Publications

Background: Engineering strategies to create promoters that are both higher strength and tunable in the presence of inexpensive compounds are of high importance to develop metabolic engineering technologies that can be commercialized. Lignocellulosic biomass stands out as the most abundant renewable feedstock for the production of biofuels and chemicals. However, lignin a major polymeric component of the biomass is made up of aromatic units and remains as an untapped resource. Novel synthetic biology tools for the expression of heterologous proteins are critical for the effective engineering of a microbe to valorize lignin. This study demonstrates the first successful attempt in the creation of engineered promoters that can be induced by aromatics present in lignocellulosic hydrolysates to increase heterologous protein production. Results: A hybrid promoter engineering approach was utilized for the construction of phenolic-inducible promoters of higher strength. The hybrid promoters were constructed by replacing the spacer region of an endogenous promoter, P emrR present in E. coli that was naturally inducible by phenolics. In the presence of vanillin, the engineered promoters P vtac, P vtrc, and P vtic increased protein expression by 4.6-, 3.0-, and 1.5-fold, respectively, in comparison with a native promoter, P emrR. In the presence of vanillic acid, P vtac, P vtrc, and P vtic improved protein expression by 9.5-, 6.8-, and 2.1-fold, respectively, in comparison with P emrR. Among the cells induced with vanillin, the emergence of a sub-population constituting the healthy and dividing cells using flow cytometry was observed. The analysis also revealed this smaller sub-population to be the primary contributor for the increased expression that was observed with the engineered promoters. Conclusions: This study demonstrates the first successful attempt in the creation of engineered promoters that can be induced by aromatics to increase heterologous protein production. Employing promoters inducible by phenolics will provide the following advantages: (1) develop substrate inducible systems; (2) lower operating costs by replacing expensive IPTG currently used for induction; (3) develop dynamic regulatory systems; and (4) provide flexibility in operating conditions. The flow cytometry findings strongly suggest the need for novel approaches to maintain a healthy cell population in the presence of phenolics to achieve increased heterologous protein expression and, thereby, valorize lignin efficiently.

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it remains a formidable challenge to extract unbiased and interpretable descriptions of how rapid single-trial circuit dynamics change slowly over many trials to mediate learning. We demonstrate a simple tensor component analysis (TCA) can meet this challenge by extracting three interconnected, low-dimensional descriptions of neural data: neuron factors, reflecting cell assemblies; temporal factors, reflecting rapid circuit dynamics mediating perceptions, thoughts, and actions within each trial; and trial factors, describing both long-term learning and trial-to-trial changes in cognitive state. We demonstrate the broad applicability of TCA by revealing insights into diverse datasets derived from artificial neural networks, large-scale calcium imaging of rodent prefrontal cortex during maze navigation, and multielectrode recordings of macaque motor cortex during brain machine interface learning. Williams et al. describe an unsupervised method to uncover simple structure in large-scale recordings by extracting distinct cell assemblies with rapid within-trial dynamics, reflecting interpretable aspects of perceptions, actions, and thoughts, and slower across-trial dynamics reflecting learning and internal state changes.

We report the first experimental study into the thermomechanical and viscoelastic properties of a metal-organic framework (MOF) material. Nanoindentations show a decrease in the Young's modulus, consistent with classical molecular dynamics simulations, and hardness of HKUST-1 with increasing temperature over the 25-100 °C range. Variable-temperature dynamic mechanical analysis reveals significant creep behavior, with a reduction of 56% and 88% of the hardness over 10 min at 25 and 100 °C, respectively. This result suggests that, despite the increased density that results from increasing temperature in the negative thermal expansion MOF, the thermally induced softening due to vibrational and entropic contributions plays a more dominant role in dictating the material's temperature-dependent mechanical behavior.

This document presents tests from the Sierra Structural Mechanics verification test suite. Each of these tests is run nightly with the Sierra/SD code suite and the results of the test checked versus the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the Sierra/SD code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.

Verification and validation (V&V) of scientific computing programs are important at San- dia National Laboratories (SNL) due to the expanding role of computational simulation in managing the United States nuclear stockpile. This document presents the verification plan for the Sierra Structural Dynamics application. This verification plan includes code devel- opment practices, structure of test suites, and additional quality assurance practices used by the Sierra/SD team.

Annual Milestone (joint NREL/SNL): Create and disseminate documentation that compares the Nalu and SOWFA codes for actuator-line-based wind farm models, including the demonstration of the Windpark Egmond aan Zee (OWEZ). Comparisons will include simulation results for the same cases, assessing computational speed and scalability.

Nanosecond pulsed discharges provide versatile experimental and computational testbeds for the exploration of fundamental plasma physics. In particular, the fast rise time and short duration produce plasmas which are both spatially diffuse and uniform enough to probe experimentally and confine the kinetics of interest to sufficiently short time scales to be computationally tractable. This work will focus on validation of particle-in-cell with Monte Carlo collisions (PIC-MCC) modeling and analysis of plasma phenomenon during and after formation of the conductive plasma channel of a nanosecond pulse discharge in helium at 200 Torr and 300 K over a 1 cm gap. The validation will compare results of the simulation to measurements of electron number density, temperature, 1D electron energy distribution function, and Townsend ionization coefficient, as well as ion mobility. Analysis of the stochastic nature of the electron avalanche ahead of the ionization wave front and of significant ionization overshoot in the presheath region is also performed.

A second series of experiments were performed in August 2017 on the Clam Shell Magnetically-Insulated Transmission Line1 (CSMITL2) at the Saturn accelerator at Sandia National Laboratories in Albuquerque. In the first series of experiments in March 2017, the CSMITL2 demonstrated utilizing four vacuum-insulator levels instead of the two in CSMITL1, increasing the load power by a factor of four compared to CSMITL1 delivering 8 TW to the load, and polarity inversion of the power pulse. Obj ectives for the second series included multiple shot per day capability and large ion current densities from a large-area flashover ion diode source.

Absolute calibration of streaked visible spectroscopy systems has been performed at Z-machine at Sandia National Labs in order to determine temperatures of electrode surfaces during the current pulse. The ability to calibrate the full system, including all fiber optic runs and probes is crucial to understanding errors in the calibration process. The calibration procedure involves imaging a blackbody light source, with a known spectral radiance which is coupled to an integrating sphere. This source is streaked slowly over a few ns using Sydor streak cameras. The slow sweep is converted to a 100-500ns sweep by imaging a bright light source on both sweep rates, and obtaining wavelength and time dependent correction curves. Any broadband light source or several laser lines of differing wavelengths can be used for this correction. This technique has yielded temperature estimates of several eV in the Z convolute.

The origin of Sandia National Laboratories began in World War II and the Manhattan Project. The engineering workforce at that time conducted ordnance design, testing, and assembly of nuclear weapons. In the early 1950s the need to understand material properties prompted a research program modeled after ATT Bell Laboratories on the response of materials to shock compression. That decision was instrumental in developing a wide range of experimental, diagnostic, material modeling, and computational capabilities.

The HERMES-III accelerator (18 MV, 700kA, 40 ns) uses Inductive Voltage Adder (IVA) architecture to drive a magnetically insulated transmission line (MITL) with a 34-ohm vacuum impedance. In normal operation, the load is a Bremsstrahlung diode operated in negative polarity, from which an intense electron beam can be extracted for gamma generation. The relatively high output voltage makes HERMES attractive as a source for high-energy ions which could be used, among other applications, for generating neutrons from high-cross section metal targets. Such beams of both protons and lithium were previously generated1 at the 16 MV level, but in positive polarity with the induction cavities reversed. To preserve the dominant negative polarity mode, ion beams now must be generated in negative polarity, with the resultant beams propagated inside the MITL.

Electrochemical double-layer capacitances of charged carbon nanotube (CNT) forests with tetraethyl ammonium tetrafluoro borate electrolyte in propylene carbonate are studied on the basis of molecular dynamics simulation. Direct molecular simulation of the filling of pore spaces of the forest is feasible even with realistic, small CNT spacings. The numerical solution of the Poisson equation based on the extracted average charge densities then yields a regular experimental dependence on the width of the pore spaces, in contrast to the anomalous pattern observed in experiments on other carbon materials and also in simulations on planar slot-like pores. The capacitances obtained have realistic magnitudes but are insensitive to electric potential differences between the electrodes in this model. This agrees with previous calculations on CNT forest supercapacitors, but not with experiments which have suggested electrochemical doping for these systems. Those phenomena remain for further theory/modeling work.

Traditionally, material identification is performed using global load and displacement data from simple boundary-value problems such as uni-axial tensile and simple shear tests. More recently, however, inverse techniques such as the Virtual Fields Method (VFM) that capitalize on heterogeneous, full-field deformation data have gained popularity. In this work, we have written a VFM code in a finite-deformation framework for calibration of a viscoplastic (i.e. strain-rate dependent) material model for 304L stainless steel. Using simulated experimental data generated via finite-element analysis (FEA), we verified our VFM code and compared the identified parameters with the reference parameters input into the FEA. The identified material model parameters had surprisingly large error compared to the reference parameters, which was traced to parameter covariance and the existence of many essentially equivalent parameter sets. This parameter non-uniqueness and its implications for FEA predictions is discussed in detail. Lastly, we present two strategies to reduce parameter covariance – reduced parametrization of the material model and increased richness of the calibration data – which allow for the recovery of a unique solution.

Detailed understanding of solid–solid interface structure–function relationships is critical for the improvement and wide deployment of all-solid-state batteries. The interfaces between lithium phosphorous oxynitride (LiPON) solid electrolyte material and lithium metal anode, and between LiPON and LixCoO2 cathode, have been reported to generate solid–electrolyte interphase (SEI)-like products and/or disordered regions. Using electronic structure calculations and crystalline LiPON models, we predict that LiPON models with purely P−N−P backbones are kinetically inert towards lithium at room temperature. In contrast, transfer of oxygen atoms from low-energy LixCoO2(104) surfaces to LiPON is much faster under ambient conditions. The mechanisms of the primary reaction steps, LiPON structural motifs that readily reacts with lithium metal, experimental results on amorphous LiPON to partially corroborate these predictions, and possible mitigation strategies to reduce degradations are discussed. LiPON interfaces are found to be useful case studies for highlighting the importance of kinetics-controlled processes during battery assembly at moderate processing temperatures.

Sensors to detect mixtures of NO_x/NH₃ are needed to monitor emissions of diesel automobiles where a selective catalytic reduction system uses an NH₃ mediated reaction to reduce NO_x. We report on the application of a three electrode La_0.8Sr_0.2CrO₃, Au_0.5Pd_0.5, Pt mixed potential sensor using yttria-stabilized-zirconia (YSZ) as a solid electrolyte to NO_x/NH₃ sensing. Artificial neural networks were used to automatically decode the concentrations of NO_x/NH₃ and errors of less than 15% are achieved. The optimal architecture for ANN decoding and the maximum density of training data points are also determined. The stability of the sensor was monitored by electrochemical impedance spectroscopy. The impedance associated with YSZ oxygen ion conduction and the electrochemical reactions at the three-phase interface are tracked for a period of over 100 days.

Here, the determination of the geometrical properties of fractures plays a critical role in many engineering problems to assess the current hydrological and mechanical states of geological media and to predict their future states. However, numerical modeling of geoelectrical responses in realistic fractured media has been challenging due to the explosive computational cost imposed by the explicit discretizations of fractures at multiple length scales, which often brings about a tradeoff between computational efficiency and geologic realism. Here, we use the hierarchical finite element method to model electrostatic response of realistically complex 3D conductive fracture networks with minimal computational cost.

We're trying to understand the math behind the Karhunen-Loéve expansion, and these are the notes we're taking along the way.

Direct laser irradiation of sputter deposited Al/Pt nanolaminate multilayers results in rapid local heating and exothermic mixing of reactant layers. Milli- and microsecond pulsed laser irradiation under certain test conditions leads to single-point ignition of rapid, self-propagating, formation reactions. Multilayers having bilayer thicknesses of 328 nm, 164 nm, and 65 nm are characterized by their ignition onset times and temperatures. Smaller bilayer thickness multilayers require less laser intensity for ignition compared with larger bilayer designs (when utilizing a particular pulse duration). The relationship between laser intensity and ignition onset time is used to calibrate an activation energy for ignition within a finite element reactive heat transport model. The local heating rate is varied from 104 K/s to 106 K/s by selecting a laser intensity. Kissinger analysis was performed on the heating rate-dependent ignition temperatures measured with high speed pyrometry to experimentally determine an activation energy in the foils of (6.2 ± 1.6 × 104 J/mole atoms). This value is then compared to an activation energy produced from model fits to an ignition onset time of 7.2 × 104 J/mole atoms.

In spite of the abundance of clustering techniques and algorithms, clustering mixed interval (continuous) and categorical (nominal and/or ordinal) scale data remain a challenging problem. In order to identify the most effective approaches for clustering mixed–type data, we use both theoretical and empirical analyses to present a critical review of the strengths and weaknesses of the methods identified in the literature. Here, the guidelines on approaches to use under different scenarios are provided, along with potential directions for future research.

As a first step to porting scanning tunneling microscopy methods of atomic-precision fabrication to a strained-Si/SiGe platform, we demonstrate post-growth P atomic-layer doping of SiGe heterostructures. To preserve the substrate structure and elastic state, we use a T≤800 ° C process to prepare clean Si0.86Ge0.14 surfaces suitable for atomic-precision fabrication. P-saturated atomic-layer doping is incorporated and capped with epitaxial Si under a thermal budget compatible with atomic-precision fabrication. Hall measurements at T=0.3 K show that the doped heterostructure has R□=570±30Ω, yielding an electron density ne=2.1±0.1×1014cm-2 and mobility μe=52±3cm2V-1s-1, similar to saturated atomic-layer doping in pure Si and Ge. The magnitude of μe and the complete absence of Shubnikov-de Haas oscillations in magnetotransport measurements indicate that electrons are overwhelmingly localized in the donor layer, and not within a nearby buried Si well. This conclusion is supported by self-consistent Schrödinger-Poisson calculations that predict electron occupation primarily in the donor layer.

DTRA and NNSA need to understand certain energetic products in order to define requirements for ongoing nuclear weapon enterprise programs. By characterizing shaped charges, for example, we can proactively protect our existing nuclear stockpile. Being able to effectively and accurately model these characteristics allows us to more efficiently utilize time, money, and resources so that we can best protect our assets. I was partnered with another midshipman to work on this project with our advisor, along with a team of explosives technicians, and several specialists in computational simulations. In order to determine the pressure field created by the jet and the jet velocity, I worked with and modified simulations using CTH, a code developed at Sandia. I compared values from the simulation to what was determined experimentally.

Here, the work presented in this paper details both an experimental program and an associated numerical modeling effort to characterize and predict the ballistic response of S-2 glass/SC15 epoxy composite panels. The experimental program consisted of ¼ inch diameter soft carbon steel spheres impacting ¼ and ½ inch thick flat composite panels at velocities ranging from 220 to 1570 m/s. High speed cameras were used to capture the impact event and resulting residual velocity of the spheres for each test configuration. After testing, each panel was inspected both visually and with ultrasonic C-scan techniques to determine the extent and depth of damage imparted on the panel by the impactor. The numerical modeling efforts utilized the anisotropic multi-constituent composite model (MCM) within the CTH shock physics hydrocode. The MCM model allows for evaluation of damage at the constituent level through continuum averaged stress and strain fields. The model also accounts for the inherent coupling of the equation of state and strength response that occurs in anisotropic composite materials. Finally, the simulation results are compared against the experimentally measured residual velocity as a quantitative metric and against the measured damage extent and patterns as a qualitative metric. The comparisons show good agreement in residual velocity and damage extent.

In many organizations, intrusion detection and other related systems are tuned to generate security alerts, which are then manually inspected by cyber-security analysts. These analysts often devote a large portion of time to inspecting these alerts, most of which are innocuous. Thus, it would be greatly beneficial to reduce the number of innocuous alerts, allowing analysts to utilize their time and skills for other aspects of cyber defense. In this work, we devise several simple, fast, and easily understood models to cut back this manual inspection workload, while maintaining high true positive and true negative rates. We demonstrate their effectiveness on real data, and discuss their potential utility in application by others.

Wind turbine yaw offset reduces power and alters the loading on a stand-alone wind turbine. The manner in which loads are affected by yaw offset has been analyzed and characterized based on atmospheric conditions in this paper using experimental data from the SWiFT facility to better understand the correlation between yaw offset and turbine performance.

Large scale molecular dynamics simulations for bidisperse nanoparticle suspensions with an explicit solvent are used to investigate the effects of evaporation rates and volume fractions on the nanoparticle distribution during drying. Our results show that "small-on-top" stratification can occur when Pesøs ≳ c with c ∼ 1, where Pes is the Péclet number and øs is the volume fraction of the smaller particles. This threshold of Pesøs for "small-on-top" is larger by a factor of ∼α2 than the prediction of the model treating solvent as an implicit viscous background, where α is the size ratio between the large and small particles. Our simulations further show that when the evaporation rate of the solvent is reduced, the "small-on-top" stratification can be enhanced, which is not predicted by existing theories. This unexpected behavior is explained with thermophoresis associated with a positive gradient of solvent density caused by evaporative cooling at the liquid/vapor interface. For ultrafast evaporation the gradient is large and drives the nanoparticles toward the liquid/vapor interface. This phoretic effect is stronger for larger nanoparticles, and consequently the "small-on-top" stratification becomes more distinct when the evaporation rate is slower (but not too slow such that a uniform distribution of nanoparticles in the drying film is produced), as thermophoresis that favors larger particles on the top is mitigated. A similar effect can lead to "large-on-top" stratification for Pesøs above the threshold when Pes is large but øs is small. Our results reveal the importance of including the solvent explicitly when modeling evaporation-induced particle separation and organization and point to the important role of density gradients brought about by ultrafast evaporation.

Intracellular cargos are transported by molecular motors along actin and microtubules, but how their dynamics depends on the complex structure of the cytoskeletal network remains unclear. In this study, we investigated this longstanding question by measuring simultaneously the rotational and translational dynamics of cargos at microtubule intersections in living cells. We engineered two-faced particles that are fluorescent on one hemisphere and opaque on the other and used their optical anisotropy to report the rotation of cargos. We show that cargos undergo brief episodes of unidirectional and rapid rotation while pausing at microtubule intersections. Probability and amplitude of the cargo rotation depend on the geometry of the intersecting filaments. The cargo rotation is not random motion due to detachment from microtubules, as revealed by statistical analyses of the translational and rotational dynamics. Instead, it is an active rotation driven by motor proteins. Although cargos are known to pause at microtubule intersections, this study reveals a different dimension of dynamics at this seemingly static state and, more importantly, provides direct evidence showing the correlation between cargo rotation and the geometry of underlying microtubule intersections.

Here, compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quantification analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several compressive sensing solvers that target the unconstrained LASSO formulation, with a focus on linear systems that arise in the construction of polynomial chaos expansions. With core solvers l1_ls, SpaRSA, CGIST, FPC_AS, and ADMM, we develop techniques to mitigate overfitting through an automated selection of regularization constant based on cross-validation, and a heuristic strategy to guide the stop-sampling decision. Practical recommendations on parameter settings for these techniques are provided and discussed. The overall method is applied to a series of numerical examples of increasing complexity, including large eddy simulations of supersonic turbulent jet-in-crossflow involving a 24-dimensional input. Through empirical phase-transition diagrams and convergence plots, we illustrate sparse recovery performance under structures induced by polynomial chaos, accuracy, and computational trade-offs between polynomial bases of different degrees, and practicability of conducting compressive sensing for a realistic, high-dimensional physical application. Across test cases studied in this paper, we find ADMM to have demonstrated empirical advantages through consistent lower errors and faster computational times.

Abstract not provided.

One major problem in the design of aerospace components is the nonlinear changes in the response due to a change in the geometry and material properties. Many of these components have small nominal values and any change can lead to a large variability. In order to characterize this large variability, traditional methods require either many simulation runs or the calculations of many higher order derivatives. Each of these paths requires a large amount of computational power to evaluate the response curve. In order to perform uncertainty quantification analysis, even more simulation runs are required. The hyper-dual meta-model is introduced and used to characterize the response curve with the use of basis functions. The information of the response is generated with the utilization of the hyper-dual step to determine the sensitivities at a few number of simulation runs to greatly enrich the response space. This study shows the accuracy of this method for two different systems with parameterizations at different stages in the design analysis.

The goal of the ExaWind project is to enable predictive simulations of wind farms composed of many MW-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines, and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. We describe in this report our efforts to decrease the setup and solution time for the mass-continuity Poisson system with respect to the benchmark timing results reported in FY18 Q1. In particular, we investigate improving and evaluating two types of algebraic multigrid (AMG) preconditioners: Classical Ruge-Stfiben AMG (C-AMG) and smoothed-aggregation AMG (SA-AMG), which are implemented in the Hypre and Trilinos/MueLu software stacks, respectively.

Acetic acid (CH3COOH) is one of the most abundant carboxylic acids in the troposphere. In the study, the tropospheric chemistry of CH3COOH is investigated using the 3-D global chemistry transport model, STOCHEM-CRI. The highest mixing ratios of surface CH3COOH are found in the tropics by as much as 1.6 ppb in South America. The model predicts the seasonality of CH3COOH reasonably well and correlates with some surface and flight measurement sites, but the model drastically underpredicts levels in urban and midlatitudinal regions. The possible reasons for the underprediction are discussed. The simulations show that the lifetime and global burden of CH3COOH are 1.6–1.8 days and 0.45–0.61 Tg, respectively. The reactions of the peroxyacetyl radical (CH3CO3) with the hydroperoxyl radical (HO2) and other organic peroxy radicals (RO2) are found to be the principal sources of tropospheric CH3COOH in the model, but the model-measurement discrepancies suggest the possible unknown or underestimated sources which can contribute large fractions of the CH3COOH burden. The major sinks of CH3COOH in the troposphere are wet deposition, dry deposition, and OH loss. However, the reaction of CH3COOH with Criegee intermediates is proposed to be a potentially significant chemical loss process of tropospheric CH3COOH that has not been previously accounted for in global modeling studies. Inclusion of this loss process reduces the tropospheric CH3COOH level significantly which can give even larger discrepancies between model and measurement data, suggesting that the emissions inventory and the chemical production sources of CH3COOH are underpredicted even more so in current global models.

Process-induced residual stresses occur in composite structures composed of dissimilar materials. As these residual stresses could result in fracture, their consideration when designing composite parts is necessary. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. Alternatively, it is possible for computational tools to predict potential residual stresses. Therefore, the objectives of the presented work are to demonstrate an efficient method for simulating residual stresses in composite parts, as well as the potential value of statistical methods during analyses for which material properties are unknown. Specifically, a simplified residual stress modeling approach is implemented within Sandia National Laboratories’ SIERRA/SolidMechanics code. Concurrent with the model development, bi-material composite structures are designed and manufactured to exhibit significant residual stresses. Then, the presented modeling approach is rigorously verified and validated through simulations of the bi-material composite structures’ manufacturing processes, including a mesh convergence study, sensitivity analysis, and uncertainty quantification. The simulations’ final results show adequate agreement with the experimental measurements, indicating the validity of a simple modeling approach, as well as a necessity for the inclusion of material parameter uncertainty in the final residual stress predictions.

two-color, volumetric laser-induced fluorescence (TC-VLIF) was demonstrated for three-dimensional, tomographic imaging of the structural properties of the OH radical and temperature field in a turbulent hydrogen-air flame. Two narrow-band laser sources were tuned to the Q_i(5) and Q_i(14) transitions of the (1,0) band in the A²E<—X²II system and illuminated a volumetric region of the flame. Images from eight unique perspectives collected simultaneously from each of the two transitions were used to reconstruct overlapping 011 fields with different Boltzmann fractions and map the 3D temperature distribution with nanosecond precision. Key strategies for minimizing sources of error, such as detector sensitivity and spatial overlap of the two fields, are discussed.

A new yield surface with an evolving effective stress definition is proposed for consistently and efficiently describing anisotropic distortional hardening. Specifically, a new internal state variable is introduced to capture the thermodynamic evolution between different effective stress definitions. The corresponding yield surface and evolution equations of the internal variables are derived from thermodynamic considerations enabling satisfaction of the second law. A closest point projection return mapping algorithm for the proposed model is formulated and implemented for use in finite element analyses. Select constitutive and larger scale boundary value problems are solved to explore the capabilities of the model and examine the impact of distortional hardening on constitutive and structural responses. Importantly, these simulations demonstrate the tractability of the proposed formulation in investigating large-scale problems of interest.

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. Although these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. Parallel sparse matrix–vector operations are used to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.

Solid-state hydrogen storage materials undergo complex phase transformations whose behavior are collectively determined by thermodynamic (e.g., Gibbs free energy), mechanical (e.g., lattice and elastic constants), and mass transport (e.g., diffusivity) properties. These properties depend on the reaction conditions and evolve continuously during (de)hydrogenation. Thus, they are difficult to measure in experiments. Because of this, past progress to improve solid-state hydrogen storage materials has been prolonged. Using PdHx as a representative example for interstitial metal hydride, we have recently applied molecular dynamics simulations to quantify hydrogen diffusion in the entire reaction space of temperature and composition. Here, we have further applied molecular dynamics simulations to obtain well-converged expressions for lattice constants, Gibbs free energies, and elastic constants of PdHx at various stages of the reaction. Our studies confirm significant dependence of elastic constants on temperature and composition. Specifically, a new dynamic effect of hydrogen diffusion on elastic constants is discovered and discussed.

The role that van der Waals (vdW) attractive forces play in the hydration and association of atomic hydrophobic solutes such as argon (Ar) in water is reanalyzed using the local molecular field (LMF) theory of those interactions. In this problem, solute vdW attractive forces can reduce or mask hydrophobic interactions as measured by contact peak heights of the ArAr correlation function compared to reference results for purely repulsive core solutes. Nevertheless, both systems exhibit a characteristic hydrophobic inverse temperature behavior in which hydrophobic association becomes stronger with increasing temperature through a moderate temperature range. The new theoretical approximation obtained here is remarkably simple and faithful to the statistical mechanical LMF assessment of the necessary force balance. Our results extend and significantly revise approximations made in a recent application of the LMF approach to this problem and, unexpectedly, support a theory of nearly 40 years ago.

Laying a basis for molecularly specific theory for the mobilities of ions in solutions of practical interest, we report a broad survey of velocity autocorrelation functions (VACFs) of Li+ and PF6- ions in water, ethylene carbonate, propylene carbonate, and acetonitrile solutions. We extract the memory function, γ(t), which characterizes the random forces governing the mobilities of ions. We provide comparisons controlling for the effects of electrolyte concentration and ion-pairing, van der Waals attractive interactions, and solvent molecular characteristics. For the heavier ion (PF6-), velocity relaxations are all similar: negative tail relaxations for the VACF and a clear second relaxation for γt, observed previously also for other molecular ions and with n-pentanol as the solvent. For the light Li+ ion, short time-scale oscillatory behavior masks simple, longer time-scale relaxation of γt. But the corresponding analysis of the solventberg Li+H2O4 does conform to the standard picture set by all the PF6- results.

Additive manufacturing (AM) processes for metals can yield as-built microstructures that vary significantly from their cast or wrought counterparts. These microstructural variations can in turn, have profound effects on the properties of a component. Here, a modeling methodology is presented to investigate microstructurally-influenced mechanical response in additively manufactured structures via direct numeral simulation. Three-dimensional, synthetic voxelized microstructures are generated by kinetic Monte Carlo (kMC) additive manufacturing process simulations performed at four scan speeds to create a thin-wall cylindrical geometry notionally constructed using a concentric-pathed directed energy deposition AM process. The kMC simulations utilize a steady-state molten pool geometry that is held constant throughout the study. Resultant microstructures are mapped onto a highly-refined conformal finite-element mesh of a part geometry. A grain-scale anisotropic crystal elasticity model is then used to represent the constitutive response of each grain. The response of the structure subjected to relatively simple load conditions is studied in order to provide understanding of both the influence of AM processing on microstructure as well as the microstructure's influence on the macroscale mechanical response.

By deploying a photon Doppler velocimetry based plasma diagnostic, we have directly observed low density plasma in the load anode/cathode gap of cylindrically converging pulsed power targets. The arrival of this plasma is temporally correlated with gross current loss and subtle power flow differences between the anode and the cathode. The density is in the range where Hall terms in the electromagnetic equations are relevant, but this physics is lacking in the magnetohydrodynamics codes commonly used to design, analyze, and optimize pulsed power experiments. Here, the present work presents evidence of the importance of physics beyond traditional resistive magnetohydrodynamics for the design of pulsed power targets and drivers.

This three-year effort started in FY17 with the primary objective of detailing the environmental compliance costs and lessons learned from U.S. based MHK projects that have gone through the permitting and compliance process. The project goal is to find ways to improve the efficiency and effectiveness of the permitting and compliance process that reduce deployment uncertainties and associated risks/costs; ultimately encouraging investment in MHK projects. The project team is composed of Sandia National Laboratories, H. T. Harvey & Associates, Integral Consulting, and Kearns & West. Step one of the project process, collect data to determine permitting and compliance costs, was a focus during 2017, but is an ongoing process to ensure the project team is working with the most recent and accurate data as possible. Currently, the project team is focusing on step two of the project process, identify cost reduction pathways. Step three, develop cost reduction strategies, will follow during Fall 2018 and Winter 2019. Each step is envisioned as an iterative approach working with industry and regulators to best meet the project goal.

We discuss a maritime surveillance and detection concept based on Raman scattering of water molecules. Using a range-gated scanning lidar that detects Raman scattered photons from water, the absence or change of signal indicates the presence of a non-water object. With sufficient spatial resolution, a two-dimensional outline of the object can be generated by the scanning lidar. Because Raman scattering is an inelastic process with a relatively large wavelength shift for water, this concept avoids the often problematic elastic scattering for objects at or very close to the water surface or from the bottom surface for shallow waters. The maximum detection depth for this concept is limited by the attenuation of the excitation and return Raman light in water. If excitation in the UV is used, fluorescence can be used for discrimination between organic and non-organic objects. In this paper, we present a lidar model for this concept and discuss results of proof-of-concept measurements. Using published cross section values, the model and measurements are in reasonable agreement and show that a sufficient number of Raman photons can be generated for modest lidar parameters to make this concept useful for near-surface detection.

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming. We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.

Electricity markets rely on the rapid solution of the optimal power flow (OPF) problem to determine generator power levels and set nodal prices. Traditionally, the OPF problem has been formulated using linearized, approximate models, ignoring nonlinear alternating current (AC) physics. These approaches do not guarantee global optimality or even feasibility in the real ACOPF problem. We introduce an outer-approximation approach to solve the ACOPF problem to global optimality based on alternating solution of upper- and lower-bounding problems. The lower-bounding problem is a piecewise relaxation based on strong second-order cone relaxations of the ACOPF, and these piecewise relaxations are selectively refined at each major iteration through increased variable domain partitioning. Our approach is able to efficiently solve all but one of the test cases considered to an optimality gap below 0.1%. Furthermore, this approach opens the door for global solution of MINLP problems with AC power flow equations.

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of this framework is to enable more robust evaluation of model cloud properties, so that differences between models and observations can more confidently be attributed to model errors. A critical step in this process is accounting for the difference between the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4-km global model output from the multiscale modeling framework to evaluate the sensitivity of simulated satellite retrievals to common assumptions about cloud and precipitation overlap and condensate variability used in climate models whose grid spacing is many tens to hundreds of kilometers. We find the simulated retrievals are sensitive to these assumptions. Using maximum-random overlap with homogeneous cloud and precipitation condensate leads to errors in Multiangle Imaging Spectroradiometer and International Satellite Cloud Climatology Project-simulated cloud cover and in CloudSat-simulated radar reflectivity that are significant compared to typical differences between the model simulations and observations. A more realistic treatment of unresolved clouds and precipitation is shown to substantially reduce these errors. The sensitivity to these assumptions underscores the need for the adoption of more realistic subcolumn treatments in models and the need for consistency among subcolumn assumptions between models and simulators to ensure that simulator-diagnosed errors are consistent with the model formulation.

Here, the transparent electric conductors made of indium tin oxide (ITO)-doped glass prepared by a flash lamp annealing (FLA) process were compared with ITO-doped glass prepared via a conventional rapid thermal annealing (RTA) process. Stylus surface profilometry was used to determine thicknesses, scanning electron microscopy was used to image surfaces, X-ray diffraction was used to determine film structures, X-ray photoelectron spectroscopy was used to determine oxidation states and film compositions, 4-point probe measurements were used to determine electrical conductivities, UV–Vis spectroscopy was used to determine film transparencies, and selective light filtering was used to determine which wavelengths of light are needed to anneal ITO into a visibly transparent electrically conductive thin film via an FLA process. The results showed that FLA with visible light can be used to nearly instantaneously anneal ITO to create visibly transparent and electrically conductive ITO thin films on glass. The FLA process achieved this by predominately exciting unoxidized indium, unoxidized tin, tin monoxide (SnO), and non-stoichiometric indium oxide (InO x ), appropriately distributed in an electron beam physical vapor-deposited amorphous ITO thin film, to allow their oxidation and crystallization into an electrically conductive visibly transparent ITO. Though it is possible to prepare ITO-doped glass that is more transparent with an RTA process, the FLA process is significantly faster, has comparable electrical conductivity, and can strongly localize heating to areas of the as-deposited ITO thin film that are not electrically conductive and visibly transparent.

In HIHE01-1, "Evaluate a PathForward/Facilities memory-relevant performance study/analysis," we conducted a focused study on the performance differences between HBM2 and HBM3 as revealed through execution of representative benchmarks. We used measurements on an existing many-core system, Knight's Landing (KNL), to calibrate simulator settings, and then performed Structural Simulation Toolkit (SST) simulations of KNL-like CPUs that access future high bandwidth memories. This report documents our findings.

The ability to relax a macroscopically applied stress is often associated with molecular mobility, or the possibility for a molecule to move outside the confines of its current position, within the material of which the stress is applied. Here, a viscoelastic constitutive analysis is used to investigate the counter-intuitive experimental observation of “mobility decrease with increased deformation through yield” [1] for a glass forming polymer during stress relaxation while under compressive and tensile loading conditions. The behavior of an epoxy thermoset is examined using an extensively validated, thermorheologically simple, material “clock” model, the Simplified Potential Energy Clock (SPEC) model.[2] This methodology allows for a comparison between the linear viscoelastic (LVE) limit and the true non-linear viscoelastic (NLVE) representation and enables exploration of a wide range of conditions that are not practical to investigate experimentally. The model predicts the behavior previously described as “mobility decrease with increased deformation” in the LVE limit and at low strain rates for NLVE. Only when loading rates are sufficient to decrease the material shift factor by multiple orders of magnitude is the anticipated deformation induced mobility or “mobility increase with increased deformation” observed. While the model has not been “trained” for these behaviors, it also predicts that the normalized stress relaxation response is indistinguishable amongst strain levels in the “post-yield” region, as has been experimentally reported. At long time, which has not been examined experimentally, the model predicts that even the normalized relaxation curves that exhibit “mobility increase with increased deformation” “cross back over” and return to the LVE ordering. These findings demonstrate the ability of rheologically simple models to represent the counter-intuitive experimentally measured material response and present predictions at long time scales that could be tested experimentally.

The RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate its utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.

Uncertainty is ubiquitous in virtually all engineering applications, and, for such problems, it is inadequate to simulate the underlying physics without quantifying the uncertainty in unknown or random inputs, boundary and initial conditions, and modeling assumptions. Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In particular, we postulate conditions on the random variable objective function as well as the PDE solution that guarantee existence of minimizers. Furthermore, we derive optimality conditions and apply our results to the control of an environmental contaminant. Lastly, we introduce a new risk measure, called the conditional entropic risk, that fuses desirable properties from both the conditional value-at-risk and the entropic risk measures.

For this study, diamond-like carbon (DLC) films were tribochemically formed from ambient hydrocarbons on the surface of a highly stable nanocrystalline Pt-Au alloy. A sliding contact between an alumina sphere and Pt-Au coated steel exhibited friction coefficients as low as μ = 0.01 after dry sliding in environments containing trace (ppb) organics. Ex situ analysis indicated that the change in friction coefficient was due to the formation of amorphous carbon films, and Raman spectroscopy and elastic recoil analysis showed that these films consist of sp²/sp³ amorphous carbon with as much as 20% hydrogen. Transmission electron microscopy indicated these films had thicknesses exceeding 100 nm, and were enhanced by the incorporation of worn Pt-Au nanoparticles. The result was highly wear-resistant, low-friction DLC/Pt-Au nanocomposites. Atomistic simulations of hydrocarbons under shear between rigid Pt slabs using a reactive force field showed stress-induced changes in bonding through chain scission, a likely route towards the formation of these coatings. This novel demonstration of in situ tribochemical formation of self-lubricating films has significant impact potential in a wide range of engineering applications.

Here, we demonstrate coupled triple dot operation and charge sensing capability for the recently introduced quantum dot technology employing undoped Si/Si_0.8Ge_0.2 hetero-structures which also incorporate a single metal-gate layer to simplify fabrication. Si/SiGe hetero-structures with a Ge concentration of 20% rather than the more usual 30% typically encountered offer higher electron mobility. The devices consist of two in-plane parallel electron channels that host a double dot in one channel and a single dot in the other channel. In a device where the channels are sufficiently close a triple dot in a triangular configuration is induced leading to regions in the charge stability diagram where three charge-addition lines of different slope approach each other and anti-cross. In a device where the channels are further apart, the single dot charge-senses the double dot with relative change of ~2% in the sensor current.

The free energy reduction of a dislocation due to a Cottrell atmosphere of solutes is computed using a continuum model. We show that the free energy change is composed of near-core and far-field components. The far-field component can be computed analytically using the linearized theory of solid solutions. Near the core the linearized theory is inaccurate, and the near-core component must be computed numerically. The influence of interactions between solutes in neighbouring lattice sites is also examined using the continuum model. We show that this model is able to reproduce atomistic calculations of the nickel–hydrogen system, predicting hydride formation on dislocations. The formation of these hydrides leads to dramatic reductions in the free energy. Finally, the influence of the free energy change on a dislocation’s line tension is examined by computing the equilibrium shape of a dislocation shear loop and the activation stress for a Frank–Read source using discrete dislocation dynamics.

This paper presents a novel approach to the modeling and control of AC microgrids that contain spinning machines, power electronic inverters and energy storage devices. The inverters in the system can adjust their frequencies and power angles very quickly, so the modeling focuses on establishing a common reference frequency and angle in the microgrid based on the spinning machines. From this dynamic model, nonlinear Hamiltonian surface shaping and power flow control method is applied and shown to stabilize. From this approach the energy flow in the system is used to show the energy storage device requirements and limitations for the system. This paper first describes the model for a single bus AC microgrid with a Hamiltonian control, then extends this model and control to a more general class of multiple bus AC microgrids. Simulation results demonstrate the efficacy of the approach in stabilizing and optimization of the microgrid.

We perform epicentral relocations for a broad area using cross-correlation measurements made on Lg waves recorded at regional distances on a sparse station network. Using a two-step procedure (pairwise locations and cluster locations), we obtain final locations for 5623 events—3689 for all of China from 1985 to 2005 and 1934 for the Wenchuan area from May to August 2008. These high-quality locations comprise 20% of a starting catalog for all of China and 25% of a catalog for Wenchuan. Of the 1934 events located for Wenchuan, 1662 (86%) were newly detected. The final locations explain the residuals 89 times better than the catalog locations for all of China (3.7302–0.0417 s) and 32 times better than the catalog locations for Wenchuan (0.8413–0.0267 s). The average semimajor axes of the 95% confidence ellipses are 420 m for all of China and 370 m for Wenchuan. The average azimuthal gaps are 205° for all of China and 266° for Wenchuan. 98% of the station distances for all of China are over 200 km. The mean and maximum station distances are 898 and 2174 km. The robustness of our location estimates and various trade-offs and sensitivities is explored with different inversion parameters for the location, such as starting locations for iterative solutions and which singular values to include. Our results provide order-of-magnitude improvements in locations for event clusters, using waveforms from a very sparse far-regional network for which data are openly available.

Exterior acoustic problems occur in a wide range of applications, making the finite element analysis of such problems a common practice in the engineering community. Various methods for truncating infinite exterior domains have been developed, including absorbing boundary conditions, infinite elements, and more recently, perfectly matched layers (PML). PML are gaining popularity due to their generality, ease of implementation, and effectiveness as an absorbing boundary condition. PML formulations have been developed in Cartesian, cylindrical, and spherical geometries, but not ellipsoidal. In addition, the parallel solution of PML formulations with iterative solvers for the solution of the Helmholtz equation, and how this compares with more traditional strategies such as infinite elements, has not been adequately investigated. In this paper, we present a parallel, ellipsoidal PML formulation for acoustic Helmholtz problems. To faciliate the meshing process, the ellipsoidal PML layer is generated with an on-the-fly mesh extrusion. Though the complex stretching is defined along ellipsoidal contours, we modify the Jacobian to include an additional mapping back to Cartesian coordinates in the weak formulation of the finite element equations. This allows the equations to be solved in Cartesian coordinates, which is more compatible with existing finite element software, but without the necessity of dealing with corners in the PML formulation. Herein we also compare the conditioning and performance of the PML Helmholtz problem with infinite element approach that is based on high order basis functions. On a set of representative exterior acoustic examples, we show that high order infinite element basis functions lead to an increasing number of Helmholtz solver iterations, whereas for PML the number of iterations remains constant for the same level of accuracy. This provides an additional advantage of PML over the infinite element approach.

Short-period fundamental-mode Rayleigh waves (Rg) are commonly observed on seismograms of anthropogenic seismic events and shallow, naturally occurring tectonic earthquakes (TEs) recorded at local distances. In the Utah region, strong Rg waves traveling with an average group velocity of about 1:8 km=s are observed at ∼1 Hz on waveforms from shallow events (depth < 10 km) recorded at distances up to about 150 km. At these distances, Sg waves, which are direct shear waves traveling in the upper crust, are generally the dominant signals for TEs. In this study, we leverage the well-known notion that Rg amplitude decreases dramatically with increasing event depth to propose a new depth discriminant based on Rg-to-Sg spectral amplitude ratios. The approach is successfully used to discriminate shallow events (both earthquakes and anthropogenic events) from deeper TEs in the Utah region recorded at local distances (< 150 km) by the University of Utah Seismographic Stations (UUSS) regional seismic network. Using Mood’s median test, we obtained probabilities of nearly zero that the median Rg-to-Sg spectral amplitude ratios are the same between shallow events on the one hand (including both shallow TEs and anthropogenic events), and deeper earthquakes on the other, suggesting that there is a statistically significant difference in the estimated Rg-to-Sg ratios between the two populations. We also observed consistent disparities between the different types of shallow events (e.g., mining blasts vs. mining-induced earthquakes), implying that it may be possible to separate the subpopulations that make up this group. This suggests that using local distance Rg-to-Sg spectral amplitude ratios one can not only discriminate shallow events from deeper events but may also be able to discriminate among different populations of shallow events.

Acetaldehyde is an observed emission species and a key intermediate produced during the combustion and low-temperature oxidation of fossil and bio-derived fuels. Investigations into the low-temperature oxidation chemistry of acetaldehyde are essential to develop a better core mechanism and to better understand auto-ignition and cool flame phenomena. Here, the oxidation of acetaldehyde was studied at low-temperatures (528–946 K) in a jet-stirred reactor (JSR) with the corrected residence time of 2.7 s at 700 Torr. This work describes a detailed set of experimental results that capture the negative temperature coefficient (NTC) behavior in the low-temperature oxidation of acetaldehyde. The mole fractions of 28 species were measured as functions of the temperature by employing a vacuum ultra-violet photoionization molecular-beam mass spectrometer. To explain the observed NTC behavior, an updated mechanism was proposed, which well reproduces the concentration profiles of many observed peroxide intermediates. The kinetic analysis based on the updated mechanism reveals that the NTC behavior of acetaldehyde oxidation is caused by the competition between the O2-addition to and the decomposition of the CH3CO radical.

A variety of Earth surface and atmospheric sources generate low-frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth's surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult.We describe the deployment of four drifting microphone stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while travelling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves at 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 s.

For over a decade, velocimetry based techniques have been used to infer the electrical current delivered to dynamic materials properties experiments on pulsed power drivers such as the Z Machine. Though originally developed for planar load geometries, in recent years, inferring the current delivered to cylindrical coaxial loads has become a valuable diagnostic tool for numerous platforms. Presented is a summary of uncertainties that can propagate through the current inference technique when applied to expanding cylindrical anodes. An equation representing quantitative uncertainty is developed which shows the unfold method to be accurate to a few percent above 10 MA of load current.

Over the past decade, polyhedral meshing has been gaining popularity as a better alternative to tetrahedral meshing in certain applications. Within the class of polyhedral elements, Voronoi cells are particularly attractive thanks to their special geometric structure. What has been missing so far is a Voronoi mesher that is sufficiently robust to run automatically on complex models. In this video, we illustrate the main ideas behind the VoroCrust algorithm, highlighting both the theoretical guarantees and the practical challenges imposed by realistic inputs.

We study the problem of decomposing a volume bounded by a smooth surface into a collection of Voronoi cells. Unlike the dual problem of conforming Delaunay meshing, a principled solution to this problem for generic smooth surfaces remained elusive. VoroCrust leverages ideas from α-shapes and the power crust algorithm to produce unweighted Voronoi cells conforming to the surface, yielding the first provably-correct algorithm for this problem. Given an ϵ-sample on the bounding surface, with a weak σ-sparsity condition, we work with the balls of radius δ times the local feature size centered at each sample. The corners of this union of balls are the Voronoi sites, on both sides of the surface. The facets common to cells on opposite sides reconstruct the surface. For appropriate values of ϵ, σ and δ, we prove that the surface reconstruction is isotopic to the bounding surface. With the surface protected, the enclosed volume can be further decomposed into an isotopic volume mesh of fat Voronoi cells by generating a bounded number of sites in its interior. Compared to state-of-the-art methods based on clipping, VoroCrust cells are full Voronoi cells, with convexity and fatness guarantees. Compared to the power crust algorithm, VoroCrust cells are not filtered, are unweighted, and offer greater flexibility in meshing the enclosed volume by either structured grids or random samples.

© Ahmed Abdelkader, Chandrajit L. Bajaj, Mohamed S. Ebeida, Ahmed H. Mahmoud, Scott A. Mitchell, John D. Owens and Ahmad A. Rushdi; licensed under Creative Commons License CC-BY 34th Symposium on Computational Geometry (SoCG 2018). We study the problem of decomposing a volume bounded by a smooth surface into a collection of Voronoi cells. Unlike the dual problem of conforming Delaunay meshing, a principled solution to this problem for generic smooth surfaces remained elusive. VoroCrust leverages ideas from α-shapes and the power crust algorithm to produce unweighted Voronoi cells conforming to the surface, yielding the first provably-correct algorithm for this problem. Given an ϵ-sample on the bounding surface, with a weak σ-sparsity condition, we work with the balls of radius δ times the local feature size centered at each sample. The corners of this union of balls are the Voronoi sites, on both sides of the surface. The facets common to cells on opposite sides reconstruct the surface. For appropriate values of ϵ, σ and δ, we prove that the surface reconstruction is isotopic to the bounding surface. With the surface protected, the enclosed volume can be further decomposed into an isotopic volume mesh of fat Voronoi cells by generating a bounded number of sites in its interior. Compared to state-of-the-art methods based on clipping, VoroCrust cells are full Voronoi cells, with convexity and fatness guarantees. Compared to the power crust algorithm, VoroCrust cells are not filtered, are unweighted, and offer greater flexibility in meshing the enclosed volume by either structured grids or random samples.

Over the past decade, polyhedral meshing has been gaining popularity as a better alternative to tetrahedral meshing in certain applications. Within the class of polyhedral elements, Voronoi cells are particularly attractive thanks to their special geometric structure. What has been missing so far is a Voronoi mesher that is sufficiently robust to run automatically on complex models. In this video, we illustrate the main ideas behind the VoroCrust algorithm, highlighting both the theoretical guarantees and the practical challenges imposed by realistic inputs.

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. In this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results show that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μ m when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Last, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.

The scintillation anisotropy effect for proton recoil events has been investigated in five pure organic crystalline materials: Anthracene, trans-stilbene, p-terphenyl, bibenzyl, and diphenylacetylene (DPAC). These measurements include the characterization of the scintillation response for one hemisphere of proton recoil directions in each crystal. In addition to standard measurements of the total light output and pulse shape at each angle, the prompt and delayed light anisotropies are analyzed, allowing for the investigation of the singlet and triplet molecular excitation behaviors independently. This paper provides new quantitative and qualitative observations that make progress toward understanding the physical mechanisms behind the scintillation anisotropy. These measurements show that the relationship between the prompt and delayed light anisotropies is correlated with a crystal structure, as it changes between the pi-stacked crystal structure materials (anthracene and p-terphenyl) and the herringbone crystal structure materials (stilbene, bibenzyl, and DPAC). The observations are consistent with a model in which there are preferred directions of kinetic processes for the molecular excitations. These processes and the impact of their directional dependences on the scintillation anisotropy are discussed.

For over a decade, velocimetry based techniques have been used to infer the electrical current delivered to dynamic materials properties experiments on pulsed power drivers such as the Z Machine. Though originally developed for planar load geometries, in recent years inferring the current delivered to cylindrical coaxial loads has become a valuable diagnostic tool for numerous platforms. Previous work summarized uncertainties that can propagate through the current inference technique when applied to cylindrical anodes. The present work compensates for a known source of error generated when openings (slots) are cut into the cylindrical anode to allow optical diagnostic access to the load anode/cathode gap.

In the early 2000s, industry switched to multicore microprocessors to address semiconductors' speed and power limits. However, the change was unsuccessful, leading to dire claims that 'Moore's law is ending.' This column suggests that while the approach was sound, it needed a deeper architectural transformation. Industry has since discovered a suitable architecture, but work remains on software to support it.

This report summarizes the results of a two-year project funded by the U.S. Department of Energy's Solar Energy Technologies Office (SuNLaMP 1506) to evaluate the performance of high-temperature (>700 °C) particle receivers for concentrating solar power (see Appendix A for project information). In the first year, novel particle release patterns were designed and tested to increase the effective solar absorptance of the particle curtain. Modeling results showed that increasing the magnitude and frequency of different wave-like patterns increased the effective absorptance and thermal efficiency by several percentage points, depending on the mass flow rate. Tests showed that triangular-wave, square-wave, and parallel-curtain particle release patterns could be implemented and maintained at flow rates of ~10 kg/s/m. The second year of the project focused on the development and testing of particle mass-flow control and measurement methods. An automated slide gate controlled by the outlet temperature of the particles was designed and tested. Testing demonstrated that the resolution accuracy of the slide-gate positioning was less than ~1 mm, and the speed of the slide gate enabled rapid adjustments to accommodate changes in the irradiance to maintain a desired outlet temperature range. Different in-situ particle mass-flow measurement techniques were investigated, and two were tested. The in-situ microwave sensor was found to be unreliable and sensitive to variations in particle flow patterns. However, the in-situ weigh hopper using load cells was found to provide reliable and repeatable measurements of real-time in-situ particle mass flow. On-sun tests were performed to determine the thermal efficiency of the receiver as a function of mass flow rate, particle temperature, and irradiance. Models of the tests were also developed and compared to the tests.

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The complexity of radiation effects in a material's microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditions can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. This computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.

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The Crude Oil Characterization Research Study is designed to evaluate whether crude oils currently transported in North America, including those produced from “tight” formations, exhibit physical or chemical properties that are distinct from conventional crudes, and how these properties associate with combustion hazards that may be realized during transportation and handling. The current report presents results from Task 2, investigating which commercially available methods can accurately and reproducibly collect and analyze crude oils for vapor pressure and composition, including dissolved gases. This issue, Revision 1 – Winter Sampling, incorporates additional seasonal data and compositional analysis results that have become available since publication of a prior report, SAND2017-12482, released in December 2017. Both reports compare performance of commercially available methods to that of a well-established mobile laboratory system that currently serves as the baseline instrument system for the U.S. Strategic Petroleum Reserve Crude Oil Vapor Pressure Program. The experimental matrix evaluates the performance of selected methods for (i) capturing, transporting, and delivering hydrocarbon fluid samples from the field to the analysis laboratory, coupled with (ii) analyzing for properties related to composition and volatility of the oil, including vapor pressure, gas-oil ratio, and dissolved gases and light hydrocarbons. Several combinations of sample capture and analysis were observed to perform well in both summer and winter sampling environments, though conditions apply that need to be considered carefully for given applications. Methods that perform well from Task 2 will then be utilized in subsequent Task 3 (combustion studies) and Task 4 (compositional analyses of multiple crude types), to be addressed in subsequent reports.

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Sandia National Laboratories, New Mexico (SNL/NM) is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's (DOE) National Nuclear Security Administration (NNSA) under contract DE-NA0003525. The DOE/NNSA Sandia Field Office administers the contract and oversees contractor operations at the site.

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Facilities that manufacture, store or transport significant quantities of radiological material must protect against the risk posed by sabotage events. Much of the analysis of this type of event has been focused on the threat from a radiological dispersion device (RDD) or "dirty bomb" scenario, in which a malicious assailant would, by explosives or other means, loft a significant quantity of radioactive material into a plume that would expose and contaminate people and property. Although the consequences in cost and psychological terror would be severe, no intentional RDD terrorism events are on record. Conversely, incidents in which a victim or victims were maliciously exposed to a Radiological Exposure Device (RED), without dispersal of radioactive material, are well documented. This paper represents a technical basis for the threat profile related to the risk of nefarious use of an RED, including assailant and material characterization. Radioactive materials of concern are detailed in Appendix A.

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This report documents the installation of injection well TAV-INJ1 at the Technical Area-V (TA-V) Groundwater Area of Concern at Sandia National Laboratories, New Mexico (SNL/NM). The U.S. Department of Energy (DOE) and the management and operating contractor for Sandia National Laboratories beginning on May 1, 2017, National Technology & Engineering Solutions of Sandia, LLC (NTESS), hereinafter collectively referred to as DOE/NTESS, prepared this well installation report.

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The Gamma Detector Response and Analysis Software (GADRAS) team has enhanced the source term input for the creation of synthetic spectra. These enhancements include the following: allowing users to programmatically provide source information to GADRAS through memory, rather than through a string limited to 256 characters; allowing users to provide their own source decay database information; and updating the default GADRAS decay database to fix errors and include coincident gamma information.

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Marine hydrokinetic (MHK) devices generate electricity from the motion of tidal and ocean currents, as well as ocean waves, to provide an additional source of renewable energy available to the United States. These devices are a source of anthropogenic noise in the marine ecosystem and must meet regulatory guidelines that mandate a maximum amount of noise that may be generated. In the absence of measured levels from in situ deployments, a model for predicting the propagation of sound from an array of MHK sources in a real environment is essential. A set of coupled, linearized velocity-pressure equations in the time-domain are derived and presented in this paper, which are an alternative solution to the Helmholtz and wave equation methods traditionally employed. Discretizing these equations on a three-dimensional (3D), finite-difference grid ultimately permits a finite number of complex sources and spatially varying sound speeds, bathymetry, and bed composition. The solution to this system of equations has been parallelized in an acoustic-wave propagation package developed at Sandia National Labs, called Paracousti. This work presents the broadband sound pressure levels from a single source in two-dimensional (2D) ideal and Pekeris wave-guides and in a 3D domain with a sloping boundary. The paper concludes with demonstration of Paracousti for an array of MHK sources in a simple wave-guide.

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