developed a numerical model that may beapplied to analyze the 3D flow pattern of the tunnel or chute spillways, particularly the inlet geometry effect on flow condition. Olsen and Kjellesvig (1988) included viscous effects by numerically solving the Reynolds-averaged Navier-Stokes (RANS) equations, using the standard-equations to model turbulence. They showed excellent agreement for water surfaces and discharge coefficients. Recently, investigations of flow over ogee-spillways were carried out using a commercially available computational fluid dynamics program, FLOW-3D, which solves the RANS equations (Ho et al., 2001; Kim, 2003; Savage et al., 2001). They showed that there is reasonably good agreement between the physical and numerical models for both pressures and discharges. Especially, Kim (2003) investigated the scale effects of the physical model by using FLOW-3D. The results of numerical simulation on the series of scale models showed different flow discharges. Discharge and velocity of larger scale models has shown larger value than the smaller scale models. Existing studies using CFD model mostly deal with the models applicability to discharge flowrate, water surfaces, and crest pressures on the spillway. In this study, flow characteristics such as flowrate, water surfaces, crest pressures on the spillway, and vertical distributions of velocity and pressure in consideration of model scale and surface roughness effects are investigated in detail by using commercial CFD model, FLOW-3D, which is widely verified and used in the field of spillway flow analysis. The objective of this study is to investigate quantitatively the scale and roughness effects on the flow characteristics by analyzing the computational results.待添加的隐藏文字内容22. Scaling and Roughness A hydraulic model uses a scaled model for replicating flow patterns in many natural flow systems and for evaluating the performance of hydraulic structures. Shortcomings in models usually are termed scale effects of laboratory effects. Scale effects increase in severity as the ratio of prototype to model size increases or the number of physical processes to be replicated simultaneously increases. Laboratory effects arise because of limitations in space, model constructability, instrumentation, or measurement. Generally, steady nonuniform flow characteristics in open channel flow with hydraulic structures can be explained as a following relationship (ASCE, 2000). where Sw is water surface slope, So is channel bottom slope, h is water depth, k is roughness height of solid boundary, V is flow velocity, g is gravitational acceleration, and v, U, V are dynamic iscosity, density, surface tension of water, respectively. Eq. (1) states that water surface profile is expressed as bottom slope, relative roughness height, Froude number, Reynolds number and Weber number. Similarity of variables in Eq. (1) between scaled model and prototype is maintained for the hydraulic model to properly replicate features of a complicated prototype flow situation. Generally, geometric similarity (So) is achieved and experiments are carried out by using Froude number similarity in the hydraulic Table 1. Approximate Values of Roughness Height, kmodel on the open channel flow and hydraulic structures. Water is used to analyze the flow characteristics of scaled model, thus modeling accuracy is compromised because the properties of water are not scaled. So, a small scale model may causes a failure to simulate the forces attendant to fluid properties such as viscosity and surface tension, to exhibit different flow behavior than that of a prototype. Moreover, relative roughness height of the scaled model cannot be exactly reproduced because materials of experiment are limited.Previous study on the scale limits of hydraulic models leads to some guidelines. The Bureau of Reclamation (1980) used length scale ratios of Lr = 30100 for models of spillways on large dams. And model flow depths over a spillway crest should be at least 75 mm for the spillways design operating range. The average roughness height for a given surface can be determined by experiments. Table 1 gives values of roughness height for several kinds of material which are used for construction of hydraulics structures and scaled models (Hager, 1999). To determine quantitatively how scale and roughness effects influence the model results, it is possible to use a series of scale models with different surface roughness including prototype. But the hydraulic model experiments are expensive, time-consuming, and there are many difficulties in measuring the data in detail. Today, with the advance in computer technology and more efficient CFD codes, the flow behavior over ogee-spillways can be investigated numerically in a reasonable amount of time and cost.3.Governing Equations and Computational Scheme The commercially available CFD package, FLOW-3D, uses the finite-volume approach to solve the RANS equations by the implementation of the Fractional Area / Volume Obstacle Representation (FAVOR) method to define an obstacle (Flow Science, 2002). The general governing RANS and continuity equations for incompressible flow, including the FAVOR variables, are given by where ui represent the velocities in the xi directions which are x, y, z-directions; t is time; Ai is fractional areas open to flow in the subscript directions; VF is volume fraction of fluid in each cell; U is density; p is hydrostatic pressure; gi is gravitational force in the subscript directions; fi represents the Reynolds stresses for which a turbulence model is required for closure. To numerically solve the rapidly varying flow over an ogee crest, it is important that the free surface is accurately tracked. In FLOW-3D, free surface is defined in terms of the volume of fluid (VOF) function which represents the volume of fraction occupied by the fluid. A two-equation renormalized group theory models (RNG model) was used for turbulence closure. The RNG model is known to describe more accurately low intensity turbulence flows and flow hav