Publications

This letter report presents a probabilistic performance assessment model to evaluate the probability of canister failure (through-wall penetration) by SCC. The model first assesses whether environmental conditions for SCC – the presence of an aqueous film – are present at canister weld locations (where tensile stresses are likely to occur) on the canister surface. Geometry-specific storage system thermal models and weather data sets representative of U.S. spent nuclear fuel (SNF) storage sites are implemented to evaluate location-specific canister surface temperature and relative humidity (RH). As the canister cools and aqueous conditions become possible, the occurrence of corrosion is evaluated. Corrosion is modeled as a two-step process: first, pitting is initiated, and the extent and depth of pitting is a function of the chloride surface load and the environmental conditions (temperature and RH). Second, as corrosion penetration increases, the pit eventually transitions to a SCC crack, with crack initiation becoming more likely with increasing pit depth. Once pits convert to cracks, a crack growth model is implemented. The SCC growth model includes rate dependencies on both temperature and crack tip stress intensity factor, and crack growth only occurs in time steps when aqueous conditions are predicted. The model suggests that SCC is likely to occur over potential SNF interim storage intervals; however, this result is based on many modeling assumptions. Sensitivity analyses provide information on the model assumptions and parameter values that have the greatest impact on predicted storage canister performance, and provide guidance for further research to reduce uncertainties.

COBRA-TF (CTF) is a low-resolution code currently maintained as CASL's subchannel analysis tool. CTF operates as a two-phase, compressible code over a mesh comprised of subchannels and axial discretized nodes. In part because CTF is a low-resolution code, simulation run time is not computationally expensive, only on the order of minutes. Hi-resolution codes such as STAR-CCM+ can be used to train lower-fidelity codes such as CTF. Unlike STAR-CCM+, CTF has no turbulence model, only a two-phase turbulent mixing coefficient, β. β can be set to a constant value or calculated in terms of Reynolds number using an empirical correlation. Results from STAR-CCM+ can be used to inform the appropriate value of β. Once β is calibrated, CTF runs can be an inexpensive alternative to costly STAR-CCM+ runs for scoping analyses. Based on the results of CTF runs, STAR-CCM+ can be run for specific parameters of interest. CASL areas of application are CIPS for single phase analysis and DNB-CTF for two-phase analysis.

STAR-CCM+ (STAR) is a high-resolution computational fluid dynamics (CFD) code developed by CD-adapco. STAR includes validated physics models and a full suite of turbulence models including ones from the k-ε and k-ω families. STAR is currently being developed to be able to do two phase flows, but the current focus of the software is single phase flow. STAR can use imported meshes or use the built in meshing software to create computation domains for CFD. Since the solvers generally require a fine mesh for good computational results, the meshes used with STAR tend to number in the millions of cells, with that number growing with simulation and geometry complexity. The time required to model the flow of a full 5x5 Mixing Vane Grid Assembly (5x5MVG) in the current STAR configuration is on the order of hours, and can be very computationally expensive. COBRA-TF (CTF) is a low-resolution subchannel code that can be trained using high fidelity data from STAR. CTF does not have turbulence models and instead uses a turbulent mixing coefficient β. With a properly calibrated β, CTF can be used a low-computational cost alternative to expensive full CFD calculations performed with STAR. During the Hi2Lo work with CTF and STAR, STAR-CCM+ will be used to calibrate β and to provide high-resolution results that can be used in the place of and in addition to experimental results to reduce the uncertainty in the CTF results.

This report documents conceptual design development for the Deep Borehole Field Test (DBFT), including test packages (simulated waste packages, not containing waste) and a system for demonstrating emplacement and retrieval of those packages in the planned Field Test Borehole (FTB). For the DBFT to have demonstration value, it must be based on conceptualization of a deep borehole disposal (DBD) system. This document therefore identifies key options for a DBD system, describes an updated reference DBD concept, and derives a recommended concept for the DBFT demonstration. The objective of the DBFT is to confirm the safety and feasibility of the DBD concept for long-term isolation of radioactive waste. The conceptual design described in this report will demonstrate equipment and operations for safe waste handling and downhole emplacement of test packages, while contributing to an evaluation of the overall safety and practicality of the DBD concept. The DBFT also includes drilling and downhole characterization investigations that are described elsewhere (see Section 1). Importantly, no radioactive waste will be used in the DBFT, nor will the DBFT site be used for disposal of any type of waste. The foremost performance objective for conduct of the DBFT is to demonstrate safe operations in all aspects of the test.

As the title suggests, this report provides a summary of the status and progress for the Preliminary Design Concepts Work Package. Described herein are design concepts and thermal analysis for crystalline and salt host media. The report concludes that thermal management of defense waste, including the relatively small subset of high thermal output waste packages, is readily achievable. Another important conclusion pertains to engineering feasibility, and design concepts presented herein are based upon established and existing elements and/or designs. The multipack configuration options for the crystalline host media pose the greatest engineering challenges, as these designs involve large, heavy waste packages that pose specific challenges with respect to handling and emplacement. Defense-related Spent Nuclear Fuel (DSNF) presents issues for post-closure criticality control, and a key recommendation made herein relates to the need for special packaging design that includes neutron-absorbing material for the DSNF. Lastly, this report finds that the preliminary design options discussed are tenable for operational and post-closure safety, owing to the fact that these concepts have been derived from other published and well-studied repository designs.

The thermal performance of commercial nuclear spent 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). 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 below-ground 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 above-ground and below-ground 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 above-ground configuration.

This paper presents a method for predicting how sensitive a frictional contact’s steady-state behavior is to its initial conditions. Previous research has proven that if a contact is uncoupled, i.e. if slip displacements do not influence the contact pressure distribution, then its steady-state response is independent of initial conditions, but if the contact is coupled, the steady-state response depends on initial conditions. In this paper, two metrics for quantifying coupling in discrete frictional systems are examined. These metrics suggest that coupling is dominated by material dissimilarity due to Dundurs’ composite material parameter β when β ≥ 0.2, but geometric mismatch becomes the dominant source of coupling for smaller values of β. Based on a large set of numerical simulations with different contact geometries, material combinations, and friction coefficients, a contact’s sensitivity to initial conditions is found to be correlated with the product of the coupling metric and the friction coefficient. For cyclic shear loading, this correlation is maintained for simulations with different contact geometries, material combinations, and friction coefficients. Furthermore, for cyclic bulk loading, the correlation is only maintained when the contact edge angle is held constant.

We propose a reformulation of the composite tetrahedral finite element first introduced by Thoutireddy et al. By choosing a different numerical integration scheme, we obtain an element that is more accurate than the one proposed in the original formulation. We also show that in the context of Lagrangian approaches, the gradient and projection operators derived from the element reformulation admit fully analytic expressions, which offer a significant improvement in terms of accuracy and computational expense. For plasticity applications, a mean-dilatation approach on top of the underlying Hu–Washizu variational principle proves effective for the representation of isochoric deformations. The performance of the reformulated element is demonstrated by hyperelastic and inelastic calculations. Copyright © 2016 John Wiley & Sons, Ltd.

The capability for statically pre-compressing fluid targets for Hugoniot measurements utilizing gas gun driven flyer plates has been developed. Pre-compression expands the capability for initial condition control, allowing access to thermodynamic states off the principal Hugoniot. Absolute Hugoniot measurements with an uncertainty less than 3% on density and pressure were obtained on statically pre-compressed fluid helium utilizing a two stage light gas gun. Helium is highly compressible; the locus of shock states resulting from dynamic loading of an initially compressed sample at room temperature is significantly denser than the cryogenic fluid Hugoniot even for relatively modest (0.27-0.38 GPa) initial pressures. The dynamic response of pre-compressed helium in the initial density range of 0.21-0.25 g/cm3 at ambient temperature may be described by a linear shock velocity (us) and particle velocity (up) relationship: us = C0 + sup, with C0 = 1.44 ± 0.14 km/s and s = 1.344 ± 0.025.

Mesoscale (100s of particles) electrochemical-thermal-mechanical models and simulations of NMC cathodes are a critical outcome of the CABS project. While the mathematical model formulation for these mesoscale simulations is well established, these simulations also require (1) calibrated parameterization of the mathematical model and (2) mesostructure geometries on which to perform the simulations. In this milestone report, we present a parameterized mathematical model, primarily based on parameter values available in the open literature, that will form the basis of future simulations. We also discuss options for obtaining and using representative mesostructure data in these simulations.

Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high fidelity, validated models used in modal, vibration, static and shock analysis of weapons systems. This document provides a users guide to the input for Sierra/SD. Details of input specifications for the different solution types, output options, element types and parameters are included. The appendices contain detailed examples, and instructions for running the software on parallel platforms.

Room D was an in-situ, isothermal, underground experiment conducted at the Waste Isolation Pilot Plant between 1984 and 1991. The room was carefully instrumented to measure the horizontal and vertical closure immediately upon excavation and for several years thereafter. Early finite element simulations of salt creep around Room D under-predicted the vertical closure by 4.5×, causing investigators to explore a series of changes to the way Room D was modeled. Discrepancies between simulations and measurements were resolved through a series of adjustments to model parameters, which were openly acknowledged in published reports. Interest in Room D has been rekindled recently by the U.S./German Joint Project III and Project WEIMOS, which seek to improve the predictions of rock salt constitutive models. Joint Project participants calibrate their models solely against laboratory tests, and benchmark the models against underground experiments, such as room D. This report describes updating legacy Room D simulations to today’s computational standards by rectifying several numerical issues. Subsequently, the constitutive model used in previous modeling is recalibrated two different ways against a suite of new laboratory creep experiments on salt extracted from the repository horizon of the Waste Isolation Pilot Plant. Simulations with the new, laboratory-based, calibrations under-predict Room D vertical closure by 3.1×. A list of potential improvements is discussed.

Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high fidelity, validated models used in modal, vibration, static and shock analysis of structural systems. This manual describes the theory behind many of the constructs in Sierra/SD. For a more detailed description of how to use Sierra/SD , we refer the reader to Sierra/SD, User's Notes. Many of the constructs in Sierra/SD are pulled directly from published material. Where possible, these materials are referenced herein. However, certain functions in Sierra/SD are specific to our implementation. We try to be far more complete in those areas. The theory manual was developed from several sources including general notes, a programmer_notes manual, the user's notes and of course the material in the open literature.

MPI includes all processes in MPI COMM WORLD; this is untenable for reasons of scale, resiliency, and overhead. This paper offers a new approach, extending MPI with a new concept called Sessions, which makes two key contributions: a tighter integration with the underlying runtime system; and a scalable route to communication groups. This is a fundamental change in how we organise and address MPI processes that removes well-known scalability barriers by no longer requiring the global communicator MPI COMM - WORLD.

Scientific workloads running on current extreme-scale systems routinely generate tremendous volumes of data for postprocessing. This data movement has become a serious issue due to its energy cost and the fact that I/O bandwidths have not kept pace with data generation rates. In situ analytics is an increasingly popular alternative in which post-simulation processing is embedded into an application, running as part of the same MPI job. This can reduce data movement costs but introduces a new potential source of interference for the application. Using a validated simulation-based approach, we investigate how best to mitigate the interference from time-shared in situ tasks for a number of key extreme-scale workloads. This paper makes a number of contributions. First, we show that the independent scheduling of in situ analytics tasks can significantly degradation application performance, with slowdowns exceeding 1000%. Second, we demonstrate that the degree of synchronization found in many modern collective algorithms is sufficient to significantly reduce the overheads of this interference to less than 10% in most cases. Finally, we show that many applications already frequently invoke collective operations that use these synchronizing MPI algorithms. Therefore, the syncronization introduced by these MPI collective algorithms can be leveraged to efficiently schedule analytics tasks with minimal changes to existing applications. This paper provides critical analysis and guidance for MPI users and developers on the importance of scheduling in situ analytics tasks. It shows the degree of synchronization needed to mitigate the performance impacts of these time-shared coupled codes and demonstrates how that synchronization can be realized in an extreme-scale environment using modern collective algorithms.

Exascale systems promise the potential for computation atunprecedented scales and resolutions, but achieving exascale by theend of this decade presents significant challenges. A key challenge isdue to the very large number of cores and components and the resultingmean time between failures (MTBF) in the order of hours orminutes. Since the typical run times of target scientific applicationsare longer than this MTBF, fault tolerance techniques will beessential. An important class of failures that must be addressed isprocess or node failures. While checkpoint/restart (C/R) is currentlythe most widely accepted technique for addressing processor failures, coordinated, stable-storage-based global C/R might be unfeasible atexascale when the time to checkpoint exceeds the expected MTBF. This paper explores transparent recovery via implicitly coordinated, diskless, application-driven checkpointing as a way to tolerateprocess failures in MPI applications at exascale. The discussedapproach leverages User Level Failure Mitigation (ULFM), which isbeing proposed as an MPI extension to allow applications to createpolicies for tolerating process failures. Specifically, this paper demonstrates how different implementations ofapplication-driven in-memory checkpoint storage and recovery comparein terms of performance and scalability. We also experimentally evaluate the effectiveness and scalability ofthe Fenix online global recovery framework on a production system-the Titan Cray XK7 at ORNL-and demonstrate the ability of Fenix totolerate dynamically injected failures using the execution of fourbenchmarks and mini-applications with different behaviors.

Computational simulation of structures subjected to blast loadings requires integration of computational shock-physics for blast, and structural response with potential for pervasive failure. Current methodologies for this problem space are problematic in terms of efficiency and solution quality. This report details the development of several coupling algorithms for thin shells, with an emphasis on rigorous verification where possible and comparisons to existing methodologies in use at Sandia.

The Waste Form Disposal Options Evaluation Report (SNL 2014) evaluated disposal of both Commercial Spent Nuclear Fuel (CSNF) and DOE-managed HLW and Spent Nuclear Fuel (DHLW and DSNF) in the variety of disposal concepts being evaluated within the Used Fuel Disposition Campaign. That work covered a comprehensive inventory and a wide range of disposal concepts. The primary goal of this work is to evaluate the information needs for analyzing disposal solely of a subset of those wastes in a Defense Repository (DRep; i.e., those wastes that are either defense related, or managed by DOE but are not commercial in origin). A potential DRep also appears to be safe in the range of geologic mined repository concepts, but may have different concepts and features because of the very different inventory of waste that would be included. The focus of this status report is to cover the progress made in FY16 toward: (1) developing a preliminary DRep included inventory for engineering/design analyses; (2) assessing the major differences of this included inventory relative to that in other analyzed repository systems and the potential impacts to disposal concepts; (3) designing and developing an on-line waste library (OWL) to manage the information of all those wastes and their waste forms (including CSNF if needed); and (4) constraining post-closure waste form degradation performance for safety assessments of a DRep. In addition, some continuing work is reported on identifying potential candidate waste types/forms to be added to the full list from SNL (2014 – see Table C-1) which also may be added to the OWL in the future. The status for each of these aspects is reported herein.

Salt formations represent a promising host for disposal of nuclear waste in the United States and Germany. Together, these countries provided fully developed safety cases for bedded salt and domal salt, respectively. Today, Germany and the United States find themselves in similar positions with respect to salt formations serving as repositories for heat-generating nuclear waste. German research centers are evaluating bedded and pillow salt formations to contrast with their previous safety case made for the Gorleben dome. Sandia National Laboratories is collaborating on this effort as an Associate Partner, and this report summarizes that teamwork. Sandia and German research groups have a long-standing cooperative approach to repository science, engineering, operations, safety assessment, testing, modeling and other elements comprising the basis for salt disposal. Germany and the United States hold annual bilateral workshops, which cover a spectrum of issues surrounding the viability of salt formations. Notably, recent efforts include development of a database for features, events, and processes applying broadly and generically to bedded and domal salt. Another international teaming activity evaluates salt constitutive models, including hundreds of new experiments conducted on bedded salt from the Waste Isolation Pilot Plant. These extensive collaborations continue to build the scientific basis for salt disposal. Repository deliberations in the United States are revisiting bedded and domal salt for housing a nuclear waste repository. By agreeing to collaborate with German peers, our nation stands to benefit by assurance of scientific position, exchange of operational concepts, and approach to elements of the safety case, all reflecting cost and time efficiency.

Sandia has invested heavily in scientific/engineering application development and in the research, development, and deployment of large scale HPC platforms to support the computational needs of these applications. As application developers continually expand the capabilities of their software and spend more time on performance tuning of applications for these platforms, HPC platform resources are at a premium as they are a heavily shared resource serving the varied needs of many users. To ensure that the HPC platform resources are being used effciently and perform as designed, it is necessary to obtain reliable data on resource utilization that will allow us to investigate the occurrence, severity, and causes of performance-affecting contention between applications. The work presented in this paper was an initial step to determine if resource contention can be understood and minimized through monitoring, modeling, planning and infrastructure. This paper describes the set of metric definitions, identified in this research, that can be used as meaningful and potentially actionable indicators of performance-affecting contention between applications. These metrics were verified using the observed slowdown of IOR, IMB, and CTH in operating scenarios that forced contention. This paper also describes system/application monitoring activities that are critical to distilling vast amounts of data into quantities that hold the key to understanding for an application's performance under production conditions and that will ultimately aid in Sandia's efforts to succeed in extreme-scale computing.

As high-performance computing systems continue to grow in scale and complexity, the study of faults and errors is critical to the design of future systems and mitigation schemes. Fault modes in system DRAM are a frequently-investigated key aspect of memory reliability. While current schemes require offline analysis for proper classification, current state-of-the-art mitigation techniques require accurate online prediction for optimal performance. In this work, we explore the predictive performance of an online machine learning-based approach in classifying DRAM fault modes from two leadership-class supercomputing facilities. Our results compare the predictive performance of this online approach with the current rule-based approach based on expert knowledge, finding a 12% predictive performance improvement. We also investigate the universality of our classifiers by evaluating predictive performance using training data from disparate computing systems to achieve a 7% improvement in predictive performance. Our work provides a critical analysis of this online learning technique and can benefit system designers to help inform best practices for dealing with reliability on future systems.

The Used Fuel Disposition Campaign (UFDC) of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (OFCT) is conducting research and development (R&D) on geologic disposal of used nuclear fuel (UNF) and high-level nuclear waste (HLW). Two of the high priorities for UFDC disposal R&D are design concept development and disposal system modeling (DOE 2011). These priorities are directly addressed in the UFDC Generic Disposal Systems Analysis (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 (e.g., salt, granite, clay, and deep borehole disposal). This report describes specific GDSA activities in fiscal year 2016 (FY 2016) toward the development of the enhanced disposal system modeling and analysis capability for geologic disposal of nuclear waste. The GDSA framework employs the PFLOTRAN thermal-hydrologic-chemical multi-physics code and the Dakota uncertainty sampling and propagation code. Each code is designed for massively-parallel processing in a high-performance computing (HPC) environment. Multi-physics representations in PFLOTRAN are used to simulate various coupled processes including heat flow, fluid flow, waste dissolution, radionuclide release, radionuclide decay and ingrowth, precipitation and dissolution of secondary phases, and radionuclide transport through engineered barriers and natural geologic barriers to the biosphere. Dakota is used to generate sets of representative realizations and to analyze parameter sensitivity.

Broad bandwidth coatings allow angle of incidence flexibility and accommodate spectral shifts due to aging and water absorption. Higher refractive index materials in optical coatings, such as TiO₂, Nb₂O₅, and Ta₂O₅, can be used to achieve broader bandwidths compared to coatings that contain HfO₂ high index layers. We have identified the deposition settings that lead to the highest index, lowest absorption layers of TiO₂, Nb₂O₅, and Ta₂O₅, via e-beam evaporation using ion-assisted deposition. We paired these high index materials with SiO₂ as the low index material to create broad bandwidth high reflection coatings centered at 1054 nm for 45 deg angle of incidence and P polarization. Furthermore, high reflection bandwidths as large as 231 nm were realized. Laser damage tests of these coatings using the ISO 11254 and NIF-MEL protocols are presented, which revealed that the Ta₂O₅/SiO₂ coating exhibits the highest resistance to laser damage, at the expense of lower bandwidth compared to the TiO₂/SiO₂ and Nb₂O₅/SiO₂ coatings.

The objective of the Crystalline Disposal R&D Work Package is to advance our understanding of long-term disposal of used fuel in crystalline rocks and to develop necessary experimental and computational capabilities to evaluate various disposal concepts in such media. FY16 continued to be a successful year in both experimental and modeling arenas in evaluation of used fuel disposal in crystalline rocks. The work covers a wide range of research topics identified in the R&D plan.

A key element of successful world-class technical organizations is the ability to learn from problems, large and small. Mature technical organizations have procedures that support this learning process, but it is not the procedures alone that cause the organization to succeed. Organizational success is the result of managers understanding the objectives of learning from problems and the discipline managers bring to bear to follow through on corrective actions. Following through includes checking if the actions fixed the problem and to implement alternate actions if the original actions did not achieve the objectives.

This report provides documentation for the SIERRA Toolkit (STK) modules. STK modules are intended to provide infrastructure that assists the development of computational engineering software such as finite-element analysis applications. STK includes modules for unstructured-mesh data structures, reading/writing mesh files, geometric proximity search, and various utilities. This document contains a chapter for each module, and each chapter contains overview descriptions and usage examples. Usage examples are primarily code listings which are generated from working test programs that are included in the STK code-base. A goal of this approach is to ensure that the usage examples will not fall out of date.

Metamaterial dielectric resonators represent a promising path toward low-loss metamaterials at optical frequencies. In this paper we utilize perturbations of high symmetry resonator geometries, such as cubes, either to overlap the electric and magnetic dipole resonances, thereby enabling directional scattering and Huygens' metasurfaces, or to induce couplings between the otherwise orthogonal resonator modes to achieve high-quality factor Fano resonances. Our results are fully scalable across any frequency bands where high-permittivity dielectric materials are available, including microwave, THz, and infrared frequencies.

Cable shielding to protect against coupling of electromagnetic radiation into a component or circuit, particularly over large frequency bands, is at times a challenging task. It is general understanding that increasing the number of shields of a cable will improve the shielding performance. However, there are situations in which a cable with multiple shields may perform similar to or in some cases worse than a cable with a single shield, and this analysis has seldom been discussed in the literature. We intend to shed more light onto this topic in this paper.

Metamaterial dielectric resonators represent a promising path toward low-loss metamaterials at optical frequencies. In this paper we utilize perturbations of high symmetry resonator geometries, such as cubes, either to overlap the electric and magnetic dipole resonances, thereby enabling directional scattering and Huygens' metasurfaces, or to induce couplings between the otherwise orthogonal resonator modes to achieve high-quality factor Fano resonances. Our results are fully scalable across any frequency bands where high-permittivity dielectric materials are available, including microwave, THz, and infrared frequencies.

Narrow-bandgap semiconductors such as alloys of InAsAlSb and their heterostructures are considered promising candidates for next generation infrared photodetectors and devices. The prospect of actively tuning the spectral responsivity of these detectors at the pixel level is very appealing. In principle, this could be achieved with a tunable metasurface fabricated monolithically on the detector pixel. Here, we present first steps towards that goal using a complementary metasurface strongly coupled to an epsilon-near-zero (ENZ) mode operating in the long-wave region of the infrared spectrum. We fabricate such a coupled system using the same epitaxial layers used for infrared pixels in a focal plane array and demonstrate the existence of ENZ modes in high mobility layers of InAsSb. We confirm that the coupling strength between the ENZ mode and the metasurface depends on the ENZ layer thickness and demonstrate a transmission modulation on the order of 25%. We further show numerically the expected tunable spectral behavior of such coupled system under reverse and forward bias, which could be used in future electrically tunable detectors.

The ability to create optical materials with arbitrary index distributions would prove transformative for optics design and applications. However, current fabrication techniques for graded index (GRIN) materials rely on diffusion profiles and therefore are unable to realize arbitrary distribution GRIN design. Here, we demonstrate the laser direct writing of graded index structures in protein-based hydrogels using multiphoton lithography. We show index changes spanning a range of 10-2, which is comparable with laser densified glass and polymer systems. Further, we demonstrate the conversion of these written density variation structures into SiO2, opening up the possibility of transforming GRIN hydrogels to a wide range of material systems.

Ultra violet light emitting diodes (UV LEDs) face critical limitations in both the injection efficiency and the light extraction efficiency due to the resistive and absorbing p-type contact layers. In this work, we investigate the design and application of polarization engineered tunnel junctions for ultra-wide bandgap AlGaN (Al mole fraction >50%) materials towards highly efficient UV LEDs. We demonstrate that polarization-induced three dimensional charge is beneficial in reducing tunneling barriers especially for high composition AlGaN tunnel junctions. The design of graded tunnel junction structures could lead to low tunneling resistance below 10-3 Ω cm2 and low voltage consumption below 1 V (at 1 kA/cm2) for high composition AlGaN tunnel junctions. Experimental demonstration of 292 nm emission was achieved through non-equilibrium hole injection into wide bandgap materials with bandgap energy larger than 4.7 eV, and detailed modeling of tunnel junctions shows that they can be engineered to have low resistance and can enable efficient emitters in the UV-C wavelength range.

Narrow-bandgap semiconductors such as alloys of InAsAlSb and their heterostructures are considered promising candidates for next generation infrared photodetectors and devices. The prospect of actively tuning the spectral responsivity of these detectors at the pixel level is very appealing. In principle, this could be achieved with a tunable metasurface fabricated monolithically on the detector pixel. Here, we present first steps towards that goal using a complementary metasurface strongly coupled to an epsilon-near-zero (ENZ) mode operating in the long-wave region of the infrared spectrum. We fabricate such a coupled system using the same epitaxial layers used for infrared pixels in a focal plane array and demonstrate the existence of ENZ modes in high mobility layers of InAsSb. We confirm that the coupling strength between the ENZ mode and the metasurface depends on the ENZ layer thickness and demonstrate a transmission modulation on the order of 25%. We further show numerically the expected tunable spectral behavior of such coupled system under reverse and forward bias, which could be used in future electrically tunable detectors.

Deep Borehole Disposal (DBD) of high-level radioactive wastes has been considered an option for geological isolation for many years (Hess et al. 1957). Recent advances in drilling technology have decreased costs and increased reliability for large-diameter (i.e., ≥50 cm [19.7”]) boreholes to depths of several kilometers (Beswick 2008; Beswick et al. 2014). These advances have therefore also increased the feasibility of the DBD concept (Brady et al. 2009; Cornwall 2015), and the current field test design will demonstrate the DBD concept and these advances. The US Department of Energy (DOE) Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste (DOE 2013) specifically recommended developing a research and development plan for DBD. DOE sought input or expression of interest from States, local communities, individuals, private groups, academia, or any other stakeholders willing to host a Deep Borehole Field Test (DBFT). The DBFT includes drilling two boreholes nominally 200m [656’] apart to approximately 5 km [16,400’] total depth, in a region where crystalline basement is expected to begin at less than 2 km depth [6,560’]. The characterization borehole (CB) is the smaller-diameter borehole (i.e., 21.6 cm [8.5”] diameter at total depth), and will be drilled first. The geologic, hydrogeologic, geochemical, geomechanical and thermal testing will take place in the CB. The field test borehole (FTB) is the larger-diameter borehole (i.e., 43.2 cm [17”] diameter at total depth). Surface handling and borehole emplacement of test package will be demonstrated using the FTB to evaluate engineering feasibility and safety of disposal operations (SNL 2016).

Although increased availability of computational resources has enabled high-fidelity simulations (e.g., large eddy simulations) of turbulent flows, the Reynolds-Averaged Navier–Stokes (RANS) models are still the dominant tools in industrial applications. However, the predictive capabilities of RANS models are limited by large model-form discrepancies due to the Reynolds stress closure. Recently, a Physics-Informed Machine Learning (PIML) approach has been proposed to learn the functional form of Reynolds stress discrepancy in RANS simulations based on available data. It has been demonstrated that the learned discrepancy function can be used to improve Reynolds stresses in new flows where data are not available. However, due to a number of challenges, the improvements are only demonstrated in the Reynolds stress prediction but not in corresponding propagated quantities of interest (e.g., velocity field). In this work, we investigate the prediction performance on the velocity field by propagating the corrected Reynolds stresses in PIML approach. To enrich the input features, an integrity basis of invariants is implemented. The fully developed turbulent flow in a square duct is used as the test case. The discrepancy model is trained on flow fields from several Reynolds numbers and evaluated on a duct flow at a higher Reynolds number than any of the training cases. The predicted Reynolds stresses are propagated to velocity field via RANS equations. Numerical results show excellent predictive performances in both Reynolds stresses and their propagated velocities, demonstrating the merits of the PIML approach in predictive turbulence modeling.

A critical aspect of applying modern computational solution methods to complex multiphysics systems of relevance to nuclear reactor modeling, is the assessment of the predictive capability of specific proposed mathematical models. In this respect the understanding of numerical error, the sensitivity of the solution to parameters associated with input data, boundary condition uncertainty, and mathematical models is critical. Additionally, the ability to evaluate and or approximate the model efficiently, to allow development of a reasonable level of statistical diagnostics of the mathematical model and the physical system, is of central importance. In this study we report on initial efforts to apply integrated adjoint-based computational analysis and automatic differentiation tools to begin to address these issues. The study is carried out in the context of a Reynolds averaged Navier-Stokes approximation to turbulent fluid flow and heat transfer using a particular spatial discretization based on implicit fully-coupled stabilized FE methods. Initial results are presented that show the promise of these computational techniques in the context of nuclear reactor relevant prototype thermal-hydraulics problems.

For a projection-based reduced order model (ROM) of a fluid flow to be stable and accurate, the dynamics of the truncated subspace must be taken into account. This paper proposes an approach for stabilizing and enhancing projection-based fluid ROMs in which truncated modes are accounted for a priori via a minimal rotation of the projection subspace. Attention is focused on the full non-linear compressible Navier-Stokes equations in specific volume form as a step toward a more general formulation for problems with generic non-linearities. Unlike traditional approaches, no empirical turbulence modeling terms are required, and consistency between the ROM and the Navier-Stokes equation from which the ROM is derived is maintained. Mathematically, the approach is formulated as a trace minimization problem on the Stiefel manifold. The reproductive as well as predictive capabilities of the method are evaluated on several compressible flow problems, including a problem involving laminar flow over an airfoil with a high angle of attack, and a channel-driven cavity flow problem.

We will introduce a new framework called cyber zone defense (CZD) that treats malware like a black box: a process we can study solely based on its internal and external communication. We can reduce the impact of malware, without regard to its functionality or even existence, by limiting only these connections. In this paper, we propose two metrics for measuring CZD effectiveness and an illustrative simulation and a closed form mathematical model that predicts these statistics. The simulation is intuitive; it allows the analyst to provision arbitrary configurations and see how changes in topology affect the efficacy of the CZD. The model provides a mathematical verification for CZD and matches the results of the simulation well. These artifacts test the feasibility of CZD while deferring implementation details.

As cyber monitoring capabilities expand and data rates increase, cyber security analysts must filter through an increasing number of alerts in order to identify potential intrusions on the network. This process is often manual and time-consuming, which limits the number of alerts an analyst can process. This generation of a vast number of alerts without any kind of ranking or prioritization is often referred to as alert desensitization [1]. This is the phenomenon where competent analysts become so numbed by the barrage of false positives that they are unable to identify the true positives, leading to unfortunate breaches. Our goal is to alleviate alert desensitization by placing the most important alerts at the front of the queue. With less time and energy expended investigating false positives, critical alerts may not be overlooked allowing timely responses to potential breaches. This paper discusses the use of supervised machine learning to rank these cyber security alerts to ensure that an analyst's time and energy are focused on the most important alerts.

Nonlinear optical phenomena in nanostructured materials have been challenging our perceptions of nonlinear optical processes that have been explored since the invention of lasers. For example, the ability to control optical field confinement, enhancement, and scattering almost independently allows nonlinear frequency conversion efficiencies to be enhanced by many orders of magnitude compared to bulk materials. Also, the subwavelength length scale renders phase matching issues irrelevant. Compared with plasmonic nanostructures, dielectric resonator metamaterials show great promise for enhanced nonlinear optical processes due to their larger mode volumes. Here, we present, for the first time, resonantly enhanced second-harmonic generation (SHG) using gallium arsenide (GaAs) based dielectric metasurfaces. Using arrays of cylindrical resonators we observe SHG enhancement factors as large as 104 relative to unpatterned GaAs. At the magnetic dipole resonance, we measure an absolute nonlinear conversion efficiency of ∼2 × 10-5 with ∼3.4 GW/cm2 pump intensity. The polarization properties of the SHG reveal that both bulk and surface nonlinearities play important roles in the observed nonlinear process.

A major challenge facing the design and operation of next-step high-power steady-state fusion devices is to develop a viable divertor solution with order-of-magnitude increases in power handling capability relative to present experience, while having acceptable divertor target plate erosion and being compatible with maintaining good core plasma confinement. A new initiative has been launched on DIII-D to develop the scientific basis for design, installation, and operation of an advanced divertor to evaluate boundary plasma solutions applicable to next step fusion experiments beyond ITER. Developing the scientific basis for fusion reactor divertor solutions must necessarily follow three lines of research, which we plan to pursue in DIII-D: (1) Advance scientific understanding and predictive capability through development and comparison between state-of-the art computational models and enhanced measurements using targeted parametric scans; (2) Develop and validate key divertor design concepts and codes through innovative variations in physical structure and magnetic geometry; (3) Assess candidate materials, determining the implications for core plasma operation and control, and develop mitigation techniques for any deleterious effects, incorporating development of plasma-material interaction models. These efforts will lead to design, installation, and evaluation of an advanced divertor for DIII-D to enable highly dissipative divertor operation at core density (n e/n GW), neutral fueling and impurity influx most compatible with high performance plasma scenarios and reactor relevant plasma facing components (PFCs). This paper highlights the current progress and near-term strategies of boundary/PMI research on DIII-D.

Rewarding experiences are often well remembered, and such memory formation is known to be dependent on dopamine modulation of the neural substrates engaged in learning and memory; however, it is unknown how and where in the brain dopamine signals bias episodic memory toward preceding rather than subsequent events. Here we found that photostimulation of channelrhodopsin-2-expressing dopaminergic fibers in the dentate gyrus induced a long-term depression of cortical inputs, diminished theta oscillations, and impaired subsequent contextual learning. Computational modeling based on this dopamine modulation indicated an asymmetric association of events occurring before and after reward in memory tasks. In subsequent behavioral experiments, preexposure to a natural reward suppressed hippocampus-dependent memory formation, with an effective time window consistent with the duration of dopamine-induced changes of dentate activity. Overall, our results suggest a mechanism by which dopamine enables the hippocampus to encode memory with reduced interference from subsequent experience.

Terahertz quantum cascade lasers (QCLs) with a broadband gain medium could play an important role for sensing and spectroscopy since then distributed-feedback schemes could be utilized to produce laser arrays on a single semiconductor chip with wide spectral coverage. QCLs can be designed to emit at two different frequencies when biased with opposing electrical polarities. Here, terahertz QCLs with bidirectional operation are developed to achieve broadband lasing from the same semiconductor chip. A three-well design scheme with shallow-well GaAs/Al 0.10 Ga 0.90 As superlattices is developed to achieve high-temperature operation for bidirectional QCLs. It is shown that shallow-well heterostructures lead to optimal quantum-transport in the superlattice for bidirectional operation compared to the prevalent GaAs/Al 0.15 Ga 0.85 As material system. Broadband lasing in the frequency range of 3.1-3.7 THz is demonstrated for one QCL design, which achieves maximum operating temperatures of 147 K and 128 K respectively in opposing polarities. Dual-color lasing with large frequency separation is demonstrated for a second QCL, that emits at ∼3.7 THz and operates up to 121 K in one polarity, and at ∼2.7 THz up to 105 K in the opposing polarity. These are the highest operating temperatures achieved for broadband terahertz QCLs at the respective emission frequencies, and could lead to commercial development of broadband terahertz laser arrays.

The structure–property relationships of bulk CeO₂ and Ce₂O₃ have been investigated using AM05 and PBEsol exchange–correlation functionals within the frameworks of Hubbard-corrected density functional theory (DFT+U) and density functional perturbation theory (DFPT+U). Compared with conventional PBE+U, RPBE+U, PW91+U and LDA+U functionals, AM05+U and PBEsol+U describe experimental crystalline parameters and properties of CeO₂ and Ce₂O₃ with superior accuracy, especially when +U is chosen close to its value derived by the linear-response approach. Lastly, the present findings call for a reexamination of some of the problematic oxide materials featuring strong f- and d-electron correlation using AM05+U and PBEsol+U.

On Thursday, August 25, 2016, the ATDM L2 milestone review panel met with the milestone team to conduct a final assessment of the completeness and quality of the work performed. First and foremost, the panel would like to congratulate and commend the milestone team for a job well done. The team completed a significant body of high-quality work toward very ambitious goals. Additionally, their persistence in working through the technical challenges associated with evolving technology, the nontechnical challenges associated with integrating across multiple software development teams, and the many demands on their time speaks volumes about their commitment to delivering the best work possible to advance the ATDM program. The panel’s comments on the individual completion criteria appear in the last section of this memo.

Gypsum wallboard has been used for over 100 years as a barrier to the spread of fire in residential and commercial structures. The gypsum molecule, CaSO4·2H2O, provides two crystalline waters that are released upon heating providing an endothermic effect. Manufacturers have recognized that the source of the gypsum ore is a factor that affects all aspects of its performance; thus, it is hypothesized that the impurities present in the gypsum ore are the causes of the performance differences. Differential Thermal Analysis/Thermogravimetric Analysis (DTA/TGA) and X-ray Diffraction (XRD) were used to compare and characterize samples of gypsum ore representing sources of natural, synthetic from a Flue Gas Desulfurization process (FGD) and blends thereof. The hemihydrate phase of representative natural, FGD, and reagent grade calcium sulfate were rehydrated with distilled water and evaluated by DTA/TGA. Analysis of the data shows distinct areas of similarity separated by the conversion to anhydrite ∼250 °C. Compositional reconstructions based on DTA/TGA and XRD data were compared and although, the results were comparable, the DTA/TGA suggests thermally active compounds that were not detected by XRD. Anhydrite, silica and halite were reported by XRD but were not thermally reactive in the temperature range evaluated by DTA/TGA (ambient to 1050 °C). The presence of carbonate compounds (e.g., calcite and dolomite) were indicated by XRD and estimated from the thermal decomposition reaction ∼700 °C.

Here, observing geosynchronous satellites has numerous applications. Lighting conditions near the equinoxes routinely cause problems for traditional observations of sensors near the equator – the solar exclusion. We investigate using sensors on satellites (in polar and high- altitude orbits) to observe satellites that are in geosynchronous orbit. It is hoped that these satellite configurations will alleviate many of these problems. Assessing the orbit insertion and station-keeping requirements are important to understand. We summarize the literature to understand the relevant perturbing forces and assess the delta-v requirements.

Moving to lighter and less expensive battery chemistries compared to contemporary lithium-ion requires the control of energy storage mechanisms based on chemical transformations rather than intercalation. Lithium-sulfur (Li/S) has tremendous theoretical specific energy, but contemporary approaches to control this solution-mediated, precipitation-dissolution chemistry require large excesses of electrolyte to fully solubilize the polysulfide intermediates. Achieving reversible electrochemistry under lean electrolyte operation is the most promising path for Li/S to move beyond niche applications to potentially transformational performance. An emerging Li/S research area is the use of sparingly solvating electrolytes and the creation of design rules for discovering new electrolyte systems that fundamentally decouple electrolyte volume from sulfur and polysulfide reaction mechanism. This Perspective presents an outlook for sparingly solvating electrolytes as a key path forward for long-lived, high energy density Li/S batteries including an overview of this promising new concept and some strategies for accomplishing it.

Electrostatic modes of atomic force microscopy have shown to be non-destructive and relatively simple methods for imaging conductors embedded in insulating polymers. Here we use electrostatic force microscopy to image the dispersion of carbon nanotubes in a latex-based conductive composite, which brings forth features not observed in previously studied systems employing linear polymer films. A fixed-potential model of the probe-nanotube electrostatics is presented which in principle gives access to the conductive nanoparticle's depth and radius, and the polymer film dielectric constant. Comparing this model to the data results in nanotube depths that appear to be slightly above the film-air interface. This result suggests that water-mediated charge build-up at the film-air interface may be the source of electrostatic phase contrast in ambient conditions.

The final review for the FY16 ASC Computational Systems and Software Environment (CSSE) L2 Milestone #5676 was conducted on August 17, 2016 at Sandia National Laboratories in Albuquerque, New Mexico. The review panel unanimously agreed that the milestone has been successfully completed

This letter report provides a Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) well grading system based on the geomechanical simulation. The analyses described in this letter were used to evaluate the caverns’ geomechanical effect on wellbore integrity, which is an important component in the well integrity grading system recently developed by Roberts et al. [2015]. Using these analyses, the wellbores for caverns BC-17 and 20 are expected to be significantly impacted by cavern geomechanics, BC-18 and 19 are expected to be medium impacted; and the other caverns are expected to be less impacted.

Exascale studies project reliability challenges for future HPC systems. We present the Global View Resilience (GVR) system, a library for portable resilience. GVR begins with a subset of the Global Arrays interface, and adds new capabilities to create versions, name versions, and compute on version data. Applications can focus versioning where and when it is most productive, and customize for each application structure independently. This control is portable, and its embedding in application source makes it natural to express and easy to maintain. The ability to name multiple versions and “partially materialize” them efficiently makes ambitious forward-recovery based on “data slices” across versions or data structures both easy to express and efficient. Using several large applications (OpenMC, preconditioned conjugate gradient (PCG) solver, ddcMD, and Chombo), we evaluate the programming effort to add resilience. The required changes are small (< 2% lines of code (LOC)), localized and machine-independent, and perhaps most important, require no software architecture changes. We also measure the overhead of adding GVR versioning and show that overheads < 2% are generally achieved. This overhead suggests that GVR can be implemented in large-scale codes and support portable error recovery with modest investment and runtime impact. Our results are drawn from both IBM BG/Q and Cray XC30 experiments, demonstrating portability. We also present two case studies of flexible error recovery, illustrating how GVR can be used for multi-version rollback recovery, and several different forward-recovery schemes. GVR’s multi-version enables applications to survive latent errors (silent data corruption) with significant detection latency, and forward recovery can make that recovery extremely efficient. Lastly, our results suggest that GVR is scalable, portable, and efficient. GVR interfaces are flexible, supporting a variety of recovery schemes, and altogether GVR embodies a gentle-slope path to tolerate growing error rates in future extreme-scale systems.

The thermal conductivity of n- and p-type doped gallium nitride (GaN) epilayers having thicknesses of 3-4 μm was investigated using time domain thermoreflectance. Despite possessing carrier concentrations ranging across 3 decades (1015-1018cm-3), n-type layers exhibit a nearly constant thermal conductivity of 180 W/mK. The thermal conductivity of p-type epilayers, in contrast, reduces from 160 to 110 W/mK with increased doping. These trends - and their overall reduction relative to bulk - are explained leveraging established scattering models where it is shown that, while the decrease in p-type layers is partly due to the increased impurity levels evolving from its doping, size effects play a primary role in limiting the thermal conductivity of GaN layers tens of microns thick. Device layers, even of pristine quality, will therefore exhibit thermal conductivities less than the bulk value of 240 W/mK owing to their finite thickness.

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The crazing behavior of polymer nanocomposites formed by blending polymer grafted nanoparticles with an entangled polymer melt is studied by molecular dynamics simulations. We focus on the three key differences in the crazing behavior of a composite relative to the pure homopolymer matrix, namely, a lower yield stress, a smaller extension ratio, and a grafted chain length dependent failure stress. The yield behavior is found to be mostly controlled by the local nanoparticle-grafted polymer interfacial energy, with the grafted polymer-polymer matrix interfacial structure being of little to no relevance. Increasing the attraction between nanoparticle core and the grafted polymer inhibits void nucleation and leads to a higher yield stress. In the craze growth regime, the presence of "grafted chain" sections of ≈100 monomers alters the mechanical response of composite samples, giving rise to smaller extension ratios and higher drawing stresses than for the homopolymer matrix. The dominant failure mechanism of composite samples depends strongly on the length of the grafted chains, with disentanglement being the dominant mechanism for short chains, while bond breaking is the failure mode for chain lengths >10Ne, where Ne is the entanglement length.

World energy demand is projected to increase by more than a third by 2035 and with it the use of water to extract and process fuels and generate electricity. Management of this energy-water nexus requires a clear understanding of the inter-related demands of these resources as well as their regional distribution. Toward this need the fresh water consumed for energy production was mapped for almost 12 000 watersheds distributed across the 21-economies comprising the Asia-Pacific Economic Cooperation. Fresh water consumption was estimated for ten different sectors including thermoelectric and hydroelectric power; energy extraction including coal, oil, natural gas, uranium and unconventional oil/gas; energy processing including oil and biofuels; and biofuel feedstock irrigation. These measures of water consumption were put in context by drawing comparison with published measures of water risk. In total 791 watersheds (32%) of the 2511 watersheds where energy related water consumption occurred were also characterized by high to extreme water risk, these watersheds were designated as being at energy-water risk. For six economies watersheds at energy-water risk represented half or more of all basins where energy related water consumption occurred, while four additional economies exceeded 30%.

A physically-based form of the Mie–Grüneisen equation of state (EOS) is derived for calculating 1d planar shock temperatures, as well as hot spot temperature distributions from heterogeneous impact simulations. This form utilises a multi-term Einstein oscillator model for specific heat, and is completely algebraic in terms of temperature, volume, an integrating factor, and the cold curve energy. Moreover, any empirical relation for the reference pressure and energy may be substituted into the equations via the use of a generalised reference function. The complete EOS is then applied to calculations of the Hugoniot temperature and simulation of hydrodynamic pore collapse using data for the secondary explosive, hexanitrostilbene (HNS). From these results, it is shown that the choice of EOS is even more significant for determining hot spot temperature distributions than planar shock states. The complete EOS is also compared to an alternative derivation assuming that specific heat is a function of temperature alone, i.e. cv(T). Temperature discrepancies on the order of 100–600 K were observed corresponding to the shock pressures required to initiate HNS (near 10 GPa). Overall, the results of this work will improve confidence in temperature predictions. By adopting this EOS, future work may be able to assign physical meaning to other thermally sensitive constitutive model parameters necessary to predict the shock initiation and detonation of heterogeneous explosives.

Efficient management and coordination of distributed energy resources with advanced automation schemes requires accurate distribution system modeling and monitoring. Big data from smart meters and photovoltaic (PV) micro-inverters can be leveraged to calibrate existing utility models. This paper presents computationally efficient distribution system parameter estimation algorithms to improve the accuracy of existing utility feeder radial secondary circuit model parameters. The method is demonstrated using a real utility feeder model with advanced metering infrastructure (AMI) and PV micro-inverters, along with alternative parameter estimation approaches that can be used to improve secondary circuit models when limited measurement data is available. The parameter estimation accuracy is demonstrated for both a three-phase test circuit with typical secondary circuit topologies and single-phase secondary circuits in a real mixed-phase test system.

We describe here a method for modifying the bulk composition (pH, salinity, hardness) of fracturing fluids and overflushes to modify wettability and increase oil recovery from tight formations. Oil wetting of tight formations is usually controlled by adhesion to illite, kerogen, or both; adhesion to carbonate minerals may also play a role when clays are minor. Oil-illite adhesion is sensitive to salinity, dissolved divalent cation content, and pH. We measure adhesion between middle Bakken formation oil and core to verify a surface complexation model of reservoir wettability. The agreement between the model and experiments suggests that wettability trends in tight formations can be quantitatively predicted and that the bulk compositions of fracturing fluid and overflush compositions might be individually tailored to increase oil recovery.

Leaner lifted-flame combustion (LLFC) is a mixing-controlled combustion strategy for compression-ignition (CI) engines that does not produce soot because the equivalence ratio at the lift-off length is less than or equal to approximately two. In addition to completely preventing soot formation, LLFC can simultaneously control emissions of nitrogen oxides because it is tolerant to the use of exhaust-gas recirculation for lowering in-cylinder temperatures. Experiments were conducted in a heavy-duty CI engine that has been modified to provide optical access to the combustion chamber, to study whether LLFC is facilitated by an oxygenated fuel blend (T50) comprising a 1:1 mixture by volume of tri-propylene glycol mono-methyl ether with an ultra-low-sulfur #2 diesel emissions-certification fuel (CFA). Results from the T50 experiments are compared against baseline results using the CFA fuel without the oxygenate. Experimental measurements include crank-angle-resolved natural luminosity and chemiluminescence imaging. Dilution effects were studied by adding nitrogen and carbon dioxide to the intake charge. Initial experiments with a 2-hole fuel-injector tip achieved LLFC at low loads with the T50 fuel, and elucidated the most important operating parameters necessary to achieve LLFC. The strategy was then extended to more moderate loads by employing a 6-hole injector tip, where lowering the intake-manifold temperature, reducing the coolant temperature, and retarding the start-ofcombustion timing resulted in sustained LLFC at both 21% and 16% intake-oxygen mole fractions at loads greater than 5 bar gross indicated mean effective pressure. In contrast to the results with T50, LLFC was not achieved under any of the test conditions with CFA.

Neutron sensing is critical in civilian, military, industrial, biological, medical, basic research, and environmental applications. Conventional neutron sensors are limited by size, weight, cost, portability, and helium supply. Here the microfabrication of Gd conversion material-based heterojunction diodes is described for detecting thermal neutrons using electrical signals produced by internal conversion electrons (ICE). Films with negligible stress were produced at the tensile-compressive crossover point, enabling Gd coatings of any desired thickness by controlling the radiofrequency sputtering power and using the zero-point near p(Ar) of 50 mTorr at 100 W. Post-deposition Gd oxidation-induced spallation was eliminated by growing a residual stress-free 50 nm neodymium-doped aluminum cap layer atop Gd. Resultant coatings were stable for at least six years demonstrating excellent product shelf life. Depositing Gd on the diode surface eliminated air gap, leading to improved efficiency and facilitating monolithic microfabrication. The conversion electron spectrum was dominated by ICE with energies of 72, 132, and 174 keV. Results are reported on neutron reflection and moderation by polyethylene for enhanced sensitivity and γ- and X-ray elimination for improved specificity. Optimal Gd thickness was 10.4 μm with 300 μm thick partially depleted diode of 300 mm2 active surface area. Fast detection within 10 minutes at a neutron source-to-diode distance of 11.7 cm was achieved using this configuration. All ICE energies along with γ-ray and Kα X-ray were modeled to emphasize correlations between experiment and theory and to calculate efficiencies. Semiconductor thermal neutron detectors offer advantages for field-sensing of radioactive neutron sources.

The R&D program from the DOE Used Fuel Disposition Campaign (UFDC) has documented key advances in coupled Thermal-Hydrological-Mechanical-Chemical (THMC) modeling of clay to simulate its complex dynamic behavior in response to thermal and hydrochemical feedbacks. These efforts have been harnessed to assess the isolation performance of heatgenerating nuclear waste in a deep geological repository in clay/shale/argillaceous rock formations. This report describes the ongoing disposal R&D efforts on the advancement and refinement of coupled THMC process models, hydrothermal experiments on barrier clay interactions, used fuel and canister material degradation, thermodynamic database development, and reactive transport modeling of the near-field under non-isothermal conditions. These play an important role to the evaluation of sacrificial zones as part of the EBS exposure to thermallydriven chemical and transport processes. Thermal inducement of chemical interactions at EBS domains enhances mineral dissolution/precipitation but also generates mineralogical changes that result in mineral H2O uptake/removal (hydration/dehydration reactions). These processes can result in volume changes that can affect the interface / bulk phase porosities and the mechanical (stress) state of the bentonite barrier. Characterization studies on bentonite barrier samples from the FEBEX-DP international activity have provided important insight on clay barrier microstructures (e.g., microcracks) and interactions at EBS interfaces. Enhancements to the used fuel degradation model outlines the need to include the effects of canister corrosion due the strong influence of H₂ generation on the source term.

The paper is intended to define a benchmark problem related to groundwater flow and natural tracer transport using observations of discharge and isotopic tracers in fractured, crystalline rock. Three numerical simulators: Flow123d, OpenGeoSys, and PFLOTRAN are compared. The data utilized in the project were collected in a water-supply tunnel in granite of the Jizera Mountains, Bedřichov, Czech Republic. The problem configuration combines subdomains of different dimensions, 3D continuum for hard-rock blocks or matrix and 2D features for fractures or fault zones, together with realistic boundary conditions for tunnel-controlled drainage. Steady-state and transient flow and a pulse injection tracer transport problem are solved. The results confirm mostly consistent behavior of the codes. Both the codes Flow123d and OpenGeoSys with 3D–2D coupling implemented differ by several percent in most cases, which is appropriate to, e.g., effects of discrete unknown placing in the mesh. Some of the PFLOTRAN results differ more, which can be explained by effects of the dispersion tensor evaluation scheme and of the numerical diffusion. The phenomenon can get stronger with fracture/matrix coupling and with parameter magnitude contrasts. Although the study was not aimed on inverse solution, the models were fit to the measured data approximately, demonstrating the intended real-case relevance of the benchmark.

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 ad- dressed 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 describe 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.

This work studies the microstructural evolution of nanocrystalline (<1 µm) barium titanate (BaTiO3), and presents high pressure in field-assisted sintering (FAST) as a robust methodology to obtain >100 nm BaTiO3 compacts. Using FAST, two commercial ~50 nm powders were consolidated into compacts of varying densities and grain sizes. Microstructural inhomogeneities were investigated for each case, and an interpretation is developed using a modified Monte Carlo Potts (MCP) simulation. Two recurrent microstructural inhomogeneities are highlighted, heterogeneous grain growth and low-density regions, both ubiqutously present in all samples to varying degrees. In the worst cases, HGG presents an area coverage of 52%. Because HGG is sporadic but homogenous throughout a sample, the catalyst (e.g., the local segregation of species) must be, correspondingly, distributed in a homogenous manner. MCP demonstrates that in such a case, a large distance between nucleating abnormal grains is required—otherwise abnormal grains prematurely impinge on each other, and their size is not distinguishable from that of normal grains. Compacts sintered with a pressure of 300 MPa and temperatures of 900 °C, were 99.5% dense and had a grain size of 90±24 nm. These are unprecedented results for commercial BaTiO3 powders or any starting powder of 50 nm particle size—other authors have used 16 nm lab-produced powder to obtain similar results.

As an optimum energy-absorbing material system, polymeric foams are needed to dissipate the kinetic energy of an impact, while maintaining the impact force transferred to the protected object at a low level. Therefore, it is crucial to accurately characterize the load bearing and energy dissipation performance of foams at high strain rate loading conditions. There are certain challenges faced in the accurate measurement of the deformation response of foams due to their low mechanical impedance. In the present work, a non-parametric method is successfully implemented to enable the accurate assessment of the compressive constitutive response of rigid polymeric foams subjected to impact loading conditions. The method is based on stereovision high speed photography in conjunction with 3D digital image correlation, and allows for accurate evaluation of inertia stresses developed within the specimen during deformation time. Full-field distributions of stress, strain and strain rate are used to extract the local constitutive response of the material at any given location along the specimen axis. In addition, the effective energy absorbed by the material is calculated. Finally, results obtained from the proposed non-parametric analysis are compared with data obtained from conventional test procedures.

We describe the study we have undertaken to evaluate the effect of component tolerances in obtaining a voltage output flat top for a linear transformer driver (LTD) cavity containing 3rd and 5th harmonic bricks [A. A. Kim et al., in Proc. IEEE Pulsed Power and Plasma Science PPPS2013 (San Francisco, California, USA, 2013), pp. 1354-1356.] and for 30 cavity voltage adder. Our goal was to define the necessary component value precision in order to obtain a voltage output flat top with no more than ±0.5% amplitude variation.

The current outbreak of Ebola virus disease (EVD) in West Africa has infected more than 28,000 people, killed more than 11,000 and disrupted social life. We studied retrospectively the clinical presentation and risk factors for fatal outcome among the 31 Ebola virus (EBV) positive patients admitted to the Ebola Treatment Center (ETC) in Moyamba District, Sierra Leone. We found a higher rate of bleeding manifestations than reported elsewhere during the current outbreak. Significant predictors for fatal outcome were shorter time from onset to admission, male sex, high viral load on initial lab test, severe pain, diarrhea, bloody stools, and development of other bleeding manifestations during hospital admission. Awareness of risk factors for fatal outcome could be used to identify patients in need of more intensive medical support. The lack of fever in as much as a third of EVD cases may have implications for temperature screening practices and case definitions.

Newton–Krylov solvers for ocean tracers have the potential to greatly decrease the computational costs of spinning up deep-ocean tracers, which can take several thousand model years to reach equilibrium with surface processes. One version of the algorithm uses offline tracer transport matrices to simulate an annual cycle of tracer concentrations and applies Newton's method to find concentrations that are periodic in time. Here we present the impact of time-averaging the transport matrices on the equilibrium values of an ideal-age tracer. We compared annually-averaged, monthly-averaged, and 5-day-averaged transport matrices to an online simulation using the ocean component of the Community Earth System Model (CESM) with a nominal horizontal resolution of 1° × 1° and 60 vertical levels. We found that increasing the time resolution of the offline transport model reduced a low age bias from 12% for the annually-averaged transport matrices, to 4% for the monthly-averaged transport matrices, and to less than 2% for the transport matrices constructed from 5-day averages. The largest differences were in areas with strong seasonal changes in the circulation, such as the Northern Indian Ocean. For many applications the relatively small bias obtained using the offline model makes the offline approach attractive because it uses significantly less computer resources and is simpler to set up and run.

Sandia National Laboratories (SNL) is a multiprogram laboratory managed and operated by Sandia Corporation (Sandia), a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA) under contract DE-AC04-94AL85000. The DOE/NNSA Sandia Field Office administers the contract and oversees contractor operations at the SNL, Tonopah Test Range (SNL/TTR) in Nevada and the SNL, Kaua‘i Test Facility (SNL/KTF) in Hawai‘i. Sandia manages and conducts operations at SNL/TTR in support of the DOE/NNSA’s Weapons Ordnance Program and has operated the site since 1957. Navarro Research and Engineering subcontracts with Sandia to administer most of the environmental programs at SNL/TTR. The DOE/NNSA/Nevada Field Office retains responsibility for cleanup and management of SNL/TTR Environmental Restoration sites. Sandia operates SNL/KTF as a rocket preparation launching and tracking facility. This Annual Site Environmental Report (ASER) summarizes data and the compliance status of Sandia’s sustainability, environmental protection, and monitoring programs at SNL/TTR and SNL/KTF during calendar year 2015. Major environmental programs include air quality, water quality, groundwater protection, terrestrial surveillance, waste management, pollution prevention, environmental restoration, oil and chemical spill prevention, and implementation of the National Environmental Policy Act. Sandia is responsible only for those environmental program activities related to its operations. This ASER is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety, and Health Reporting.

SANSMIC is solution mining software that was developed by SNL and is utilized in in Sandia’s role as geotechnical advisor to the US DOE SPR for salt cavern development and maintenance. Four SANSMIC leach modes – withdrawal, direct, reverse and leach-fill – can be modeled. This report updates and expands the original 1983 documentation. It provides execution instructions, input data descriptions, input file format, output file descriptions and an example problem.

Streamers are a type of ionization wave occurring during the early time phase of a gas discharge. They are typically launched when the evolving space charge of an electron avalanche reaches a certain critical level, beyond which the field of the space charge itself is sufficient to drive further evolution of the ionization process. One of the most common ways to model streamers is known as a 1.5D model where the field of a uniformly charged set of discs of chosen radius is evaluated along the cylinder axis. This field drives a one-dimensional kinetic ionization process, which results in the nonlinear evolution of the streamer. This model is efficient, but has the drawback of fixing the radius and requiring it as an input parameter. Previously, we tried to extend the 1.5D model to include evolution of its radius by developing a two-step process of axial and radial expansion but we encountered stability issues with the model that we thought could have been due to decoupling the two steps. In this report we introduce a new formulation of a streamer model that includes radial expansion. The goal is to take radial moments of the starting axisymmetric fluid equations and thereby include the radial evolution of the streamer naturally and self-consistently from the beginning. We first develop the fluid model moments without electron attachment. We review the calculation of the electric fields required for the model and investigate approximations to improve computational efficiency. We discuss the code implementation of the model and finally, we add attachment to allow the treatment of electronegative gases.

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Sodium as a heat transfer fluid (HTF) can achieve temperatures above 700°C to improve power cycle performance for reducing large infrastructure costs of high-temperature systems. Current concentrating solar power (CSP) sensible HTF’s (e.g. air, salts) have poor thermal conductivity, and thus low heat transfer capabilities, requiring a large receiver. The high thermal conductivity of sodium has demonstrated high heat transfer rates on dish and towers systems, which allow a reduction in receiver area by a factor of two to four, reducing re-radiation and convection losses and cost by a similar factor. Sodium produces saturated vapor at pressures suitable for transport starting at 600°C and reaches one atmosphere at 870°C, providing a wide range of suitable latent operating conditions that match proposed high temperature, isothermal input power cycles. This advantage could increase the receiver and system efficiency while lowering the cost of CSP tower systems. Although there are a number of desirable thermal performance advantages associated with sodium, its propensity to rapidly oxidize presents safety challenges. This investigation presents a literature review that captures historical operations/handling lessons for advanced sodium systems, and the current state-of-knowledge related to sodium combustion behavior. Technical and operational solutions addressing sodium safety and applications in CSP will be discussed, including unique safety hazards and advantages using latent sodium. Operation and maintenance experience from the nuclear industry with sensible and latent systems will also be discussed in the context of safety challenges and risk mitigation solutions.

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This document presents the revised Technology Performance Level (TPL) assessment methodology. There are three parts to this revised methodology 1) the Stakeholder Needs and Assessment Guidance (this document), 2) the Technical Submission form, 3) the TPL scoring spreadsheet. The TPL assessment is designed to give a technology neutral or agnostic assessment of any wave energy converter technology. The focus of the TPL is on the performance of the technology in meeting the customer’s needs. The original TPL is described in [1, 2] and those references also detail the critical differences in the nature of the TPL when compared to the more widely used technology readiness level (TRL). (Wave energy TRL is described in [3]). The revised TPL is particularly intended to be useful to investors and also to assist technology developers to conduct comprehensive assessments in a way that is meaningful and attractive to investors. The revised TPL assessment methodology has been derived through a structured Systems Engineering approach. This was a formal process which involved analyzing customer and stakeholder needs through the discipline of Systems Engineering. The results of the process confirmed the high level of completeness of the original methodology presented in [1] (as used in the Wave Energy Prize judging) and now add a significantly increased level of detail in the assessment and an improved more investment focused structure. The revised TPL also incorporates the feedback of the Wave Energy Prize judges.

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Three different ways of combining scores are used in the revised formulation. These are arithmetic mean, geometric mean and multiplication with normalisation. Arithmetic mean is used when combining scores that measure similar attributes, e.g. used for combining costs. The arithmetic mean has the property that it is similar to a logical OR, e.g. when combining costs it does not matter what the individual costs are only what the combined cost is. Geometric mean and Multiplication are used when combining scores that measure disparate attributes. Multiplication is similar to a logical AND, it is used to combine ‘must haves.’ As a result, this method is more punitive than the geometric mean; to get a good score in the combined result it is necessary to have a good score in ALL of the inputs. e.g. the different types of survivability are ‘must haves.’ On balance, the revised TPL is probably less punitive than the previous spreadsheet, multiplication is used sparingly as a method of combining scores. This is in line with the feedback of the Wave Energy Prize judges.

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Commonly used performance models, such as PVsyst, Sandia Array Performance Model (SAPM), and PV LIB, treat the PV array as being constructed of identical modules. Each of the models attempts to account for mismatch losses by applying a simple percent reduction factor to the overall estimated power. The present work attempted to reduce uncertainty of mismatch losses by determining a representative set of performance coefficients for the SAPM that were developed from a characterization of a sample of modules. This approach was compared with current practice, where only a single module’s thermal and electrical properties are testing. However, the results indicate that minimal to no improvements in model predictions were achieved.

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In this study, we investigate a semiconductor quantum dot as a microscopic analog of a basic optomechanical setup. We show that optomechanical features can be reproduced by the solid-state platform, arising from parallels of the underlying interaction processes, which in the optomechanical case is the radiation pressure coupling and in the semiconductor case the electron–phonon coupling. We discuss bistabilities, lasing, and phonon damping, and recover the same qualitative behaviors for the semiconductor and the optomechanical cases expected for low driving strengths. However, in contrast to the optomechanical case, distinct signatures of higher order processes arise in the semiconductor model.

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A wide range of machine learning problems, including astronomical inference about galaxy clusters, scene classification, parametric statistical inference, and predictions of public opinion, can be well-modeled as learning a function on (samples from) distributions. This project explores problems in learning such functions via kernel methods, particularly for large-scale problems. When learning from large numbers of distributions, the computation of typical methods scales between quadratically and cubically, and so they are not amenable to large datasets. We investigate the approach of approximate embeddings into Euclidean spaces such that inner products in the embedding space approximate kernel values between the source distributions. We first improve the understanding of the workhorse methods of random Fourier features: we show that of the two approaches in common usage, one is strictly superior. We then present a new embedding for a class of information-theoretic distribution distances, and evaluate it and existing embeddings on several real-world applications.

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The next two Advanced Technology platforms for the ASC program will feature complex memory hierarchies – in the Trinity supercomputer being deployed in 2016, Intel’s Knights Landing processors will feature 16GB of on-package, high-bandwidth memory, combined with a larger capacity DDR4 memory and in 2018, the Sierra machine deployed at Lawrence Livermore National Laboratory will feature powerful compute nodes containing POWER9 processors with large capacity memories and an array of coherent GPU accelerators also with high bandwidth memories.

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The 2015-2016 Aliso Canyon/Porter Ranch natural gas well blowout emitted approximately 100,000 tonnes of natural gas (mostly methane, CH₄) over four months. The blowout impacted thousands of nearby residents, who were displaced from their homes. The high visibility of the event has led to increased scrutiny of the safety of natural gas storage at the Aliso Canyon facility, as well as broader concern for natural gas storage integrity throughout the country. This report presents the findings of the DOE National Laboratories Well Integrity Work Group efforts in the four tasks. In addition to documenting the work of the Work Group, this report presents high priority recommendations to improve well integrity and reduce the likelihood and consequences of subsurface natural gas leaks.

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