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Simulating Flood Due to Dam Break
Published in Saeid Eslamian, Faezeh Eslamian, Flood Handbook, 2022
Ali Ersin Dinçer, Zafer Bozkuş, Ahmet Nazım Şahin, Abdullah Demir, Saeid Eslamian
Since the dam-break problem involves highly transient gravity-dominated flows, the role of turbulence becomes secondary, especially in the upstream reservoir where the potential flow theory can be used to describe the flow. Unlike the conditions upstream, the downstream part is highly turbulent (LaRocque et al., 2013b). In general, there are two most used turbulence models, Reynolds-Averaged Navier-Stokes (RANS) and large eddy simulation (LES). In RANS models, a variable such as velocity is decomposed into its fluctuating and Reynolds-averaged components. In the LES approach, large eddies are computed directly and only small-scale motions are modeled separately (Zhiyin, 2015). Therefore, the range of length scales decreases. Since the smaller mesh sizes must be used in the LES models, the computational time is higher.
Force-System Resultants and Equilibrium
Published in Richard C. Dorf, The Engineering Handbook, 2018
In current aerodynamic analyses, turbulence effects are accounted for by phenomenological models. The time-averaged form of the Navier-Stokes equations (known as the Reynolds-averaged Navier-Stokes equations) are solved. Time-averaging introduces the turbulent Reynolds stresses in the Navier-Stokes equations, and these are calculated by multiplying an eddy-viscosity coefficient with the strain-rate tensor The phenomenological description of eddy viscosity is known as “turbulence modeling.” At present, there is no universal turbulence model that works for all flow situations. Generally, turbulence models are developed by validating them against experimental data for simple flow situations, and are then used for calculation of complex flow fields. This approach introduces an element of uncertainty into the prediction of complex flows.
Introduction
Published in Wolfgang Rodi, Turbulence Models and Their Application in Hydraulics, 2017
Empirical information can be put into the system of equations in two distinctly different ways. Integral methods, which are suitable mainly for thin shear layers (boundary-layer-type flows), introduce empirical profile shapes so that the originally partial differential equations can be reduced to ordinary ones. Further input is necessary which describes the global effect of turbulence, like the entrainment laws for free shear flows and the friction or energy dissipation laws for wall boundary layers. In contrast, the so-called field methods, which employ the original partial differential equations, require specification of the turbulent transport terms appearing in the equations at each point in the flow. This specification is accomplished by a mathematical model of the turbulent transport processes which is called a “turbulence model”. Therefore, a turbulence model is defined as a set of equations (algebraic or differential) which determine the turbulent transport terms in the mean-flow equations and thus close the system of equations. Turbulence models are based on hypotheses about turbulent processes and require empirical input in the form of constants or functions; they do not simulate the details of the turbulent motion but only the effect of turbulence on the mean-flow behaviour.
Machine learning-accelerated aerodynamic inverse design
Published in Engineering Applications of Computational Fluid Mechanics, 2023
Ahmad Shirvani, Mahdi Nili-Ahmadabadi, Man Yeong Ha
The computational domain was discretized using a structural grid, as shown in Figure 4. The free stream conditions for the simulation were a Mach number of 0.45 () and a Reynolds number of 107. To enforce the pressure far-field boundary condition, the free stream Mach number and the angle of attack (AOA) were taken into account. Zero-degree AOA in the case of the NACA-0012 airfoil, four-degree AOA for the DSMA-523A, and one degree AOA for the FX63-137 airfoil were used. The CFD solution was evaluated based on a compressible flow model with atmospheric boundary condition, where pressure and temperature were set to 1 atm and 298 K (, ). An inviscid flow solver numerically solved the flow over the NACA-0012 airfoil, whereas a viscous turbulent flow solver resolved the flow over the DSMA-523A and the FX63-137. The turbulence model is the one-equation Spalart–Allmaras model (Spalart & Allmaras, 1992), which calculates the turbulence dynamic viscosity.
Theoretical analysis of unsteady buoyant turbulent heat and mass transport from a vertical plate using LRN k-ϵ model
Published in Waves in Random and Complex Media, 2023
Suresha S. P., G. Janardhana Reddy
In the field of engineering applications, turbulence models have been researched enormously due to its vital role in energy and mass transport, dispersion and mixing, surface drag, and momentum transport, etc. Particularly, turbulent flows occur in the process of determining the heat and mass transport in chemical engineering problems, affecting the chemical reactions and its performance. Also, micromixing is identified as the restrictive time scale in these procedures. Guichao et al. [1] reported that micromixing arises at small time scales as predicted by the TKE and its dissipation rate. Further, one of the most fundamental problems in fluid dynamics is turbulent natural convection flows. Therefore, those problems are essential in meteorology since they appear as a wind in the atmosphere generated by solar radiation. Furthermore, the study of turbulent convection flows is important and useful in electronic component refrigeration [2] and also can be used in room ventilation, electronic device cooling or airflow in buildings to minimize noise exposure and technical failures [3] and so on. Mainly, one of the key research areas focused on elucidating the basic structure of turbulent heat and mass transport processes is the investigation of the convection turbulent boundary layer from solid vertical bodies. Accordingly, turbulent natural convection flow problems and their models received a lot of attention from the researchers in the 1960s and also a lot of experimental studies were done at that time which is explained in the below succeeding paragraphs.
Implicit solution of harmonic balance equation system using the LU-SGS method and one-step Jacobi/Gauss-Seidel iteration
Published in International Journal of Computational Fluid Dynamics, 2018
Xiuquan Huang, Hangkong Wu, Dingxi Wang
The governing equations to be solved for all the analyses to be presented in the following are the URANS equations in a cylindrical coordinate system. The equations are written for a frame of reference which is attached to a blade row under consideration. That is to say different frames of reference are used for a rotor domain and a stator domain: a rotating frame is used for a rotor and a stationary frame is used for a stator. However, the solution variables are those measured in a stationary frame of reference, which allows for an easier treatment at a rotor–stator interface. where where and are the total dynamic viscosity and thermal conductivity which are the summation of their laminar and turbulent components. The turbulent viscosity is obtained from the solution of the Spalart-Allmaras turbulence model (Spalart 1992). The turbulent thermal conductivity is calculated from the turbulent viscosity with a fixed turbulent Prandtl number of 1.0.