Channeled spectropolarimetry can measure the complete polarization state of light as a function of wavelength. Typically, a channeled spectropolarimeter uses high order retarders made of uniaxial crystal to amplitude modulate the measured spectrum with the spectrally-dependent Stokes polarization information. A primary limitation of conventional channeled spectropolarimeters is related to the thermal variability of the retarders. Thermal variation often forces frequent system recalibration, particularly for field deployed systems. However, implementing thermally stable retarders, made of biaxial crystal, results in an athermal channeled spectropolarimeter that relieves the need for frequent recalibration. This report presents experimental results for an anthermalized channeled spectropolarimeter prototype produced using potassium titanyl phosphate. The results of this prototype are compared to the current thermal stabilization state of the art. Finally, the application of the technique to the thermal infrared is studied, and the athermalization concept is applied to an infrared imaging spectropolarimeter design.
The study develops a novel stochastic frontier modeling approach to the gravity equation for rare earth element (REE) trade between China and its trading partners between 2001 and 2009. The novelty lies in differentiating betweenbehind the border' trade costs by China and theimplicit beyond the border costs' of China's trading partners. Results indicate that the significance level of the independent variables change dramatically over the time period. While geographical distance matters for trade flows in both periods, the effect of income on trade flows is significantly attenuated, possibly capturing the negative effects of financial crises in the developed world. Second, the total export losses due tobehind the border' trade costs almost tripled over the time period. Finally, looking atimplicit beyond the border' trade costs, results show China gaining in some markets, although it is likely that some countries are substituting away from Chinese REE exports.
Currently, much of protection planning is conducted separately for each infrastructure and hazard. Limited funding requires a balance of expenditures between terrorism and natural hazards based on potential impacts. This report documents the results of a Laboratory Directed Research & Development (LDRD) project that created a modeling framework for investment planning in interdependent infrastructures focused on multiple hazards, including terrorism. To develop this framework, three modeling elements were integrated: natural hazards, terrorism, and interdependent infrastructures. For natural hazards, a methodology was created for specifying events consistent with regional hazards. For terrorism, we modeled the terrorists actions based on assumptions regarding their knowledge, goals, and target identification strategy. For infrastructures, we focused on predicting post-event performance due to specific terrorist attacks and natural hazard events, tempered by appropriate infrastructure investments. We demonstrate the utility of this framework with various examples, including protection of electric power, roadway, and hospital networks.
This project focuses on the development and demonstration of anion exchange membrane (AEM) fuel cells for portable power applications. Novel polymeric anion exchange membranes and ionomers with high chemical stabilities were prepared characterized by researchers at Sandia National Laboratories. Durable, non-precious metal catalysts were prepared by Dr. Plamen Atanassovs research group at the University of New Mexico by utilizing an aerosol-based process to prepare templated nano-structures. Dr. Andy Herrings group at the Colorado School of Mines combined all of these materials to fabricate and test membrane electrode assemblies for single cell testing in a methanol-fueled alkaline system. The highest power density achieved in this study was 54 mW/cm2 which was 90% of the project target and the highest reported power density for a direct methanol alkaline fuel cell.
The technology of acoustic emission (AE) testing has been advanced and used at Sandia for the past 40 years. AE has been used on structures including pressure vessels, fire bottles, wind turbines, gas wells, nuclear weapons, and solar collectors. This monograph begins with background topics in acoustics and instrumentation and then focuses on current acoustic emission technology. It covers the overall design and system setups for a test, with a wind turbine blade as the object. Test analysis is discussed with an emphasis on source location. Three test examples are presented, two on experimental wind turbine blades and one on aircraft fire extinguisher bottles. Finally, the code for a FORTRAN source location program is given as an example of a working analysis program. Throughout the document, the stress is on actual testing of real structures, not on laboratory experiments.
The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. The limited nature of the measured data leads to a severely-underdetermined estimation problem. If the estimation is performed at fine spatial resolutions, it can also be computationally expensive. In order to enable such estimations, advances are needed in the spatial representation of ffCO2 emissions, scalable inversion algorithms and the identification of observables to measure. To that end, we investigate parsimonious spatial parameterizations of ffCO2 emissions which can be used in atmospheric inversions. We devise and test three random field models, based on wavelets, Gaussian kernels and covariance structures derived from easily-observed proxies of human activity. In doing so, we constructed a novel inversion algorithm, based on compressive sensing and sparse reconstruction, to perform the estimation. We also address scalable ensemble Kalman filters as an inversion mechanism and quantify the impact of Gaussian assumptions inherent in them. We find that the assumption does not impact the estimates of mean ffCO2 source strengths appreciably, but a comparison with Markov chain Monte Carlo estimates show significant differences in the variance of the source strengths. Finally, we study if the very different spatial natures of biogenic and ffCO2 emissions can be used to estimate them, in a disaggregated fashion, solely from CO2 concentration measurements, without extra information from products of incomplete combustion e.g., CO. We find that this is possible during the winter months, though the errors can be as large as 50%.
This report contains the one-year feasibility study for our three-year LDRD proposal that is aimed to develop an experimental technique to measure the 3D deformation fields inside a material body. In this feasibility study, we first apply Digital Volume Correlation (DVC) algorithm to pre-existing in-situ Xray Computed Tomography (XCT) image sets with pure rigid body translation. The calculated displacement field has very large random errors and low precision that are unacceptable. Then we enhance these tomography images by setting threshold of the intensity of each slice. DVC algorithm is able to obtain accurate deformation fields from these enhanced image sets and the deformation fields are consistent with the global mechanical loading that is applied to the specimen. Through this study, we prove that the internal markers inside the pre-existing tomography images of aluminum alloy can be enhanced and are suitable for DVC to calculate the deformation field throughout the material body.
Biological imaging and assay technologies rely on fluorescent organic dyes as reporters for a number of interesting targets and processes. However, limitations of organic dyes such as small Stokes shifts, spectral overlap of emission signals with native biological fluorescence background, and photobleaching have all inhibited the development of highly sensitive assays. To overcome the limitations of organic dyes for bioassays, we propose to develop lanthanide-based luminescent dyes and demonstrate them for molecular reporting applications. This relatively new family of dyes was selected for their attractive spectral and chemical properties. Luminescence is imparted by the lanthanide atom and allows for relatively simple chemical structures that can be tailored to the application. The photophysical properties offer unique features such as narrow and non-overlapping emission bands, long luminescent lifetimes, and long wavelength emission, which enable significant sensitivity improvements over organic dyes through spectral and temporal gating of the luminescent signal.Growth in this field has been hindered due to the necessary advanced synthetic chemistry techniques and access to experts in biological assay development. Our strategy for the development of a new lanthanide-based fluorescent reporter system is based on chelation of the lanthanide metal center using absorbing chromophores. Our first strategy involves "Click" chemistry to develop 3-fold symmetric chelators and the other involves use of a new class of tetrapyrrole ligands called corroles. This two-pronged approach is geared towards the optimization of chromophores to enhance light output.
A unique aerosol flow chamber coupled with a bistatic LIDAR system was implemented to measure the optical scattering cross sections and depolarization ratio of common atmospheric particulates. Each of seven particle types (ammonium sulfate, ammonium nitrate, sodium chloride, potassium chloride, black carbon and Arizona road dust) was aged by three anthropogenically relevant mechanisms: 1. Sulfuric acid deposition, 2. Toluene ozonolysis reactions, and 3. m-Xylene ozonolysis reactions. The results of pure particle scattering properties were compared with their aged equivalents. Results show that as most particles age under industrial plume conditions, their scattering cross sections are similar to pure black carbon, which has significant impacts to our understanding of aerosol impacts on climate. In addition, evidence emerges that suggest chloride-containing aerosols are chemically altered during the organic aging process. Here we present the direct measured scattering cross section and depolarization ratios for pure and aged atmospheric particulates.
This report summarizes findings and results of the Quantifiably Secure Power Grid Operation, Management, and Evolution LDRD. The focus of the LDRD was to develop decisionsupport technologies to enable rational and quantifiable risk management for two key grid operational timescales: scheduling (day-ahead) and planning (month-to-year-ahead). Risk or resiliency metrics are foundational in this effort. The 2003 Northeast Blackout investigative report stressed the criticality of enforceable metrics for system resiliency the grids ability to satisfy demands subject to perturbation. However, we neither have well-defined risk metrics for addressing the pervasive uncertainties in a renewable energy era, nor decision-support tools for their enforcement, which severely impacts efforts to rationally improve grid security. For day-ahead unit commitment, decision-support tools must account for topological security constraints, loss-of-load (economic) costs, and supply and demand variability especially given high renewables penetration. For long-term planning, transmission and generation expansion must ensure realized demand is satisfied for various projected technological, climate, and growth scenarios. The decision-support tools investigated in this project paid particular attention to tailoriented risk metrics for explicitly addressing high-consequence events. Historically, decisionsupport tools for the grid consider expected cost minimization, largely ignoring risk and instead penalizing loss-of-load through artificial parameters. The technical focus of this work was the development of scalable solvers for enforcing risk metrics. Advanced stochastic programming solvers were developed to address generation and transmission expansion and unit commitment, minimizing cost subject to pre-specified risk thresholds. Particular attention was paid to renewables where security critically depends on production and demand prediction accuracy. To address this concern, powerful filtering techniques for spatio-temporal measurement assimilation were used to develop short-term predictive stochastic models. To achieve uncertaintytolerant solutions, very large numbers of scenarios must be simultaneously considered. One focus of this work was investigating ways of reasonably reducing this number.
The Quantitative Risk Assessment (QRA) Toolkit Introduction Workshop was held at Energetics on June 11-12. The workshop was co-hosted by Sandia National Laboratories (Sandia) and HySafe, the International Association for Hydrogen Safety. The objective of the workshop was twofold: (1) Present a hydrogen-specific methodology and toolkit (currently under development) for conducting QRA to support the development of codes and standards and safety assessments of hydrogen-fueled vehicles and fueling stations, and (2) Obtain feedback on the needs of early-stage users (hydrogen as well as potential leveraging for Compressed Natural Gas [CNG], and Liquefied Natural Gas [LNG]) and set priorities for %E2%80%9CVersion 1%E2%80%9D of the toolkit in the context of the commercial evolution of hydrogen fuel cell electric vehicles (FCEV). The workshop consisted of an introduction and three technical sessions: Risk Informed Development and Approach; CNG/LNG Applications; and Introduction of a Hydrogen Specific QRA Toolkit.
Enzymes can be used to catalyze a myriad of chemical reactions and are a cornerstone in the biotechnology industry. Enzymes have a wide range of uses, ranging from medicine with the production of pharmaceuticals to energy were they are applied to biofuel production. However, it is difficult to produce large quantities of enzymes, especially if they are non-native to the production host. Fortunately, filamentous fungi, such as Aspergillus niger, are broadly used in industry and show great potential for use a heterologous enzyme production hosts. Here, we present work outlining an effort to engineer A. niger to produce thermophilic bacterial cellulases relevant to lignocellulosic biofuel production.
Chemical functionalization is required to adapt graphenes properties to many applications. However, most covalent functionalization schemes are spontaneous or defect driven and are not suitable for applications requiring directed assembly of molecules on graphene substrates. In this work, we demonstrated electrochemically driven covalent bonding of phenyl iodoniums onto epitaxial graphene. The amount of chemisorption was demonstrated by varying the duration of the electrochemical driving potential. Chemical, electronic, and defect states of phenyl-modified graphene were studied by photoemission spectroscopy, spatially resolved Raman spectroscopy, and water contact angle measurement. Covalent attachment rehybridized some of the delocalized graphene sp2 orbitals to localized sp3 states. Control over the relative spontaneity (reaction rate) of covalent graphene functionalization is an important first step to the practical realization of directed molecular assembly on graphene. More than 10 publications, conference presentations, and program highlights were produced (some invited), and follow-on funding was obtained to continue this work.
Time-encoded imaging is an approach to directional radiation detection that is being developed at SNL with a focus on fast neutron directional detection. In this technique, a time modulation of a detected neutron signal is inducedtypically, a moving mask that attenuates neutrons with a time structure that depends on the source position. An important challenge in time-encoded imaging is to develop high-resolution two-dimensional imaging capabilities; building a mechanically moving high-resolution mask presents challenges both theoretical and technical. We have investigated an alternative to mechanical masks that replaces the solid mask with a liquid such as mineral oil. Instead of fixed blocks of solid material that move in pre-defined patterns, the oil is contained in tubing structures, and carefully introduced air gapsbubblespropagate through the tubing, generating moving patterns of oil mask elements and air apertures. Compared to current moving-mask techniques, the bubble mask is simple, since mechanical motion is replaced by gravity-driven bubble propagation; it is flexible, since arbitrary bubble patterns can be generated by a software-controlled valve actuator; and it is potentially high performance, since the tubing and bubble size can be tuned for high-resolution imaging requirements. We have built and tested various single-tube mask elements, and will present results on bubble introduction and propagation as a function of tubing size and cross-sectional shape; real-time bubble position tracking; neutron source imaging tests; and reconstruction techniques demonstrated on simple test data as well as a simulated full detector system.
Over the last three years the Neurons to Algorithms (N2A) LDRD project teams has built infrastructure to discover computational structures in the brain. This consists of a modeling language, a tool that enables model development and simulation in that language, and initial connections with the Neuroinformatics community, a group working toward similar goals. The approach of N2A is to express large complex systems like the brain as populations of a discrete part types that have specific structural relationships with each other, along with internal and structural dynamics. Such an evolving mathematical system may be able to capture the essence of neural processing, and ultimately of thought itself. This final report is a cover for the actual products of the project: the N2A Language Specification, the N2A Application, and a journal paper summarizing our methods.
This is the final report on the LDRD, though the interested reader is referred to the ANS Transactions paper which more thoroughly documents the technical work of this project.
Density-functional theory calculations, ab-initio molecular dynamics, and the Kubo-Greenwood formula are applied to predict electrical conductivity in Ta2Ox (0 x 5) as a function of composition, phase, and temperature, where additional focus is given to various oxidation states of the O monovacancy (VOn; n=0,1+,2+). Our calculations of DC conductivity at 300K agree well with experimental measurements taken on Ta2Ox thin films and bulk Ta2O5 powder-sintered pellets, although simulation accuracy can be improved for the most insulating, stoichiometric compositions. Our conductivity calculations and further interrogation of the O-deficient Ta2O5 electronic structure provide further theoretical basis to substantiate VO0 as a donor dopant in Ta2O5 and other metal oxides. Furthermore, this dopant-like behavior appears specific to neutral VO cases in both Ta2O5 and TiO2 and was not observed in other oxidation states. This suggests that reduction and oxidation reactions may effectively act as donor activation and deactivation mechanisms, respectively, for VO0 in transition metal oxides.
Molybdenum electrical interconnects for thermoelectric modules were produced by air plasma spraying a 30%CE%BCm size molybdenum powder through a laser-cut Kapton tape mask. Initial feasibility demonstrations showed that the molybdenum coating exhibited excellent feature and spacing retention (~170%CE%BCm), adhered to bismuth-telluride, and exhibited electrical conductivity appropriate for use as a thermoelectric module interconnect. A design of experiments approach was used to optimize air plasma spray process conditions to produce a molybdenum coating with low electrical resistivity. Finally, a molybdenum coating was successfully produced on a fullscale thermoelectric module. After the addition of a final titanium/gold layer deposited on top of the molybdenum coating, the full scale module exhibited an electrical resistivity of 128%CE%A9, approaching the theoretical resistivity value for the 6mm module leg of 112%CE%A9. Importantly, air plasma sprayed molybdenum did not show significant chemical reaction with bismuth-telluride substrate at the coating/substrate interface. The molybdenum coating microstructure consisted of lamellar splats containing columnar grains. Air plasma sprayed molybdenum embedded deeply (several microns) into the bismuth-telluride substrate, leading to good adhesion between the coating and the substrate. Clusters of round pores (and cracks radiating from the pores) were found immediately beneath the molybdenum coating. These pores are believed to result from tellurium vaporization during the spray process where the molten molybdenum droplets (2623%C2%B0C) transferred their heat of solidification to the substrate at the moment of impact. Substrate cooling during the molybdenum deposition process was recommended to mitigate tellurium vaporization in future studies.
This report describes X-cut lithium niobates (LiNbO3) utilization for voltage sensing by monitoring the acoustic wave propagation changes through LiNbO3 resulting from applied voltage. Direct current (DC), alternating current (AC) and pulsed voltage signals were applied to the crystal. Voltage induced shift in acoustic wave propagation time scaled quadratically for DC and AC voltages and linearly for pulsed voltages. The measured values ranged from 10 - 273 ps and 189 ps 2 ns for DC and non-DC voltages, respectively. Data suggests LiNbO3 has a frequency sensitive response to voltage. If voltage source error is eliminated through physical modeling from the uncertainty budget, the sensors U95 estimated combined uncertainty could decrease to ~0.025% for DC, AC, and pulsed voltage measurements.
The objective of this work was to describe several of the ductile failure criteria com- monly used to solve practical problems. The following failure models were considered: equivalent plastic strain, equivalent plastic strain in tension, maximum shear, Mohr- Coulomb, Wellman's tearing parameter, Johnson-Cook and BCJ MEM. The document presents the main characteristics of each failure model as well as sample failure predic- tions for simple proportional loading stress histories in three dimensions and in plane stress. Plasticity calculations prior to failure were conducted with a simple, linear hardening, J2 plasticity model. The resulting failure envelopes were plotted in prin- cipal stress space and plastic strain space, where the dependence on stress triaxiality and Lode angle are clearly visible. This information may help analysts select a ductile fracture model for a practical problem and help interpret analysis results.
The recently developed Magnetically Applied Pressure-Shear (MAPS) experimental technique to measure material shear strength at high pressures on magneto-hydrodynamic (MHD) drive pulsed power platforms was fielded on August 16, 2013 on shot Z2544 utilizing hardware set A0283A. Several technical and engineering challenges were overcome in the process leading to the attempt to measure the dynamic strength of NNSA Ta at 50 GPa. The MAPS technique relies on the ability to apply an external magnetic field properly aligned and time correlated with the MHD pulse. The load design had to be modified to accommodate the external field coils and additional support was required to manage stresses from the pulsed magnets. Further, this represents the first time transverse velocity interferometry has been applied to diagnose a shot at Z. All subsystems performed well with only minor issues related to the new feed design which can be easily addressed by modifying the current pulse shape. Despite the success of each new component, the experiment failed to measure strength in the samples due to spallation failure, most likely in the diamond anvils. To address this issue, hydrocode simulations are being used to evaluate a modified design using LiF windows to minimize tension in the diamond and prevent spall. Another option to eliminate the diamond material from the experiment is also being investigated.
The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNLs mission, the PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.
This report describes the theoretical background on modeling electron transport in the presence of electric and magnetic fields by incorporating the effects of the Lorentz force on electron motion into the Boltzmann transport equation. Electromagnetic fields alter the electron energy and trajectory continuously, and these effects can be characterized mathematically by differential operators in terms of electron energy and direction. Numerical solution techniques, based on the discrete-ordinates and finite-element methods, are developed and implemented in an existing radiation transport code, SCEPTRE.
The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S&T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.
Atomistic-scale behavior drives performance in many micro- and nano-fluidic systems, such as mircrofludic mixers and electrical energy storage devices. Bringing this information into the traditionally continuum models used for engineering analysis has proved challenging. This work describes one such approach to address this issue by developing atomistic-to-continuum multi scale and multi physics methods to enable molecular dynamics (MD) representations of atoms to incorporated into continuum simulations. Coupling is achieved by imposing constraints based on fluxes of conserved quantities between the two regions described by one of these models. The impact of electric fields and surface charges are also critical, hence, methodologies to extend finite-element (FE) MD electric field solvers have been derived to account for these effects. Finally, the continuum description can have inconsistencies with the coarse-grained MD dynamics, so FE equations based on MD statistics were derived to facilitate the multi scale coupling. Examples are shown relevant to nanofluidic systems, such as pore flow, Couette flow, and electric double layer.
This report documents work conducted in FY13 to conduct a feasibility study on thermal spray coated cathodes to be used in the RITS-6 accelerator in an attempt to improve surface uniformity and repeatability. Currently, the cathodes are coated with colloidal silver by means of painting by hand. It is believed that improving the cathode coating process could simplify experimental setup and improve flash x-ray radiographic performance. This report documents the experimental setup and summarizes the results of our feasibility study. Lastly, it describes the path forward and potential challenges that must be overcome in order to improve the process for creating uniform and repeatable silver coatings for cathodes.
We present the results of a three-year LDRD project focused on understanding microstructural evolution and related property changes in Zr-based nuclear cladding materials towards the development of high fidelity predictive simulations for long term dry storage. Experiments and modeling efforts have focused on the effects of hydride formation and accumulation of irradiation defects. Key results include: determination of the influence of composition and defect structures on hydride formation; measurement of the electrochemical property differences between hydride and parent material for understanding and predicting corrosion resistance; in situ environmental transmission electron microscope observation of hydride formation; development of a predictive simulation for mechanical property changes as a function of irradiation dose; novel test method development for microtensile testing of ionirradiated material to simulate the effect of neutron irradiation on mechanical properties; and successful demonstration of an Idaho National Labs-based sample preparation and shipping method for subsequent Sandia-based analysis of post-reactor cladding.
This document provides a detailed discussion and a guide for the use of the RadCat 6.0 Graphical User Interface input file generator for the RADTRAN code, Version 6. RadCat 6.0 integrates the newest analysis capabilities of RADTRAN 6.0, including an economic model, updated loss-of-lead shielding model, a new ingestion dose model, and unit conversion. As of this writing, the RADTRAN version in use is RADTRAN 6.02.
At sufficiently high energies, the wavelengths of electrons and photons are short enough to only interact with one atom at time, leading to the popular %E2%80%9Cindependent-atom approximation%E2%80%9D. We attempted to incorporate atomic structure in the generation of cross sections (which embody the modeled physics) to improve transport at lower energies. We document our successes and failures. This was a three-year LDRD project. The core team consisted of a radiation-transport expert, a solid-state physicist, and two DFT experts.
This report describes an Early Career Laboratory Directed Research and Development (LDRD) project to develop an interface tracking model for droplet electrocoalescence. Many fluid-based technologies rely on electrical fields to control the motion of droplets, e.g. microfluidic devices for high-speed droplet sorting, solution separation for chemical detectors, and purification of biodiesel fuel. Precise control over droplets is crucial to these applications. However, electric fields can induce complex and unpredictable fluid dynamics. Recent experiments (Ristenpart et al. 2009) have demonstrated that oppositely charged droplets bounce rather than coalesce in the presence of strong electric fields. A transient aqueous bridge forms between approaching drops prior to pinch-off. This observation applies to many types of fluids, but neither theory nor experiments have been able to offer a satisfactory explanation. Analytic hydrodynamic approximations for interfaces become invalid near coalescence, and therefore detailed numerical simulations are necessary. This is a computationally challenging problem that involves tracking a moving interface and solving complex multi-physics and multi-scale dynamics, which are beyond the capabilities of most state-of-the-art simulations. An interface-tracking model for electro-coalescence can provide a new perspective to a variety of applications in which interfacial physics are coupled with electrodynamics, including electro-osmosis, fabrication of microelectronics, fuel atomization, oil dehydration, nuclear waste reprocessing and solution separation for chemical detectors. We present a conformal decomposition finite element (CDFEM) interface-tracking method for the electrohydrodynamics of two-phase flow to demonstrate electro-coalescence. CDFEM is a sharp interface method that decomposes elements along fluid-fluid boundaries and uses a level set function to represent the interface.
Chronic infection with Hepatitis C virus (HCV) results in cirrhosis, liver cancer and death. As the nations largest provider of care for HCV, US Veterans Health Administration (VHA) invests extensive resources in the diagnosis and treatment of the disease. This report documents modeling and analysis of HCV treatment dynamics performed for the VHA aimed at improving service delivery efficiency. System dynamics modeling of disease treatment demonstrated the benefits of early detection and the role of comorbidities in disease progress and patient mortality. Preliminary modeling showed that adherence to rigorous treatment protocols is a primary determinant of treatment success. In depth meta-analysis revealed correlations of adherence and various psycho-social factors. This initial meta-analysis indicates areas where substantial improvement in patient outcomes can potentially result from VA programs which incorporate these factors into their design.