The complex physical phenomenon of shock wave interaction with material heterogeneities has significant importance and nevertheless remains little understood. In many materials, the observed macroscale response to shock loading is governed by characteristics of the microstructure. Yet, the majority of computational studies aimed at predicting phenomena affected by these processes, such as the initiation and propagation of detonation waves in explosives or shock propagation in geological materials, employ continuum material and reactive burn model treatment. In an effort to highlight the grain-scale processes that underlie the observable effects in an energetic system, a grain-scale model for hexanitrostilbene (HNS) has been developed. The measured microstructures were used to produce synthetic computational representations of the pore structure, and a density functional theory molecular dynamics derived equation of state (EOS) was used for the fully dense HNS matrix. The explicit inclusion of the microstructure along with a fully dense EOS resulted in close agreement with historical shock compression experiments. More recent experiments on the dynamic reaction threshold were also reproduced by inclusion of a global kinetics model. The complete model was shown to reproduce accurately the expected response of this heterogeneous material to shock loading. Mesoscale simulations were shown to provide a clear insight into the nature of threshold behavior and are a way to understand complex physical phenomena.
Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclectic treatment in these circumstances, some of it being more qualitative and empirical. Here in this paper, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.
Despite the advances in the methods for fabricating nanoscale materials, critical issues remain, such as the difficulties encountered in anchoring, and the deterioration in their stability after integration with other components. These issues need to be addressed to further increase the scope of their applicability. In this study, using epitaxial mesoscopic host matrices, materials are spatially confined at the nanoscale, and are supported, anchored, and stabilized. They also exhibit properties distinct from the bulk counterparts proving their high quality nanoscale nature. ZnFe2O4 and SrTiO3 are used as the model confined material and host matrix, respectively. The ZnFe2O4 phases are spatially confined by the SrTiO3 mesoscopic matrix and have strongly enhanced ferrimagnetic properties as compared to bulk and plain thin films of ZnFe2O4, with a Curie temperature of ≈500 K. The results of a series of control experiments and characterization measurements indicate that cationic inversion, which originates from the high interface-to-volume ratio of the ZnFe2O4 phase in the ZnFe2O4–SrTiO3 nanocomposite film, is responsible for the magnetization enhancement. An exchange bias is observed, owing to the coexistence of ferrimagnetic and antiferromagnetic regions in the confined ZnFe2O4 phase. The magnetic properties are dependent on the ZnFe2O4 crystallite size, which can be controlled by the growth conditions.
Li metal is the preferred anode material for all-solid-state Li batteries. However, a stable plating and stripping of Li metal at the anode-solid electrolyte interface remains a significant challenge particularly at practically feasible current densities. This problem usually relates to high and/or inhomogeneous Li-electrode-electrolyte interfacial impedance and formation and growth of high-aspect-ratio dendritic Li deposits at the electrode-electrolyte interface, which eventually shunt the battery. To better understand details of Li metal plating, we use operando electron microscopy and Auger spectroscopy to probe nucleation, growth, and stripping of Li metal during cycling of a model solid-state Li battery as a function of current density and oxygen pressure. We find a linear correlation between the nucleation density of Li clusters and the charging rate in an ultrahigh vacuum, which agrees with a classical nucleation and growth model. Moreover, the trace amount of oxidizing gas (≈10-6 Pa of O2) promotes the Li growth in a form of nanowires due to a fine balance between the ion current density and a growth rate of a thin lithium-oxide shell on the surface of the metallic Li. Interestingly, increasing the partial pressure of O2 to 10-5 Pa resumes Li plating in a form of 3D particles. Our results demonstrate the importance of trace amounts of preexisting or ambient oxidizing species on lithiation processes in solid-state batteries.
Chairman Smith, Ranking Member Johnson, and distinguished members of the Committee on Science, Space, and Technology, I thank you for the opportunity to testify today on the role of science, engineering, and research at Sandia National Laboratories, one of the nation’s premiere national labs and the nation’s largest Federally Funded Research and Development Center (FFRDC) laboratory. I am Dr. Susan Seestrom, Sandia’s Associate Laboratories Director for Advanced Science & Technology (AST) and Chief Research Officer (CRO). As CRO I am responsible for research strategy, Laboratory Directed Research & Development (LDRD), partnerships strategy, and technology transfer. As director and line manager for AST I manage capabilities and mission delivery across a variety of the physical and mathematical sciences and engineering disciplines, such as pulsed power, radiation effects, major environmental testing, high performance computing, and modeling and simulation.
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.
Control and manipulation of polarization is an important topic for imaging and light matter interactions. In the infrared regime, the large wavelengths make wire grid polarizers a viable option, as it is possible to create periodic arrays of metallic wires at that scale. The recent advent of metamaterials has spurred an increase in non-traditional polarizer motifs centred around more complicated repeat units, which potentially provide more functionality. In this paper we explore the use of two-dimensional (2D) arrays of single and back-to-back vertically oriented cross dipoles arranged in a cubic in-plane silicon matrix. Here, we show that both single and back-to-back versions have higher rejection ratios and larger bandwidths than either wire grid polarizers or 2D arrays of linear dipoles.
Solid-state hydrogen storage materials undergo complex phase transformations whose kinetics is often limited by hydrogen diffusion. Among metal hydrides, palladium hydride undergoes a diffusional phase transformation upon hydrogen uptake, during which the hydrogen diffusivity varies with hydrogen composition and temperature. Here we perform robust statistically-averaged molecular dynamics simulations to obtain a well-converged analytical expression for hydrogen diffusivity in bulk palladium that is valid throughout all stages of the reaction. Our studies confirm significant dependence of the diffusivity on composition and temperature that elucidate key trends in the available experimental measurements. Whereas at low hydrogen compositions, a single process dominates, at high hydrogen compositions, diffusion is found to exhibit behavior consistent with multiple hopping barriers. Further analysis, supported by nudged elastic band computations, suggests that the multi-barrier diffusion can be interpreted as two distinct mechanisms corresponding to hydrogen-rich and hydrogen-poor local environments.
Many important chemical and biochemical processes in the condensed phase are notoriously difficult to simulate numerically. Often, this difficulty arises from the complexity of simulating dynamics resulting from coupling to structured, mesoscopic baths, for which no separation of time scales exists and statistical treatments fail. A prime example of such a process is vibrationally assisted charge or energy transfer. A quantum simulator, capable of implementing a realistic model of the system of interest, could provide insight into these processes in regimes where numerical treatments fail. We take a first step towards modeling such transfer processes using an ion-trap quantum simulator. By implementing a minimal model, we observe vibrationally assisted energy transport between the electronic states of a donor and an acceptor ion augmented by coupling the donor ion to its vibration. We tune our simulator into several parameter regimes and, in particular, investigate the transfer dynamics in the nonperturbative regime often found in biochemical situations.
The burning core of an inertial confinement fusion (ICF) plasma produces bright x-rays at stagnation that can directly diagnose core conditions essential for comparison to simulations and understanding fusion yields. These x-rays also backlight the surrounding shell of warm, dense matter, whose properties are critical to understanding the efficacy of the inertial confinement and global morphology. In this work, we show that the absorption and fluorescence spectra of mid-Z impurities or dopants in the warm dense shell can reveal the optical depth, temperature, and density of the shell and help constrain models of warm, dense matter. This is illustrated by the example of a high-resolution spectrum collected from an ICF plasma with a beryllium shell containing native iron impurities. Lastly, analysis of the iron K-edge provides model-independent diagnostics of the shell density (2.3 × 1024 e/cm3) and temperature (10 eV), while a 12-eV red shift in Kβ and 5-eV blue shift in the K-edge discriminate among models of warm dense matter: Both shifts are well described by a self-consistent field model based on density functional theory but are not fully consistent with isolated-atom models using ad-hoc density effects.
The shock Hugoniot for full-density and porous CeO2 was investigated in the liquid regime using ab initio molecular dynamics (AIMD) simulations with Erpenbeck's approach based on the Rankine-Hugoniot jump conditions. The phase space was sampled by carrying out NVT simulations for isotherms between 6000 and 100 000 K and densities ranging from ρ=2.5 to 20g/cm3. The impact of on-site Coulomb interaction corrections +U on the equation of state (EOS) obtained from AIMD simulations was assessed by direct comparison with results from standard density functional theory simulations. Classical molecular dynamics (CMD) simulations were also performed to model atomic-scale shock compression of larger porous CeO2 models. Results from AIMD and CMD compression simulations compare favorably with Z-machine shock data to 525 GPa and gas-gun data to 109 GPa for porous CeO2 samples. Using results from AIMD simulations, an accurate liquid-regime Mie-Grüneisen EOS was built for CeO2. In addition, a revised multiphase SESAME-Type EOS was constrained using AIMD results and experimental data generated in this work. This study demonstrates the necessity of acquiring data in the porous regime to increase the reliability of existing analytical EOS models.
Two dimensional SiC-air phononic crystals have been modeled, fabricated, and tested with a measured bandgap ranging from 665 to 693 MHz. Snowflake air inclusions on a hexagonal lattice were used for the phononic crystal. By manipulating the phononic crystal lattice and inserting circular inclusions, a waveguide was created at 680 MHz. The combined insertion loss and propagation loss for the waveguide is 8.2 dB, i.e., 39% of the energy is guided due to the high level of the confinement afforded by the phononic crystal. The SiC-air phononic crystals and waveguides were fabricated using a CMOS-compatible process, which allows for seamless integration of these devices into wireless communication systems operating at microwave frequencies.
Traditional (macro-) economic impact analysis has a role in the long-run analysis of the effects of changes in resilience, since in the long-run the economy adjusts to the microeconomic impacts through various mechanisms (Kunreuther & Roth, 1998). However, measures of economic health, growth, or expansion are not sufficient for measuring resilience. The majority of infrastructure in the United States is privately owned and operated or is managed through some private-public arrangement. Most effects from changes in resilience should be assessed through short-run microeconomic analysis since the actions of firms will be spurred by internal economic decisionmaking that will have immediate impacts on local economies. Any forthcoming efforts to include resilience in the economic impacts of long duration EP outages must accommodate the private and simultaneously public nature of the EP infrastructure as well as its role as lifeline infrastructure. Resilience metrics and methodologies will only be helpful to stakeholders if these metrics help them understand the value of improvements to the resilience of communities, infrastructures, or industries. In their paper, Schellenberg et al. (2018) have provided a well thought out "lay of the lane of the common methods of estimating the economic costs of EP disruptions, which includes discussion of the difference between costs of outage and regional economic modeling, strengths and weaknesses of methods, the difficulty in incorporating resilience, data collection and availability issues, and recommendations for future research.
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. Here, 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.
Lavina, Barbara; Kim, Eunja; Cynn, Hyunchae; Weck, Philippe F.; Seaborg, Kelly; Siska, Emily; Meng, Yue; Evans, William
Using combined experimental and computational approaches, we show that at 43 GPa and 1300 K gallium phosphide adopts the super-Cmcm structure, here indicated with its Pearson notation oS24. First-principles enthalpy calculations demonstrate that this structure is more thermodynamically stable above ∼20 GPa than previously proposed polymorphs. In contrast to other polymorphs, the oS24 phase shows a strong bonding differentiation and distorted fivefold coordination geometries of both P atoms. The shortest bond of the phase is a single covalent P-P bond measuring 2.171(11) Å at synthesis pressure. Phosphorus dimerization in GaP sheds light on the nature of the super-Cmcm phase and provides critical new insights into the high-pressure polymorphism of octet semiconductors. Bond directionality and anisotropy explain the relatively low symmetry of this high-pressure phase.
Fatigue crack growth rate (FCGR) data were measured in high pressure hydrogen gas versus stress intensity factor range (ΔK) in specimens removed from a X100 welded steel pipe. Three distinct regions of the pipe weld were examined: base metal, weld fusion zone, and heat affected zone. Tests were performed at a load ratio (R) of 0.5, frequency of 1 Hz, and at a hydrogen gas pressure of 21 MPa. Tests were also performed in air at 10 Hz as a reference. Fatigue crack growth rates were observed to be over an order of magnitude higher for tests performed in hydrogen compared to the rates from tests in air. Residual stress measurements were collected on identical specimens cut from the base metal, weld, and heat affected zone to account for their influence on measured FCGR data. The slitting method provided residual stress and residual stress intensity factor (Kres), the effect of which was removed from the FCGR data using Knorm in order to provide a more direct comparison of crack growth resistance of the base metal, weld and heat affected zone. Prior to accounting for residual stress, FCGR in hydrogen gas appeared to be highest in the weld fusion zone. Furthermore, after accounting for residual stress effects, the weld fusion zone FCGR data converged to the base metal FCGR data, which underscores the importance of accounting for residual stress effects when assessing fatigue performance.
Various technologies presented herein relate to enhancing mixing inside a combustion chamber to form one or more locally premixed mixtures comprising fuel and charge-gas with low peak fuel to charge-gas ratios to enable minimal, or no, generation of soot and other undesired emissions during ignition and subsequent combustion of the locally premixed mixtures. To enable sufficient mixing of the fuel and charge-gas, a jet of fuel can be directed to pass through a bore of a duct causing charge-gas to be drawn into the bore creating turbulence to mix the fuel and the drawn charge-gas. The duct can be located proximate to an opening in a tip of a fuel injector. The duct can comprise of one or more holes along its length to enable charge-gas to be drawn into the bore, and further, the duct can cool the fuel and/or charge-gas prior to combustion.
Muniz, Collin N.; Patel, Hiral; Fast, Dylan B.; Rohwer, Lauren E.S.; Reinheimer, Eric W.; Dolgos, Michelle; Graham, Matt W.; Nyman, May
Rare-earth (RE) coordination polymers are infinitely tailorable to yield luminescent materials for various applications. Here we described the synthesis of a heterometallic rare-earth coordination compound ((CH3)2SO)3(RE)NbO(C2O4)3 ((CH3)2SO) = dimethylsulfoxide, DMSO, (C2O2 = oxalate), (RE=La, Ce, Pr, Nd, Sm, Eu, Gd, Tb). The structure was obtained from single crystal X-ray diffraction of the La analogue. The Nb˭O and DMSO terminal-bonding character guides assembly of an open framework structure with noncentrosymmetric RE-coordination geometry, and large spacing between the RE centers. A second structure was observed by PXRD for the smaller rare earths (Dy, Ho, Er, Yb); this structure has not yet been determined. The materials were further characterized using FTIR, and photoluminescence measurements. Characteristic excitation and emission transitions were observed for RE = Nd, Sm, Eu, and Tb. Quantum yield (QY) measurements were performed by exciting Eu and Tb analoges at 394 nm (QY 66%) and 464 nm (QY 71%) for Eu; and 370 nm (QY=40%) for Tb. We attribute the high QY and bright luminescence to two main structure-function properties of the system; namely the absence of water in the structure, and absence of concentration quenching.
Chen, Yongqiang; Xie, Quan; Sari, Ahmad; Brady, Patrick V.; Saeedi, Ali
Wettability of the oil/brine/rock system is an essential petro-physical parameter which governs subsurface multiphase flow behaviour and the distribution of fluids, thus directly affecting oil recovery. Recent studies [1–3] show that manipulation of injected brine composition can enhance oil recovery by shifting wettability from oil-wet to water-wet. However, what factor(s) control system wettability has not been completely elucidated due to incomplete understanding of the geochemical system. To isolate and identify the key factors at play we used SO42—free solutions to examine the effect of salinity (formation brine/FB, 10 times diluted formation brine/10 dFB, and 100 times diluted formation brine/100 dFB) on the contact angle of oil droplets at the surface of calcite. We then compared contact angle results with predictions of surface complexation by low salinity water using PHREEQC software. We demonstrate that the conventional dilution approach likely triggers an oil-wet system at low pH, which may explain why the low salinity water EOR-effect is not always observed by injecting low salinity water in carbonated reservoirs. pH plays a fundamental role in the surface chemistry of oil/brine interfaces, and wettability. Our contact angle results show that formation brine triggered a strong water-wet system (35°) at pH 2.55, yet 100 times diluted formation brine led to a strongly oil-wet system (contact angle = 175°) at pH 5.68. Surface complexation modelling correctly predicted the wettability trend with salinity; the bond product sum ([>CaOH2+][–COO−] + [>CO3−][–NH+] + [>CO3−][–COOCa+]) increased with decreasing salinity. At pH < 6 dilution likely makes the calcite surface oil-wet, particularly for crude oils with high base number. Yet, dilution probably causes water wetness at pH > 7 for crude oils with high acid number.
Absolute Hugoniot measurements for empty plastic foams at ∼10% of solid polystyrene density and supporting rad-hydro simulation results are reported. Planar foam slabs, ∼400 μm thick and ∼500 μm wide, some of which were covered with a 10 μm solid plastic ablator, were directly driven by 4 ns long Nike krypton-fluoride 248 nm wavelength laser pulses that produced strong shock waves in the foam. The shock and mass velocities in our experiments were up to 104 km/s and 84 km/s, respectively, and the shock pressures up to ∼9 Mbar. The motion of the shock and ablation fronts was recorded using side-on monochromatic x-ray imaging radiography. The steadiness of the observed shock and ablation fronts within ∼1% has been verified. The Hugoniot data inferred from our velocity measurements agree with the predictions of the SESAME and CALEOS equation-of-state models near the highest pressure ∼9 Mbar and density compression ratio ∼5. In the lower pressure range 2-5 Mbar, a lower shock density compression is observed than that predicted by the models. Possible causes for this discrepancy are discussed.
A finite element numerical analysis model has been constructed that consists of a mesh that effectively captures the geometries of Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) site and multimechanism deformation (M-D) salt constitutive model using the daily data of actual wellhead pressure and oil–brine interface location. The salt creep rate is not uniform in the salt dome, and the creep test data for BC salt are limited. Therefore, the model calibration is necessary to simulate the geomechanical behavior of the salt dome. The cavern volumetric closures of SPR caverns calculated from CAVEMAN are used as the field baseline measurement. The structure factor, A2, and transient strain limit factor, K0, in the M-D constitutive model are used for the calibration. The value of A2, obtained experimentally from BC salt, and the value of K0, obtained from Waste Isolation Pilot Plant salt, are used for the baseline values. To adjust the magnitude of A2 and K0, multiplication factors A2F and K0F are defined, respectively. The A2F and K0F values of the salt dome and salt drawdown skins surrounding each SPR cavern have been determined through a number of back analyses. The cavern volumetric closures calculated from this model correspond to the predictions from CAVEMAN for six SPR caverns. Therefore, this model is able to predict behaviors of the salt dome, caverns, caprock, and interbed layers. The geotechnical concerns associated with the BC site from this analysis will be explained in a follow-up paper.
We demonstrate a statistical procedure for learning a high-order eddy viscosity model (EVM) from experimental data and using it to improve the predictive skill of a Reynoldsaveraged Navier-Stokes (RANS) simulator. The method is tested in a three-dimensional (3D), transonic jet-in-crossflow (JIC) configuration. The process starts with a cubic eddy viscosity model (CEVM) developed for incompressible flows. It is fitted to limited experimental JIC data using shrinkage regression. The shrinkage process removes all the terms from the model, except an intercept, a linear term, and a quadratic one involving the square of the vorticity. The shrunk eddy viscosity model is implemented in an RANS simulator and calibrated, using vorticity measurements, to infer three parameters. The calibration is Bayesian and is solved using a Markov chain Monte Carlo (MCMC) method. A 3D probability density distribution for the inferred parameters is constructed, thus quantifying the uncertainty in the estimate. The phenomenal cost of using a 3D flow simulator inside an MCMC loop is mitigated by using surrogate models ("curve-fits"). A support vector machine classifier (SVMC) is used to impose our prior belief regarding parameter values, specifically to exclude nonphysical parameter combinations. The calibrated model is compared, in terms of its predictive skill, to simulations using uncalibrated linear and CEVMs. We find that the calibrated model, with one quadratic term, is more accurate than the uncalibrated simulator. The model is also checked at a flow condition at which the model was not calibrated.
This paper presents the application of a theoretically developed method that provides plasma parameter solution space information from measured RF attenuation that occurs during reentry. The purpose is to provide reentry plasma parameter information from the communication signal attenuation. The theoretical development centers around the attenuation and the complex index of refraction. The methodology uses an imaginary index of the refraction matching algorithm with a tolerance to find suitable solutions that satisfy the theory. The imaginary matching terms are then used to determine the real index of refraction resulting in the complex index of refraction. Then a filter is used to reject nonphysical solutions. Signal attenuation-based plasma parameter properties investigated include the complex index of refraction, plasma frequency, electron density, collision frequency, propagation constant, attenuation constant, phase constant, complex plasma conductivity, and electron mobility. RF plasma thickness attenuation is investigated and compared to the literature. Similar plasma thickness for a specific signal attenuation can have different plasma properties.
We consider the utilization of a computational model to guide the optimal acquisition of experimental data to inform the stochastic description of model input parameters. Our formulation is based on the recently developed consistent Bayesian approach for solving stochastic inverse problems, which seeks a posterior probability density that is consistent with the model and the data in the sense that the push-forward of the posterior (through the computational model) matches the observed density on the observations almost everywhere. Given a set of potential observations, our optimal experimental design (OED) seeks the observation, or set of observations, that maximizes the expected information gain from the prior probability density on the model parameters. We discuss the characterization of the space of observed densities and a computationally efficient approach for rescaling observed densities to satisfy the fundamental assumptions of the consistent Bayesian approach. Numerical results are presented to compare our approach with existing OED methodologies using the classical/statistical Bayesian approach and to demonstrate our OED on a set of representative partial differential equations (PDE)-based models.
The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.
Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate compressed sensing (CS) as an in situ method to reduce the size of the data as it is being generated during a large-scale simulation. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured datasets, such as image data, we investigate its usefulness for point clouds such as unstructured mesh datasets often found in finite element simulations. We sample using a technique that exhibits low coherence with tree wavelets found to be suitable for point clouds. We reconstruct using the stagewise orthogonal matching pursuit algorithm that we improved to facilitate automated use in batch jobs. We analyze the achievable compression ratios and the quality and accuracy of reconstructed results at each compression ratio. In the considered case studies, we are able to achieve compression ratios up to two orders of magnitude with reasonable reconstruction accuracy and minimal visual deterioration in the data. Our results suggest that, compared to other compression techniques, CS is attractive in cases where the compression overhead has to be minimized and where the reconstruction cost is not a significant concern.
The delocalization of x-ray signals limits the spatial resolution in atomic-scale elemental mapping by scanning transmission electron microscopy (STEM) using energy-dispersive x-ray spectroscopy (EDS). In this study, using a SrTiO 3 [001] single crystal, we show that the x-ray localization to atomic columns is strongly dependent on crystal thickness, and a thin crystal is critical for improving the spatial resolution in atomic-scale EDS mapping. A single-frame scanning technique is used in this study instead of the multiple-frame technique to avoid peak broadening due to tracking error. The strong thickness dependence is realized by measuring the full width at half maxima (FWHM) as well as the peak-to-valley (P/V) ratio of the EDS profiles for Ti K and Sr K + L, obtained at several crystal thicknesses. A FWHM of about 0.16 nm and a P/V ratio of greater than 7.0 are obtained for Ti K for a crystal thickness of less than 20 nm. With increasing crystal thickness, the FWHM and P/V ratio increases and decreases, respectively, indicating the advantage of using a thin crystal for high-resolution EDS mapping.
This paper explores the viability of using counterfactual reasoning for impact analyses when understanding and responding to "beyond-design-basis" nuclear power plant accidents. Currently, when a severe nuclear power plant accident occurs, plant operators rely on Severe Accident Management Guidelines. However, the current guidelines are limited in scope and depth: for certain types of accidents, plant operators would have to work to mitigate the damage with limited experience and guidance for the particular situation. We aim to fill the need for comprehensive accident support by using a dynamic Bayesian network to aid in the diagnosis of a nuclear reactor's state and to analyze the impact of possible response measures. The dynamic Bayesian network, DBN, offers an expressive representation of the components and relationships that make up a complex causal system. For this reason, and for its tractable reasoning, the DBN supports a functional model for the intricate operations of nuclear power plants. In this domain, it is also pertinent that a Bayesian network can be composed of both probabilistic and knowledge-based components. Though probabilities can be calculated from simulated models, the structure of the network, as well as the value of some parameters, must be assigned by human experts. Since dynamic Bayesian network-based systems are capable of running better-than-real-time situation analyses, they can support both current event and alternate scenario impact analyses.
ACM Transactions on Architecture and Code Optimization
Deng, Bobin; Srikanth, Sriseshan; Hein, Eric R.; Conte, Thomas M.; Debenedictis, Erik; Cook, Jeanine; Frank, Michael P.
Dennard scaling has ended. Lowering the voltage supply (Vdd) to sub-volt levels causes intermittent losses in signal integrity, rendering further scaling (down) no longer acceptable as a means to lower the power required by a processor core. However, it is possible to correct the occasional errors caused due to lower Vddin an efficient manner and effectively lower power. By deploying the right amount and kind of redundancy, we can strike a balance between overhead incurred in achieving reliability and energy savings realized by permitting lower Vdd. One promising approach is the Redundant Residue Number System (RRNS) representation. Unlike other error correcting codes, RRNS has the important property of being closed under addition, subtraction and multiplication, thus enabling computational error correction at a fraction of an overhead compared to conventional approaches. We use the RRNS scheme to design a Computationally-Redundant, Energy-Efficient core, including the microarchitecture, Instruction Set Architecture (ISA) and RRNS centered algorithms. From the simulation results, this RRNS system can reduce the energy-delay-product by about 3× for multiplication intensive workloads and by about 2× in general, when compared to a non-error-correcting binary core.
Molecular dynamics (MD) simulations and experimental evaporation were applied to study the growth of evaporated (Cu)ZnTe on mono- and polycrystalline CdTe. The simulated structures show polytypism and polycrystallinity, including texturing and grain boundaries, diffusion, and other phenomena in excellent qualitative agreement with experimental atomic probe tomography, transmission electron microscope, and secondary ion mass spectrometry. Results show formation of Cu clusters in nonstoichiometric growths even at early stages of deposition. Results also show significantly faster diffusion along defected regions (uncorrelated CdTe grain boundaries) as compared with more highly crystalline areas (high-symmetry grain boundaries and pristine regions). Activation energies and pre-exponential factors of Cu, Zn, and Te diffusion were determined using simulation. The MD model captures crystal growth phenomena with a high degree of fidelity.
This paper presents the model-based design and evaluation of an instrument that estimates incident neutron direction using the kinematics of neutron scattering by hydrogen-1 nuclei in an organic scintillator. The instrument design uses a single, nearly contiguous volume of organic scintillator that is internally subdivided only as necessary to create optically isolated pillars, i.e., long, narrow parallelepipeds of organic scintillator. Scintillation light emitted in a given pillar is confined to that pillar by a combination of total internal reflection and a specular reflector applied to the four sides of the pillar transverse to its long axis. The scintillation light is collected at each end of the pillar using a photodetector, e.g., a microchannel plate photomultiplier (MCP-PM) or a silicon photomultiplier (SiPM). In this optically segmented design, the (x,y) position of scintillation light emission (where the x and y coordinates are transverse to the long axis of the pillars) is estimated as the pillar's (x,y) position in the scintillator “block”, and the z-position (the position along the pillar's long axis) is estimated from the amplitude and relative timing of the signals produced by the photodetectors at each end of the pillar. The neutron's incident direction and energy is estimated from the (x,y,z)-positions of two sequential neutron–proton scattering interactions in the scintillator block using elastic scatter kinematics. For proton recoils greater than 1 MeV, we show that the (x,y,z)-position of neutron–proton scattering can be estimated with < 1 cm root-mean-squared [RMS] error and the proton recoil energy can be estimated with < 50 keV RMS error by fitting the photodetectors’ response time history to models of optical photon transport within the scintillator pillars. Finally, we evaluate several alternative designs of this proposed single-volume scatter camera made of pillars of plastic scintillator (SVSC-PiPS), studying the effect of pillar dimensions, scintillator material (EJ-204, EJ-232Q and stilbene), and photodetector (MCP-PM vs. SiPM) response vs. time. We demonstrate that the most precise estimates of incident neutron direction and energy can be obtained using a combination of scintillator material with high luminosity and a photodetector with a narrow impulse response. Specifically, we conclude that an SVSC-PiPS constructed using EJ-204 (a high luminosity plastic scintillator) and an MCP-PM will produce the most precise estimates of incident neutron direction and energy.
Directed energy deposited (DED) and forged austenitic stainless steels possess dissimilar microstructures but can exhibit similar mechanical properties. In this study, annealing was used to evolve the microstructure of both conventional wrought and DED type 304L austenitic stainless steels, and significant differences were observed. In particular, the density of geometrically necessary dislocations and hardness were used to probe the evolution of the microstructure and properties. Forged type 304L exhibited the expected decrease in measured dislocation density and hardness as a function of annealing temperature. The more complex microstructure–property relationship observed in the DED type 304L material is attributed to compositional heterogeneities in the solidification microstructure.
Diffusion of point defects during irradiation is simulated via a two-way coupling between mechanical stress and defect diffusion in iron. This diffusion is based on a modified chemical potential that includes not only the local concentration of radiation-induced defects, but also the influence of the residual stress field from both the microstructure (i.e. dislocations or grain boundaries) and the eigenstrain caused by the defects themselves. Defect flux and concentration rates are derived from this chemical potential using Fick's first and second laws. Mean field rate theory is incorporated to model the annihilation of Frenkel pairs, and increased annihilation near grain boundaries is included based on the elastic energy of each grain boundary. Mechanical equilibrium is coupled with diffusion by computing eigenstrain from point defects and adding this to the total strain. Intrinsic stresses associated with the dislocations and grain boundaries are calculated using dislocation and disclination mechanics. Through this two-way-coupled model, regions of low concentration are seen near grain boundaries, and sink efficiency is calculated for different types of microstructure. The results show that the two-way mechanical coupling has a strong influence on sink efficiency for dislocation loops. The results also suggest that misorientation is a poor metric for determining sink efficiency, with sink density and elastic energy being much more informative.
Presented are the results from the liner ablation experiments conducted at 550 kA on the Michigan Accelerator for Inductive Z-Pinch Experiments. These experiments were performed to evaluate a hypothesis that the electrothermal instability (ETI) is responsible for the seeding of magnetohydrodynamic instabilities and that the cumulative growth of ETI is primarily dependent on the material-specific ratio of critical temperature to melting temperature. This ratio is lower in refractory metals (e.g., tantalum) than in non-refractory metals (e.g., aluminum or titanium). The experimental observations presented herein reveal that the plasma-vacuum interface is remarkably stable in tantalum liner ablations. This stability is particularly evident when contrasted with the observations from aluminum and titanium experiments. These results are important to various programs in pulsed-power-driven plasma physics that depend on liner implosion stability. Examples include the magnetized liner inertial fusion (MagLIF) program and the cylindrical dynamic material properties program at Sandia National Laboratories, where liner experiments are conducted on the 27-MA Z facility.
The properties of hot, dense plasmas generated by the irradiation of GaAs targets by the Titan laser at Lawrence Livermore National Laboratory were determined by the analysis of high resolution K shell spectra in the 9 keV to 11 keV range. The laser parameters, such as relatively long pulse duration and large focal spot, were chosen to produce a steady-state plasma with minimal edge gradients, and the time-integrated spectra were compared to non-LTE steady state spectrum simulations using the FLYCHK and NOMAD codes. The bulk plasma streaming velocity was measured from the energy shifts of the Ga He-like transitions and Li-like dielectronic satellites. The electron density and the electron energy distribution, both the thermal and the hot non-thermal components, were determined from the spectral line ratios. After accounting for the spectral line broadening contributions, the plasma turbulent motion was measured from the residual line widths. The ionization balance was determined from the ratios of the He-like through F-like spectral features. The detailed comparison of the experimental Ga spectrum and the spectrum simulated by the FLYCHK code indicates two significant discrepancies, the transition energy of a Li-like dielectronic satellite (designated t) and the calculated intensity of a He-like line (x), that should lead to improvements in the kinetics codes used to simulate the X-ray spectra from highly-charged ions.
Criegee intermediates (CIs), carbonyl oxides formed in ozonolysis of alkenes, play key roles in the troposphere. The decomposition of CIs can be a significant source of OH to the tropospheric oxidation cycle especially during nighttime and winter months. A variety of model-measurement studies have estimated surface-level stabilized Criegee intermediate (sCI) concentrations on the order of 1 × 104 cm-3 to 1 × 105 cm-3, which makes a non-negligible contribution to the oxidising capacity in the terrestrial boundary layer. The reactions of sCI with the water monomer and the water dimer have been found to be the most important bimolecular reactions to the tropospheric sCI loss rate, at least for the smallest carbonyl oxides; the products from these reactions (e.g. hydroxymethyl hydroperoxide, HMHP) are also of importance to the atmospheric oxidation cycle. The sCI can oxidise SO2 to form SO3, which can go on to form a significant amount of H2SO4 which is a key atmospheric nucleation species and therefore vital to the formation of clouds. The sCI can also react with carboxylic acids, carbonyl compounds, alcohols, peroxy radicals and hydroperoxides, and the products of these reactions are likely to be highly oxygenated species, with low vapour pressures, that can lead to nucleation and SOA formation over terrestrial regions.
The design, fabrication, and performance of InGaAs and InGaP/GaAs microcells are presented. These cells are integrated with a Si wafer providing a path for insertion in hybrid concentrated photovoltaic modules. Comparisons are made between bonded cells and cells fabricated on their native wafer. The bonded cells showed no evidence of degradation in spite of the integration process that involved significant processing including the removal of the III-V substrate.
A measurement instrument utilizing dual, chromatic, confocal, distance sensors has been jointly developed by General Atomics and Sandia National Laboratories (SNL) for thickness and flatness measurement of target components used in dynamic materials properties (DMP) experiments on the SNL Z-Machine (Z). Compared to previous methods used in production of these types of targets, the tool saves time and yields a 4× reduction in thickness uncertainty which is one of the largest sources of error in equation of state measurements critical to supporting the National Nuclear Security Administration Stockpile Stewardship program and computer modeling of high energy density experiments. It has numerous differences from earlier instruments operating on the dual confocal sensor principle to accommodate DMP components including larger lateral travel, longer working distance, ability to measure flatness in addition to thickness, built-in thickness calibration standards for quickly checking calibration before and after each measurement, and streamlined operation. Thickness and flatness of 0.2- to 3.3-mm-thick sections of diamond-machined copper and aluminum can be measured to submicron accuracy. Sections up to 6 mm thick can be measured with as-yet undetermined accuracy. Samples must have one surface which is flat to within 300 µm, lateral dimensions of no more than 50 ×50 mm, and height less than 40 mm.
Grid operators are increasingly turning to advanced grid-support functions in distributed energy resources (DER) to assist with distribution circuit voltage regulation, bulk system frequency control, and power system protection. The U.S. DER certification standard, Underwriters Laboratories (UL) 1741, was revised in September 2016 to add test procedures for multiple grid-support functions. Sandia National Laboratories, SunSpec Alliance, and growing community of collaborators have undertaken a multiyear effort to create an open-source system validation platform (SVP) that automates DER interconnection and interoperability test procedures by communicating with grid simulators, photovoltaic (PV) simulators, data acquisition systems, and interoperable equipment under test. However, the power hardware required for generating the test conditions may be untenable for many organizations. Herein, we discuss development of the SVP testing capabilities for UL 1741 tests utilizing a controller hardware-in-The-loop testbed that precludes the need for power hardware using a 34.5 kW Austrian Institute of Technology smart grid controller. Analysis of normal ramp rate, soft start ramp rate, specified power factor, volt-VAr, and frequency-watt advanced grid functions, and the effectiveness of the UL 1741 test protocols are included.
This study shows fuel film measurements in a spark-ignited direct injection engine using refractive index matching (RIM). The RIM technique is applied to measure the fuel impingement of a high research octane number gasoline fuel with 30 vol% ethanol content at two intake pressures and coolant temperatures. Measurements are conducted for an alkylate fuel at one operating case, as well. It is shown that the fuel volume on the piston surface increases for lower intake pressure and lower coolant temperature and that the alkylate fuel shows very little spray impingement. The fuel films can be linked to increased soot emissions. A detailed description of the calibration technique is provided and measurement uncertainties are discussed. The dependency of the RIM signal on refractive index changes is measured. The RIM technique provides quantitative film thickness measurements up to 0.9 µm in this engine. For thicker films, semi-quantitative results of film thickness can be utilized to study the distribution of impinged fuel.
This review article is dedicated to the Dynamic Behavior of Materials Technical Division for celebrating the 75th anniversary of the Society for Experimental Mechanics (SEM). Understanding dynamic behavior of geomaterials is critical for analyzing and solving engineering problems of various applications related to underground explosions, seismic, airblast, and penetration events. Determining the dynamic tensile response of geomaterials has been a great challenge in experiments due to the nature of relatively low tensile strength and high brittleness. Various experimental approaches have been made in the past century, especially in the most recent half century, to understand the dynamic behavior of geomaterials in tension. In this review paper, we summarized the dynamic tensile experimental techniques for geomaterials that have been developed. The major dynamic tensile experimental techniques include dynamic direct tension, dynamic split tension, and spall tension. All three of the experimental techniques are based on Hopkinson or split Hopkinson (also known as Kolsky) bar techniques and principles. Uniqueness and limitations for each experimental technique are also discussed.
Backprojection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. While backprojection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed and simplified to overcome imaging challenges. Real data issues include aliased station spacing, inadequate array aperture, inaccurate velocity model, low signal-to-noise ratio, large noise bursts and varying waveform polarity. We compare the performance of backprojection with four previously used data pre-processing methods: raw waveform, envelope, short-termaveraging/long-termaveraging and kurtosis. Our primary goal is to detect and locate events smaller than noise by stacking prior to detection to improve the signal-to-noise ratio. The objective is to identify an optimized strategy for automated imaging that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the source images, preserves magnitude, and considers computational cost. Imaging method performance is assessed using a real aftershock data set recorded by the dense AIDA array following the 2011 Virginia earthquake. Our comparisons show that raw-waveform backprojection provides the best spatial resolution, preserves magnitude and boosts signal to detect events smaller than noise, but is most sensitive to velocity error, polarity error and noise bursts. On the other hand, the other methods avoid polarity error and reduce sensitivity to velocity error, but sacrifice spatial resolution and cannot effectively reduce noise by stacking. Of these, only kurtosis is insensitive to large noise bursts while being as efficient as the raw-waveformmethod to lower the detection threshold; however, it does not preserve the magnitude information. For automatic detection and location of events in a large data set, we therefore recommend backprojecting kurtosis waveforms, followed by a second pass on the detected events using noise-filtered raw waveforms to achieve the best of all criteria.
A novel adaptive time stepping scheme for fluid-structure interaction (FSI) problems is proposed that allows for controlling the accuracy of the time-discrete solution. Furthermore, it eases practical computations by providing an efficient and very robust time step size selection. This has proven to be very useful, especially when addressing new physical problems, where no educated guess for an appropriate time step size is available. The fluid and the structure field, but also the fluid-structure interface are taken into account for the purpose of a posteriori error estimation, rendering it easy to implement and only adding negligible additional cost. The adaptive time stepping scheme is incorporated into a monolithic solution framework, but can straightforwardly be applied to partitioned solvers as well. The basic idea can be extended to the coupling of an arbitrary number of physical models. Accuracy and efficiency of the proposed method are studied in a variety of numerical examples ranging from academic benchmark tests to complex biomedical applications like the pulsatile blood flow through an abdominal aortic aneurysm. The demonstrated accuracy of the time-discrete solution in combination with reduced computational cost make this algorithm very appealing in all kinds of FSI applications.
Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. This article explores the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.
Borjas, R.; Balasekaran, Samundeeswari M.; Kim, Eunja; Weck, Philippe F.; Poineau, Frederic
Zirconium tetrachloride, ZrCl4, is a strategic material with wide-ranging applications. Until now, only one crystallographic study on ZrCl4 has been reported [Krebs (1970). Z. Anorg. Allg. Chem.378, 263-272] and that was more than 40 years ago. The compound used for the previous determination was prepared from ZrO2 and Cl2-CCl4, and single-crystal X-ray diffraction (SCXRD) studies on ZrCl4 obtained from Zr metal have not yet been reported. In this context, we prepared ZrCl4 from the reaction of Zr metal and Cl2 gas in a sealed tube and investigated its structure at 100, 150, 200, 250, and 300 K. At 300 K, the SCXRD analysis indicates that ZrCl4 crystallizes in the orthorhombic space group Pca21 [a = 6.262 (9), b = 7.402 (11), c = 12.039 (17) Å, and V = 558.0 (14) Å3] and consists of infinite zigzag chains of edge-sharing ZrCl6 octahedra. This chain motif is similar to that observed previously in ZrCl4, but the structural parameters and space group differ. In the temperature range 100-300 K, no phase transformation was identified, while elongation of intra-chain Zr...Zr [3.950 (1) Å at 100 K and 3.968 (5) Å at 300 K] and inter-chain Cl...Cl [3.630 (3) Å at 100 K and 3.687 (9) Å at 300 K] distances occurred.ZrCl4 has been prepared from the reaction of Zr metal and Cl2 gas in a sealed tube and its structure determined at 100, 150, 200, 250, and 300 K. The chain motif is similar to that observed previously in ZrCl4, but the structural parameters and space group differ.
Flow batteries are an attractive technology for energy storage of grid-scale renewables. However, performance issues related to ion-exchange membrane (IEM) fouling and crossover of species have limited the success of flow batteries. In this work we propose the use of the solid-state sodium-ion conductor NaSICON as an IEM to fully eliminate active species crossover in room temperature, aqueous, neutral pH flow batteries. We measure the room temperature conductivity of NaSICON at 2.83–4.67 mS cm−1 and demonstrate stability of NaSICON in an aqueous electrolyte with conductivity values remaining near 2.5 mS cm−1 after 66 days of exposure. Charge and discharge of a full H-cell battery as well as symmetric cycling in a flow battery configuration using NaSICON as an IEM in both cases demonstrates the capability of the solid-state IEM. Extensive analysis of aged cells through electrochemical impedance spectroscopy (EIS) and UV–vis spectroscopy show no contaminant species having crossed over the NaSICON membrane after 83 days of exposure, yielding an upper limit to the permeability of NaSICON of 4 × 10−10 cm2 min−1. The demonstration of NaSICON as an IEM enables a wide new range of chemistries for application to flow batteries that would previously be impeded by species crossover and associated degradation.
Sandia National Laboratories has tested and evaluated two Guralp Affinity digitizers. The Affinity digitizers are intended to record sensor output for seismic and infrasound monitoring applications. The purpose of this digitizer evaluation is to measure the performance characteristics in such areas as power consumption, input impedance, sensitivity, full scale, self- noise, dynamic range, system noise, response, passband, and timing. The Affinity digitizers are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO).
Suppose Tom is working to develop a rocket. Susan is very interested in knowing what Tom is doing but cannot directly observe his testing of the rocket propulsion system. Specifically, she would like to know if Tom has the ability to launch a heavy rocket or a light rocket. She thinks she can learn about Tom’s capability by learning about what type of rocket engine Tom is using, and the number of rockets in the design. She is considering buying a special sensor that can observe flashes from the rocket firing up during the tests and indicate if the rockets fire in a sufficiently narrow window of time such that they would successfully lift a heavy rocket.
This paper discusses relevant findings and theories regarding the role of ideology, culture, and context in shaping the behaviors of individuals within violent social movements. Accordingly, this focus concerns the comparative weight placed on ideology and culture (expressed principles and motives) versus external factors as chief influencers for the propensity of individuals to act outside of the norms of society and politics by resorting to violent behaviors. In doing so, we have drawn upon theory from anthropology, behavioral economics, political science, psychology, and sociology to better understand how these variables give birth to and nurture militant social movements. F u r t h e r d i s s e m i n a t i o n o n l y a s a u t h o r i z e d t o U . S . G o v e r n m e n t a g e n c i e s a n d t h e i r c o n t r a c t o r s ; o t h e r r e q u e s t s s h a l l b e a p p r o v e d b y t h e o r i g i n a t i n g f a c i l i t y o r h i g h e r D O E p r o g r a m m a t i c a u t h o r i t y .
This report captures the initial conclusions of the DOE seven National Lab team collaborating on the “Solving the Information Technology Energy Challenge Beyond Moore’s Law” initiative from the DOE Big Idea Summit III held in April of 2016. The seven Labs held a workshop in Albuquerque, NM in late July 2016 and gathered 40 researchers into 5 working groups: 4 groups spanning the levels of the co-design framework shown below, and a 5th working group focused on extending and advancing manufacturing approaches and coupling their constraints to all of the framework levels. These working groups have identified unique capabilities within the Labs to support the key challenges of this Beyond Moore’s Law Computing (BMC) vision, as well as example first steps and potential roadmaps for technology development.
While there are several heat pump technologies such thermoelectric, adsorption and magnetocaloric cycles, the oldest and most widely used is the vapor compression cycle (VCC). Currently, thermoelectric cycles have not yet achieved efficiencies nor cooling capacities comparable to VCCs. Adsorption cycles offer the benefit of using low-quality heat as the energy input, but are significantly more complex and expensive and are therefore limited to certain niche applications. Magnetocaloric cycles are still in the research phase. Consequently, improvements made for VCCs will likely have the most immediate and encompassing impact. The objective of this work is to develop an alternative VCC topology to reduce the above inefficiencies.
Presented in this document is a small portion of the tests that exist in the Sierra / SolidMechanics (Sierra / SM) verification test suite. Most of these tests are run nightly with the Sierra / SM code suite, and the results of the test are checked versus the correct analytical result. For each of the tests presented in this document, the test setup, a description of the analytic solution, and comparison of the Sierra / SM code results to the analytic solution is provided. Mesh convergence is also checked on a nightly basis for several of these tests. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems. Additional example problems are provided in the Sierra / SM Example Problems Manual. Note, many other verification tests exist in the Sierra / SM test suite, but have not yet been included in this manual.
A Directional Unfolded Source Term (DUST) algorithm was developed to enable improved spectral analysis capabilities using data collected by Compton cameras. Achieving this objective required modification of the detector response function in the Gamma Detector Response and Analysis Software (GADRAS). Experimental data that were collected in support of this work include measurements of calibration sources at a range of separation distances and cylindrical depleted uranium castings.
Code inter-comparison studies are useful exercises to verify and benchmark independently developed software to ensure proper function, especially when the software is used to model high-consequence systems which cannot be physically tested in a fully representative environment. This summary describes the results of the first portion of the code inter-comparison between PFLOTRAN and RepoTREND, which compares the radionuclide source term used in a typical performance assessment.
Experiments were performed to characterize the mechanical response of a 15 pcf flexible polyurethane foam to large deformation at different strain rates and temperatures. Results from these experiments indicated that at room temperature, flexible polyurethane foams exhibit significant nonlinear elastic deformation and nearly return to their original undeformed shape when unloaded. However, when these foams are cooled to temperatures below their glass transition temperature of approximately -35 o C, they behave like rigid polyurethane foams and exhibit significant permanent deformation when compressed. Thus, a new model which captures this dramatic change in behavior with temperature was developed and implemented into SIERRA with the name Flex_Foam to describe the mechanical response of both flexible and rigid foams to large deformation at a variety of temperatures and strain rates. This report includes a description of recent experiments. Next, development of the Flex Foam model for flexible polyurethane and other flexible foams is described. Selection of material parameters are discussed and finite element simulations with the new Flex Foam model are compared with experimental results to show behavior that can be captured with this new model.
The Nuclear Science Advisory Committee (NSAC) 99Molybdenum (99Mo) Subcommittee met December 14-15, 2017 to address the charge to NSAC requesting that a fourth annual review of the National Nuclear Security Administration (NNSA) 99Mo program be performed. The Subcommittee found that the NNSA has continued to make progress over the course of the year based on the specific American Medical Isotopes Production Act of 2012 (AMIPA) requirements.
This report shows the results of constructing predictive atmospheric models for the Source Physics Experiments 1-6. Historic atmospheric data are combined with topography to construct an atmo- spheric model that corresponds to the predicted (or actual) time of a given SPE event. The models are ultimately used to construct atmospheric Green's functions to be used for subsequent analysis. We present three atmospheric models for each SPE event: an average model based on ten one- hour snap shots of the atmosphere and two extrema models corresponding to the warmest, coolest, windiest, etc. atmospheric snap shots. The atmospheric snap shots consist of wind, temperature, and pressure profiles of the atmosphere for a one-hour time window centered at the time of the predicted SPE event, as well as nine additional snap shots for each of the nine preceding years, centered at the time and day of the SPE event.
This report describes the development of Radical-Ion Flow Battery (RIFB) technology for electrochemical grid storage, and solar thermochemical cycles for conversion of concentrated solar energy to stored chemical energy. The Radical-Ion Flow Battery stores energy via electrolysis of a molten salt electrolyte such as NaNO2 into an alkali metal and nitrogen dioxide, both of which can be stored as liquids in non-pressurized tanks. The use of extremely facile ion-radical single electron transfer reactions at both electrodes that entail no breaking of covalent bonds is directed towards minimizing thermodynamic irreversibility in the charge/discharge cycle, and eliminating the need for catalytically active electrode materials. Both kinetics and mass transport are also facilitated by the absence of diluent species; the battery electrolyte and active chemical ingredient are one and the same. Our underlying strategy for low-cost scalability is the use of only earth abundant starting materials (NaCl, N2, O2, and steel). The underlying strategy for avoiding the problem of capacity fade over 10,000 charge/discharge cycles is the use of extremely simple chemistry. It is argued that operation at elevated temperature is highly advantageous for very large-scale batteries from the standpoint of battery heat-sinking, access to ultrahigh conductivity electrolytes, and increased electrochemical kinetic rate constants. Numerous practical considerations, such as seals, insulators, and electrical feedthroughs are examined in detail, as are questions related to low-cost mass production and battery techno-economic analysis.