Publications

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This study investigates the mechanical and corrosion properties of as-built and annealed equiatomic CoCrFeMnNi alloy produced by laser-based directed energy deposition (DED) Additive Manufacturing (AM). The high cooling rates of DED produced a single-phase, cellular microstructure with cells on the order of 4 μm in diameter and inter-cellular regions that were enriched in Mn and Ni. Annealing created a chemically homogeneous recrystallized microstructure with a high density of annealing twins. The average yield strength of the as-built condition was 424 MPa and exceeded the annealed condition (232 MPa), however; the strain hardening rate was lower for the as-built material stemming from higher dislocation density associated with DED parts and the fine cell size. In general, the yield strength, ultimate tensile strength, and elongation-to-failure for the as-built material exceeded values from previous studies that explored other AM techniques to produce the CoCrFeMnNi alloy. Ductile fracture occurred for all specimens with dimple initiation associated with nanoscale oxide inclusions. The breakdown potential (onset of pitting corrosion) was similar for the as-built and annealed conditions at 0.40 VAg/AgCl when immersed in 0.6 M NaCl. Pit morphology/propagation for the as-built condition exhibited preferential corrosion of inter-cellular Ni/Mn regions leading to a tortuous pit bottom and cover, while the annealed conditions pits resembled lacy pits similar to 304 L steel. A passive oxide film depleted in Cr cations with substantial incorporation of Mn cations is proposed as the primary mechanism for local corrosion susceptibility of the CoCrFeMnNi alloy.

Microstructure reconstruction problems are usually limited to the representation with finitely many number of phases, e.g. binary and ternary. However, images of microstructure obtained through experimental, for example, using microscope, are often represented as a RGB or grayscale image. Because the phase-based representation is discrete, more rigid, and provides less flexibility in modeling the microstructure, as compared to RGB or grayscale image, there is a loss of information in the conversion. In this paper, a microstructure reconstruction method, which produces images at the fidelity of experimental microscopy, i.e. RGB or grayscale image, is proposed without introducing any physics-based microstructure descriptor. Furthermore, the image texture is preserved and the microstructure image is represented with continuous variables (as in RGB or grayscale images), instead of binary or categorical variables, which results in a high-fidelity image of microstructure reconstruction. The advantage of the proposed method is its quality of reconstruction, which can be applied to any other binary or multiphase 2D microstructure. The proposed method can be thought of as a subsampling approach to expand the microstructure dataset, while preserving its image texture. Moreover, the size of the reconstructed image is more flexible, compared to other machine learning microstructure reconstruction method, where the size must be fixed beforehand. In addition, the proposed method is capable of joining the microstructure images taken at different locations to reconstruct a larger microstructure image. A significant advantage of the proposed method is to remedy the data scarcity problem in materials science, where experimental data is scare and hard to obtain. The proposed method can also be applied to generate statistically equivalent microstructures, which has a strong implication in microstructure-related uncertainty quantification applications. The proposed microstructure reconstruction method is demonstrated with the UltraHigh Carbon Steel micrograph DataBase (UHCSDB).

The morphology of the stagnated plasma resulting from Magnetized Liner Inertial Fusion (MagLIF) is measured by imaging the self-emission x-rays coming from the multi-keV plasma, and the evolution of the imploding liner is measured by radiographs. Equivalent diagnostic response can be derived from integrated rad-MHD simulations from programs such as Hydra and Gorgon. There have been only limited quantitative ways to compare the image morphology, that is the texture, of simulations and experiments. We have developed a metric of image morphology based on the Mallat Scattering Transformation (MST), a transformation that has proved to be effective at distinguishing textures, sounds, and written characters. This metric has demonstrated excellent performance in classifying ensembles of synthetic stagnation images. We use this metric to quantitatively compare simulations to experimental images, cross experimental images, and to estimate the parameters of the images with uncertainty via a linear regression of the synthetic images to the parameter used to generate them. This coordinate space has proved very adept at doing a sophisticated relative back-ground subtraction in the MST space. This was needed to compare the experimental self emission images to the rad-MHD simulation images. We have also developed theory that connects the transformation to the causal dynamics of physical systems. This has been done from the classical kinetic perspective and from the field theory perspective, where the MST is the generalized Green's function, or S-matrix of the field theory in the scale basis. From both perspectives the first order MST is the current state of the system, and the second order MST are the transition rates from one state to another. An efficient, GPU accelerated, Python implementation of the MST was developed. Future applications are discussed.

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The cybersecurity research community has focused primarily on the analysis and automation of intrusion detection systems by examining network traffic behaviors. Expanding on this expertise, advanced cyber defense analysis is turning to host-based data to use in research and development to produce the next generation network defense tools. The ability to perform deep packet inspection of network traffic is increasingly harder with most boundary network traffic moving to HTTPS. Additionally, network data alone does not provide a full picture of end-to-end activity. These are some of the reasons that necessitate looking at other data sources such as host data. We outline our investigation into the processing, formatting, and storing of the data along with the preliminary results from our exploratory data analysis. In writing this report, it is our goal to aid in guiding future research by providing foundational understanding for an area of cybersecurity that is rich with a variety of complex, categorical, and sparse data, with a strong human influence component. Including suggestions for guiding potential directions for future research.

The Waste Isolation Pilot Plant (WIPP) is an operating geologic repository in southeastern New Mexico for transuranic (TRU) waste from nuclear defense activities. Past nuclear criticality concerns have generally been low at the WIPP due to the low initial concentration of fissile material and the natural tendency of fissile solute to disperse during fluid transport in porous media (Rechard et al. 2000). On the other hand, the list of acceptable WIPP waste types has expanded over the years to include Criticality Control Overpack (CCO) containers and Pipe Overpack (POP) containers. Containers bound for WIPP are bundled together in hexagon shaped 7-packs (six containers surround one container in the center). Two 7-packs are often combined into a TRUPACT-II package for a total of 14 containers. Most TRUPACT-II packages are restricted to a maximum fissile mass equivalent to plutonium (FMEP) between 0.1 and 0.38 kg, but a CCO TRUPACT-II package and a POP TRUPACT-II package are respectively permitted to have 5.32 kg and 2.80 kg FMEP (see Section 3 of US DOE (2013)). Consequently, CCO container criticality after emplacement at the WIPP was evaluated in Saylor and Scaglione (2018), and Oak Ridge National Laboratories is currently at work on POP container criticality analyses.

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In this paper, we study, analyze, and validate some important zero-dimensional physics-based models for vanadium redox batch cell (VRBC) systems and formulate an adequate physics-based model that can predict the battery performance accurately. In the model formulation process, a systems approach to multiple parameters estimation has been conducted using VRBC systems at low C-rates (~C/30). In this batch cell system, the effect of ions' crossover through the membrane is dominant, and therefore, the capacity loss phenomena can be explicitly observed. Paradoxically, this means that using the batch system might be a better approach for identifying a more suitable model describing the effect of ions transport. Next, we propose an efficient systems approach, which enables to help understand the battery performance quickly by estimating all parameters of the battery system. Finally, open source codes, executable files, and experimental data are provided to enable people's access to robust and accurate models and optimizers. In battery simulations, different models and optimizers describing the same systems produce different values of the estimated parameters. Providing an open access platform can accelerate the process to arrive at robust models and optimizers by continuous modification from the users' side.

The aim and scope of this project was the development of a capability to prepare high-quality, epitaxial beta gallium oxide films by oxide reactive molecular-beam epitaxy. The purpose was to demonstrate that beta gallium oxide could be grown by such a method using Sandia’s existing oxide molecular-beam epitaxy instrument. The key activity in this project was the installation of a gallium oxide capability on the Sandia instrument. This required the acquisition of several custom items for the instrument, including: a gallium effusion cell, appropriate cell power supplies and temperature controllers, a shutter to block beam flux, installation of an existing ozone generator with a directed gas nozzle and controlled leak valve, and re-routing the chilled water system to accommodate the cell. In addition, beta gallium oxide single crystals were acquired and their surfaces characterized by reflection high energy electron diffraction.

A 150 lb_f thrust class, modular, bi-propellant, rocket engine/gas-generator and supporting test infrastructure has been developed in a cooperative effort between Sandia National Laboratories and the New Mexico Institute of Mining and Technology’s (NMIMT’s) Energetic Materials Research and Testing Center (EMRTC). This modular test engine design consists of a head end fuel-oxidizer injector, a spark ignition gaseous H₂/O₂ torch igniter, combustion chamber and nozzle module. This robust design allows for rapid configuration changes as well as economical repair should hardware become damaged in testing. The engine interfaces with a permanently installed pressurizing system capable of delivering liquid nitrous oxide and a variety of liquid fuels for both rocket engine development and propellant performance evaluation. The regulated high pressure systems allow for delivery of liquefied gases above their saturation pressure as well as allowing for high pressure rocket engine/gas-generator operation. The facility test cell houses a 1 ton thrust capacity test stand leaving room for larger scale engine development.

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling (DOE 2011, Table 6). These priorities are directly addressed in the SFWST Geologic Disposal Safety Assessment (GDSA) work package, which is charged with developing a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media.

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The thermal performance of commercial spent nuclear fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Canistered dry storage cask systems rely on ventilation between the inner canister and the overpack to convect heat away from the canister to the surrounding environment for both horizontal and vertical configurations. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a canister in part by increasing the efficiency of internal conduction pathways and by increasing the internal convection through greater canister helium pressure. Carefully measured data sets generated from testing of full-sized casks or smaller cask analogs are widely recognized as vital for validating these models. While several testing programs have been previously conducted, these earlier validation studies did not integrate all the physics or components important in a modern, horizontal dry cask system. The purpose of the present investigation is to produce data sets that can be used to benchmark the codes and best practices presently used to determine cladding temperatures and induced cooling air flows in modern horizontal dry storage systems. The horizontal dry cask simulator (HDCS) has been designed to generate this benchmark data and add to the existing knowledge base. The objective of the HDCS investigation is to capture the dominant physics of a commercial dry storage system in a well-characterized test apparatus for any given set of operational parameters. The close coupling between the thermal response of the canister system and the resulting induced cooling air flow rate is of particular importance.

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