### Sandia National Laboratories, New Mexico

Randomized Algorithms for Sparse Matrix Block Discovery.

Peter Ahrens, Massachusetts Institute of Technology

**Practicum Year:**2019

**Practicum Supervisor:**Erik Boman, PMTS, Center for Computing Research, Sandia National Laboratories, New Mexico

We explored implementations of cutting-edge theoretical randomized algorithms with the example application of finding row and column permutations of sparse matrices which induce blocks. These algorithms can be used to accelerate sparse matrix operations. The time savings of the accelerated operation must offset the time it takes to run the algorithm, so approximate algorithms which run very quickly are highly desirable in this setting. There are applications to problems like graph partitioning.

Uncertainty Quantification on Ionization Models in 1D Kinetic Simulations

Claire Kopenhafer, Michigan State University

**Practicum Year:**2019

**Practicum Supervisor:**Thomas Mattsson, Manager, High Energy Density Physics Theory, Org. 1641, Sandia National Laboratories, New Mexico

One of the biggest problems affecting energy yields from inertial confinement fusion is that of interface mixing. In order to better understand the plasma physics occurring in this phenomenon, I worked with 1D kinetic simulations and set up an uncertainty quantification analysis on the ionization models that feed into the simulations. This allows us to determine how much the uncertainty in the ionization model propagates into the uncertainty in the overall simulation. In turn, this uncertainty quantification can be used with synthetic observation tools to explore how much the uncertainty affects experimental observations, and if experiments are sensitive enough to distinguish between ionization models.

Singular graph editing for hex meshable singular graphs

Paul Zhang, Massachusetts Institute of Technology

**Practicum Year:**2019

**Practicum Supervisor:**Scott A. Mitchell, Principal Member Technical Staff, Center for Computing Research, Sandia National Lab, Sandia National Laboratories, New Mexico

The goal is to compute frame fields for hex meshing. The majority of frame fields have bad singular graphs which fail to be hex meshed. By modifying the singular graphs we aim to fix these frame fields so that they can be hex meshed.

Predicting Tribochemically Induced Reactions of Two-Dimensional Materials

Quentarius Moore, Texas A&M University

**Practicum Year:**2019

**Practicum Supervisor:**Dr. Michael Chandross, Principal Member of the Technical Staff, Computational Materials and Data Science, Sandia National Laboratories, New Mexico

We propose to utilize the time to investigate how local surface strains influence the evolution of the frictional properties of two-dimensional (2D) materials while simultaneously examining the change in reactivity induced by surface strain and applied loads; this will give insight into properties such as reduction and oxidation potentials. As a 2D material is deformed, changes in the local bond-order should render specific locations more susceptible to tribochemical reactions. The nature of tribochemical reactions is still vague; thus we will employ a coordinated set of density functional theory (DFT) and molecular dynamics (MD) simulations using high-performance computing to systematically investigate the reactions to infer their origins in detail.
As a continuation from the previous practicum, we will begin to investigate the reactivity of strained states with select molecules by creating a model to compare with experimental results. Solid-state DFT is slated to be implemented to simulate further the system of interest along with determining the accuracy of the MD simulations. This DFT approach also serves as a tool for simulations when there are no MD force fields available for future problems that we want to investigate. Learning software to perform DFT calculations on solid-state systems will add to my knowledge of running DFT calculations on large periodic systems.

Thermomechanical Basis of Friction in MoS2

Quentarius Moore, Texas A&M University

**Practicum Year:**2018

**Practicum Supervisor:**Michael Chandross, Principal Member of the Technical Staff, Computational Materials and Data Science, Sandia National Laboratories, New Mexico

Tribology is the study of friction and wear at interacting surfaces. The impact of friction and wear on the global economy is directly related to energy loss in systems and how that energy may be recovered to reduce fuel consumption. Holmberg, K. et al., Friction 2017. 5, 263-264 indicated that by utilizing new surfaces, materials, and lubrication technologies for friction reduction and wear protection in vehicles and other machinery worldwide, a savings of 1.4% of the GDP annually and 8.7% of total energy consumption could be realized long term. Molybdenum disulfide (MoS2) has been an integral part of material technologies used to control friction and wear in applications.
MoS2 is a transition metal dichalcogenide that is useful in solid lubrication, heterostructures, catalysis, and 2D-based electronic devices. The lamellar structure of MoS2 is similar to that of graphene, mica, and hexagonal boron nitride, with weak interactions between the lamella leading to exceptional frictional properties. This leads to the need to understand the interactions at the atomic scale, and uncovering the physics of atomic-scale friction and its influence on energetics during sliding is of value in a fundamental understanding.
We investigate how local surface strains influence the evolution of the frictional properties of MoS2 while simultaneously examining the change in reactivity induced by surface strain and applied loads; this will give insight into properties such as reduction and oxidation potentials. As a 2D material is deformed, changes in the local bond-order should render specific locations more susceptible to tribochemical reactions.
The nature of tribochemical reactions is still vague thus we used atomistic simulation to construct models that accurately predict results from tribological experiments. Establishing relationships between the properties of MoS2 and frictional performance aids in developing more robust experimental studies and helps to better understand friction, wear, and lubrication.
Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energyâ€™s National Nuclear Security Administration under contract DE-NA0003525.

Optimized Algorithm for High-efficiency Atom Transport

Zane Crawford, Michigan State University

**Practicum Year:**2017

**Practicum Supervisor:**Michael Martin, Harry S. Truman Postdoctoral Fellow, 1000 (Org. 1728), Sandia National Laboratories, New Mexico

The project entailed creating a robust algorithm capable of creating a series of holograms that served as optical traps for atoms. By creating a series of holograms, one could potentially move atoms into certain arrangements and measure quantum effects between the atoms. The holograms that were created needed to have certain properties to ensure atoms were properly trapped, including in transition between certain end states. Furthermore, to accelerate the rate at which holograms were created, GPUs were to be used to assist in hologram generation.

Finite Element in Angle Charged Particle Transport

Mario Ortega, University of California, Berkeley

**Practicum Year:**2017

**Practicum Supervisor:**Len Lorence, Manager, Radiation Effects Theory Department, 01341, , Sandia National Laboratories, New Mexico

Implemented finite element in angle schemes to discretize the angular portion of the charged particle transport equation. Investigated unit sphere mappings to two-dimensional coordinate systems to determine best transformations for meshing.

Release Isentropes for Aluminum

Aurora Pribram-Jones, University of California, Irvine

**Practicum Year:**2013

**Practicum Supervisor:**Michael Desjarlais, Senior Scientist, High Energy Science Department, Sandia National Laboratories, New Mexico

Two different methods for computation of release isentropes for aluminum were compared. This allowed verification of the accuracy of a new method for computation of isentropes using quantum molecular dynamics that requires fewer calculations. These isentropes are crucial for modeling shock experiments, especially those that involve transfer of shock across different materials. The high computational cost of quantum molecular dynamics simulations demands development of the most efficient schemes possible.

Large Scale Conflict in Massively Multiplayer Online Games

Rogelio Cardona-Rivera, North Carolina State University

**Practicum Year:**2012

**Practicum Supervisor:**James C. Forsythe, Distinguished Member of Technical Staff, Org 1462, Sandia National Laboratories, New Mexico

Multi-Agent System Simulations are costly to produce because of the amount of data required and the length of observation required to make any meaningful simulations. Massively Multiplayer Online Games (MMOG) have recently become a useful source of data in creating and validating Multi-Agent Models. I used an MMOG to study real-world phenomena of interest: the conditions that gave rise to Large Scale Conflicts (LSC's), with the intent of producing a Multi-Agent Model of virtual LSC that would help predict real-world LSC.

Subgraph Isomorphism for Multithreaded Architectures

Claire Ralph, Cornell University

**Practicum Year:**2011

**Practicum Supervisor:**Vitus Leung, PhD, Computer Science Research Institute, Sandia National Laboratories, New Mexico

We continue to study algorithms for the subgraph isomorphism problem implemented
for massively multithreaded shared memory architectures such as the
Cray XMT. Fast algorithms for the subgraph isomorphism problem will
have important implications in many fields including biology, data mining, and satellite imaging.

Subgraph Isomorphism Algorithms for Multithreaded Architectures

Claire Ralph, Cornell University

**Practicum Year:**2010

**Practicum Supervisor:**Vitus Leung, PhD, , Sandia National Laboratories, New Mexico

We study algorithms for the subgraph isomorphism problem implemented
for massively multithreaded shared memory architectures such as the
Cray XMT. Fast algorithms for the subgraph isomorphism problem will
have important implications in Biology. Recently the availability of
genomic data has increased drastically due to the use of high
throughput methods which have made sequencing relatively easy.
Automated techniques are needed in order to glean useful information
from this wealth of data. Many of these techniques rely on solving an
underlying subgraph isomorphism problem and will thus benefit from
fast highly parallel algorithms. By implementing these algorithms on a
multithreaded shared memory platform, we minimize the communication
latency due to the need for random access into the large graph which
is inherent to these types of problems.

Applying the Two Temperature Model to Radiation Damage in an Amorphizing Material

Carolyn Phillips, University of Michigan

**Practicum Year:**2009

**Practicum Supervisor:**Paul Crozier, , Multiscale Dynamic Material Modelling, Sandia National Laboratories, New Mexico

I evaluated a new version of a two temperature model that was being implemented in the LAMMPS Molecular Dynamics Code. I first tested the model of on the annealing of a Frenkel Defect in a Lennard-Jones system. Then I modeled the annealing a heat deposit event in a Lennard-Jones Crystal, a Binary Lennard-Jones Crystal, and a alpha-Quartz crystal with various attached electronic subsystems.

Biophysical basis for community-level infectious disease models

Danilo Scepanovic, Harvard/Massachusetts Institute of Technology

**Practicum Year:**2009

**Practicum Supervisor:**Robert Glass, , NISAC (Nat'l Infrastructure Sim. and Anal. Ctr.), Sandia National Laboratories, New Mexico

The Loki-infect model is an agent based infectious disease model developed at Sandia NL and used to study community-level mitigation strategies in the event of an influenza pandemic. At this point in time, all such models (both agent-based and deterministic) use a simplified disease manifestation based mostly on epidemiological data and various assumptions regarding immeasurable quantities such as infectivity. The most popularly-used disease manifestation model was derived in a "top-down" manner, using data from a study where influenza patients and their contacts were followed, and the statistics of who got sick, how long they were sick, and how frequently they went to the hospital were used to derive the model. This model can accurately represent the observed statistics on average, but is not ideal for agent-based modeling studies. To solve this problem, we aimed to derive a completely new, "bottom-up" disease manifestation that begins with a model of viral proliferation in individuals, and uses the calculated viral load and basic physical principles to derive symptom intensity, infectiousness, death, etc. of individual agents. More specifically, our project had two elements: 1) improving the implementation of the agent-based model and 2) providing a biophysical basis for disease manifestation in individual agents.

Explicit multiscale time integrator for transient dynamic simulations

Cameron Talischi, University of Illinois at Urbana-Champaign

**Practicum Year:**2009

**Practicum Supervisor:**Martin Heinstein, , Computational Solid Mechanics/Structural Dynamics, Sandia National Laboratories, New Mexico

Title: Investigating an explicit multiscale time integrator
The focus of my project was to investigate the stability properties of an explicit multiscale time integration scheme, in which information obtained from fine scale computations are used to enhance the accuracy of quantities of interest on coarse grids. The method leads to substantial savings for problems that require fine spatial discretization for stress gradient or failure modeling but do not need the associated small time steps dictated by stability criteria.

Developing database tools to process data for use in large-scale airline optimization models

Brian Levine, Cornell University

**Practicum Year:**2008

**Practicum Supervisor:**Dean Jones, , 6323, Sandia National Laboratories, New Mexico

My project involved coming up with the input data necessary to run a large-scale airline optimization model. Every month, airlines provide their operating data to the government, who then makes it available to the general public. This data includes details about every scheduled domestic flight by all the main carriers, as well as a 10% survey of individual itineraries by passengers. Clearly, these datasets are extremely large in size and difficult to manipulate effectively, and effective tools need to be developed to aggregate the data in order to extract key relationships among carriers, aircraft usage, flights flown, and passenger routings.

Variational Multiscale and Monotone Methods for Magnetohydrodynamics

John Evans, University of Texas

**Practicum Year:**2007

**Practicum Supervisor:**John Shadid, Distinguished Member of Technical Staff, Computational Sciences Group, Sandia National Laboratories, New Mexico

The project I was involved with dealt with the development of new stable and efficient algorithms for solving partial differential equations arising in magnetohydrodynamics (MHD), the science of electrically conducting fluids. MHD arises in a number of application areas important to the Department of Energy, including fusion energy research, nuclear weapons stewardship and simulation, geodynamics, and astrophysics. My group was particularly interested in the development of stabilized higher-order finite element methods for the simulation of MHD applications.

Implementation of a particle migration application for the Stochastic Parallel PARticle Kinetic Simulator (SPPARKS) framework

Kristi Harris, University of Maryland, Baltimore County

**Practicum Year:**2007

**Practicum Supervisor:**Aidan P. Thompson, Principle Member of Technical Staff, Multiscale Computational Materials Methods, Sandia National Laboratories, New Mexico

Currently in development, SPPARKS is a parallel implementation of the kinetic Monte Carlo (KMC) algorithm that will span the gap between atomistic (e.g., molecular dynamics) and continuum simulation approaches. Parallelizing the KMC algorithm makes it possible to maintain the stochastic nature of the modeled phenomenon while achieving the necessary size and/or time scales for large simulations. Concurrent with the development of the SPPARKS framework is the creation of a suite of materials science applications, enabling simulation of phenomena such as surface deposition and growth, grain growth, and others. My project was to implement an application for simulating particle migration within the parallel KMC simulation framework. The motivating use of the application is the simulation of biased random motion of aluminum surface atoms, which models electromigration-induced void formation in embedded current-carrying interconnects in integrated circuits.

A Vector Finite-Element Implementation for Modeling Inhomogeneous Waveguides

David Ketcheson, University of Washington

**Practicum Year:**2007

**Practicum Supervisor:**Hung (Jacques) Loui, Truman Fellow, Dept. 5345 SAR Sensors Technologies, Sandia National Laboratories, New Mexico

A vector finite element method implementation in MATLAB was developed for application to microwave waveguide calculations. The use of divergence-free vector basis functions for the transverse field components ensures that all nonphysical modes appear with zero frequency. The method is capable of handling general nonsymmetric transversally anisotropic
materials. The use of arbitrarily high order nodal and vector elements is enabled through a Mathematica routine that generates MATLAB code to compute the elemental matrices.

Designing DNA biosensors for the detection of genetic variation

Miler Lee, University of Pennsylvania

**Practicum Year:**2007

**Practicum Supervisor:**Elebeoba E. May, , Computational Biology Department, Sandia National Laboratories, New Mexico

We are refining a new computational paradigm for the detection of genetic variation, using deoxyribozymes -- catalytic single-stranded DNA sequences. Deoxyribozymes can be designed to combinatorially detect the presence or absence of particular nucleotide sequences in vitro, and thus can be used for genetic subtyping. The challenges include identifying informative sequences from the samples of interest, creating optimally functional deoxyribozymes, and interpreting the signals produced by the deoxyribozyme-catalyzed reactions.

Understanding Resveratrol, its stilbene derivatives and potential targets

Ariella Sasson, Rutgers University

**Practicum Year:**2007

**Practicum Supervisor:**W. Michael Brown, Senior Member of the Technical Staff, Sandia National Labs, Sandia National Laboratories, New Mexico

The purpose of this project is to better understand resveratrol, its stilbene derivatives and their potential targets using various quantitative methods. Resveratrol is a naturally occurring polyphenol whose anti-oxidant properties have been linked to help prevent or slow the progression of many illnesses including cancer, cardiovascular disease, and Alzheimer's disease. Understanding how resveratrol interacts in various pathways is critical to better understanding how resveratrol can be used in developing drug therapies. Relating a molecule's structure to its function is one of the larger problems in biology/chemistry, and there are many different approaches that can be taken in order to study it. The quantitative structure-activity relationship (QSAR) is a mathematical way to correlate the molecular structure with biochemical activity. Using Support Vector Machines (SVMs) to interpret this relationship has become a powerful tool due to the ability to interpret the non-linear correlations. The SVMs transforms the data to a feature space in which the model becomes linear. Using a subset of the Resveratrol Analogue Library, various techniques including the use of Support Vector Machines and Kernel Molecular Dynamics were used to elucidate the molecular structure and classification between active and inactive drug.

A Study of Computational Approaches for Parameter Estimation in the Escherichia coli K-12 Central Metabolic System

Jimena Davis, North Carolina State University

**Practicum Year:**2006

**Practicum Supervisor:**Dr. Elebeoba E. May, , Computational Biology Department, Sandia National Laboratories, New Mexico

The Xyce electrical circuit simulation tool (developed by Sandia National Laboratories) has been extended to create a large-scale, parallel, biocircuit simulator. This required the development of individual circuit elements representing metabolic and genetic substrates and an accurate description of the coupling between elements as demonstrated in the simulation of the tryptophan biosynthesis pathway. A challenge in this project is determining simulation parameters that produce results consistent with experimental data. To this end, we are interested in computational approaches that can accurately estimate multiple parameters for biological network simulations.
We focused on the simulation of the Escherichia coli K-12 central metabolic system. Our previous work with this system included the construction of a hybrid whole-cell model, which incorporates both stoichiometric and gene regulatory data in one circuit. The central metabolism model was derived from supplemental data provided in Covert and Palsson (2002). Our initial circuit model did not include empirically-determined reaction rate information in the simulation. Using Michaelis-Menten kinetics and the King-Altman method, we reformulated the metabolic subcircuits to incorporate reaction rates reported in the BRENDA database (http://www.brenda.uni-koeln.de/). In order to estimate the parameters for which no empirical rate information is available, we coupled Xyce to DAKOTA, an optimization toolkit also developed by Sandia National Laboratories. Using DAKOTA and empirical data, we examined various computational approaches for the estimation of multiple rate parameters for the E. coli central metabolic system.

Thermal Conductivity of Carbon Nanotubes Using Molecular Dynamics Simulations

Asegun Henry, Massachusetts Institute of Technology

**Practicum Year:**2006

**Practicum Supervisor:**Steven Plimpton, Dr, Computational Biology Dept, Sandia National Laboratories, New Mexico

We implemented a new adaptive intermolecular reactive empirical bond order (AIREBO) potential into the LAMMPS software package. This new potential allows us to simulate the interactions within hydrocarbon molecules and has additional terms to treat long range interactions between molecules. We intend to use this potential to calculate the thermal conductivity of a wide variety of single and multi-walled carbon nanotubes. Using the computational resources available to the national labs, we can explore new aspects of this problem with greater detail and confidence.

Characterization of Distributed Micro-releases of Pathogens

Michael Wolf, University of Illinois at Urbana-Champaign

**Practicum Year:**2006

**Practicum Supervisor:**Karen Devine, Principal Member of Technical Staff, Computation, Computers, Inform. and Math (CCIM), Sandia National Laboratories, New Mexico

In this project, we are working on identification of the time and location of several small "micro-releases" of pathogen based on the identification of infected individuals at medical institutions. Large releases of pathogen can be more easily detected by sensors placed at a relatively small number of key locations. However, distributed micro-releases can evade sensor detection since the amount of contagion is smaller at each location and the targets can be much more varied. The first indication of the pathogen will be patients at clinics or hospitals showing sufficiently obvious symptoms for positive diagnosis. Timely identification and characterization of the threat of these micro-releases is essential for the containment of the disease propagation. Since detection is difficult and the dynamics of the disease propagation is complex, obtaining an accurate model is very challenging and computationally intensive, requiring the solution of many interesting computational science problems. The general approach towards this problem of inferring the micro-release characterization from the patient data is to formulate a Bayesian inverse problem which can provide probabilistic descriptions to identify the most likely timings and locations of the onset of pathogen. With these probabilistic descriptions, appropriate responses can be shaped to most effectively mitigate the spread of the pathogens. In order to solve the Bayesian inverse problem, a forward disease propagation problem must be solved numerous times to provide the information necessary to solve this inverse problem accurately.
I also spent some of my summer working on a combinatorial optimization problem with Erik Boman.

Coarse-grained MD simulations of biomembrane phase transitions

Erik Allen, Massachusetts Institute of Technology

**Practicum Year:**2005

**Practicum Supervisor:**Paul Crozier, , Computational Materials and Molecular Biology, Sandia National Laboratories, New Mexico

Poorly understood biomembrane phase transitions are required for
important biological processes such as cell fusing and budding.
Molecular simulation gives insight into these phase transitions that
adds substantially to the knowledge gained through theory and
experiment(1). Recent improvements in force field development(2,3) for
coarse grained molecular dynamics (CGMD) simulation of biomolecular
systems has enabled computer experiments of unprecedented size and
timescale. We use atomistic molecular dynamics (MD)
simulations with their standard biomolecular force fields (i.e. CHARMM,
AMBER) to parameterize CGMD force fields through a least-squares
force-matching procedure. The resulting CGMD simulation capability
enables a 50-fold or greater enhancement in simulation speed (over
atomistic simulation), with only a modest loss of accuracy. With this
improved CGMD simulation capability we will investigate transitions
between the lamellar and hexagonal phases of biomembranes consisting of
phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipid
mixtures.
1. Marrink, SJ, Mark, AE, Biophys. J., 87, 3894 (2004).
2. Izvekov, S, Parrinello, M, Burnham, CJ, Voth, GA, J. Chem. Phys.,
120, 10896 (2004).
3. Izvekov, S, Voth, GA, J. Phys. Chem. B, in press.

Theoretical and Experimental Examination of the Dynamic Response of Carbon Nanotubes

William Conley, Purdue University

**Practicum Year:**2005

**Practicum Supervisor:**Stephen W. Howell, Technical Staff, Micro-Total-Analytical Systems, Sandia National Laboratories, New Mexico

First, a nonlinear beam model was adopted. In 2-D this model couples vibrations by including stretching modes. This model was examined to determine the resonance behavior of the beam. Additionally, it also resulted in static deflection predictions.
Following the theoretical work, experiments were performed where the electrical properties of the CNT were monitored while the CNT was deflected both statically and dynamically.

Free energy profile of ion diffusion through silicate pores via WHAM

Peter Kekenes-Huskey, California Institute of Technology

**Practicum Year:**2005

**Practicum Supervisor:**Crozier, Paul S., , , Sandia National Laboratories, New Mexico

WHAM, weighted histogram analysis method, is an intuitive and surprisingly accurate methodology for extracting work information from molecular dynamics. One advantage of this methodology is its foundation in umbrella sampling computations and ability to combine several simulations without worrying about overlap issues. This method, along with several other established protocols, was applied to driving solvated ions through a silicon dioxide pore.

Simulation of Z-pinches

Ian Parrish, Princeton University

**Practicum Year:**2005

**Practicum Supervisor:**Thomas Mehlhorn, Manager, HEDP Theory, HEDP Theory/ICF Target Deisgn, Sandia National Laboratories, New Mexico

The project involved verification and validation of the MHD portion of the radiation magnetohydrodynamics code ALEGRA. In addition work was included on the study of experiment and theory of early-time axial variations that are observed in Z-pinches.

Molecular Dynamics Study of the Gating Mechanism of Synechococcus RuBisCO

Christina Payne, Vanderbilt University

**Practicum Year:**2005

**Practicum Supervisor:**Dr. Paul S. Crozier, Senior Member of Technical Staff, Information, Computation and Engineering Sciences, Sandia National Laboratories, New Mexico

Using the LAMMPS molecular dynamics software package, the gating mechanism of Synechococcus RuBisCO and a subset of mutations were examined with the intention of comparing the results to previous simulations performed using an implicit solvent model. Additionally, information about the specificity factor was related to the work profiles of individual mutant molecules in the hopes that this relationship could be used as a potential predictor of theoretical mutant specificity.

Applying Spatially Varying Material Strengths to Simulate High-Rate Fragmentation of Armor-Grade Ceramics

Michael Veilleux, Cornell University

**Practicum Year:**2005

**Practicum Supervisor:**Dr. Rebecca M. Brannon, Principal Member of Technical Staff, Geomechanics Dept 6117, Sandia National Laboratories, New Mexico

The project goal is to develop a finite element framework that accurately models impact-induced damage in armor-grade ceramics. This framework accounts for inherent variability in material strength of brittle ceramics that is directly related to random distributions of microcracks in the material. These microcracks, which are on the order of grain size, are too small to be modeled explicitly in a field-scale simulation where the finite elements contain thousands of grains. Although the material is statistically homogeneous on this scale, observed material response is not spatially homogeneous. The material fails into cube-shaped fragments.
In order to simulate this behavior, computational tools are being developed that create realizations of a material in which the strength of each finite element is allowed to vary in a manner consistent with Weibull theory so that small finite elements have a higher average strength than the large elements. This aspect of the work hypothetically eliminates mesh dependencies in existing finite element failure models without requiring users to supply microscale properties such as flaw densities.
In addition to being spatially variable, the fragmentation process is often high-rate for these armor-grade ceramics. This second characteristic is being simulated by introducing material particles in failed zones that replace the role of integration points in traditional finite elements. Unlike integration points, which are tied to the mesh topology, these material points can move independently from the mesh and therefore support massively large deformations without requiring the finite element mesh to significantly distort. This new finite element framework, having a combination of material particle and spatial variability methods, should accurately predict debris-formation and penetration depths into metal-clad ceramic armor.

Modeling Impact Mechanics using PRESTO

Paul Bauman, University of Texas

**Practicum Year:**2004

**Practicum Supervisor:**Rod May, , Materials Models and Physics, Sandia National Laboratories, New Mexico

Sandia is currently developing the new sierra based, explicit, non-linear mechanics, finite-element code PRESTO. Currently, it is being used for component qualification of materials subjected to intense x-ray environments and impact. However, there remains the question of model validity of the currently available models in PRESTO for modeling these problems. This summer, then, was spent modeling a simple gas-gun impact problem with PRESTO using a variety of models to test he results of PRESTO with corresponding experimental results.

Molecular Modeling of Triglycerides and Vegetable Oils

Mary Biddy, University of Wisconsin

**Practicum Year:**2004

**Practicum Supervisor:**John Curro, , , Sandia National Laboratories, New Mexico

My practicum experience at Sandia was unique. Instead of working on just one project with one collaborator, I actually worked on four projects with four different researchers. The commonality of these projects was that we were using different molecular modeling techniques to look at the physical properties and molecular structure of different chemical species. This opportunity to work on various projects allowed me to learn a great deal about the simulation work that occurs at Sandia. The focus of three of these projects was on the molecular modeling of triglycerides and vegetable oils (which are mixtures of triglycerides), and was directly relevant to my thesis work.
The first project I studied under the guidance of Dr. John Curro and my thesis advisor, Professor Juan de Pablo. This work was very similar to the studies we have been performing at the University of Wisconsin but on a much larger scale. The goal of my thesis work is to model and understand the behavior of vegetable oils which can be used as environmentally friendly lubricating oils. At low temperatures, vegetable oils tend to gel or crystallize. It is important to understand this behavior and why this phenomenon occurs. Using LAMMPS, a parallel molecular dynamics (MD) simulation code developed at Sandia, and the computer resources of Sandia, we were able to perform MD simulations of vegetable oils on a much larger scale than we could have performed at Wisconsin.
The second project, performed under the guidance of Dr. John Curro, looked at an alternative way to model triglycerides. One important physical property used to describe lubricants is viscosity. However, calculating viscosity using MD simulations takes a great deal of computer time (on the order of months). We have developed a coarse grain model of the triglycerides based on soft spheres that can be used instead of an atomistic model. This developed technique has significantly reduced the amount of simulation time to calculate viscosity.
The third project studied the molecular structuring of triglycerides. This project, performed under the guidance of Dr. John Curro, Dr. Laura Frink and Dr. Amalie Frischknecht, focused on using polymeric density functional theory (DFT) to determine what kinds of different structures are formed by triglycerides. Previous work at Sandia had focused on using these methods to look at molecular structuring of polymers near surfaces as well as lipid bilayers in bulk solution. Since triglycerides are lipids, we believe, and have observed in our MD simulations, that they form molecular structures. However, these simulations were performed on a small number of molecules so that absolute conclusions were not possible. By using DFT methods we can perform simulations on a much larger length scale and allow conclusions about triglyceride structuring.
The fourth project, which was performed under the guidance of Dr. Marcus Martin, stemmed from the Second Industrial Fluid

Molecular dynamics simulations of grafted polyelectrolytes on apposing walls

Owen Hehmeyer, Princeton University

**Practicum Year:**2004

**Practicum Supervisor:**Mark Stevens, Principal Member of Technical Staff, Materials & Process Sciences Center (in Div. 1000), Sandia National Laboratories, New Mexico

Molecular dynamics simulations were used to study a model system that approximates polyelectrolytes, including double stranded DNA and sodium poly(styrene sulfonate), tethered on apposing surfaces. The effect of the surface density of the grafted polymer, the chain length, and the gap width on the structure and wall pressure were studied. Results are compared to previous results for a single grafted chain on a single wall, experimental measurements, and scaling theory results. The origin of high lubrication between these apposing walls was investigated by examining the distribution of counterions and monomers. Results are compared to experimental systems where polyelectrolyte layers have been observed to offer a high degree of lubrication.

Nonequilibrium molecular dynamics simulation of a large solute in charged nanopore

Tod Pascal, California Institute of Technology

**Practicum Year:**2004

**Practicum Supervisor:**Aidan P. Thompson, , Computational Materials and Molecular Biology, Sandia National Laboratories, New Mexico

Using molecular dynamics (LAMMPS) we analyze the electrophoretic mobility of a large spherical solute in a charge cylindrical nanopore. Factors influencing the electrophoretic mobility of the solute (mass, charge, radius) were investigated, particularly for deviations from continuum flow behavior. The fluid was composed of cationic counter ions and non-polar monatomic solvent molecules. The cylindrical surface of the pore wall was represented by a stochastic scattering boundary condition.

Finding the Code: Looking for Error Correcting Codes in the binding region of E.Coli mRNA (continuing the effort from the previous summer)

David Schmidt, University of Illinois at Urbana-Champaign

**Practicum Year:**2004

**Practicum Supervisor:**Elebeoba May, Senior Member Technical Staff, Computational Biology Department, Sandia National Laboratories, New Mexico

The project is an ongoing effort at the interface of genetics and information theory. The exact process of how ribosomal subunits bind to mRNA preceeding the translation process is not well understood, and one theory is that these ribosomal subunits act like something of an Error Correcting Code (ECC) Decoder. To evaluate this theory, one must first determine if an ECC indeed exists on the region of mRNA upstream of the start codon or not. This determination is the goal of the project.

Samuel Schofield, University of Arizona

**Practicum Year:**2004

**Practicum Supervisor:**Mark A. Christon, , Computational Physics R&D Dept., Sandia National Laboratories, New Mexico

The project involved the study of interface tracking methods for use in hydanmic applications on unstructured grids.

Investigation of the Conformal Changes of Rubisco

Obioma Uche, Princeton University

**Practicum Year:**2004

**Practicum Supervisor:**Paul S. Crozier, , Computational Materials and Molecular Biology, Sandia National Laboratories, New Mexico

Rubisco (ribulose 1,5-biphosphate carboxylase/oxygenase) is a key enzyme in photosynthesis (catalyzing the fixation of carbon dioxide in the biosphere), and in photorespiration (oxidizing ribulose 1,5-biphosphate (RuBP) with molecular oxygen). The specificity factor of Rubisco, defined as the ratio of apparent first order rate constants for carboxylation and oxygenation is of utmost interest for many species. In an attempt to understand the molecular basis of Rubisco's specificity, we investigate the structure of the enzyme via molecular simulation techniques.

Cellular Concrete Studies: Model Calibration and Simulation Results

Kristine Cochran, University of Illinois at Urbana-Champaign

**Practicum Year:**2003

**Practicum Supervisor:**Shawn Burns, Dr., Computational Physics Research and Development, Sandia National Laboratories, New Mexico

The ability of two simple constitutive models to represent the behavior of a highly porous concrete material under large strains was studied. These constitutive models are part of the Alegra Shock Solid Dynamics code developed at Sandia National Laboratory. One model is a Mie-Gruneisen equation of state with pressure dependent porosity (P-alpha). The second is the soil crushable foam model (SCF). This project was part of a larger effort to improve simulation capabilities for modeling buried structures subject to blast loading. The constitutive models were calibrated for a material specific to one such event, and then large-scale simulations of the event were examined with respect to differences in material model formulation and calibration. This study led to recommendations for improving the constitutive models and targeted additional areas of concern in the large scale simulations.

Optimal robot base placement for automatic weld planning

Sommer Gentry, Massachusetts Institute of Technology

**Practicum Year:**2003

**Practicum Supervisor:**Arlo Ames, Distinguished Member of the Technical Staff, Intelligent Systems and Robotics Center, Sandia National Laboratories, New Mexico

AUTOGEN is a software package for automatic planning of robot welding for the shipbuilding industry. The geometric modeling, inverse kinematics, and inverse dynamics required make solving this problem a true research endeavor.

Real-Time Three-Dimensional Visualization of Standard Light Microscope Image Sequences

Michael Greminger, University of Minnesota

**Practicum Year:**2003

**Practicum Supervisor:**David Kozlowski, Principal Member of Technical Staff, Intelligent Systems and Robotics Center, Sandia National Laboratories, New Mexico

Three-dimensional visualization of microscope images provides the microscope user with a sense of depth when handling microsized objects. Before recent advances in graphics hardware, the real-time three-dimensional visualization of microscope image sequences was not possible.
In this project I demonstrated a method for the three-dimensional visualization of microscope image sequences in real-time. First a series of microscope images are acquired. After some preprocessing, the images are volume rendered using the ray-casting technique. The volume rendering is performed by the graphics hardware using the 3d texture mapping extension to OpenGL. The three-dimensional rendering can be updated at a rate of 12 frames per second.

Finding the Code: Looking for Error Correcting Codes in the binding region of E.Coli mRNA

David Schmidt, University of Illinois at Urbana-Champaign

**Practicum Year:**2003

**Practicum Supervisor:**Elebeoba May, Senior Member Technical Staff, Computational Biology Department, Sandia National Laboratories, New Mexico

The project is an ongoing effort at the interface of genetics and information theory. The exact process of how ribosomal subunits bind to mRNA preceeding the translation process is not well understood, and one theory is that these ribosomal subunits act like something of an Error Correcting Code (ECC) Decoder. To evaluate this theory, one must first determine if an ECC indeed exists on the region of mRNA upstream of the start codon or not. This determination is the goal of the project.

High-Order Positivity Preserving Algorithms for Transport Processes

Benjamin Kirk, University of Texas

**Practicum Year:**2002

**Practicum Supervisor:**Dr. Robert MacKinnon, , , Sandia National Laboratories, New Mexico

In many transport applications there are physical constraints imposed on a solution field. In chemical transport applications it is often the case that the solution field must be nonnegative. However, this issue is not addressed by many numerical techniques used in simulating these processes.
For example, in simulating chemically reacting processes one is often concerned with the spatial concentration of a chemical species in some region of space. It does not make physical sense for the concentration to be less than zero, and relevant constitutive relations & reaction rates often reflect this (involving square-roots, logarithms, etc.). However, in standard numerical techniques negative solution values are admissible and often obtained, leading to problems. This is especially true of high-order methods required to obtain very accurate solutions. The practicum research was involved in analyzing standard techniques for these problems and deriving conditions under which they will produce nonnegative solutions. Numerical experiments were conducted to verify the validity of the methods.

Slip Model Accuracy in MEMS Flows

Matthew McNenly, University of Michigan

**Practicum Year:**2002

**Practicum Supervisor:**Wahid Hermina, Manager, Microscale Science and Noncontinuum Transport, Sandia National Laboratories, New Mexico

The purpose of my summer project was to evaluate the performance of slip models used with continuum-based simulations to predict MEMS gas flows. Their use is motivated by the rapid simulation times compared to using Direct Simulation Monte Carlo (DSMC); however, with the increased speed comes a loss of accuracy. My project was to focus on the slip models currently proposed in literature, understand when and where they lose accuracy, and determine their range of applicability for systems design.

"Defining linear problems for Trilinos"

Allison Baker, University of Colorado

**Practicum Year:**2001

**Practicum Supervisor:**Rich Lehoucq, Principal Member of Technical Staff, Computational Math and Algorithms, Sandia National Laboratories, New Mexico

Trilinos is a C++ library for large-scale linear algebra problems that has been under development at Sandia for some time. My involvement with the Trilinos project was to create a C++ class (and supporting classes) that could completely define a linear problem (based on certain user specifications) for use with any of the linear solvers in the Trilinos package.

Redundant Serial Manipulator Workspace Dexterity Design for Mobile Robot

Eric Lee, Rutgers University

**Practicum Year:**2001

**Practicum Supervisor:**Pablo Garcia, Department Manager, Intelligent Systems Principles Department, ISRC, Sandia National Laboratories, New Mexico

Project Summary: In mobile manipulation, most effort has been concentrated on solving the motion planning and control problems for existing manipulators, few have addressed the design issue of manipulator itself. The first step towards a design is a performance index suitable for mobile manipulation. In this project, a new performance index called the Workspace Dexterity Volume is proposed. This index characterizes the orientability of a manipulator within its workspace. The computational method has been explored. It has been demonstrated that this tool can be used both as a quantitative performance analysis tool and as a qualitative tool for workspace dexterity visualization in complex environment that can include multiple obstacles.

The Use of Single Fiber Models for the Prediction of Novel Oxygenator Performance

Kenneth Gage, University of Pittsburgh

**Practicum Year:**1999

**Practicum Supervisor:**Randy Schunk, DMTS Distinguished Member Technical Staff, Incompressible Fluid Mechanics, Sandia National Laboratories, New Mexico

Extended duration respiratory support with membrane oxygenators often results in poor outcomes. Patient morbidity, mortality and device failure are frequently related to imperfect device properties such as sluggish flow paths, membranes with limited biological compatibility, and inadequate fiber arrangements. Although performance improvement is possible, current oxygenator design processes rely heavily upon prototype manufacture and testing, resulting in limited investigation of the possible design space. The advent of inexpensive computing power coupled with advanced computational fluid dynamics (CFD) and optimization software suggests a more thorough evaluation of the design space is possible given accurate and robust physical models. Existing CFD models of mass transfer can provide some spatial data required for optimization but require determination of correlative constants prior to use, resulting in a loss of model generality. The elimination of empirical correlations from the CFD mass transfer model would allow the investigation of novel oxygenator designs with little or no prior testing.
One approach to eliminating empirical mass transfer correlations from oxygenator CFD models involves the use of small-scale fiber simulations. Simulation results involving single fibers and multiple fibers arranged in various configurations may reveal significant performance differences. Sound application of the models could allow prediction of device performance without testing, resulting in a shortened design cycle. In addition, many novel oxygenator designs utilize active mixing to minimize the mass transfer boundary layer thickness. Direct simulation of the coupled fluid-solid problem could allow unconventional mixing regimes to be investigated prior to

Gradient Driven Diffusion in Nanoporous Media

Marcus Martin, University of Minnesota

**Practicum Year:**1998

**Practicum Supervisor:**Dr. Grant Heffelfinger, , Computational Materials Science Department, Sandia National Laboratories, New Mexico

The goal of this project is to study the diffusion of molecules in nanoporous materials (such as elastic polymers) under the action of a finite chemical potential gradient. The method used is a massively parallel implementation of Dual Control Volume grand canonical molecular dynamics.

Connecting Gas Phase and Surface Problems in Modeling CVD Reactors

Rajesh Venkataramani, Massachusetts Institute of Technology

**Practicum Year:**1996

**Practicum Supervisor:**Dr. Harry Moffat, , Massively Parallel Computing Research Laboratories, Sandia National Laboratories, New Mexico

The MPSalsa project has developed a parallel finite element code to simulate fluid flow, heat transfer, and chemical reactions. My work entailed examining how the MPSalsa code interfaces the gas phase finite element problem with surface problems through the boundary conditions.

Implementation of CUERVO on the IBMSP2

Melinda Sirman, University of Texas

**Practicum Year:**1995

**Practicum Supervisor:**Dr. David Gartling, , Engineering Sciences Center, Sandia National Laboratories, New Mexico

CUERVO is a finite element code for nonlinear scalar transport problems. Several finite element codes in the department have the same fundamental structure. The objective of the project was to parallelize CUERVO using MPI and find any problem areas that might prevent parallelization of more complicated codes.

Upwind Leap-Frog Scheme on Massively Parallel Message Passing Computers

Brian Gunney, University of Michigan

**Practicum Year:**1994

**Practicum Supervisor:**Dr. Scott Hutchinson, , Computational Sciences, Sandia National Laboratories, New Mexico

An electromagnetic scattering code using the upwind-leap-frog scheme was proted to two massively parallel computer platforms and evaluated.

Simulation of Residual Oil Hydroprocessing Units on Massively Parallel Supercomputers

James Comer, North Carolina State University

**Practicum Year:**1993

**Practicum Supervisor:**Dr. James Tomkins, , Massively Parallel Computing Research Laboratory, Sandia National Laboratories, New Mexico

This project was a Cooperative Research and Development Agreement (CRADA) between Sandia, Los Alamos, and Amoco Oil Company. Sandia's responsibility included the development of a parallel version of a multiphase flow code which had originally been written for a Cray Supercomputer. The parallel version was required to run on both massively parallel computers such as the N-cube and the Paragaon, as well as a collection of workstations running in parallel.

Modelling Toroidal Solder Drop

Stephen Cronen-Townsend, Cornell University

**Practicum Year:**1993

**Practicum Supervisor:**Dr. Elizabeth Holm, , Metallurgy and Joining Technology, Sandia National Laboratories, New Mexico

This project is aimed at gaining insight into attainable solder configurations by using computer modelling in conjunction with pre-existing experimental techniques. 'Parallel Re-implementation of Evolver' The ultimate goal of "Parallel Re-implementation of Evolver" is rewriting Evolver to take advantage of massively parallel computer architectures. "Geometry of Grain Disappearance in Thin Polycrystalline Films" uses Evolver in novel ways to investigate the critical size-to-thickness ratio for grains (crystallites) in polycrystaline films.

Optimization of Reliability Models Under Uncertainty

Laura Swiler, Carnegie Mellon University

**Practicum Year:**1993

**Practicum Supervisor:**Dr. James Campbell, , Energy and Environment Division, Sandia National Laboratories, New Mexico

This project focuses on the optimization of output measures from reliability models which have uncertainty in the inputs. The optimization problem is how to find the best system structure (configuration topology) and parameter values (i.e. component failure rates) to meet the specified goals of the system. (i.e. minimize cost, maximize system Mean Time Between Failures (MTBF), etc.) My approach to this type of problem is to discretize part of the space, turn the problem into a cominatorial one, and use new probabilistic based combinatorial optimization techniques such as simulated annealing or genetic algorithms as the solution method.