David S. Thompson

Bio: David S. Thompson is an academic researcher from Mississippi State University. The author has contributed to research in topics: Mesh generation & Vortex. The author has an hindex of 18, co-authored 113 publications receiving 1220 citations. Previous affiliations of David S. Thompson include University of Alabama at Birmingham & University of Texas at Arlington.

Eduction of swirling structure using the velocity gradient tensor

Abstract: We propose a technique for locating swirling regions of a flowfield. The technique is based on the eigenvalues of the velocity gradient tensor. We show that regions of swirling flow are characterized by complex eigenvalues for a constant velocity gradient tensor. Using results obtained in this analysis, we define an approximate parameter to indicate the tendency for the fluid to swirl about the point in question. The technique is illustrated by application to several two- and three-dimensional flowfields. In addition, the basic ideas contained here suggest the existence of a fluid property that we have termed intrinsic swirl

A novel approach to vortex core region detection

Abstract: In this paper we present a simple and efficient vortex core region detection algorithm based on ideas derived from combinatorial topology. These ideas originated from Sperner's lemma, which by itself is of little value to detecting vortex cores. However, we take these ideas from the lemma and apply them in a point-based fashion to detecting vortex core regions. The resulting algorithms for both 2D and 3D are quite simple and very efficient compared to existing ones. We applied our algorithms to both numerically simulated and procedurally generated datasets to illustrate the efficacy of our approach.

Simulating the Freezing of Supercooled Water Droplets Impacting a Cooled Substrate

Abstract: To study ice adhesion at the droplet scale, a strategy is presented to simulate the impact and solidification of a supercooled water droplet on a cooled substrate. Upon impact, nucleation is assumed to occur instantaneously, and properties of the droplet are chosen to account for the nucleation process. Simulations are performed in ANSYS Fluent using a coupled volume-of-fluid and level-set method to capture the air–water interface, and an enthalpy-porosity method is used to capture the liquid–solid interface. Calibration of a simulation parameter Amush is performed in order to match experimental data for different ideal surface types and surface temperatures. The simulation strategy successfully predicts the overall droplet response for several droplet impact conditions.

Investigation of a Dynamic Hybrid RANS/LES Modelling Methodology for Finite-Volume CFD Simulations

Abstract: This paper investigates a recently proposed dynamic hybrid RANS-LES framework using a general-purpose finite-volume flow solver. The new method is highly generalized, allowing coupling of any selected RANS model with any selected LES model and containing no explicit grid dependence in its formulation. Selected results are presented for three test cases: two-dimensional channel flow, backward facing step, and a nozzle flow relevant to biomedical applications. Comparison with experimental and DNS data, and with other hybrid RANS-LES approaches, highlights the advantages of the new method and suggests that further investigation is warranted.

Geometric verification of swirling features in flow fields

Abstract: In this paper, we present a verification algorithm for swirling features in flow fields, based on the geometry of streamlines. The features of interest in this case are vortices. Without a formal definition, existing detection algorithms lack the ability to accurately identify these features, and the current method for verifying the accuracy of their results is by human visual inspection. Our verification algorithm addresses this issue by automating the visual inspection process. It is based on identifying the swirling streamlines that surround the candidate vortex cores. We apply our algorithm to both numerically simulated and procedurally generated datasets to illustrate the efficacy of our approach.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

New insights into large eddy simulation

Abstract: Fluid dynamic turbulence is one of the most challenging computational physics problems because of the extremely wide range of time and space scales involved, the strong nonlinearity of the governing equations, and the many practical and important applications. While most linear fluid instabilities are well understood, the nonlinear interactions among them makes even the relatively simple limit of homogeneous isotropic turbulence difficult to treat physically, mathematically, and computationally. Turbulence is modeled computationally by a two-stage bootstrap process. The first stage, direct numerical simulation, attempts to resolve the relevant physical time and space scales but its application is limited to diffusive flows with a relatively small Reynolds number (Re). Using direct numerical simulation to provide a database, in turn, allows calibration of phenomenological turbulence models for engineering applications. Large eddy simulation incorporates a form of turbulence modeling applicable when the large-scale flows of interest are intrinsically time dependent, thus throwing common statistical models into question. A promising approach to large eddy simulation involves the use of high-resolution monotone computational fluid dynamics algorithms such as flux-corrected transport or the piecewise parabolic method which have intrinsic subgrid turbulence models coupled naturally to the resolved scales in the computed flow. The physical considerations underlying and evidence supporting this monotone integrated large eddy simulation approach are discussed.

On the relationships between local vortex identification schemes

Abstract: We analyse the currently popular vortex identification criteria that are based on point-wise analysis of the velocity gradient tensor. A new measure of spiralling compactness of material orbits in vortices is introduced and using this measure a new local vortex identification criterion and requirements for a vortex core are proposed. The inter-relationships between the different criteria are explored analytically and in a few flow examples, using both zero and non-zero thresholds for the identification parameter. These inter-relationships provide a new interpretation of the various criteria in terms of the local flow kinematics. A canonical turbulent flow example is studied, and it is observed that all the criteria, given the proposed usage of threshold, result in remarkably similar looking vortical structures. A unified interpretation based on local flow kinematics is offered for when similarity or differences can be expected in the vortical structures educed using the different criteria.

The State of the Art in Flow Visualisation: Feature Extraction and Tracking

Abstract: Flow visualisation is an attractive topic in data visualisation, offering great challenges for research. Very large data sets must be processed, consisting of multivariate data at large numbers of grid points, often arranged in many time steps. Recently, the steadily increasing performance of computers again has become a driving force for new advances in flow visualisation, especially in techniques based on texturing, feature extraction, vector field clustering, and topology extraction. In this article we present the state of the art in feature-based flow visualisation techniques. We will present numerous feature extraction techniques, categorised according to the type of feature. Next, feature tracking and event detection algorithms are discussed, for studying the evolution of features in time-dependent data sets. Finally, various visualisation techniques are demonstrated.