Publications

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The National Nuclear Security Agency (NNSA) created a Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA’s enduring technical workforce at the laboratories and production plants and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new program in early FY17 focused on Tribal Colleges and Universities (TCUs). The following report summarizes the project focus and status update during this reporting period.

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This report describes data collection and analysis of solar photovoltaic (PV) equipment events, which consist of faults and fa ilures that occur during the normal operation of a distributed PV system or PV power plant. We present summary statistics from locations w here maintenance data is being collected at various intervals, as well as reliability statistics gathered from that da ta, consisting of fault/failure distributions and repair distributions for a wide range of PV equipment types.

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This memo summarizes the aerodynamic drag scoping work done for Goodyear in early FY18. The work is to evaluate the feasibility of using Sierra/Low-Mach (Fuego) for drag predictions of rolling tires, particularly focused on the effects of tire features such as lettering, sidewall geometry, rim geometry, and interaction with the vehicle body. The work is broken into two parts. Part 1 consisted of investigation of a canonical validation problem (turbulent flow over a cylinder) using existing tools with different meshes and turbulence models. Part 2 involved calculating drag differences over plate geometries with simple features (ridges and grooves) defined by Goodyear of approximately the size of interest for a tire. The results of part 1 show the level of noise to be expected in a drag calculation and highlight the sensitivity of absolute predictions to model parameters such as mesh size and turbulence model. There is 20-30% noise in the experimental measurements on the canonical cylinder problem, and a similar level of variation between different meshes and turbulence models. Part 2 shows that there is a notable difference in the predicted drag on the sample plate geometries, however, the computational cost of extending the LES model to a full tire would be significant. This cost could be reduced by implementation of more sophisticated wall and turbulence models (e.g. detached eddy simulations - DES) and by focusing the mesh refinement on feature subsets with the goal of comparing configurations rather than absolute predictivity for the whole tire.

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Wind applications require the ability to simulate rotating blades. To support this use-case, a novel design-order sliding mesh algorithm has been developed and deployed. The hybrid method combines the control volume finite element methodology (CVFEM) with concepts found within a discontinuous Galerkin (DG) finite element method (FEM) to manage a sliding mesh. The method has been demonstrated to be design-order for the tested polynomial basis (P=1 and P=2) and has been deployed to provide production simulation capability for a Vestas V27 (225 kW) wind turbine. Other stationary and canonical rotating ow simulations are also presented. As the majority of wind-energy applications are driving extensive usage of hybrid meshes, a foundational study that outlines near-wall numerical behavior for a variety of element topologies is presented. Results indicate that the proposed nonlinear stabilization operator (NSO) is an effective stabilization methodology to control Gibbs phenomena at large cell Peclet numbers. The study also provides practical mesh resolution guidelines for future analysis efforts. Application-driven performance and algorithmic improvements have been carried out to increase robustness of the scheme on hybrid production wind energy meshes. Specifically, the Kokkos-based Nalu Kernel construct outlined in the FY17/Q4 ExaWind milestone has been transitioned to the hybrid mesh regime. This code base is exercised within a full V27 production run. Simulation timings for parallel search and custom ghosting are presented. As the low-Mach application space requires implicit matrix solves, the cost of matrix reinitialization has been evaluated on a variety of production meshes. Results indicate that at low element counts, i.e., fewer than 100 million elements, matrix graph initialization and preconditioner setup times are small. However, as mesh sizes increase, e.g., 500 million elements, simulation time associated with \setup-up" costs can increase to nearly 50% of overall simulation time when using the full Tpetra solver stack and nearly 35% when using a mixed Tpetra- Hypre-based solver stack. The report also highlights the project achievement of surpassing the 1 billion element mesh scale for a production V27 hybrid mesh. A detailed timing breakdown is presented that again suggests work to be done in the setup events associated with the linear system. In order to mitigate these initialization costs, several application paths have been explored, all of which are designed to reduce the frequency of matrix reinitialization. Methods such as removing Jacobian entries on the dynamic matrix columns (in concert with increased inner equation iterations), and lagging of Jacobian entries have reduced setup times at the cost of numerical stability. Artificially increasing, or bloating, the matrix stencil to ensure that full Jacobians are included is developed with results suggesting that this methodology is useful in decreasing reinitialization events without loss of matrix contributions. With the above foundational advances in computational capability, the project is well positioned to begin scientific inquiry on a variety of wind-farm physics such as turbine/turbine wake interactions.

This memo concerns calibration of an elastic-plastic J₂ material model for Ti-6Al-4V (grade 5) alloy based on tensile uniaxial stress-strain data obtained in the laboratory. In addition, tension tests on notched specimens provided data to calibrate two ductile failure models: Johnson-Cook and Wellman's tearing parameter. The tests were conducted by Kim Haulen- beek and Dave Johnson (1528) in the Structural Mechanics Laboratory (SML) during late March and early April, 2017. The SML EWP number was 4162. The stock material was a TIMETALR® 6-4 Titanium billet with 9 in. by 9 in. square section and length of 137 in. The product description indicates that it was a forging delivered in annealed condition (2 hours @ 1300oF, AC at the mill). The tensile mechanical properties reported in the material certi cation are given in Table 1, where σ_o represents the 0.2% strain offset yield stress, σ_u the ultimate stress, ε_f the elongation at failure and R.A. the reduction in area.

The objective of the work presented here arose from abnormal, drop scenarios and specifically the question of how the accelerations and accumulation of plastic strains of internal components could be a ected by the material properties of the external structure. In some scenarios, the impact loads can induce cyclic motion of the internal components. Therefore, a second objective was to explore di erences that could be expected when simulations are conducted using isotropic hardening vs. kinematic hardening plasticity models. The simplest model that can be used to investigate the objectives above is a two-degree-offreedom mass/spring model where the springs exhibit elastic-plastic behavior. The purpose of this memo is to develop such model and present a few results that address the objectives.

During calendar year 2017, Sandia National Laboratories (SNL) made strides towards developing an open portable design platform rich in highperformance computing (HPC) enabled modeling, analysis and synthesis tools. The main focus was to lay the foundations of the core interfaces that will enable plug-n-play insertion of synthesis optimization technologies in the areas of modeling, analysis and synthesis.

The purpose of the work presented in this memo was to calibrate the Sierra material model Multilinear Elastic-Plastic Hardening Model with Failure (MLEP-Fail) for 1/8 inch thick cast plate of 17-4 steel. The calibration approach is essentially the same as that recently used in a previous memo using data from smooth and notched tensile specimens. The notched specimens were manufactured with three notch radii R = 1=8, 1/32 and 1/64 inches. The dimensions of the smooth and notched specimens are given in the prints in Appendix A. Two cast plates, Plate 3 and Plate 4, with nominally identical properties were considered.

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The 2017 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 19 to July 28, 2017. NOMAD seeks to bring together participants with diverse technical backgrounds to work in small teams to utilize an interactive approach to cultivate new ideas and approaches in engineering . NOMAD provides an opportunity for researchers - especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 17 students from around the world came to Albuquerque, New Mexico to participate in the six - week long program held at the University of New Mexico campus. The students collaborated on one of six research projects that were developed by various mentors from Sandia National Laboratories, academia, and other government laboratories. In addition to the research activities, the students attended weekly technical seminars, toured the National Museum of Nuclear Science & History, and socialized at various off - hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation o n their research findings that was broadcast via Skype. Many of the research discoveries made at NOMAD are published as proceedings at technical conference s and have direct alignment with the critical mission work performed at Sandia.

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems involving multiple time-dependent failure modes are developed. The following topics are described: (i) defining properties for WLs and SLs, (ii) background on cumulative distribution functions (CDFs) for link failure time, link property value at link failure, and time at which LOAS occurs, (iii) CDFs for failure time margins defined by (time at which SL system fails) – (time at which WL system fails), (iv) CDFs for SL system property values at LOAS, (v) CDFs for WL/SL property value margins defined by (property value at which SL system fails) – (property value at which WL system fails), and (vi) CDFs for SL property value margins defined by (property value of failing SL at time of SL system failure) – (property value of this SL at time of WL system failure). Included in this presentation is a demonstration of a verification strategy based on defining and approximating the indicated margin results with (i) procedures based on formal integral representations and associated quadrature approximations and (ii) procedures based on algorithms for sampling-based approximations.

Probability of loss of assured safety (PLOAS) is modeled for weak link (WL)/strong link (SL) systems in which one or more WLs or SLs could potentially degrade into a precursor condition to link failure that will be followed by an actual failure after some amount of elapsed time. The following topics are considered: (i) Definition of precursor occurrence time cumulative distribution functions (CDFs) for individual WLs and SLs, (ii) Formal representation of PLOAS with constant delay times, (iii) Approximation and illustration of PLOAS with constant delay times, (iv) Formal representation of PLOAS with aleatory uncertainty in delay times, (v) Approximation and illustration of PLOAS with aleatory uncertainty in delay times, (vi) Formal representation of PLOAS with delay times defined by functions of link properties at occurrence times for failure precursors, (vii) Approximation and illustration of PLOAS with delay times defined by functions of link properties at occurrence times for failure precursors, and (viii) Procedures for the verification of PLOAS calculations for the three indicated definitions of delayed link failure.

Representations are developed and illustrated for the distribution of link property values at the time of link failure in the presence of aleatory uncertainty in link properties. The following topics are considered: (i) defining properties for weak links and strong links, (ii) cumulative distribution functions (CDFs) for link failure time, (iii) integral-based derivation of CDFs for link property at time of link failure, (iv) sampling-based approximation of CDFs for link property at time of link failure, (v) verification of integral-based and sampling-based determinations of CDFs for link property at time of link failure, (vi) distributions of link properties conditional on time of link failure, and (vii) equivalence of two different integral-based derivations of CDFs for link property at time of link failure.

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CTH is a Eulerian code developed at Sandia National Laboratories capable of modeling the hydrodynamic response of explosives, liquids, gases, and solids. The code solves complex multi-dimensional problems characterized by large deformations and strong shocks that are composed of various material configurations. CTH includes models for material strength, fracture, porosity, and high explosive detonation and initiation. The code is an acronym for a complex series of names relating to its origin. A full explanation can be seen in Appendix A. The software breaks penetration simulations into millions of grid-like “cells”. As a modeled projectile impacts and penetrates a target, progressively smaller blocks of cells are placed around the projectile, which show in detail deformations and breakups. Additionally, the code is uniquely suited to modeling blunt impact and blast loading leading to human body injury.

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A magnetically active Fe3O4/poly(ethylene oxide)-block-poly(butadiene) (PEO-b-PBD) nanocomposite is formed by the encapsulation of magnetite nanoparticles with a short-chain amphiphilic block copolymer. This material is then incorporated into the self-assembly of higher order polymer architectures, along with an organic pigment, to yield biosynthetic, bifunctional optical and magnetically active Fe3O4/bacteriochlorophyll c/PEO-b-PBD polymeric chlorosomes.

The purpose of the ART Energy Conversion (EC) Project is to provide solutions to convert the heat from an advanced reactor to useful products that support commercial application of the reactor designs.

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In random vibration environments, sinusoidal line noise may appear in the vibration signal and can affect analysis of the resulting data. We studied two methods which remove stationary sine tones from random noise: a matrix inversion algorithm and a chirp-z transform algorithm. In addition, we developed new methods to determine the frequency of the tonal noise. The results show that both of the removal methods can eliminate sine tones in prefabricated random vibration data when the sine-to-random ratio is at least 0.25. For smaller ratios down to 0.02 only the matrix inversion technique can remove the tones, but the metrics to evaluate its effectiveness also degrade. We also found that using fast Fourier transforms best identified the tonal noise, and determined that band-pass-filtering the signals prior to the process improved sine removal. When applied to actual vibration test data, the methods were not as effective at removing harmonic tones, which we believe to be a result of mixed-phase sinusoidal noise.

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Continued progress in computing has augmented the quest for higher performance with a new quest for higher energy efficiency. This has led to the re-emergence of Processing-In-Memory (PIM) ar- chitectures that offer higher density and performance with some boost in energy efficiency. Past PIM work either integrated a standard CPU with a conventional DRAM to improve the CPU- memory link, or used a bit-level processor with Single Instruction Multiple Data (SIMD) control, but neither matched the energy consumption of the memory to the computation. We originally proposed to develop a new architecture derived from PIM that more effectively addressed energy efficiency for high performance scientific, data analytics, and neuromorphic applications. We also originally planned to implement a von Neumann architecture with arithmetic/logic units (ALUs) that matched the power consumption of an advanced storage array to maximize energy efficiency. Implementing this architecture in storage was our original idea, since by augmenting storage (in- stead of memory), the system could address both in-memory computation and applications that accessed larger data sets directly from storage, hence Processing-in-Memory-and-Storage (PIMS). However, as our research matured, we discovered several things that changed our original direc- tion, the most important being that a PIM that implements a standard von Neumann-type archi- tecture results in significant energy efficiency improvement, but only about a O(10) performance improvement. In addition to this, the emergence of new memory technologies moved us to propos- ing a non-von Neumann architecture, called Superstrider, implemented not in storage, but in a new DRAM technology called High Bandwidth Memory (HBM). HBM is a stacked DRAM tech- nology that includes a logic layer where an architecture such as Superstrider could potentially be implemented.

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This paper discusses the broad use of rotational kinetic energy stored in wind turbine rotors to supply services to the electrical power grid. The grid services are discussed in terms of zero-net-energy, which do not require a reduction in power output via pitch control (spill), but neither do they preclude doing so. The services discussed include zero-net-energy regulation, transient and small signal stability, and other frequency management services. The delivery of this energy requires a trade-off between the frequency and amplitude of power modulation and is limited, in some cases, by equipment ratings and the unresearched long-term mechanical effects on the turbine. As wind displaces synchronous generation, the grid's inertial storage is being reduced, but the amount of accessible kinetic energy in a wind turbine at rated speed is approximately 6 times greater than that of a generator with only a 0.12% loss in efficiency and 75 times greater at 10% loss. The potential flexibility of the wind's kinetic storage is also high. However, the true cost of providing grid services using wind turbines, which includes a potential increase in operations and maintenance costs, have not been compared to the value of the services themselves.

This report documents the use of wind turbine inertial energy for the supply of two specific electric power grid services; system balancing and real power modulation to improve grid stability. Each service is developed to require zero net energy consumption. Grid stability was accomplished by modulating the real power output of the wind turbine at a frequency and phase associated with wide-area modes. System balancing was conducted using a grid frequency signal that was high-pass filtered to ensure zero net energy. Both services used Phasor Measurement Units (PMUs) as their primary source of system data in a feedforward control (for system balancing) and feedback control (for system stability).

Shock wave interactions with defects, such as pores, are known to play a key role in the chemical initiation of energetic materials. The shock response of hexanitrostilbene is studied through a combination of large-scale reactive molecular dynamics and mesoscale hydrodynamic simulations. In order to extend our simulation capability at the mesoscale to include weak shock conditions (<6 GPa), atomistic simulations of pore collapse are used to define a strain-rate-dependent strength model. Comparing these simulation methods allows us to impose physically reasonable constraints on the mesoscale model parameters. In doing so, we have been able to study shock waves interacting with pores as a function of this viscoplastic material response. We find that the pore collapse behavior of weak shocks is characteristically different than that of strong shocks.

One critical issue related to shale oil/gas production is a rapid decline in wellbore production and a low recovery rate. Therefore, maximizing wellbore production and extending the production life cycle are crucial for the sustainability of shale oil/gas production. Shale oil/gas production starts with creating a fracture network by injecting a pressurized fluid in a wellbore. The induced fractures are then held open by proppant particles. During production, oil and gas release from the shale matrix, migrate to nearby fractures, and ultimately reach a production wellbore. Given the relatively high permeability of the induced fractures, oil/gas release and transport in low-permeability shale matrix are likely a limiting step for long-term wellbore production. This project is aimed to (1) fundamentally understand the disposition and release of complex hydrocarbon mixtures in nanopore networks of shale matrix and their transport from low-permeability matrix to hydrofracking-induced fractures under various reservoir conditions ranging from black oil to dry gas and (2) use machine learning to upscale and integrate the nanometer-scale understanding into reservoir-scale model simulations. The work will help develop new stimulation strategies to enable efficient resource recovery from fewer and less environmentally impactful wells.

This paper presents simulation results of a control scheme for damping inter-area oscillations using high-voltage DC (HVDC) power modulation. The control system utilizes realtime synchrophasor feedback to construct a supplemental commanded power signal for the Pacific DC Intertie (PDCI) in the North American Western Interconnection (WI). A prototype of this controller has been implemented in hardware and, after multiple years of development, successfully tested in both open and closed-loop operation. This paper presents simulation results of the WI during multiple severe contingencies with the damping controller in both open and closed-loop. The primary results are that the controller adds significant damping to the controllable modes of the WI and that it does not adversely affect the system response in any of the simulated cases. Furthermore, the simulations show that a feedback signal composed of the frequency difference between points of measurement near the Washington-Oregon border and the California-Oregon border can be employed with similar results to a feedback signal constructed from measurements taken near the Washington-Oregon border and southern California. This is an important consideration because it allowed the control system to be designed without relying upon cross-system measurements, which would have introduced significant additional delay.

Distributed control compensation based on local and remote sensor feedback can improve small-signal stability in large distributed systems, such as electric power systems. Long distance remote measurements, however, are potentially subject to relatively long and uncertain network latencies. In this work, the issue of asymmetrical network latencies is considered for an active damping application in a two-area electric power system. The combined effects of latency and gain are evaluated in time domain simulation and in analysis using root-locus and the maximum singular value of the input sensitivity function. The results aid in quantifying the effects of network latencies and gain on system stability and disturbance rejection.

Distributed control compensation based on local and remote sensor feedback can improve small-signal stability in large distributed systems, such as electric power systems. Long distance remote measurements, however, are potentially subject to relatively long and uncertain network latencies. In this work, the issue of asymmetrical network latencies is considered for an active damping application in a two-area electric power system. The combined effects of latency and gain are evaluated in time domain simulation and in analysis using root-locus and the maximum singular value of the input sensitivity function. The results aid in quantifying the effects of network latencies and gain on system stability and disturbance rejection.

Distributed control compensation based on local and remote sensor feedback can improve small-signal stability in large distributed systems, such as electric power systems. Long distance remote measurements, however, are potentially subject to relatively long and uncertain network latencies. In this work, the issue of asymmetrical network latencies is considered for an active damping application in a two-area electric power system. The combined effects of latency and gain are evaluated in time domain simulation and in analysis using root-locus and the maximum singular value of the input sensitivity function. The results aid in quantifying the effects of network latencies and gain on system stability and disturbance rejection.

FERC Order 755 requires RTO/ISOs to compensate the frequency regulation resources based on the actual regulation service provided. Based on this rule, a resource is compensated by a performance-based payment including a capacity payment which accounts for its provided regulation capacity and a performance payment which reflects the quantity and accuracy of its regulation service. The RTO/ISOs have been implementing different market rules to comply with FERC Order 755. This paper focuses on the MISO's implementation and presents the calculations to maximize the potential revenue of electrical energy storage (EES) from participation in arbitrage and frequency regulation in the day-ahead market using linear programming. A case study was conducted for the Indianapolis Power & Light's 20MW/20MWh EES at Harding Street Generation Station based on MISO historical data from 2014 and 2015. The results showed the maximum revenue was primarily produced by frequency regulation.

Distribution system analysis with ever increasing numbers of distributed energy resources (DER) requires quasistatic time-series (QSTS) analysis to capture the time-varying and time-dependent aspects of the system. Previous literature has demonstrated the benefits of QSTS, but there is limited information available for the requirements and standards for performing QSTS simulations. This paper provides a novel analysis of the QSTS requirements for the input data timeresolution, the simulation time-step resolution, and the length of the simulation. Detailed simulations quantify the specific errors introduced by not performing yearlong high-resolution QSTS simulations.

In controlling the thermal properties of the surrounding environment, we provide insight into the underlying mechanisms driving the widely used laser direct write method for additive manufacturing. In this study, we find that the onset of silver nitrate reduction for the formation of direct write structures directly corresponds to the calculated steady-state temperature rises associated with both continuous wave and high-repetition rate, ultrafast pulsed laser systems. Furthermore, varying the geometry of the heat affected zone, which is controllable based on in-plane thermal diffusion in the substrate, and laser power, allows for control of the written geometries without any prior substrate preparation. In conclusion, these findings allow for the advance of rapid manufacturing of micro- and nanoscale structures with minimal material constraints through consideration of the laser-controllable thermal transport in ionic liquid/substrate media.

Lightly damped electromechanical oscillations are a source of concern in the western interconnect. Recent development of a reliable real-time wide-area measurement system (WaMS) has enabled the potential for large-scale damping control approaches for stabilizing critical oscillation modes. a recent research project has focused on the development of a prototype feedback modulation controller for the Pacific DC Intertie (PDCI) aimed at stabilizing such modes. The damping controller utilizes real-time WaMS signals to form a modulation command for the DC power on the PDCI. This paper summarizes results from the first actual-system closed-loop tests. Results demonstrate desirable performance and improved modal damping consistent with previous model studies.

Moulins permit access of surface meltwater to the glacier bed, causing basal lubrication and ice speedup in the ablation zone of western Greenland during summer. Despite the substantial impact of moulins on ice dynamics, the conditions under which they form are poorly understood. We assimilate a time series of ice surface velocity from a network of eleven Global Positioning System receivers into an ice sheet model to estimate ice sheet stresses during winter, spring, and summer in a ∼30 × 10 km region. Surface-parallel von Mises stress increases slightly during spring speedup and early summer, sufficient to allow formation of 16% of moulins mapped in the study area. In contrast, 63% of moulins experience stresses over the tensile strength of ice during a short (hours) supraglacial lake drainage event. Lake drainages appear to control moulin density, which is itself a control on subglacial drainage efficiency and summer ice velocities.

Here, diammonium dodecahydro-closo-dodecaborate (NH₄)₂B₁₂H₁₂ is the ionic compound combining NH₄⁺ cations and [B₁₂H₁₂]^2– anions, both of which can exhibit high reorientational mobility. To study the dynamical properties of this material, we measured the proton NMR spectra and spin–lattice relaxation rates in (NH₄)₂B₁₂H₁₂ over the temperature range of 6–475 K. Two reorientational processes occurring at different frequency scales have been revealed. In the temperature range of 200–475 K, the proton spin–lattice relaxation data are governed by thermally activated reorientations of the icosahedral [B₁₂H₁₂]^2– anions. This motional process is characterized by the activation energy of 486(8) meV, and the corresponding reorientational jump rate reaches ~10⁸ s^–1 near 410 K. Below 100 K, the relaxation data are governed by the extremely fast process of NH₄⁺ reorientations which are not “frozen out” at the NMR frequency scale down to 6 K. The experimental results in this range are described in terms of a gradual transition from the regime of low-temperature quantum dynamics (rotational tunneling of NH₄ groups) to the regime of classical jump reorientations of NH₄ groups with an activation energy of 26.5 meV. Our study offers physical insights into the rich dynamical behavior of (NH₄)₂B₁₂H₁₂ on an atomic level, providing a link between the microscopic and thermodynamic properties of this compound.

Battery energy storage systems (BESS) are a critical technology for integrating high penetration renewable power on an intelligent electrical grid. As limited energy restricts the steady-state operational state-of-charge (SoC) of storage systems, SoC forecasting models are used to determine feasible charge and discharge schedules that supply grid services. Smart grid controllers use SoC forecasts to optimize BESS schedules to make grid operation more efficient and resilient. This study presents three advances in BESS state-of-charge forecasting. First, two forecasting models are reformulated to be conducive to parameter optimization. Second, a new method for selecting optimal parameter values based on operational data is presented. Last, a new framework for quantifying model accuracy is developed that enables a comparison between models, systems, and parameter selection methods. The accuracies achieved by both models, on two example battery systems, with each method of parameter selection are then compared in detail. The results of this analysis suggest variation in the suitability of these models for different battery types and applications. Finally, the proposed model formulations, optimization methods, and accuracy assessment framework can be used to improve the accuracy of SoC forecasts enabling better control over BESS charge/discharge schedules.

Ketohydroperoxides are important in liquid-phase autoxidation and in gas-phase partial oxidation and pre-ignition chemistry, but because of their low concentration, instability, and various analytical chemistry limitations, it has been challenging to experimentally determine their reactivity, and only a few pathways are known. In the present work, 75 elementary-step unimolecular reactions of the simplest γ-ketohydroperoxide, 3-hydroperoxypropanal, were discovered by a combination of density functional theory with several automated transition-state search algorithms: the Berny algorithm coupled with the freezing string method, single- and double-ended growing string methods, the heuristic KinBot algorithm, and the single-component artificial force induced reaction method (SC-AFIR). The present joint approach significantly outperforms previous manual and automated transition-state searches - 68 of the reactions of γ-ketohydroperoxide discovered here were previously unknown and completely unexpected. All of the methods found the lowest-energy transition state, which corresponds to the first step of the Korcek mechanism, but each algorithm except for SC-AFIR detected several reactions not found by any of the other methods. We show that the low-barrier chemical reactions involve promising new chemistry that may be relevant in atmospheric and combustion systems. Our study highlights the complexity of chemical space exploration and the advantage of combined application of several approaches. Overall, the present work demonstrates both the power and the weaknesses of existing fully automated approaches for reaction discovery which suggest possible directions for further method development and assessment in order to enable reliable discovery of all important reactions of any specified reactant(s).

Since 2010, the concept of human readiness levels has been under development as a possible supplement to the existing technology readiness level (TRL) scale. The intent is to provide a mechanism to address safety and performance risks associated with the human component in a system that parallels the TRL structure already familiar to the systems engineering community. Sandia National Laboratories in Albuquerque, New Mexico, initiated a study in 2015 to evaluate options to incorporate human readiness planning for Sandia processes and products. The study team has collected the majority of baseline assessment data and has conducted interviews to understand staff perceptions of four different options for human readiness planning. Preliminary results suggest that all four options may have a vital role, depending on the type of work performed and the phase of product development. Upon completion of data collection, the utility of identified solutions will be assessed in one or more test cases.

Exposure to extreme environments is both mentally and physically taxing, leading to suboptimal performance and even life-threatening emergencies. Physiological and cognitive monitoring could provide the earliest indicator of performance decline and inform appropriate therapeutic intervention, yet little research has explored the relationship between these markers in strenuous settings. The Rim-to-Rim Wearables at the Canyon for Health (R2RWATCH) study is a research project at Sandia National Laboratories funded by the Defense Threat Reduction Agency to identify which physiological and cognitive phenomena collected by non-invasive wearable devices are the most related to performance in extreme environments. In a pilot study, data were collected from civilians and military warfighters hiking the Rim-to-Rim trail at the Grand Canyon. Each participant wore a set of devices collecting physiological, cognitive, and environmental data such as heart rate, memory, ambient temperature, etc. Promising preliminary results found correlates between physiological markers recorded by the wearable devices and decline in cognitive abilities, although further work is required to refine those measurements. Planned follow-up studies will validate these findings and further explore outstanding questions.

Endosomes in cells are known to move directionally along microtubules, but their rotational dynamics have rarely been investigated. Even less is known, specifically, about the rotation of nonspherical endosomes. Here we report a single-Janus rod rotational tracking study to reveal the rich rotational dynamics of rod-shaped endosomes in living cells. The rotational reporters were Janus rods that display patches of different fluorescent colors on opposite sides along their long axes. When the Janus rods are wrapped tightly inside endosomes, their shape and optical anisotropy allow the simultaneous measurements of all three rotational angles (in-plane, out-of-plane, and longitudinal) and the translational motion of single endosomes with high spatiotemporal resolutions. We demonstrate that endosomes undergo in-plane rotation and rolling during intracellular transport and that such rotational dynamics are driven by rapid microtubule fluctuations. We reveal for the first time the "rock-and-roll" of endosomes in living cells and how the intracellular environment modifies such rotational dynamics. This study demonstrates a unique application of Janus particles as imaging probes in the elucidation of fundamental biological questions.

Since 2010, the concept of human readiness levels has been under development as a possible supplement to the existing technology readiness level (TRL) scale. The intent is to provide a mechanism to address safety and performance risks associated with the human component in a system that parallels the TRL structure already familiar to the systems engineering community. Sandia National Laboratories in Albuquerque, New Mexico, initiated a study in 2015 to evaluate options to incorporate human readiness planning for Sandia processes and products. The study team has collected the majority of baseline assessment data and has conducted interviews to understand staff perceptions of four different options for human readiness planning. Preliminary results suggest that all four options may have a vital role, depending on the type of work performed and the phase of product development. Upon completion of data collection, the utility of identified solutions will be assessed in one or more test cases.

Exposure to extreme environments is both mentally and physically taxing, leading to suboptimal performance and even life-threatening emergencies. Physiological and cognitive monitoring could provide the earliest indicator of performance decline and inform appropriate therapeutic intervention, yet little research has explored the relationship between these markers in strenuous settings. The Rim-to-Rim Wearables at the Canyon for Health (R2RWATCH) study is a research project at Sandia National Laboratories funded by the Defense Threat Reduction Agency to identify which physiological and cognitive phenomena collected by non-invasive wearable devices are the most related to performance in extreme environments. In a pilot study, data were collected from civilians and military warfighters hiking the Rim-to-Rim trail at the Grand Canyon. Each participant wore a set of devices collecting physiological, cognitive, and environmental data such as heart rate, memory, ambient temperature, etc. Promising preliminary results found correlates between physiological markers recorded by the wearable devices and decline in cognitive abilities, although further work is required to refine those measurements. Planned follow-up studies will validate these findings and further explore outstanding questions.

Here, we study quasi-chemical theory (QCT) for the free energies of divalent alkaline earth ions (Ba 2+, Sr 2+, Ca 2+, Mg 2+) in water, emphasizing that: (a) interactions between metal ions and proximal water molecules are as strong as traditional chemical effects; (b) QCT builds directly from accessible electronic structure calculations but rests on fully elaborated molecular statistical thermodynamics; (c) QCT offers choices of convenience in identifying coordination numbers for analysis. We investigate utilisation of direct QCT with inner-shell conditioning (Formula presented.), alternative to the traditional nλ=0 conditioning motivated by a generalised van der Waals view. The alternative (Formula presented.) works well: deleterious non-Gaussian effects of van der Waals repulsive interactions are not serious, and the alternative conditioning improves the convenience of QCT calculations. Comparison between ab initio and force field molecular dynamics (AIMD and FFMD) with standard models suggests that FFMD likely exaggerates the anharmonicity in the thermal motion of inner-shell ion-water clusters. Together with the general encouraging support for the harmonic approximations implied by the (Formula presented.) conditioning, that observation helps explain the remarkable success of the cluster-based QCT solution free energies, which do not require assessment of all inner-shell occupancies by simulation.

Modal testing was performed on the uncut BARC structure as a whole and broken into its two sub-assemblies. The structure was placed on soft foam during the test. Excitation was provided with a small modal hammer attached to an actuator. Responses were measured using a 3D Scanning Laser Doppler Vibrometer. Data, shapes, and geometry from this test can be downloaded in Universal File Format from the Sandia Connect SharePoint site.

We use scanning tunneling microscopy (STM) to investigate the spatial arrangement of carbon monoxide (CO) and hydrogen (H) coadsorbed on a model catalyst surface, Ru(0001). We find that at cryogenic temperatures, CO forms small triangular islands of up to 21 molecules with hydrogen segregated outside of the islands. Furthermore, whereas for small island sizes (3-6 CO molecules) the molecules adsorb at hcp sites, a registry shift toward top sites occurs for larger islands (10-21 CO molecules). To characterize the CO structures better and to help interpret the data, we carried out density functional theory (DFT) calculations of the structure and simulations of the STM images, which reveal a delicate interplay between the repulsions of the different species.

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble when applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.