Publications

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Dynamic mode decomposition (DMD) is a method that has gained notoriety in the field of turbulent fluid flows as a method for decomposing the flow field into modes that could be further deconstructed to understand their influence on the overall dynamics of the system. Forays into solids and non-linear systems were considered, but not applied. In this work, DMD was applied for the first time to the heat-diffusion and reactive heat diffusion equations on a random particle pack of uniform solid spheres. A verification of a linear heat-diffusion test problem was successful, showing equality between the normal modes and Koopman modes obtained from DMD. Further application to a non-linear reactive system revealed stability limits of the underlying modes which are dependent on microstructure and chemical kinetics. This work will enable the development of reactive material models based on further analysis using DMD to quantify the statistical dependencies of transient response on microstructural characteristics.

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Sandia National Laboratories’ California site is celebrating its 60th anniversary (1956 to 2016), and high performance computing has been a key enabler for its scientists and engineers throughout much of its history. Since its founding, Sandia California has helped pioneer the use of HPC platforms including hosting Sandia’s first Cray-1 supercomputer in the 1970s and supporting development of scalable cluster computing platforms to create a new paradigm for cost-effective supercomputing in the 1990s. Recent decades of investment in creation of scalable application frameworks for scientific computing have also enabled new generations of modeling and simulation codes. These resources have facilitated computational analysis of complex phenomena in diverse applications spanning national defense, energy, and homeland security. Today, Sandia California researchers work with partners in academia, industry, and national labs to evolve the state-of-the-art in HPC, modeling, and data analysis (including foundational capabilities for exascale computing platforms) and apply them in transformational ways. Research efforts include mitigating the effects of silent hardware failures that can jeopardize the results of large-scale computations, developing exascale-capable asynchronous task-parallel programming models and runtime systems, formulating new techniques to better explore and analyze extreme-scale data sets, and increasing our understanding of materials and chemical sciences which has applications spanning nuclear weapons stockpile stewardship to more efficient automobile engines. The following section highlights some of these research and applications projects and further illustrates the breadth of our HPC capabilities.

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A viscoelastic constitutive analysis is used to investigate the counter-intuitive observation of “mobility decrease with increased deformation through yield” in a glass forming polymer under compressive and tensile loading conditions. Current Sandia National Laboratory polymer models are built on the assumption that deformation enhances the mobility of the material. If this assumption is not true at small strain rates (e.g., thermal fluctuations in stockpile storage) then models will not be able to accurately predict stress evolution and potential failure of components during stockpile storage. The behavior of an epoxy thermoset is explored using an extensively validated material “clock” model, the Simplified Potential Energy Clock (SPEC) model. This methodology allows for a comparison between the linear viscoelastic (LVE) limit and the true non-linear viscoelastic (NLVE) representation and enables exploration of a wide range of conditions that are not practical to explore experimentally. The model predicts the behavior described as “mobility decrease with increased deformation” in the LVE limit and at low strain rates for NLVE. Only when loading rates are sufficient to decrease the material shift factor by multiple orders of magnitude is the anticipated deformation induced mobility or “mobility increase with increased deformation” observed. While the model has not been “trained” for these behaviors, it also predicts that the normalized stress relaxation response is indistinguishable amongst strain levels in the “post-yield” region as has been experimentally reported. At long time, which has not been examined experimentally, the model predicts the normalized relaxation curves “crossover” and return to the LVE ordering. These findings further demonstrate the ability of rheologically simple models to represent experimentally measured material response and present predictions at long time scales that could be tested experimentally.

This project was funded through the Campus Executive Fellowship at University of California (UC) Berkeley, and had two principal aims. First, it sought to explore predictive tools for estimating fuel properties based on molecular structure, with the goal of identifying promising candidates for new fuels to be synthesized. Second, it sought to investigate the possibility of increasing engine efficiency by substituting air for a working fluid with higher efficiency potential employed in a closed loop, namely a mixture of argon and oxygen. In pursuing the predictive tool for novel fuels, a new model was built that proved to be highly predictive of autoignition characteristics for a wide variety of hydrocarbons, esters, ethers and alcohols, and reasonably predictive for furan and tetrahydrofuran compounds, the target class of novel fuels. Obtaining more “training data” for the model improved its predictive capabilities, and further reductions in the uncertainty of the predictions would be possible with more training data. In investigating the concept of a closed-loop engine cycle using an argon-oxygen working fluid, substantial progress was made. Initial engineering models were built showing the feasibility of the concept; numerous collaborations were formed with industry and academic partners; external funding was secured from the California Energy Commission (CEC) to build a dedicated engine platform for research; and this engine platform was designed and constructed. Experimental work and associated modeling studies will take place in late 2016 and early 2017.

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Engineering decisions are often formulated as optimization problems such as the optimal design or control of physical systems. In these applications, the resulting optimization problems are constrained by large-scale simulations involving systems of partial differential equations (PDEs), ordinary differential equations (ODEs), and differential algebraic equations (DAEs). In addition, critical components of these systems are fraught with uncertainty, including unverifiable modeling assumptions, unknown boundary and initial conditions, and uncertain coefficients. Typically, these components are estimated using noisy and incomplete data from a variety of sources (e.g., physical experiments). The lack of knowledge of the true underlying probabilistic characterization of model inputs motivates the need for optimal solutions that are robust to this uncertainty. In this report, we introduce a framework for handling "distributional" uncertainties in the context of simulation-based optimization. This includes a novel measure discretization technique that will lead to an adaptive optimization algorithm tailored to exploit the structures inherent to simulation- based optimization.

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The Data Inferencing on Semantic Graphs project (DISeG) was a two-year investigation of inferencing techniques (focusing on belief propagation) to social graphs with a focus on semantic graphs (also called multi-layer graphs). While working this problem, we developed a new directed version of inferencing we call Directed Propagation (Chapters 2 and 4), identified new semantic graph sampling problems (Chapter 3).

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This report summarizes the work performed as part of a Laboratory Directed Research and Development project focused on evaluating and mitigating risk associated with biological dual use research of concern. The academic and scientific community has identified the funding stage as the appropriate place to intervene and mitigate risk, so the framework developed here uses a portfolio-level approach and balances biosafety and biosecurity risks, anticipated project benefits, and available mitigations to identify the best available investment strategies subject to cost constraints. The modeling toolkit was designed for decision analysis for dual use research of concern, but is flexible enough to support a wide variety of portfolio-level funding decisions where risk/benefit tradeoffs are involved. Two mathematical optimization models with two solution methods are included to accommodate stakeholders with varying levels of certainty about priorities between metrics. An example case study is presented.

The ability to track nuclear material is a challenge for resiliency of complex systems, e.g., harsh environments. RF tags, frequently used in national security applications, cannot be used for technological, operational, or safety reasons. Magnetic Smart Tags (MaST) is a novel tag technology based on magnetoelastic sensing that circumvents these issues. This technology is enabled by a new, cost-effective, batch manufacturing electrochemical deposition (ECD) process. This new advancement in fabrication enables multi-frequency tags capable of providing millions of possible codes for tag identification unlike existing theft deterrent tags that can convey only a single bit of information. Magnetostrictive 70% Co: 30% Fe was developed as the base alloy comprising the magnetoelastic resonator transduction element. Saturation magnetostriction, λ_S, has been externally measured by the Naval Research Laboratory to be as high as 78 ppm. Description of a novel MEMS variable capacitive test structure is described for future measurements of this parameter.

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Parametric sensitivities of dynamic system responses are very useful in a variety of applications, including circuit optimization and uncertainty quantification. Sensitivity calculation methods fall into two related categories: direct and adjoint methods. Effective implementation of such methods in a production circuit simulator poses a number of technical challenges, including instrumentation of device models. This report documents several years of work developing and implementing direct and adjoint sensitivity methods in the Xyce circuit simulator. Much of this work sponsored by the Laboratory Directed Research and Development (LDRD) Program at Sandia National Laboratories, under project LDRD 14-0788.

This report summarizes the methods and algorithms that were developed on the Sandia National Laboratory LDRD project entitled "Advanced Uncertainty Quantification Methods for Circuit Simulation", which was project # 173331 and proposal # 2016-0845. As much of our work has been published in other reports and publications, this report gives an brief summary. Those who are interested in the technical details are encouraged to read the full published results and also contact the report authors for the status of follow-on projects.

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The Strategic Petroleum Reserve (SPR) contains the largest supply is the largest stockpile of government-owned emergency crude oil in the world. The oil is stored in multiple salt caverns spread over four sites in Louisiana and Texas. Cavern infrastructure near the bottom of the cavern can be damaged from vertical floor movement. This report presents a comprehensive history of floor movements in each cavern. Most of the cavern floor rise rates ranged from 0.5-3.5 ft/yr, however, there were several caverns with much higher rise rates. BH103, BM106, and BH105 had the three highest rise rates. Information from this report will be used to better predict future vertical floor movements and optimally place cavern infrastructure. The reasons for floor rise are not entirely understood and should be investigated.

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The Regional Test Centers are a group of several sites around the US for testing photovoltaic systems and components related to photovoltaic systems. The RTCs are managed by Sandia National Laboratories. The data collected by the RTCs must be transmitted to Sandia for storage, analysis, and reporting. This document describes the methods that transfer the data between remote sites and Sandia as well as data movement within Sandia’s network. The methods described are in force as of September, 2016.

This report summarizes FY16 progress towards enabling uncertainty quantification for compressible cavity simulations using model order reduction (MOR). The targeted application is the quantification of the captive-carry environment for the design and qualification of nuclear weapons systems. To accurately simulate this scenario, Large Eddy Simulations (LES) require very fine meshes and long run times, which lead to week-long runs even on parallel state-of-the-art super- computers. MOR can reduce substantially the CPU-time requirement for these simulations. We describe two approaches for model order reduction for nonlinear systems, which can yield significant speed-ups when combined with hyper-reduction: the Proper Orthogonal Decomposition (POD)/Galerkin approach and the POD/Least-Squares Petrov Galerkin (LSPG) approach. The implementation of these methods within the in-house compressible flow solver SPARC is discussed. Next, a method for stabilizing and enhancing low-dimensional reduced bases that was developed as a part of this project is detailed. This approach is based on a premise termed "minimal subspace rotation", and has the advantage of yielding ROMs that are more stable and accurate for long-time compressible cavity simulations. Numerical results for some laminar cavity problems aimed at gauging the viability of the proposed model reduction methodologies are presented and discussed.

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Optical diagnostics play a central role in dynamic compression research. Currently, streak cameras are employed to record temporal and spectroscopic information in single-event experiments, yet are limited in several ways; the tradeoff between time resolution and total record duration is one such limitation. This project solves the limitations that streak cameras impose on dynamic compression experiments while reducing both cost and risk (equipment and labor) by utilizing standard high-speed digitizers and commercial telecommunications equipment. The missing link is the capability to convert the set of experimental (visible/x-ray) wavelengths to the infrared wavelengths used in telecommunications. In this report, we describe the problem we are solving, our approach, our results, and describe the system that was delivered to the customer. The system consists of an 8-channel visible-to-infrared converter with > 2 GHz 3-dB bandwidth.

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The intention of this document is to provide a path-forward for research and development (R&D) for two host rock media-specific (argillite and crystalline) disposal research work packages within the Used Fuel Disposition Campaign (UFDC). The two work packages, Argillite Disposal R&D and Crystalline Disposal R&D, support the achievement of the overarching mission and objectives of the Department of Energy Office of Nuclear Energy Fuel Cycle Technologies Program. These two work packages cover many of the fundamental technical issues that will have multiple implications to other disposal research work packages by bridging knowledge gaps to support the development of the safety case. The path-forward begins with the assumption of target dates that are set out in the January 2013 DOE Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste (http://energy.gov/downloads/strategy-management-and-disposal-used-nuclear-fuel-and-high-levelradioactive- waste). The path-forward will be maintained as a living document and will be updated as needed in response to available funding and the progress of multiple R&D tasks in the Used Fuel Disposition Campaign and the Fuel Cycle Technologies Program. This path forward is developed based on the report of “Used Fuel Disposition Campaign Disposal Research and Development Roadmap (FCR&D-USED- 2011-000065 REV0)” (DOE, 2011). This document delineates the goals and objectives of the UFDC R&D program, needs for generic disposal concept design, and summarizes the prioritization of R&D issues.

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The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

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An electromagnetic finite volume forward solver is implemented to create a suite of forward models that provide the expected response for an air-filled buried structure constructed of concrete and rebar. Model parameters considered are the conductivities and thicknesses of a two-layer subsurface and the nature of VLF plane wave source. By building this suite of models, the results can be packaged into a data set that is both easily callable and requires minimal storage. More importantly, the user is relieved of the time required to manually execute a large number of models. Instead the results are already provided along with an interpolation tool for immediately data access. This document is written in compliance the LDRD reporting requirements for a close-out report on Project 180848.

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Novel designs to increase light trapping and thermal efficiency of concentrating solar receivers at multiple length scales have been conceived, designed, and tested. The fractal-like geometries and features are introduced at both macro (meters) and meso (millimeters to centimeters) scales. Advantages include increased solar absorptance, reduced thermal emittance, and increased thermal efficiency. Radial and linear structures at the meso (tube shape and geometry) and macro (total receiver geometry and configuration) scales redirect reflected solar radiation toward the interior of the receiver for increased absorptance. Hotter regions within the interior of the receiver can reduce thermal emittance due to reduced local view factors to the environment, and higher concentration ratios can be employed with similar surface irradiances to reduce the effective optical aperture, footprint, and thermal losses. Coupled optical/fluid/thermal models have been developed to evaluate the performance of these designs relative to conventional designs. Modeling results showed that fractal-like structures and geometries can increase the effective solar absorptance by 5 – 20% and the thermal efficiency by several percentage points at both the meso and macro scales, depending on factors such as intrinsic absorptance. Meso-scale prototypes were fabricated using additive manufacturing techniques, and a macro-scale bladed receiver design was fabricated using Inconel 625 tubes. On-sun tests were performed using the solar furnace and solar tower at the National Solar Thermal Test facility. The test results demonstrated enhanced solar absorptance and thermal efficiency of the fractal-like designs.

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Additive Manufacturing (AM) provides a new avenue to design innovative materials and components that cannot be created using traditional machining operations. With current AM capabilities, complex designs (such as those required in weapon systems) can be readily manufactured with laser powder forming (or Laser-Engineered Net Shaping (LENSTM)) [1] that would be otherwise cost prohibitive or impossible to produce. However, before an AM product can be qualified for weapon applications, the characteristics of the metals produced by additive manufacturing processes need to be well understood. This work focuses on the development of computational simulation tools to model the metal additive manufacturing process. This work extends and integrates existing Sandia National Laboratories tools to accomplish the following: (i) be able to better predict residual stresses in AM product, (ii) extend high-fidelity material models to capture material evolution during the formation process, leading to prediction of end-state material properties, and (iii) provide a basis for engineering tools to propose improvements to additive manufacturing process variables, including those that minimize process variation. While this work in its current state is directly applicable to additive manufacturing processes, the tools developed may also help enable modeling welding processes such as gas tungsten arc (GTA), electron beam, and laser welding.

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Operation of concentrated solar power receivers at higher temperatures (>700°C) would enable supercritical carbon dioxide (sCO₂) power cycles for improved power cycle efficiencies (>50%) and cost-effective solar thermal power. Unfortunately, radiative losses at higher temperatures in conventional receivers can negatively impact the system efficiency gains. One approach to improve receiver thermal efficiency is to utilize selective coatings that enhance absorption across the visible solar spectrum while minimizing emission in the infrared to reduce radiative losses. Existing coatings, however, tend to degrade rapidly at elevated temperatures. In this report, we report on the initial designs and fabrication of spectrally selective metamaterial-based absorbers for high-temperature, high-thermal flux environments important for solarized sCO₂ power cycles. Metamaterials are structured media whose optical properties are determined by sub-wavelength structural features instead of bulk material properties, providing unique solutions by decoupling the optical absorption spectrum from thermal stability requirements. The key enabling innovative concept proposed is the use of structured surfaces with spectral responses that can be tailored to optimize the absorption and retention of solar energy for a given temperature range. In this initial study through the Academic Alliance partnership with University of Texas at Austin, we use Tungsten for its stability in expected harsh environments, compatibility with microfabrication techniques, and required optical performance. Our goal is to tailor the optical properties for high (near unity) absorptivity across the majority of the solar spectrum and over a broad range of incidence angles, and at the same time achieve negligible absorptivity in the near infrared to optimize the energy absorbed and retained. To this goal, we apply the recently developed concept of plasmonic Brewster angle to suitably designed nanostructured Tungsten surfaces. We predict that this will improve the receiver thermal efficiencies by at least 10% over current solar receivers.

In July 2012, protestors cut through security fences and gained access to the Y-12 National Security Complex. This was believed to be a highly reliable, multi-layered security system. This report documents the results of a Laboratory Directed Research and Development (LDRD) project that created a consistent, robust mathematical framework using complex systems analysis algorithms and techniques to better understand the emergent behavior, vulnerabilities and resiliency of multi-layered security systems subject to budget constraints and competing security priorities. Because there are several dimensions to security system performance and a range of attacks that might occur, the framework is multi-objective for a performance frontier to be estimated. This research explicitly uses probability of intruder interruption given detection (P_I) as the primary resilience metric. We demonstrate the utility of this framework with both notional as well as real-world examples of Physical Protection Systems (PPSs) and validate using a well-established force-on-force simulation tool, Umbra.

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This project was to use light ion beam induced charge (IBIC) to detect damage cascades generated by a single heavy ion, and thereby reveal details of the shape of the cascade and the physics of recombination of carriers that interact with the cluster. Further IBIC measurements using the hardware and software of this project will improve the accuracy of theoretical models used to predict electrical degradation in devices exposed to radiation environments. In addition, future use of light ion IBIC detection of single ion-induced damage could be used to locate single ion implantation sites in quantum computing applications. This project used Sandia's Pelletron and nanoImplanter (nI) to produce heavy ion-induced collision cascades in p-n diodes, simulating cascades made by primary knock-on atoms recoiled by neutrons. Si and Li beams from the nI were used to perform highly focused scans generating IBIC signal maps where regions of lower charge collection efficiency were observed without incurring further damage. The very first use of ion channeled beams for IBIC was explored to maximize ionization, improve contrast and provide very straight line trajectories to improve lateral resolution.

A basic two-way coupled discrete Lagrangian particle method has been implemented into CTH as a proof of concept. The approach has applications in modeling dilute multiphase phenomena, such as dust entrainment or explosive dispersion of debris. Only a basic Stokes drag law was implemented, but the framework allows for more advanced physics to be implemented in the future, such as particle-particle interactions or state of the art drag models. This memo outlines the modifications made to the code to implement the method, along with simple verification problems for it. The particle data structure used was designed to be as general as possible to facilitate future particle based methods being pursued in the future. For example the same data structure could be leveraged for Lagrangian notional particles used in Probability Density Function approaches, or the advection of a distribution of states such as a Weibull distribution for mechanics.

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Increased emphasis on computational simulation for NW qualification merits a corresponding increased diligence in verifying our codes. A manufactured solution process (implemented in Mathematica) for finite deformation, hyperelastic problems is presented that has been used to verify Sierra/SM for this class of problems. The process "manufactures a problem" given either a displacement field or motion map. Four test problems are examined; two provide sanity checks on symbolically calculated results, and two provide code verification results. While simple solutions from linear elasticity can be used to "seed" a manufactured solution, one from beam theory is shown to yield a n unexpectedly complex boundary value problem. The last problem combines two approaches that can significantly simplify the solution of some hypoelasticity problems, which require integration over time; a semi-manufactured approach is proposed and examined that yields the same observed rates of convergence as the classical approach at significantly reduced analytical effort.

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Magnetized Liner Inertial Fusion (MagLIF) is an inertial confinement fusion (ICF) concept that includes a strong magnetic field embedded in the fuel to mitigate thermal conduction loss during the implosion. MagLIF experiments on Sandia's 20 MA Z Machine uses an external Helmholtz-like coil pair for fuel premagnetization. By contrast, the novel AutoMag concept employs a composite liner (cylindrical tube) with helically oriented conduction paths separated by insulating material to provide axial premagnetization of the fuel. Initially, during a current prepulse that slowly rises to %7E1 MA, current flows helically through the AutoMag liner, and sources the fuel with an axial field. Next, a rapidly rising main current pulse breaks down the insulation and current in the liner becomes purely axial. The liner and premagnetized fuel are then compressed by the rapidly growing azimuthal field external to the liner. This integrated axial-field-production mechanism offers a few potential advantages when compared to the external premagnetization coils. AutoMag can increase drive current to MagLIF experiments by enabling a lower inductance transmission line, provide higher premagnetization field (>30 T), and greatly increase radial x-ray diagnostic access. 3D electromagnetic simulations using ANSYS Maxwell have been completed in order to explore the current distributions within the helical conduction paths, the inter - wire dielectric strength properties, and the thermal properties of the helical conduction paths during premagnetization (%7E1 MA in 100ns). Three liner designs, of varying peak field strength, and associated varying risk of dielectric breakdown, will soon be tested in experiments on the %7E 1 MA, 100ns Mykonos facility. Experiments will measure B_z(t) inside of the line r and assess failure mechanisms.

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The transformation of the distribution grid from a centralized to decentralized architecture, with bi-directional power and data flows, is made possible by a surge in network intelligence and grid automation. While changes are largely beneficial, the interface between grid operator and automated technologies is not well understood, nor are the benefits and risks of automation. Quantifying and understanding the latter is an important facet of grid resilience that needs to be fully investigated. The work described in this document represents the first empirical study aimed at identifying and mitigating the vulnerabilities posed by automation for a grid that for the foreseeable future will remain a human-in-the-loop critical infrastructure. Our scenario-based methodology enabled us to conduct a series of experimental studies to identify causal relationships between grid-operator performance and automated technologies and to collect measurements of human performance as a function of automation. Our findings, though preliminary, suggest there are predictive patterns in the interplay between human operators and automation, patterns that can inform the rollout of distribution automation and the hiring and training of operators, and contribute in multiple and significant ways to the field of grid resilience.

This report describes a new capability for hierarchical task-data parallelism using Sandia's Kokkos and Qthreads, and evaluation of this capability with sparse matrix Cholesky factorization and social network triangle enumeration mini-applications. Hierarchical task-data parallelism consists of a collection of tasks with executes-after dependences where each task contains data parallel operations performed on a team of hardware threads. The collection of tasks and dependences form a directed acyclic graph of tasks - a task DAG. Major challenges of this research and development effort include: portability and performance across multicore CPU; manycore Intel Xeon Phi, and NVIDIA GPU architectures; scalability with respect to hardware concurrency and size of the task DAG; and usability of the application programmer interface (API).

Conducting experiments on large-scale distributed computing systems is becoming significantly easier with the assistance of emulation. Researchers can now create a model of a distributed computing environment and then generate a virtual, laboratory copy of the entire system composed of potentially thousands of virtual machines, switches, and software. The use of real software, running at clock rate in full virtual machines, allows experiments to produce meaningful results without necessitating a full understanding of all model components. However, the ability to inspect and modify elements within these models is bound by the limitation that such modifications must compete with the model, either running in or alongside it. This inhibits entire classes of analyses from being conducted upon these models. We developed a mechanism to snapshot an entire emulation-based model as it is running. This allows us to \freeze time" and subsequently fork execution, replay execution, modify arbitrary parts of the model, or deeply explore the model. This snapshot includes capturing packets in transit and other input/output state along with the running virtual machines. We were able to build this system in Linux using Open vSwitch and Kernel Virtual Machines on top of Sandia's emulation platform Firewheel. This primitive opens the door to numerous subsequent analyses on models, including state space exploration, debugging distributed systems, performance optimizations, improved training environments, and improved experiment repeatability.

Molecular dynamics simulation was implemented using LAMMPS simulation package (1) to study the diffusivity of He³ and CO₂ in NaCl aqueous solution. To simulate at infinite dilute gas concentration, we placed one He³ or CO₂ molecule in an initial simulation box of 24x24x33ų containing 512 water molecules and a certain number of NaCl molecules depending on the concentration. Initial configuration was set up by placing water, NaCl, and gas molecules into different regions in the simulation box. Calculating diffusion coefficient for one He or CO₂ molecule consistently yields poor results. To overcome this, for each simulation at specific conditions (i.e., temperature, pressure, and NaCl concentration), we conducted 50 simulations initiated from 50 different configurations. These configurations are obtained by performing the simulation starting from the initial configuration mentioned above in the NVE ensemble (i.e., constant number of particles, volume, and energy). for 100,000 time steps and collecting one configuration every 2,000 times step. The output temperature of this simulation is about 500K. The collected configurations were then equilibrated for 2ns in the NPT ensemble (i.e., constant number of particles, pressure, and temperature) followed by 9ns simulations in the NVT ensemble (i.e., constant number of particles, volume, and temperature). The time step is 1fs for all simulations.

The 2016 Parameterized Reduced Order Modeling (PROM) Workshop was held in June, 2016, in Albuquerque, NM. This workshop included 30 researchers who took part in a two day discussion regarding the state of the art for PROMs, complimentary reduced order modeling (ROM) theories, and discussion of the future directions of PROM research. The goals of the workshop were three-fold: to assess the relative accuracy, efficiency, and merits of the different PROM methods; to discuss the state of the art for ROMs and how PROMs can benefit from these advances; and to define the pressing challenges for PROMs and a path for future research collaborations.

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An important characteristic of a radar receiver is the noise level within the receiver chain. The common parameter that specifies this is the System Noise Factor, which depends on system design and may vary with gain settings, temperature, and other factors. A modified Y-factor technique is detailed to calculate System Noise Factor for a radar receiver. Error sources are also detailed.

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The purpose of this Failure Modes and Effects Analysis (FMEA) is chosen to examine the potential failures of the systems which could result in an overspeed event with a potential for flying debris from the wind turbine blades. The FMEA method was chosen to examine the turbine hydraulic system because two important turbine protective features use hydraulic pressure to function: the blade pitching system, and the brake. The objective of the FMEA was to determine if the two safety features have a likely common failure point, or if the safety systems can be individually credited for protection of the turbine.

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The US Department of Energy (DOE) Nuclear Energy Research Initiative funded the design and construction of the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories. The start-up of the experiment facility and the execution of the experiments described here were funded by the DOE Nuclear Criticality Safety Program. The 7uPCX is designed to investigate critical systems with fuel for light water reactors in the enrichment range above 5% ²³⁵U. The 7uPCX assembly is a water-moderated and -reflected array of aluminum-clad square-pitched UO2 fuel rods. The uranium is enriched to 6.90% by mass. Sets of 36 titanium and aluminum experiment rods with the same nominal outside diameter as the fuel rods were fabricated and used as replacements for fuel rods in the array. The twenty-four 7uPCX critical experiments reported here compare the effects of the titanium and aluminum replacement rods on nearly critical fuel rod arrays. The fuel used in these experiments was fabricated using unirradiated UO₂ fuel pellets from fuel elements designed to be used in the internal nuclear superheater section of the Pathfinder boiling water reactor operated in South Dakota by the Northern States Power Company in the 1960s. The fuel elements were obtained from The Pennsylvania State University where they had been stored for many years. The fuel pellets in those fuel elements were removed from the original Incoloy cladding and reclad in 3003 aluminum tubes and end caps for use in the experiments reported here. The nominal outside diameter of the fuel pellets is 0.207 in (0.52578 cm). The nominal outside diameter of the fuel rod cladding is 0.250 in (0.635 cm). The distance between the fuel rods in the square-pitched array is 0.315 in (0.8001 cm). This geometry gives a fuel-to-water volume ratio of 0.67 in the array. The twenty-four critical experiments in this series were performed in 2015 and 2016 at the Sandia Critical Experiments Facility. The first of the experiments had no replacement rods in the array and was intended to provide a baseline against which the experiments containing replacement rods could be compared. Eight critical experiments had titanium replacement rods in various numbers and arrangements near the center of the fuel array. Eight critical experiments had aluminum replacement rods in the same numbers and arrangements as in the eight experiments containing titanium experiment rods. In the final four experiments, fuel rods were removed from a central region of the array so that the pitch of the fuel rods in this part of the array was effectively doubled. This softened the neutron spectrum in the central part of the fuel array. Thirty-six replacement rods in different combinations of titanium and/or aluminum were placed in the interstices created in the center of the array. All twenty-four critical experiments are judged to be acceptable as benchmark experiments.

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Moving target defense (MTD) is an emerging paradigm in which system defenses dynamically mutate in order to decrease the overall system attack surface. Though the initial concept is promising, implementations have not been widely adopted. The field has been actively researched for over ten years, and has only produced a small amount of extensively adopted defenses, most notably, address space layout randomization (ASLR). This is despite the fact that there currently exist a variety of moving target implementations and proofs-of-concept. We suspect that this results from the moving target controls breaking critical system dependencies from the perspectives of users and administrators, as well as making things more difficult for attackers. As a result, the impact of the controls on overall system security is not sufficient to overcome the inconvenience imposed on legitimate system users. In this paper, we analyze a successful MTD approach. We study the control's dependency graphs, showing how we use graph theoretic and network properties to predict the effectiveness of the selected control. Then, with this framework in place, the dynamic nature of some Moving Target Defenses opens the possibility of modeling them with dynamic systems approaches, such as state space representations familiar from control and systems theory. We then use this approach to develop state space models for Moving Target Defenses, provide an analysis of their properties, and suggest approaches for using them.

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Sandia National Laboratories has begun developing modeling and analysis tools of flow through the cemented portion of a cemented annulus in a Strategic Petroleum Reserve (SPR) well since August of 2015. The goal of this work is to develop models and testing procedures to diagnose the health of cemented annuli at SPR sites. In Fiscal Year 2016 (FY16), we have developed several tests and associated models that we believe are sufficient for this purpose. This report outlines progress made in FY16 and future work.

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The thermal performance of commercial nuclear spent fuel dry storage casks are 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). Carefully measured data sets generated from testing of full sized casks or smaller cask analogs are widely recognized as vital for validating these models. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask in part by increasing the efficiency of internal conduction pathways and also by increasing the internal convection through greater canister helium pressure. These same canistered cask systems rely on ventilation between the canister and the overpack to convect heat away from the canister to the environment for both above and belowground configurations. While several testing programs have been previously conducted, these earlier validation attempts did not capture the effects of elevated helium pressures or accurately portray the external convection of aboveground and belowground canistered dry cask systems. The purpose of the current investigation was to produce data sets that can be used to test the validity of the assumptions associated with the calculations used to determine steady-state cladding temperatures in modern dry casks that utilize elevated helium pressure in the sealed canister in an aboveground configuration. An existing electrically heated but otherwise prototypic BWR Incoloy-clad test assembly was deployed inside of a representative storage basket and cylindrical pressure vessel that represents a vertical canister system. The symmetric single assembly geometry with well-controlled boundary conditions simplifies interpretation of results. The arrangement of ducting was used to mimic conditions for an aboveground storage configuration in a vertical, dry cask systems with canisters. Transverse and axial temperature profiles were measured for a wide range of decay power and helium cask pressures. Of particular interest was the evaluation of the effect of increased helium pressure on peak cladding temperatures (PCTs) for identical thermal loads. All steady state peak temperatures and induced flow rates increased with increasing assembly power. Peak cladding temperatures decreased with increasing internal helium pressure for a given assembly power, indicating increased internal convection. In addition, the location of the PCT moved from near the top of the assembly to ~1/3 the height of the assembly for the highest (8 bar absolute) to the lowest (0 bar absolute) pressure studied, respectively. This shift in PCT location is consistent with the varying contribution of convective heat transfer proportional with of internal helium pressure.

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Permafrost-dominated coastlines in the Arctic are rapidly disappearing. Arctic coastal erosion rates in the United States have doubled since the middle of the twentieth century and appear to be accelerating. Positive erosion trends have been observed for highly-variable geomorphic conditions across the entire Arctic, suggesting a major (human-timescale) shift in coastal landscape evolution. Unfortunately, irreversible coastal land loss in this region poses a threat to native, industrial, scientific, and military communities. The Arctic coastline is vast, spanning more than 100,000 km across eight nations, ten percent of which is overseen by the United States. Much of area is inaccessible by all-season roads. People and infrastructure, therefore, are commonly located near the coast. The impact of the Arctic coastal erosion problem is widespread. Homes are being lost. Residents are being dispersed and their villages relocated. Shoreline fuel storage and delivery systems are at greater risk. The U.S. Department of Energy (DOE) and Sandia National Laboratories (SNL) operate research facilities along some of the most rapidly eroding sections of coast in the world. The U.S. Department of Defense (DOD) is struggling to fortify coastal radar sites, operated to ensure national sovereignty in the air, against the erosion problem. Rapid alterations to the Arctic coastline are facilitated by oceanographic and geomorphic perturbations associated with climate change. Sea ice extent is declining, sea level is rising, sea water temperature is increasing, and permafrost state is changing. The polar orientation of the Arctic exacerbates the magnitude and rate of the environmental forcings that facilitate coastal land area loss. The fundamental mechanics of these processes are understood; their non-linear combination poses an extreme hazard. Tools to accurately predict Arctic coastal erosion do not exist. To obtain an accurate predictive model, a coupling of the influences of evolving wave dynamics, thermodynamics, and sediment dynamics must be developed. The objective of this document is to present the state-of-the-science and outline the key steps for creation of a framework that will allow for improved prediction of Arctic coastal erosion rates. This is the first step towards the quantification of coastal hazards that will allow for sustainable planning and development of Arctic infrastructure.

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Mixing of injected raw (undersaturated) water with brine in Strategic Petroleum Reserve (SPR) salt caverns affects the shape of cavern walls due to leaching. Cavern shape impacts cavern geomechanical stability and available volume for oil storage. Raw water injection occurs during initial solution mining of caverns, remedial leaching of caverns, and oil drawdown. Of interest are factors that control the degree of raw water-brine mixing and thereby the concentration of the aqueous fluid mixture that contacts the salt cavern walls. It is hypothesized that poorly-mixed fresh water could potentially cause undesirable and non-uniform leaching , for example, if buoyant poorly-mixed fresh water collects and preferentially leaches under the oil-brine interface . This report presents current understanding of controls on incomplete-to-complete mixing of raw water and brine, focusing on implications for SPR cavern leaching. In the context of mixing, we review the following: SPR leaching operations; models of leaching; field measurements of leaching and cavern shapes; and previous laboratory experiments of mixing and /or leaching performed at Sandia National Laboratories. We present recent laboratory experiments in 2014-2016 that focused explicitly on understanding controls of poor-to-well mixed conditions. We find that well-mixed conditions are expected for typical operating conditions of the SPR.

A one-day workshop was held on April 14, 2016 to explore Nuclear Weapons Mission Area (NWMA) strategy enablers from a systems perspective. This report documents the workshop and is intended to identify initiatives, based on the workshop exchanges, and catalyze these initiatives to enable implementation of the NWMA strategy using systems thinking and methodology. Topics explored include Model-based Engineering, Enabling Viable Capabilities, and Enterprise Decision Awareness. The morning of the workshop featured Dr. Dinesh Verma (Stevens Institute/SERC) as keynote and during the afternoon attendees participated in three facilitated sessions on the topics. There were over 70 participants from about 40 departments across Sandia National Laboratories.

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CACTUS, developed by Sandia National Laboratories, is an open-source code for the design and analysis of wind and hydrokinetic turbines. While it has undergone extensive validation for both vertical axis and horizontal axis wind turbines, and it has been demonstrated to accurately predict the performance of horizontal (axial-flow) hydrokinetic turbines, its ability to predict the performance of crossflow hydrokinetic turbines has yet to be tested. The present study addresses this problem by comparing the predicted performance curves derived from CACTUS simulations of the U.S. Department of Energy’s 1:6 scale reference model crossflow turbine to those derived by experimental measurements in a tow tank using the same model turbine at the University of New Hampshire. It shows that CACTUS cannot accurately predict the performance of this crossflow turbine, raising concerns on its application to crossflow hydrokinetic turbines generally. The lack of quality data on NACA 0021 foil aerodynamic (hydrodynamic) characteristics over the wide range of angles of attack (AoA) and Reynolds numbers is identified as the main cause for poor model prediction. A comparison of several different NACA 0021 foil data sources, derived using both physical and numerical modeling experiments, indicates significant discrepancies at the high AoA experienced by foils on crossflow turbines. Users of CACTUS for crossflow hydrokinetic turbines are, therefore, advised to limit its application to higher tip speed ratios (lower AoA), and to carefully verify the reliability and accuracy of their foil data. Accurate empirical data on the aerodynamic characteristics of the foil is the greatest limitation to predicting performance for crossflow turbines with semi-empirical models like CACTUS. Future improvements of CACTUS for crossflow turbine performance prediction will require the development of accurate foil aerodynamic characteristic data sets within the appropriate ranges of Reynolds numbers and AoA.

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We report on the development of a model framework to simulate spray flames from direct injection of liquid fuel into an automotive cylinder engine. The approach to this challenging problem was twofold. On one hand, the interface-capturing multiphase computer code CLSVOF was used to resolve the rapidly evolving, topologically convoluted interfaces that separate the liquid fuel from the gas at injection: the main challenges to address were the treatment of the high-pressure flow inside the injector, which required the inclusion of compressibility effects; and the computational framework necessary to achieve a Direct Numerical Simulation (DNS) level of accuracy. On the other hand, the scales of turbulent fuel mixing and combustion in the cylinder engine were addressed by the high-performance computer code RAPTOR within the Large Eddy Simulation (LES) framework. To couple the two computational methods, a novel methodology was developed to de- scribe the dense spray dynamics in Raptor from the assigned spray size distribution and dispersion angle derived from CLSVOF. This new, independent Eulerian Multi-Fluid (EMF) spray module was developed based on the kinetic description of a system of droplets as a pressure-less gas; as we will show, it was demonstrated to efficiently render the near-nozzle coupling in mass, momentum, and energy with the carrier gas phase.

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Particle methods in computational physics are useful for modeling the motion of fluids and solids subject to large deformations. Under these conditions, mesh-based approaches often fail due to decreasing element quality leading to inaccuracy and instability. The developed software package called Moab investigates and prototypes next-generation particle methods, focusing on rigorous error analysis and active error minimization strategies during the computation. The present work discusses examples calculations representative of real engineering problems with quantified and maximized accuracy while demonstrating the potential for meeting engineering performance requirements.

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The Next Generation Global Atmosphere Model LDRD project developed a suite of atmosphere models: a shallow water model, an x-z hydrostatic model, and a 3D hydrostatic model, by using Albany, a finite element code. Albany provides access to a large suite of leading-edge Sandia high-performance computing technologies enabled by Trilinos, Dakota, and Sierra. The next-generation capabilities most relevant to a global atmosphere model are performance portability and embedded uncertainty quantification (UQ). Performance portability is the capability for a single code base to run efficiently on diverse set of advanced computing architectures, such as multi-core threading or GPUs. Embedded UQ refers to simulation algorithms that have been modified to aid in the quantifying of uncertainties. In our case, this means running multiple samples for an ensemble concurrently, and reaping certain performance benefits. We demonstrate the effectiveness of these approaches here as a prelude to introducing them into ACME.

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This work supports Airborne Intelligence, Surveillance, and Reconnaissance (ISR) for tactical situational awareness in challenging environments with modified imaging LIDAR (light detection and ranging). LIDAR produces an irradiance-based scene with high, three-dimensional, spatial resolution; differentiating reflecting surfaces and surface textures not just for target detection, but also target recognition. LIDAR is generally prevented from working through all weather; as the traditional source wavelengths are scattered and/or absorbed by fog, clouds, and dust known as degraded visual environments (DVEs). This work identifies and quantifies improved optical wavelength regimes and polarization strategies that should open this otherwise denied operating window for LIDAR. We demonstrate modified imaging LIDAR's utility and ability to produce images in environments that have been challenging for traditional LIDAR (fog, dust) systems. We utilize a state-of-the-art Geiger mode avalanche photodiode (GMAPD) 32X32 detecting array for imaging with an integrated fast timing circuit ROIC per imaging detector pixel. This GMAPD is equivalent to 1024 radar receivers and produces a 3-D point cloud scene for each

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The Electromagnetic Environment Simulator (EMES) is a large transverse electromagnetic (TEM) cell that propagates an ostensibly uniform, planar electromagnetic wave illuminating a test object with RF energy within a working volume. The characterization presented in this report uses measurements from three electric field components spanning a frequency range between 100 kHz and 220 MHz. This report provides guidance for using these results to predict measurement uncertainty for experiments conducted in EMES. Weapons Systems Engineering Assessment Technology (WSEAT) commissioned this effort to provide support to Nuclear Weapons qualification in accordance with Realize Product Sub System (RPSS). Motivation for this effort stems from four qualification programs: B61 LEP, W88 ALT370, W80-4 LEP, and the Mk21 fuze program.

Capabilities and functions are hierarchical structures (i.e. taxonomies) that are used in a systems engineering framework to identify complimentary requirements for the system: what the system must do to achieve what it must be. In the case of capabilities, the taxonomy embodies the list of characteristics that are desired, from the perspective of the stakeholders, for the system to be successful. In terms of the functions, the hierarchy represents the solution agnostic (i.e. independent of specific design embodiments) elements that are needed to meet the stakeholder requirements. This paper will focus on the development of the functions. The functions define the fundamental elements of the solution that must be provided in order to achieve the mission and deliver the capabilities. They identify the behaviors the farm must possess, i.e. the farm must be able to generate and deliver electricity from wave power. High-level functions are independent of the technology or design used to implement the function. However, detailed functions may begin to border on specific design choices. Hence a strong effort has been made to maintain functions that are design agnostic.

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We assess how geospatial-temporal semantic graphs and our GeoGraphy code implementation might contribute to induced seismicity analysis. We focus on evaluating strengths and weaknesses of both 1) the fundamental concept of semantic graphs and 2) our current code implementation. With extensions and research effort, code implementation limitations can be overcome. The paper also describes relevance including possible data input types, expected analytical outcomes and how it can pair with other approaches and fit into a workflow.

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While there has been a great deal of security research focused on preventing attacks, there has been less work on how one should balance security and resilience investments. In this work we developed and evaluated models that captured both explicit defenses and other mitigations that reduce the impact of attacks. We examined these issues both in more broadly applicable general Stackelberg models and in more specific network and power grid settings. Finally, we compared these solutions to existing work in terms of both solution quality and computational overhead.

The Gigahertz Transverse ElectroMagnetic (GTEM) test cell propagates planar electromagnetic waves to illuminate a test object with radio frequency (RF) energy within a bounded structure. Once illuminated, the test object produces a response or a transducer measures a parameter inside the test object providing information for computing a transfer function. The transfer function informs a model or additional testing. This report documents the behavior and characterization of the GTEM. The characterization presented in this report uses measurements from electric field measurements spanning a frequency range between 100 kHz and 18 GHz. This report provides guidance for using these results to predict uncertainty of measurements conducted in the GTEM. The GTEM is slightly smaller than EMES (Electromagnetic Environment Simulator); hence, can accommodate objects almost as large as EMES. Sandia acquired the GTEM from ETS Lindgren. ETS Lindgren installed and performed the acceptance test per requirements set forth by Sandia. This document also reports some of the features of the GTEM including safety. Weapons Systems Engineering Assessment Technology (WSEAT) commissioned this effort to provide support to Nuclear Weapons qualification in accordance with Realize Product Sub System (RPSS). Motivation for this effort stems from four qualification programs: B61 LEP, W88 ALT370, W80-4 LEP, and the Mk21 fuze program.

Concurrent processes can be extremely difficult to reason about, both for programmers and formally. One approach to coping with this difficulty is to study new programming languages and type features such as Session Types. Session types take as their conceptual notion of concurrency as a collection of processes linked together via channels and provide type-level coordination between processes using these channels. Logically motivated programming languages exploit the idea that providing a proof of a theorem in a logic is similar to proving that a given term has a particular type in a programming language and vice versa. These connections can be interesting for a few different reasons. First, when language and logic are independently discovered and independently useful, the existence of a connection suggests that both are onto some fundamentally important idea. Additionally, a connection provides a basis both for sanity checking our ideas and also can be fruitful grounds for inspiration by seeing how variants of either the logic or the language are reflected through the connection. This thesis primarily describes an exploration of logically motivated session types, SILL. Polarization, classifying propositions as either positive or negative, provides a natural way to describe a logically based session typing language with asynchronous communication while retaining a semantics that is reasonably implementable. Additionally, polarization gives us a way to smoothly integrate synchronous channels into SILL without needing a semantic extension. When combined with Adjoint Logic, this gives us an ability to incorporate a variety of modalities with relatively little work. From a practical perspective, this gives SILL access to persistent processes and garbage collection. We additionally explore a trio of loosely related extensions to SILL, and their logical connections, inspired by the above results: bundled message passing to reduce the number of communications performed by processes; racy programs, enabled by a select/epoll-like mechanism; and asynchronous receiving, an almost generalization of the basic asynchronous semantics. We have three different implementations of SILL: a simple but relatively full featured interpreter written in OCaml; a fragment of SILL as an embedded domain specific language in Haskell; and a cleaner version of the same in Idris. Lastly, we show that Liquid Types and Session Types are compatible. This gives us one notion of a dependently session typed language.