This report describes a 3-D fluid mechanics code for predicting flow past bluff bodies whose surfaces can be assumed to be made up of shell elements that are simply connected. Version 1.0 of the VIPAR code (Vortex Inflation PARachute code) is described herein. This version contains several first order algorithms that we are in the process of replacing with higher order ones. These enhancements will appear in the next version of VIPAR. The present code contains a motion generator that can be used to produce a large class of rigid body motions. The present code has also been fully coupled to a structural dynamics code in which the geometry undergoes large time dependent deformations. Initial surface geometry is generated from triangular shell elements using a code such as Patran and is written into an ExodusII database file for subsequent input into VIPAR. Surface and wake variable information is output into two ExodusII files that can be post processed and viewed using software such as EnSight{trademark}.
One problem facing today's nuclear power industry is flow-accelerated corrosion and erosion in pipe elbows. The Korean Atomic Energy Research Institute (KAERI) is performing experiments in their Flow-Accelerated Corrosion (FAC) test loop to better characterize these phenomena, and develop advanced sensor technologies for the condition monitoring of critical elbows on a continuous basis. In parallel with these experiments, Sandia National Laboratories is performing Computational Fluid Dynamic (CFD) simulations of the flow in one elbow of the FAC test loop. The simulations are being performed using the FLUENT commercial software developed and marketed by Fluent, Inc. The model geometry and mesh were created using the GAMBIT software, also from Fluent, Inc. This report documents the results of the simulations that have been made to date; baseline results employing the RNG k-e turbulence model are presented. The predicted value for the diametrical pressure coefficient is in reasonably good agreement with published correlations. Plots of the velocities, pressure field, wall shear stress, and turbulent kinetic energy adjacent to the wall are shown within the elbow section. Somewhat to our surprise, these indicate that the maximum values of both wall shear stress and turbulent kinetic energy occur near the elbow entrance, on the inner radius of the bend. Additional simulations were performed for the same conditions, but with the RNG k-e model replaced by either the standard k-{var_epsilon}, or the realizable k-{var_epsilon} turbulence model. The predictions using the standard k-{var_epsilon} model are quite similar to those obtained in the baseline simulation. However, with the realizable k-{var_epsilon} model, more significant differences are evident. The maximums in both wall shear stress and turbulent kinetic energy now appear on the outer radius, near the elbow exit, and are {approx}11% and 14% greater, respectively, than those predicted in the baseline calculation; secondary maxima in both quantities still occur near the elbow entrance on the inner radius. Which set of results better reflects reality must await experimental corroboration. Additional calculations demonstrate that whether or not FLUENT's radial equilibrium pressure distribution option is used in the PRESSURE OUTLET boundary condition has no significant impact on the flowfield near the elbow. Simulations performed with and without the chemical sensor and associated support bracket that were present in the experiments demonstrate that the latter have a negligible influence on the flow in the vicinity of the elbow. The fact that the maxima in wall shear stress and turbulent kinetic energy occur on the inner radius is therefore not an artifact of having introduced the sensor into the flow.
Over the past several decades, the development of computer models to predict the atmospheric transport of hazardous material across a local (on the order of 10s of km) to mesoscale (on the order of 100s of km) region has received considerable attention, for both regulatory purposes, and to guide emergency response teams. Wind inputs to these models cover a spectrum of sophistication and required resources. At one end is the interpolation/extrapolation of available observations, which can be done rapidly, but at the risk of missing important local phenomena. Such a model can also only describe the wind at the time the observations were made. At the other end are sophisticated numerical solutions based on so-called Primitive Equation models. These prognostic models, so-called because in principle they can forecast future conditions, contain the most physics, but can easily consume tens of hours, if not days, of computer time. They may also require orders of magnitude more effort to set up, as both boundary and initial conditions on all the relevant variables must be supplied. The subject of this report is two classes of models intermediate in sophistication between the interpolated and prognostic ends of the spectrum. The first, known as mass-consistent (sometimes referred to as diagnostic) models, attempt to strike a compromise between simple interpolation and the complexity of the Primitive Equation models by satisfying only the conservation of mass (continuity) equation. The second class considered here consists of the so-called linear models, which purport to satisfy both mass and momentum balances. A review of the published literature on these models over the past few decades was performed. Though diagnostic models use a variety of approaches, they tend to fall into a relatively few well-defined categories. Linear models, on the other hand, follow a more uniform methodology, though they differ in detail. The discussion considers the theoretical underpinnings of each category of the diagnostic models, and the linear models, in order to assess the advantages and disadvantages of each. It is concluded that diagnostic models are the better suited of the two for predicting the atmospheric dispersion of hazardous materials in emergency response scenarios, as the linear models are only able to accommodate gently-sloping terrain, and are predicated on several simplifying approximations which can be difficult to justify a priori. Of the various approaches used in diagnostic modeling, that based on the calculus of variations appears to be the most objective, in that it introduces the fewest number of arbitrary parameters. The strengths and weaknesses of models in this category, as they relate to the activities of Sandia's Nuclear Emergency Support Team (NEST), are further highlighted.
A numerical flow model is developed to simulate two-dimensional fluid flow past immersed, elastically supported tube arrays. This work is motivated by the objective of predicting forces and motion associated with both deep-water drilling and production risers in the oil industry. This work has other engineering applications including simulation of flow past tubular heat exchangers or submarine-towed sensor arrays and the flow about parachute ribbons. In the present work, a vortex method is used for solving the unsteady flow field. This method demonstrates inherent advantages over more conventional grid-based computational fluid dynamics. The vortex method is non-iterative, does not require artificial viscosity for stability, displays minimal numerical diffusion, can easily treat moving boundaries, and allows a greatly reduced computational domain since vorticity occupies only a small fraction of the fluid volume. A gridless approach is used in the flow sufficiently distant from surfaces. A Lagrangian remap scheme is used near surfaces to calculate diffusion and convection of vorticity. A fast multipole technique is utilized for efficient calculation of velocity from the vorticity field. The ability of the method to correctly predict lift and drag forces on simple stationary geometries over a broad range of Reynolds numbers is presented.