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Elements of Continuum Mechanics
Published in Clement Kleinstreuer, Biofluid Dynamics, 2016
The numerical solutions of airflow transport equations with lowReynolds-number k-ω model were carried out with a user-enhanced commercial finite-volume based program, i.e., CFX4.4 from ANSYS, Inc. The numerical program uses a structured, multiblock, body-fitted coordinate discretization scheme. In the present simulation, the PISO algorithm with under-relaxation was employed to solve the flow equations (Issa, 1986). All variables, including velocity components, pressure, and turbulence quantities, are located at the centroids of the control volumes. An improved Rhie-Chow interpolation method was employed to obtain the velocity components, pressure and turbulence variables on the control volume faces from those at the control volume centers. A Quadratic Upwind (QUICK) differencing scheme, which is third-order accurate in space, was used to model the advective terms of the transport equations. The sets of linearized and discretized equations for all variables were solved using the Block Stone’s method.
Unsteady aerodynamic forces on a railway pantograph and their influence on pantograph-catenary dynamic interaction
Published in Maksym Spiryagin, Timothy Gordon, Colin Cole, Tim McSweeney, The Dynamics of Vehicles on Roads and Tracks, 2018
M. Carnevale, A. Facchinetti, F. Robustelli, D. Rocchi
CFD numerical model has been realized in the OpenFOAM framework, using the same mesh and turbulence closure model adopted in [1] and in [2] for RANS simulations. Unsteady approach of the Reynolds Averaged Navier-Stokes (URANS) equations have been adopted for this paper, and Pisofoam solver was used. This solver uses the PISO algorithm as solution method and can capture the fluctuations associated with turbulence and flow separations. The main requirement is related to the time step (dt of integration), and the need to accomplish with the Courant-Friedrichs-Lewy (CFL) condition. For a 44-million-cells mesh with minimum dimension 2 mm, the practical implication is a very huge increase in computational time.
Research and simulation on the integration of marine SCR and exhaust muffler
Published in Ai Sheng, Energy, Environment and Green Building Materials, 2015
In view of the compressibility, complexity, and turbulence of flow field inside the Integrated SCR Muffler, the three-dimensional numerical methods should be used to predict the pressure loss. Hirata, K. 2009. In this paper, a series of numerical simulations were performed by using the v2013 version of the AVL FIRE code. The k-zeta-f turbulent model for high Reynolds numbers is applied to simulate the internal flow field of the exhaust system. The developed code is based on the pressure correction method and uses a PISO algorithm, which is an efficient method to solve the Navier-Stokes equations in unsteady problems.
Numerical simulations of scrap in the converter molten bath
Published in Canadian Metallurgical Quarterly, 2023
Liguo Yu, Lianghua Feng, Di Nie, Li Gan
The inlet boundary condition of oxygen lance was set as a pressure inlet with a pressure of 0.8 MPa, the outlet boundary condition was set as a pressure outlet with an atmospheric pressure, and the internal interface was set as a periodic boundary condition. The remaining parts were set as walls. The near-wall surface was treated with a standard wall function and all normal gradients were zero. The oxygen lance outlet Mach number is 2, the oxygen lance height is 2 m from the metal bath surface, and the location of the bottom blowing holes is uniformly arranged with two bottom blowing holes at 0.6 times the radius of the converter. The flow rate of the bottom-blowing argon gas was 88 m3/h. The Converter geometry parameters are in Table 1. The model was calculated by Fluent software with PISO algorithm used. In the process of simulation calculation, the initial time step was set as 10−5s, and after 1s calculation, it was set to dynamic adaptive model, the calculation time step is automatically adjusted. The calculation convergence was considered when the residual error of the energy equation was less than 10−6 and other parameters were less than 10−3.
A CFD Modeling Coupled with VOF Method and Solidification Model for Molten Jet Breakup at Low Velocity
Published in Nuclear Science and Engineering, 2023
Tao Liu, Yuan Zhou, Mingjun Zhong, Houjun Gong
The PISO algorithm25 based on the staggered grid method is adopted to resolve Eqs. (1), (2), and (5). The PISO algorithm was originally designed for transient incompressible flow. It has the characteristics of a small number of calculations, fast speed, and stability. In space discretization, the second-order central differencing scheme is used for diffusion terms, and the Monotonic Upstream-centered Scheme for Conservation Laws (MUSCL) is used for convection terms. MUSCL is a finite volume method that can provide highly accurate numerical solutions for a given system, even in cases where the solutions exhibit shocks, discontinuities, or large gradients. A first-order backward implicit approach is employed for the time derivative. The transportation equation of is solved as
Numerical investigation on the coupled mechanisms of bubble breakup in a venturi-type bubble generator
Published in Engineering Applications of Computational Fluid Mechanics, 2022
Qiang Li, Dezhi Ming, Mao Lei, Xu Guo, Jialin Liu, Haowei Zhu, Liang Fang, Zhenbo Wang
For a long time, the Pressure Implicit with the Splitting of Operators (PISO) algorithm has been widely used as a common discretization algorithm in transient simulation calculations. However, the linearization of the convection term in the governing equation causes a lag in the flux at each step of the PISO algorithm (Jasak, 1996). Therefore, the PISO algorithm must adopt a small time step when conducting transient simulation, which means that it will consume a lot of time in the whole computation procedure. In this paper, the PIMPLE algorithm (Pham & Choi, 2021), i.e. PISO coupled with the Semi-Implicit Method for Pressure-Linked Equations (SIMPLE), is adopted, which can better deal with transient computation for large time steps. The discretization of the PIMPLE algorithm will be introduced briefly, and the solution process of the governing equations in this paper is shown in Figure 1.