Calculation of three-dimensional turbulent flow with a finite volume multigrid method

Cornelius, Christian; Volgmann, W.; Stoff, H.

doi:10.1002/(sici)1097-0363(19991030)31:4<703::aid-fld895>3.0.co;2-d

Cited by 14 publications

(6 citation statements)

References 18 publications

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“…These typically span from about 0.1 m (which is the vertical extent of the cells adjacent to the river banks) to several hundred metres in the flow direction. The principal requirements here are that grid expansion is sufficiently small to avoid errors associated with numerical diffusion and flow instability (Cornelius et al 1999), that departures from orthogonality are minimized and that adequate grid resolution is attained while keeping the overall computational effort within practical bounds. It is extremely difficult to attain all these requirements in a natural waterway and it may well be the case that achieving solutions that are entirely free of grid effects are impossible in these flows (Nicholas 2001).…”

Section: Grid Generationmentioning

confidence: 99%

Uncertainties in the prediction of flow in a long reach of the Sacramento River

Ercan

Younis

2009

Water & Environment J

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The accurate prediction of the flow field in a long reach of a complex waterway is prerequisite to the evaluation to acceptable engineering accuracy of strategies for the restoration, resource management and hazard assessment. In this study, we consider some aspects of the numerical prediction of flow in a long reach of the Sacramento River in California with view to gaining a better understanding the sources and the extent of the uncertainties that are present in the predictions. The predictions were obtained using a finite-volume method to solve the time-averaged forms of the equations governing the conservation of mass and momentum. Body-fitted coordinates were used to define the complex river bathymetry. Both depth-averaged and fully three-dimensional (3D) computations were performed. The results were compared with data obtained from a large-scale physical model of the same reach. The outcome of the comparisons served to provide the basis for the assessment of the sensitivity of the solutions to assumptions made regarding the conditions at inlet to the solution domain, the choice of turbulence model used to close the timeaveraged equations and, for the depth-averaged calculations, the choice of method used for prescribing the bed friction. The influence of other parameters such as the density of the computational grid, the method used to define the channel bathymetry, and the unsteadiness of the mean flow that results from vortex shedding from a bridge pier and abutments were also assessed. The results obtained form a useful addition to the growing literature on the computational modelling of flows in natural waterways.

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Section: Grid Generationmentioning

confidence: 99%

Uncertainties in the prediction of flow in a long reach of the Sacramento River

Ercan

Younis

2009

Water & Environment J

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“…Second, research into the performance of numerical code has emphasized, amongst other things, the need for careful investigation of discretization. This includes the accuracy of discretization [e.g., Manson and Wallis, 1997], convergence problems associated with fine grids in finite volume discretizations [e.g., Cornelius et al, 1999] and the spatial discretization required for verification [Hardy et al, 2003]. However, provided attention is given to the way in which numerical solution achieves convergence [Cornelius et al, 1999], finite volume treatments using structured grids have particular appeal as they provide fast and efficient numerical solution and can be numerically stable in channels of simple geometry.…”

Section: Background To Approachmentioning

confidence: 99%

“…[3] Given the potential of using three-dimensional applications of computational fluid dynamics to explore fluvial flows and the demonstrated achievement of this method in certain application areas, this paper seeks to address a fundamental methodological problem that has yet to be addressed. Research into the performance of numerical code is emphasizing, amongst other things, the need for careful investigation of numerical diffusion associated with grid specification, the accuracy of discretization [e.g., Manson and Wallis, 1997], and convergence problems associated with fine grids in finite volume discretizations [e.g., Cornelius et al, 1999]. Provided attention is given to the way in which the numerical solution achieves convergence [Cornelius et al, 1999], finite volume treatments using structured grids have particular appeal as they provide a fast and efficient numerical solution and can be numerically stable in channels of simple geometry.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling of flow processes over gravelly surfaces using structured grids and a numerical porosity treatment

Lane

Hardy

Elliott

et al. 2004

Water Resources Research

114

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[1] This article describes the development and validation of a method for representing the complex surface topography of gravel bed rivers in high-resolution three-dimensional computational fluid dynamic models. This is based on a regular structured grid and the application of a porosity modification to the mass conservation equation in which fully blocked cells are assigned a porosity of zero, fully unblocked cells are assigned a porosity of one, and partly blocked cells are assigned a porosity of between 0 and 1, according to the percentage of the cell volume that is blocked. The model retains an equilibrium wall function and an RNG-type two-equation turbulence model. The model is combined with a 0.002 m resolution digital elevation model of a flume-based, waterworked, gravel bed surface, acquired using two-media digital photogrammetry and with surface elevations that are precise to ±0.001 m. The model is validated by comparison with velocity data measured using a three-component acoustic Doppler velocimeter (ADV). Model validation demonstrates a significantly improved level of agreement than in previous studies, notably in relation to shear at the bed, although the resolution of model predictions was significantly higher than the ADV measurements, making model assessment in the presence of strong shear especially difficult. A series of simulations to assess model sensitivity to bed topographic and roughness representation were undertaken. These demonstrated inherent limitations in the prediction of 3-D flow fields in gravel bed rivers without high-resolution topographic representation. They also showed that model predictions of downstream flux were more sensitive to topographic smoothing that to changes in the roughness parameterization, reflecting the importance of both mass conservation (i.e., blockage) and momentum conservation effects at the grain and bed form scale. Model predictions allowed visualization of the structure of form-flow interactions at high resolution. In particular, the most protruding bed particles exerted a critical control on the turbulent kinetic energy maxima typically observed at about 20% of the flow depth above the bed.

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“…The majority of previous 3D applications in rivers have used a finite volume approach, which is known to be a good discretization method for advanced turbulence closure models (Yu et al 1997, Cornelius et al 1999. In most cases, boundary-fitted coordinate grids (BFC), i.e.…”

Section: Introductionmentioning

confidence: 99%

Assessing different methods of generating a three-dimensional numerical model mesh for a complex stream bed topography

Biron

Haltigin

Hardy

et al. 2007

International Journal of Computational Fluid Dynamics

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Three-dimensional numerical models of flow over complex bed geometry are becoming widely used in river and coastal engineering. Boundary-fitted coordinate grids are typically used to deal with this problem in natural channels. Recently, a regular structured grid method based on numerical porosity has been developed for high-resolution gravel-bed models. A simpler alternative approach is to use a Cartesian mesh with an interpolated 3D solid object representing the river bed. The objective of this study is to assess the impact of these three methods of mesh generation on the simulated flow field above complex bed topography around stream deflectors in a laboratory setting. Results show marked differences between the three types of simulations when running mesh sensitivity analysis. Because the bed porosity approach uses the digital elevation model (DEM) information in each cell to represent bed topography, it requires a finer mesh resolution in order to reach an accurate solution. Although there was good qualitative agreement between the simulated flow fields and Acoustic Doppler Velocity measurements, the quantitative comparison showed relatively poor agreement for all mesh design types. However, the three mesh types were in good agreement when compared to each other for velocity and pressure variables (average correlation coefficient, r, of 0.95), with the 3D object bed and bed porosity showing the best agreement (r ¼ 0.97). Simulated turbulence variables (KE and EP), however, showed more scatter (r ¼ 0.85) and slopes markedly different from unity.

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Calculation of three-dimensional turbulent flow with a finite volume multigrid method

Cited by 14 publications

References 18 publications

Uncertainties in the prediction of flow in a long reach of the Sacramento River

Uncertainties in the prediction of flow in a long reach of the Sacramento River

Numerical modeling of flow processes over gravelly surfaces using structured grids and a numerical porosity treatment

Assessing different methods of generating a three-dimensional numerical model mesh for a complex stream bed topography

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