Jeffrey B. Allen

Momentum Flux in Plane, Parallel Jets

The evolution of the streamwise momentum flux for two turbulent, plane, parallel jets discharging through slots in a direction normal to a wall was studied both numerically and experimentally. The numerical results, obtained by solving the Reynolds-averaged Navier-Stokes equations employing a standard κ-e turbulence model, predicted to within experimental error measured integrals of the momentum flux downstream of the merge point for jet spacing S/d=5. Integration of the streamwise component of the Reynolds-averaged Navier-Stokes equations over a control volume results in an integral constant that was evaluated numerically for jet spacings S/d=3, 5, 7, 9, and 11, and for different levels of turbulence kinetic energy and dissipation rate at the jet inlet boundaries

Numerical Simulations of a Scramjet Isolator Using RANS and LES Approaches

The internal, compressible, turbulent flow through a scramjet-isolator configuration is presented, with the primary goal being to better determine the shock train leading edge location of a typical Mach 2 nozzle-isolator configuration. Both 2D and 3D approaches are utilized, in conjunction with a variety of different turbulence models taken from both RANS and filtered models. The effects of inlet turbulence, as well as the use of grid adaption techniques are evaluated under the 2D assumption and render certain simplifying assumptions valid for the 3D cases. Experimental comparisons reveal that the RANS approach best conform to experimental observations, while the LES approach showed the most degree of disparity. Further LES simulations are warranted however, particularly since these were performed without the aid of density based solvers, which greatly facilitates the prior to the inception of a new FLUENT release, (version 6.3) which contains several improvements over previous releases with respect to compressible, turbulent flows.

Numerical Modeling of Turbulent, Parallel, Round Jets

Although extensive research has been conducted for turbulent single and offset wall jets, relatively little research has been conducted for turbulent parallel jets. Relevant applications include burners, boilers, film cooling, fuel-injection, heating and air-conditioning systems, and designs for pollutant exhaust stacks. The objective of the present work is to evaluate the use of Reynolds-averaged Navier-Stokes, k-epsilon, numerical simulations to predict the three-dimensional evolution of twin, isothermal, turbulent, round jets at a Reynolds number (based on jet diameter d and jet exit velocity Ue) of 25,000. Comparisons with existing experimental literature are conducted with respect to the stream wise turbulence intensity. Further, the stream-wise distance to the combined point is evaluated, along with integrations of stream wise momentum flux. This research will offer an enhanced understanding of parallel jet flow interaction in terms of flow entrainment, as well as provide insights into the sensitivity of the numerical results to variations of inlet turbulence.

Million-Atom Count Simulations of the Effects of Carbon Nanotube Length Distributions on Fiber Mechanical Properties

The extraordinary mechanical properties of carbon nanotubes (CNTs) make them prime candidates as a basis for super infrastructure materials. Ab initio, tight binding, and molecular dynamics simulations and recent experiments have shown that CNTs have tensile strengths up to about 15.5 million psi (110 GPa), Young’s modulus of 150 million psi (1 TPa), and density of about 80 lbs/ft3 (1.3 g/cm3). These qualities provide tensile strength-toweight and stiffness-to-weight ratios about 900 times and 30 times, respectively, those of high-strength (100,000- psi) steel. Building macromaterials that maintain these properties is challenging. Molecular defects, voids, foreign inclusions, and, in particular, weak intermolecular bonds have, to date, prevented macromaterials formed from CNTs from having the remarkable strength and stiffness characteristics of CNTs. The van der Waals forces associated with CNTsrepresent a force per unit length between CNTs. Accordingly, one would expect the bond strength between aligned CNTs to increase with overlap length. Real filaments are likely composed of CNTs with some distribution of lengths. To understand the effects that CNT length distributions have on the tensile strength of neat filaments of aligned CNTs, we performed a series of quenched molecular dynamics simulations on high performance computers using Sandia Laboratory’s Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) code. The cross-section of each filament was composed of hexagonal closest-packed (HCP) array CNT strands that formed two HCP rings. The filaments were constructed by placing (5,5) chirality CNTs end to end. While the choice of a single-chirality CNT fiber is currently unrealizable, the use of a singlechirality fiber allowed us to focus only on the effects of CNT lengths on filament response. The lengths of the CNTs were randomly selected to have Gaussian distribution with the average length ranging from 100 to 1,600Å. A series of simulations were performed on filament with lengths ranging from 400 to 6,400Å. For each filament, the strain was increased in small increments and quenched between strain increments. The total tensile force on the filament was recorded and used to determine the uniaxial stress-strain response of the filaments. The results of the simulations quantified the improvements in Young’s modulus, tensile strength, and critical strain as a function of the increase in the average component CNT lengths. These are the first molecular dynamics simulations that the authors are aware of that treat statistical qualities of realistic CNT structures. The simulation results are being used to guide the molecular design of CNT filaments to achieve super (1 million psi) strength. The simulations would be impractical, and perhaps impossible, without massively parallel, highperformance computational platforms and molecular dynamics simulation tools optimized to run on such platforms.

Hydraulic Modeling of Large Roughness Elements with Computational Fluid Dynamics for Improved Realism in Stream Restoration Planning

Many stream restoration design procedures are based on user experience in distributing standard stream design features into stream channel types based on a stream classification scheme. Computational fluid dynamics (CFD) models, increasingly used to represent stream flow fields, offer a more quantitative path forward. However, CFD models, in practice, parameterize roughness on too large a scale and therefore do not explicitly represent discrete features such as large rocks and large woody material whose placement is the focus of stream restoration activities. The Stream Habitat Assessment Package (SHAPE), made possible by rapid advances and availability of high-performance computing resources and increased sophistication of both in-house and commercial software, overcomes barriers that prevent the routine use of CFD modeling in stream restoration planning. Capabilities of SHAPE that improve stream restoration planning include (1) realistically representing natural streambeds from potentially coarse sets of field measurements, (2) easily deforming the streambed surface with a virtual excavator, (3) selecting complex objects from a library and embedding them within the surface (e.g., rocks and fallen trees), (4) successfully meshing the channel surface and its surrounding volume in accordance with established mesh quality criteria, and (5) sufficiently resolving flow field solutions. We illustrate these capabilities of SHAPE using a coarse set of field data taken from one of four study sites along a 1.5 mile stretch along the Robinson Restoration project of the Merced River, California, along with respective challenges, solution strategies, and resulting outcomes. Flow field solutions are conducted using parallelized finite element/volume solvers.

Simulations of Anisotropic Grain Growth Subject to Thermal Gradients Using Q-State Monte Carlo

The Q-state Monte Carlo, Potts model is used to investigate 2D, anisotropic, grain growth of single-phase materials subject to temperature gradients. Anisotropy is simulated via the use of nonuniform grain boundary surface energies, and thermal gradients are simulated through the use of variable grain boundary mobilities. Hexagonal grain elements are employed, and elliptical Wulff plots are used to assign surface energies to grain lattices. The mobility is set to vary in accordance with solutions to a generalized heat equation and is solved for two separate values of the mobility coefficient. Among other findings, the results reveal that like isotropic grain growth, under the influence of a thermal gradient, anisotropic grain growth also demonstrates locally normal growth kinetics.

Simulation of Aerodynamic Influences on Rocket-Mounted Oxygen Sensors

Over the past several decades, atomic oxygen measurements taken from sounding rocket sensor payloads in the altitude range of 80-140 kilometers have shown marked variability. Many sounding rocket payloads contain atomic oxygen sensors that are located in close proximity to the payload surface, and are thus significantly influenced by flow field disturbances. Although several additional factors including Doppler shift and sensor contamination may also play a significant role in the accurate measurement of atomic oxygen concentrations, this work focuses solely on the effects due to the flow field. The present study utilizes the three-dimensional, steady-state, direct simulation Monte Carlo technique. In addition, the lower altitudes corresponding to near-continuum flow are solved via the Navier-Stokes equations with slip wall boundary conditions. The flow is simulated at 13 different altitudes, each with three separate rocket orientations, along both the rockets upleg and downleg trajectory for a total of 75 simulations. The numerical simulations show conclusively that the relative magnitudes of undisturbed versus disturbed atomic oxygen concentrations are highly dependent upon rocket orientation, and provide a quantitative means by which existing atomic oxygen concentration data sets may be corrected for aerodynamic influences.

Numerical investigation of FAST powder consolidation of Al2O3 and additive free β-SiC

In this work we examine ceramic synthesis through powder consolidation and the field assisted sintering technique. In particular, we investigate the sintering of Al2O3 and additive free from both an experimental and numerical perspective. For the numerical model, the continuum theory of sintering model is employed, and the densification mechanisms corresponding to power law creep and grain boundary diffusion are considered. Experiments are used for comparison and validation purposes. The results indicate that in general, the densification kinetics simulated by the numerical model compare favorably with the experimental results. Parametric studies involving initial grain size, heating rate, and applied stress are also examined using the numerical model, and confirm many of the expected results from previous research, including increased densification due to higher heating rates, smaller grain sizes, and increased applied loading conditions.

Grain Growth, Uniform

On heating, polycrystalline microstructures spontaneously coarsen. If the mean grain size increases with time, but the grain structure remains self-similar, then the process is called normal grain growth . There are many analogous systems that exhibit the same coarsening phenomenon, such as soap froths, lipid monolayers, and magnetic domain structures. In this article the theory of ideal two-dimensional (2-D) grain growth is analyzed and then the attempts by various theorists to extend the theory to three dimensions (3-D) are discussed. The success of computer simulations of grain growth has been marked, and a representative sampling of several different models is described.

Design of Very High-Strength Aligned and Interconnected Carbon Nanotube Fibers Based on Molecular Dynamics Simulations

The principal objective of this work is to implement a new material development paradigm using atomistic simulations to guide the molecular design of materials. Traditional empirical macroscopic material development studies omit the fundamental insight needed to understand material behavior at the atomic and molecular levels where material response begins. The new paradigm relies heavily on a tight integration between simulation and experimental efforts to design and process new materials with nanometer-scale precision. Exploiting nanotechnology requires atomic-molecular-level material design and the ability to process these materials with atomic-molecular-level precision. Processing materials with nanoscale precision poses formidable theoretical, computational, and experimental challenges to developing advanced materials. High performance computers and advanced physics-based simulations can complement experimental efforts to design, test, synthesize, and analyze novel materials and innovative structural designs. This method can be applied to a wide range of material designs. As a proof of concept, we began our work on the design of novel carbon nanotube-based materials. The mechanical properties of carbon nanotubes such as low-density, high-stiffness, and exceptional strength make them ideal candidates for reinforcement material in a wide range of high performance composites. Molecular dynamics simulations are used to predict the tensile response of fibers composed of aligned carbon nanotubes with intermolecular bonds of interstitial carbon atoms. The effects of bond density and carbon nanotube length distribution on fiber strength and stiffness are investigated. Results indicate that including cross link atoms between the carbon nanotubes in the strands significantly increases the load transfer between the carbon nanotubes and prevents them from slipping. This increases the elastic modulus and yield strength of the fibers by an order-of-magnitude. Carbon nanotube-based materials appear poised to affect civil and military engineering significantly over the next two decades by providing materials with an order-of- magnitude improvement in strength-to-weight and stiffness-to-weight ratios over existing materials.