This report provides a detailed analysis of the physical and chemical properties of three liquid hydrocarbon fuels: heptane, Bakken crude, and a diluted bitumen, that were subsequently tested in a series of 2-m pool fire experiments at Sandia National Laboratories for the National Research Council Canada. Properties such as relative density, vapor pressure (VPCRx), composition, and heat of combustion were evaluated. The heptane analysis, with relative density = 0.69 (at 15°C), confirmed that the material tested was consistent with high-purity (>99%) n-heptane. The Bakken crude, with a relative density = 0.81 (at 15°C), exhibited a vapor pressure by VPCR0.2 (37.8°C) in the range 120-157 kPa. The dilbit, with a relative density = 0.92 (at 15°C) exhibited a vapor pressure by VPCR 0.2 (37.8°C) in the range 85-98 kPa. Solids remaining in the test pans after the pool fires were also collected and weighed. No detectable solids were left after the heptane burns. In contrast, the crude oils left some brittle, black solid residue. On average, dilbit pool fires left about 40 more residue by mass than Bakken pool fires for equivalent mass of fuel feed.
We study both conforming and non-conforming versions of the practical DPG method for the convection-reaction problem. We determine that the most common approach for DPG stability analysis (construction of a local Fortin operator) is infeasible for the convection-reaction problem. We then develop a line of argument based on the direct construction of a global Fortin operator; we find that employing a polynomial enrichment for the test space does not suffice for this purpose, motivating the introduction of a (two-element) subgrid mesh. The argument combines mathematical analysis with numerical experiments
The U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system run by the U.S. Department of Energy (DOE). The reserve consists of 60 active storage caverns spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR began executing U.S. congressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 MMB, requires raw water to be used instead of saturated brine for oil withdrawals such as for sales. All sales will produce leaching within the caverns used for oil delivery. Thirty-six caverns had a combined total of over 29 MMB of water injected from CY18-CY19 for mandatory sales. Leaching effects were monitored in these caverns to understand how the sales operations may impact the long-term integrity of the caverns. While frequent sonars are the best way to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An intermediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code (SANSMIC). The results indicate that leaching induced features are not of concern in the majority of the caverns, 32 of 36. Four caverns, BH-107, BH-108, BH-114 and WH-114 have features that may grow with additional leaching and should be monitored as leaching continues in those caverns. Six caverns had post sale sonars which were compared with SANSMIC results. SANSMIC was able to capture the leaching well. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results suggest SANSMIC is a useful tool for monitoring changes in cavern shape due to leaching effects related to sales and exchanges.
Electrodialysis (ED) desalination performance of different conventional and laboratoryscale ion exchange membranes (IEMs) has been evaluated by many researchers, but most of these studies used their own sets of experimental parameters such as feed solution compositions and concentrations, superficial velocities of the process streams (diluate, concentrate, and electrode rinse), applied electrical voltages, and types of IEMs. Thus, direct comparison of ED desalination performance of different IEMs is virtually impossible. While the use of different conventional IEMs in ED has been reported, the use of bioinspired ion exchange membrane has not been reported yet. The goal of this study was to evaluate the ED desalination performance differences between novel laboratory-scale bioinspired IEM and conventional IEMs by determining (i) limiting current density, (ii) current density, (iii) current efficiency, (iv) salinity reduction in diluate stream, (v) normalized specific energy consumption, and (vi) water flux by osmosis as a function of (a) initial concentration of NaCl feed solution (diluate and concentrate streams), (b) superficial velocity of feed solution, and (c) applied stack voltage per cell-pair of membranes. A laboratory-scale single stage batchrecycle electrodialysis experimental apparatus was assembled with five cell-pairs of IEMs with an active cross-sectional area of 7.84 cm2. In this study, seven combinations of IEMs (commercial and laboratory-made) were compared: (i) Neosepta AMX/CMX, (ii) PCA PCSA/PCSK, (iii) Fujifilm Type 1 AEM/CEM, (iv) SUEZ AR204SZRA/CR67HMR, (v) Ralex AMH-PES/CMH-PES, (vi) Neosepta AMX/Bare Polycarbonate membrane (Polycarb), and (vii) Neosepta AMX/Sandia novel bioinspired cation exchange membrane (SandiaCEM). ED desalination performance with the Sandia novel bioinspired cation exchange membrane (SandiaCEM) was found to be competitive with commercial Neosepta CMX cation exchange membrane.
In response to the COVID-19 pandemic, the Exascale Computing Project’s (ECP) Interoperable Design of Extreme-scale Application Software (IDEAS) productivity team launched the panel series Strategies for Working Remotely to facilitate informal, cross-organizational dialog in the absence of face-to-face meetings. In a time of pandemic, organizations increasingly need to reach across perceived boundaries to learn from each other, so that we can move beyond stand-alone silos to more connected multidisciplinary and multiorganizational configurations. The present paper argues that the unplanned transition to remote work, overuse of electronic communication, and need to unlearn habits associated with an overreliance on face-to-face, created unique opportunities to learn from the situation and accelerate cross-institutional cooperation and collaboration through online community dialog facilitated by informal panel discussions. Recommendations for facilitating online panel discussions to foster cross-organizational dialog are provided by applying the Simulation Experience Design Method.
China is endeavoring to build nuclear power plants (NPPs) in numerous countries around the globe - an initiative that has the potential to strengthen Chinas political and economic influences on those countries. This study provides an overview of the situation and considers the issues involved in such partnerships with China. In order to assess Chinas ability to follow through with its agreements, this study also presents a technical review of its NPP production capability.
This is the second in a sequence of three Hardware Evaluation milestones that provide insight into the following questions: What are the sources of excess data movement across all levels of the memory hierarchy, going out to the network fabric? What can be done at various levels of the hardware/software hierarchy to reduce excess data movement? How does reduced data movement track application performance? The results of this study can be used to suggest where the DOE supercomputing facilities, working with their hardware vendors, can optimize aspects of the system to reduce excess data movement. Quantitative analysis will also benefit systems software and applications to optimize caching and data layout strategies. Another potential avenue is to answer cost-benefit questions, such as those involving memory capacity versus latency and bandwidth. This milestone focuses on techniques to reduce data movement, quantitatively evaluates the efficacy of the techniques in accomplishing that goal, and measures how performance tracks data movement reduction. We study a small collection of benchmarks and proxy mini-apps that run on pre-exascale GPUs and on the Accelsim GPU simulator. Our approach has two thrusts: to measure advanced data movement reduction directives and techniques on the newest available GPUs, and to evaluate our benchmark set on simulated GPUs configured with architectural refinements to reduce data movement.
he Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015) to the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA) and its Management and Operating (M&O) contractor. The current M&O contractor is National Technology & Engineering Solutions of Sandia, LLC (NTESS). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for calendar year (CY) 2020, as required by the Permit.
The purpose of this CWL Annual Post-Closure Care Report is to document monitoring, inspection, maintenance, and repair activities conducted during CY 2020 as required by PCCP Attachment 1, Section 1.12 (NMED October 2009 and subsequent revisions). This annual report documents post-closure care activities conducted from January through December 2020 and fulfills the PCCP requirement for annual reporting to the NMED.
High heat flux (>500 kW/m2) ignitions occur in scenarios involving metal fires, propellants, lightning strikes, above ground nuclear weapon use, etc. Data for material response in such environments is primarily limited to experimental programs in the 1950s and 1960s. We have recently obtained new data in this environment using concentrated solar energy. A portion of the experimental data were taken with the objective that the data be useful for model validation. To maximize the utility of the data for validation of predictive codes, additional focus is placed on repeatability of the data, reduction of uncertainties, and characterization of the environment. We illustrate here a portion of the data and methods used to assess environmental and response parameters. The data we present are novel in the flux range and materials tested, and these data constitute progress in the ability to characterize fires from high flux events.
Momentum, advection, diffusion, and turbulence are component physics relating to fire simulation tools like computational fluid dynamics (CFD). Magnetic Resonance Velocimetry and Magnetic Resonance Concentration MRV/MRC techniques can produce heretofore unrivaled detailed measurements of three-component velocity and concentration fields in turbulent flows. This study exhibits 3D flow comparisons between velocity and concentration fields obtained using MRC/MRV and SIERRA/Fuego for an urban geometry based on a section of downtown Oklahoma City. A 1:2500 scale water flow scenario provides 0.8 mm resolution data. Various techniques are employed to quantify the accuracy of the simulation results. The techniques all generally suggest a good comparison between the model and experiments throughout the compared volume. The selected metrics provide benchmark accuracy measures that can be used to indicate quantitative accuracy of the simulations, as well as for targets for future simulation improvements.
This report focuses on the two primary goals set forth in Sandia’s TAFI effort, referred to here under the name Kebab. The first goal is to overlay a trajectory onto a large database of historical trajectories, all with very different sampling rates than the original track. We demonstrate a fast method to accomplish this, even for databases that hold over a million tracks. The second goal is to then demonstrate that these matched historical trajectories can be used to make predictions about unknown qualities associated with the original trajectory. As part of this work, we also examine the problem of defining the qualities of a trajectory in a reproducible way.
Superstorm Sandy caused a major disruption to passenger-rail and other commuter systems throughout New York and New Jersey. To address this issue, New Jersey Transit (NJT) established the NJ TRANSITGRID project, an effort designed to power bus, ferry, and limited passenger-rail service during natural or man-made disasters. Given the importance of these transportation systems, NJT partnered with Sandia National Laboratories (Sandia) to assess the cyber-resilience of the information systems that monitor and control the electrical systems within the microgrid. The Sandia “tabletop” assessment is based on the most recent 20% design packages. From this assessment, the Sandia team identified several security areas that were undefined or did not implement industry best practices. Finally, the Sandia team presented possible follow-on assessment activities and recommended investigating multiple hardening technologies. Addressing these findings and adding state-of-the-art detection and mitigation technologies will help ensure the NJ TRANSITGRID is built with more comprehensive cyber-resilience features.
We have completed a series of both vented and sealed cookoff experiments of black powder and smokeless powder in our Sandia Instrumented Thermal Ignition (SITI) apparatus at bulk densities of 1078 and 729 kg/m3, respectively. The confining aluminum cylinder was ramped from room temperature to a set point temperature and then held at the setpoint temperature until ignition. The setpoint temperatures varied between 495 to 523 K for the black powder and 401 to 412 K for the more sensitive smokeless powder. The vented experiments show a significant delay in thermal ignition, indicating that the ignition is dependent on pressure. Post experimental debris shows greater violence for our smokeless powder experiments than our black powder experiments. A simplified universal cookoff model (UCM) was calibrated using the black powder and smokeless powder SITI data and used to predict pressurization and thermal ignition. The current work presents the first calibration of the UCM with a double base propellant. This work also presents the first pressure-dependent cookoff model for black powder and smokeless powder.
The GMS Station State-of-Health (SOH) monitoring capability provides the system controller the ability to view current SOH values and calculated statistics for stations and channels, view trend plots of SOH values, be notified when station SOH status changes, and acknowledge or quiet notifications while the station issues are being investigated. The SOH monitoring capability includes components to acquire CD 1.1 protocol station data, extract SOH information from the raw data packets, process the raw SOH information for display, store the SOH information, and display the SOH information in an interactive display. All these components use system and processing configuration to provide the system controller mission-relevant information about station health. This document is a guide to setting the processing configuration for GMS SOH monitoring.
The impact on the final morphology of ceria (CeO2) nanoparticles made from different precursors (commercial: cerium acetate/nitrate) and in house: cerium tri(methylsilyl)amide (Ce-TMSA)) via a microwave solid state reaction has been determined. In all instances, powder X-ray diffraction indicated that the cubic fluorite CeO2 phase (PDF# 04–004-9150, with the space group Fm-3 m) had formed. Scanning electron microscopy (SEM) images revealed spherical nanoparticles were produced from the Ce-TMSA precursor. The commercial acetate and nitrate precursors produced particles with irregular morphology. The roles of the precursor decomposition and binding energy in the synthesis of the nanocrystals with various morphologies, as well as a possible growth mechanism, were evaluated based on experimental and computational data. The formation of spherical shaped nanoparticles was determined to be due to the preferential single-step decomposition of the Ce-TMSA as well as the low activation energy to overcome decomposition. Due to the complicated decomposition of the commercial precursors and high activation energy the resulting particles adopted an irregular morphology. Highly uniform samarium doped ceria (SmxCe1-xO2-δ) nanospheres were also synthesized from Ce-TMSA and samarium tri(methylsilyl)amide (Sm-TMSA). The effects of reaction time and temperature, on the final morphology were observed through SEM. The rapid single-step decomposition of TMSA-based precursors as observed through thermogravimetric analysis (TGA) and confirmed through the calculation of potential energy surfaces and binding energies from density functional theory (DFT) calculations, indicated that nanoparticle formation follows LaMer’s classical nucleation theory.
The dynamic behavior of an elastic peridynamic material with a nonconvex bond potential is studied. In spite of the material’s inherently unstable nature, initial value problems can be solved using essentially the same techniques as with conventional materials, both analytically and numerically. In a suitably constructed material model, small perturbations grow exponentially over time until the material fails. The time for this growth is computed explicitly for a stretching bar that passes from the stable to the unstable phase of the material model. This time to failure represents an incubation time for the nucleation of a crack. The finiteness of the failure time in effect creates a rate dependence in the failure properties of the material. Thus, the unstable nature of the elastic material leads to a rate effect even though it does not contain any terms that explicitly include a strain rate dependence.
Modern electrochemical energy conversion devices require more advanced proton conductors for their broad applications. Phosphonated polymers have been proposed as anhydrous proton conductors for fuel cells. However, the anhydride formation of phosphonic acid functional groups lowers proton conductivity and this prevents the use of phosphonated polymers in fuel cell applications. Here, we report a poly(2,3,5,6-tetrafluorostyrene-4-phosphonic acid) that does not undergo anhydride formation and thus maintains protonic conductivity above 200 °C. We use the phosphonated polymer in fuel cell electrodes with an ion-pair coordinated membrane in a membrane electrode assembly. This synergistically integrated fuel cell reached peak power densities of 1,130 mW cm−2 at 160 °C and 1,740 mW cm−2 at 240 °C under H2/O2 conditions, substantially outperforming polybenzimidazole- and metal phosphate-based fuel cells. Our result indicates a pathway towards using phosphonated polymers in high-performance fuel cells under hot and dry operating conditions.
Micheli, Leonardo; Theristis, Marios; Livera, Andreas; Stein, Joshua S.; Georghiou, George E.; Muller, Matthew; Almonacid, Florencia; Fernandez, Eduardo F.
Photovoltaic (PV) soiling profiles exhibit a sawtooth shape, where cleaning events and soiling deposition periods alternate. Generally, the rate at which soiling accumulates is assumed to be constant within each deposition period. In reality, changes in rates can occur because of sudden variations in climatic conditions, e.g., dust storms or prolonged periods of rain. The existing models used to extract the soiling profile from the PV performance data might fail to capture the change points and occasionally estimate incorrect soiling profiles. This work analyzes how the introduction of change points can be beneficial for soiling extraction. Data from nine soiling stations and a 1-MW site were analyzed by using piecewise regression and three change point detection algorithms. The results showed that accounting for change points can provide significant benefits to the modeling of soiling even if not all the change point algorithms return the same improvements. Considering change points in historical trends is found to be particularly important for studies aiming to optimize cleaning schedules.
Geomechanics and Geophysics for Geo-Energy and Geo-Resources
Shalev, Eyal; Bauer, Stephen J.; Homel, Michael A.; Antoun, Tarabay H.; Herbold, Eric B.; Levin, Harel; Oren, Gal; Lyakhovsky, Vladimir
The existence of a deep borehole in the Earth’s crust disturbs the local stresses and creates a stress concentration that may result in breakout and damage to the borehole. Maintaining wellbore integrity mitigates environmental impacts such as groundwater contamination, gas leakage to the atmosphere, and fluid spills and seepage at the surface. In this paper, the stability of deep boreholes (5 km) is examined by laboratory experiments and numerical models in the context of nuclear waste disposal in Israel. Two rock types in southern Israel are considered: the crystalline basement (granite) and the Zenifim Formation (arkose). A series of room-temperature triaxial rock deformation experiments were conducted at different confining pressures. This mechanical characterization was then used to parameterize the elastic properties and damage behavior of the rocks. This facilitated modeling the stability of the deep boreholes by two different formulations of damage rheology: a dynamic-oriented formulation used to model deformation immediately after the creation of the open hole and a quasi-static formulation used to model longer stress corrosion regime. The calibrated modeling results indicate greater stability with Zenifim arkose than the crystalline granite for deep borehole conditions despite the granite having a greater triaxial compressive strength. Dissipation associated with dilation and porous compaction in the arkose during deformation plays a significant stabilizing role in the borehole compared to crystalline rocks. These results suggest that common strength-based borehole stability assessment may lead to inaccurate predictions. Three-dimensional modeling of bottom-hole stress conditions and the effects of transient borehole geometry show conventional two-dimensional analysis may not be conservative when predicting borehole damage.
Semiconductor-insulator interfaces play an important role in the reliability of integrated devices; however, the impact of these interfaces on the physical mechanisms related to single-event effects has not been previously reported. We present experimental data that demonstrate that single-event charge collection can be impacted by changes in interface quality. The experimental data, combined with simulations, show that single-event response may depend on surface recombination at interface defects. The effect depends on strike location and increases with increasing linear energy transfer (LET). Surface recombination can affect single-event charge collection for interfaces with a surface recombination velocity (SRV) of 1000 cm/s and is a dominant charge collection mechanism with SRV > 10^{5} cm/s.
Uranyl ion, UO22+, and its aqueous complexes with organic and inorganic ligands can be the dominant species for uranium transport on the Earth surface or in a nuclear waste disposal system if an oxidizing condition is present. As an important biodegradation product, oxalate, C2O42−, is ubiquitous in natural environments and is known for its ability to complex with the uranyl ion. Oxalate can also form solid phases with uranyl ion in certain environments thus limiting uranium migration. Therefore, the determination of stability constants for aqueous and solid uranyl oxalate complexes is important not only to the understanding of uranium mobility in natural environments, but also to the performance assessment of nuclear waste disposal. Here we developed a thermodynamic model for the UO22+-Na+-H+-Cl--ClO4--C2O42--NO3--H2O system to ionic strength up to ∼11 mol•kg−1. We constrained the stability constants for UO2C2O4(aq) and UO2(C2O4)22− at infinite dilution based on our evaluation of the literature data over a wide range of ionic strengths up to ∼11 mol•kg−1. We also obtained the solubility constants at infinite dilution for solid uranyl oxalates, UO2C2O4•3H2O, based on the solubility data over a wide range of ionic strengths. The developed model will enable for the accurate stability assessment of oxalate complexes affecting uranium mobility under a wide range of conditions including those in deep geological repositories.
The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.1.1 offers intrusive and non-intrusive methods for propagating input uncertainties through computational models, tools for sensitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters from experimental data. This manual discusses the download and installation process for UQTk, provides pointers to the UQ methods used in the toolkit, and describes some of the examples provided with the toolkit.
The long-term x-ray diffraction (XRD) detector scheme compatible with Z-containment experiments will involve conversion of the diffracted x-rays to optical light, which will be transported away from the Z-Dynamic Materials Properties (DMP) load and detected on a fast-gated camera. In this so-called DIffraction SCintillator Optic (DISCO) scheme , the scintillator is coupled to a long, coherent imaging fiber bundle using a custom lens system with high numerical aperture. In addition, the DISCO diagnostic incorporates time-gating to allow measurement only during the short time window of the x-ray pulse in which XRD occurs, thereby significantly reducing unwanted background generated by the Z-DMP load. Dynamic compression experiments were performed at the Chama target chamber to evaluate the DISCO diagnostic . Specifically, a Zr sample was laser-shocked with the Chaco laser while the Z-Beamlet (ZBL) laser was used to generate x-rays, which enabled time-gated 6.7-keV XRD patterns from the compressed Zr sample to be obtained.
Modeling and simulation of the legacy HERMES III Magnetically Insulated Transmission Line (MITL) has been performed using EMPHASIS, an unstructured time-domain electromagnetic (UTDEM) particle-in-cell (PIC) simulation software. This design when used lost roughly half of its current before the pulse reached the load. The cause of the current loss in the MITL was found to be the vacuum impedance changes along the MITL. The MITL was then redesigned to maintain constant impedance and simulated in EMPHASIS once again. Following predicting simulation results, the new MITL was then built, installed, and tested, showing minimal current loss and good agreement with simulation and theoretical results, all of which are reported here. Additionally, an analysis of experimental voltage calculation techniques using cathode and anode currents is performed and compared to simulation results.
The Department of Energy maintains an up-to-date documentation of the number of available full drawdowns of each of the caverns owned by the Strategic Petroleum Reserve (SPR). This information is important for assessing the SPRs ability to deliver oil to domestic oil companies expeditiously if national or world events dictate a rapid sale and deployment of the oil reserves. Sandia was directed to develop and implement a process to continuously assess and report the evolution of drawdown capacity, the subject of this report. A cavern has an available drawdown if after that drawdown, the long-term stability of the cavern, the cavern field, or the oil quality are not compromised. Thus, determining the number of available drawdowns requires the consideration of several factors regarding cavern and wellbore integrity and stability, including stress states caused by cavern geometry and operations, salt damage caused by dilatant and tensile stresses, the effect of enhanced creep on wellbore integrity, and the sympathetic stress effect of operations on neighboring caverns. A consensus has now been built regarding the assessment of drawdown capabilities and risks for the SPR caverns (Sobolik et al., 2014; Sobolik 2016). The process involves an initial assessment of the pillar - to - diameter (P/D) ratio for each cavern with respect to neighboring caverns. A large pillar thickness between adjacent caverns should be strong enough to withstand the stresses induced by closure of the caverns due to salt creep. The first evaluation of P/D includes a calculation of the evolution of P/D after a number of full cavern drawdowns. The most common storage industry standard is to keep this value greater than 1.0, which should ensure a pillar thick enough to prevent loss of fluids to the surrounding rock mass. However, many of the SPR caverns currently have a P/D less than 1.0 or will likely have a low P/D after one or two full drawdowns. For these caverns, it is important to examine the structural integrity with more detail using geomechanical models. Finite-element geomechanical models have been used to determine the stress states in the pillars following successive drawdowns. By computing the tensile and dilatant stresses in the salt, areas of potential structural instability can be identified that may represent red flags for additional drawdowns. These analyses have found that many caverns will maintain structural integrity even when grown via drawdowns to dimensions resulting in a P/D of less than 1.0. The analyses have also confirmed that certain caverns should only be completely drawn down one time. As the SPR caverns are utilized and partial drawdowns are performed to remove oil from the caverns (e.g., for occasional oil sales , purchases, or exchanges authorized by the Congress or the President), the changes to the cavern caused by these procedures must be tracked and accounted for so that an ongoing assessment of the caverns drawdown capacity may be continued. A proposed methodology for assessing and tracking the available drawdowns for each cavern was presented in Sobolik et al. (2018). This report is the latest in a series of annual reports, and it includes the baseline available drawdowns for each cavern, and the most recent assessment of the evolution of drawdown expenditure for several caverns .
Lin, Yen T.; Neumann, Jacob; Miller, Ely F.; Posner, Richard G.; Mallela, Abhishek; Safta, Cosmin S.; Ray, Jaideep R.; Thakur, Gautam; Chinthavali, Supriya; Hlavacek, William S.
To increase situational awareness and support evidence-based policymaking, we formulated a mathematical model for coronavirus disease transmission within a regional population. This compartmental model accounts for quarantine, self-isolation, social distancing, a nonexponentially distributed incubation period, asymptomatic persons, and mild and severe forms of symptomatic disease. We used Bayesian inference to calibrate region-specific models for consistency with daily reports of confirmed cases in the 15 most populous metropolitan statistical areas in the United States. We also quantified uncertainty in parameter estimates and forecasts. This online learning approach enables early identification of new trends despite considerable variability in case reporting.
This work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. [2009]). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.
Electric power is crucial to the function of other infrastructures, as well as to the stability of the economy and the social order. Disruption of commercial electric power service, even for brief periods of time, can create significant consequences to the function of other sectors, and make living in some environments untenable. This analysis, conducted in 2017 for the United States Department of Energy (DOE) as part of the Grid Modernization Laboratory Consortium (GMLC) Initiative, focuses on describing the function of each of the other infrastructure sectors and subsectors, with an eye towards those elements of these sectors that depend on primary electric power service through the commercial electric power grid. It leverages the experience of Sandia analysts in analyzing historical disruptive events, and from the development of capabilities designed to identify the physical, logical, and geographic connectivity between infrastructures. The analysis goes on to identify alternatives for the provision of primary electric power service, and the redundancy of said alternatives, to provide a picture of the sector’s ability to withstand an extended disruption.
The evaporation and combustion of n-heptane droplets under high pressure (20 atm) conditions were investigated using three-dimensional direct numerical simulations (DNS) in the present work. Two ambient temperatures were considered, i.e. 860 K and 1180 K. Low-temperature combustion, which is controlled by low-temperature chemical pathways, occurs in the 860 K cases while single-stage combustion occurs in the 1180 K cases. Droplet evaporation and combustion in isotropic turbulence were considered. The interactions of turbulence, evaporation and combustion in a cloud of droplets were explored. It was found that turbulence promotes the evaporation process. The temperature and mixture-fraction are negatively correlated after evaporation, which impacts the subsequent ignition process. For both low-temperature and single-stage combustion, ignition occurs in regions with low scalar dissipation rate. Low-temperature ignition first appears in lean mixtures while single-stage ignition in rich mixtures. Ignition kernels evolve into reaction fronts, which propagate towards thermally and compositionally stratified mixture and consume the remaining fuel. Spontaneous ignition front is dominant in low-temperature combustion while deflagrative front is playing an important role in single-stage combustion. The interactions of turbulence and the reaction front structures were examined. Cylindrical elements are the most probable shape of the reaction front for turbulent droplet combustion. The reaction front normal is misaligned with the vorticity vector for both low-temperature and single-stage combustion, indicating that the vortical structures preferentially locate along the tangential plane of the reaction front, which promotes the observed cylindrical reaction front structures in turbulent combustion of droplets.
Temperature- and irradiation-assisted failure mechanisms in miscible phase boundaries are clarified via atomistic calculations. We first establish the temperature-dependent brittle-to-ductile transition in U–Zr miscible phase boundaries. Our results confirm that these boundaries are mostly brittle at low temperatures and ductile at elevated temperatures. We then investigate the changes induced by irradiation on the fracture mechanisms in such phase boundaries. The irradiation-induced defect accumulation follows a multi-stage process that starts with the accumulation of isolated small dislocation loops before transitioning to the saturation and growth of larger dislocation loops and end up with a reorganization into forest dislocations. The accumulation of loops is the primary feature to participate in the delineation between brittle and ductile interfacial fracture in irradiated phase boundaries. At low damage levels, radiation defect interactions with the crack tip are limited and U–Zr miscible boundaries fail through the emission of dislocations ahead of the crack tip followed by brittle cleavage in agreement with the classical Griffith’s criterion for crack stability. At higher damage levels, the failure mode transitions from brittle crack growth to ductile void growth. In this case, the microcrack tip is blunted by the high density of pre-existing, radiation-induced defects in the vicinity of the crack. This interaction leads to the development and growth of a cavity at the interface as opposed to interfacial cleavage.
The evaluation of effective material properties in heterogeneous materials (e.g., composites or multicomponent structures) is critically relevant to a wide spectrum of applications, including nuclear power, electronic packaging, flame retardants, hypersonics, and gas turbine power. The work described in this paper is centered around the numerical assessment of the thermal behavior of porous materials obtained from finite element thermal modeling and simulation. Two-dimensional, steady-state analyses were performed on unit cells with centered, circular pores using a second-order accurate Galerkin finite element method (FEM). The effective thermal conductivities of the porous systems were examined, encompassing a range of porosities from 4.9% to 60.1%. The geometries of the models were generated based on ordered circular pores for each modeled porosity level. The system response quantity (SRQ) under investigation was the dimensionless effective thermal conductivity across the unit cell. The dimensionless effective thermal conductivity was compared across all simulated cases, producing a trend between porosity and effective thermal conductivity. In the presented investigation, the method of manufactured solutions (MMS) was used to perform code verification, and the grid convergence index (GCI) was employed to estimate discretization uncertainty as solution verification. Code verification concluded an approximately second order accurate Galerkin FEM solver. It was found that the introduction of porosity to the unit cell material structure reduces effective thermal conductivity, as anticipated. Numerical results obtained in this study are compared to an analytical solution and to a sample of empirical data. This approach can be readily generalized to study a wide variety of porous solids from ranging from structures at the nanoscale—such as nanocarbon tubes—to structures at macrolevel scales—such as geological features.
The IEC 61853 photovoltaic (PV) module energy rating standard requires measuring module power (and hence, efficiency) over a matrix of irradiance and temperature conditions. These matrix points represent nearly the full range of operating conditions encountered in the field in all but the most extreme locations and create an opportunity to develop alternative approaches for calculating system performance. In this article, a new PV module efficiency model is presented and compared with five published models using matrix data collected from four different PV module types. The results of the comparative analysis demonstrated that the new model improves on the existing ones exhibiting root-mean-square errors in normalized efficiency well below 0.01 for all cases and PV modules. The analysis also highlighted its ability to interpolate and extrapolate performance between and beyond measured matrix points of irradiance and temperature, establishing it as a robust yet relatively simple model for several applications that are detailed throughout this article.
Hart, Joseph L.; Gilmore, Steven; Gremaud, Pierre; Olsen, Christian H.; Mehlsen, Jesper; Olufsen, Mette S.
Imbalance in the autonomic nervous system can lead to orthostatic intolerance manifested by dizziness, lightheadedness, and a sudden loss of consciousness (syncope); these are common conditions, but they are challenging to diagnose correctly. Uncertainties about the triggering mechanisms and the underlying pathophysiology have led to variations in their classification. This study uses machine learning to categorize patients with orthostatic intolerance. We use random forest classification trees to identify a small number of markers in blood pressure, and heart rate time-series data measured during head-up tilt to (a) distinguish patients with a single pathology and (b) examine data from patients with a mixed pathophysiology. Next, we use Kmeans to cluster the markers representing the time-series data. We apply the proposed method analyzing clinical data from 186 subjects identified as control or suffering from one of four conditions: postural orthostatic tachycardia (POTS), cardioinhibition, vasodepression, and mixed cardioinhibition and vasodepression. Classification results confirm the use of supervised machine learning. We were able to categorize more than 95% of patients with a single condition and were able to subgroup all patients with mixed cardioinhibitory and vasodepressor syncope. Clustering results confirm the disease groups and identify two distinct subgroups within the control and mixed groups. The proposed study demonstrates how to use machine learning to discover structure in blood pressure and heart rate time-series data. The methodology is used in classification of patients with orthostatic intolerance. Diagnosing orthostatic intolerance is challenging, and full characterization of the pathophysiological mechanisms remains a topic of ongoing research. This study provides a step toward leveraging machine learning to assist clinicians and researchers in addressing these challenges. [Figure not available: see fulltext.].
Sondak, David; Smith, Thomas M.; Pawlowski, Roger P.; Conde, Sidafa C.; Shadid, John N.
The variational multiscale (VMS) formulation is used to develop residual-based VMS large eddy simulation (LES) models for Rayleigh-Bénard convection. The resulting model is a mixed model that incorporates the VMS model and an eddy viscosity model. The Wall-Adapting Local Eddy-viscosity (WALE) model is used as the eddy viscosity model in this work. The new LES models were implemented in the finite element code Drekar. Simulations are performed using continuous, piecewise linear finite elements. The simulations ranged from Ra=106 to Ra=1014 and were conducted at Pr=1 and Pr=7. Two domains were considered: a two-dimensional domain of aspect ratio 2 with a fluid confined between two parallel plates and a three-dimensional cylinder of aspect ratio 1/4. The Nusselt number from the VMS results is compared against three dimensional direct numerical simulations and experiments. In all cases, the VMS results are in good agreement with existing literature.
The modern scientific process often involves the development of a predictive computational model. To improve its accuracy, a computational model can be calibrated to a set of experimental data. A variety of validation metrics can be used to quantify this process. Some of these metrics have direct physical interpretations and a history of use, while others, especially those for probabilistic data, are more difficult to interpret. In this work, a variety of validation metrics are used to quantify the accuracy of different calibration methods. Frequentist and Bayesian perspectives are used with both fixed effects and mixed-effects statistical models. Through a quantitative comparison of the resulting distributions, the most accurate calibration method can be selected. Two examples are included which compare the results of various validation metrics for different calibration methods. It is quantitatively shown that, in the presence of significant laboratory biases, a fixed effects calibration is significantly less accurate than a mixed-effects calibration. This is because the mixed-effects statistical model better characterizes the underlying parameter distributions than the fixed effects model. The results suggest that validation metrics can be used to select the most accurate calibration model for a particular empirical model with corresponding experimental data.
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society.
Forward modeling of optical spectra with absolute radiometric intensities requires knowledge of the individual transition probabilities for every transition in the spectrum. In many cases, these transition probabilities, or Einstein A-coefficients, quickly become practically impossible to obtain through either theoretical or experimental methods. Complicated electronic orbitals with higher order effects will reduce the accuracy of theoretical models. Experimental measurements can be prohibitively expensive and are rarely comprehensive due to physical constraints and sheer volume of required measurements. Due to these limitations, spectral predictions for many element transitions are not attainable. In this work, we investigate the efficacy of using machine learning models, specifically fully connected neural networks (FCNN), to predict Einstein A-coefficients using data from the NIST Atomic Spectra Database. For simple elements where closed form quantum calculations are possible, the data-driven modeling workflow performs well but can still have lower precision than theoretical calculations. For more complicated nuclei, deep learning emerged more comparable to theoretical predictions, such as Hartree–Fock. Unlike experiment or theory, the deep learning approach scales favorably with the number of transitions in a spectrum, especially if the transition probabilities are distributed across a wide range of values. It is also capable of being trained on both theoretical and experimental values simultaneously. In addition, the model performance improves when training on multiple elements prior to testing. The scalability of the machine learning approach makes it a potentially promising technique for estimating transition probabilities in previously inaccessible regions of the spectral and thermal domains on a significantly reduced timeline.
Carbone, Emile; Graef, Wouter; Hagelaar, Gerjan; Boer, Daan; Hopkins, Matthew M.; Stephens, Jacob C.; Yee, Benjamin T.; Pancheshnyi, Sergey; Van Dijk, Jan; Pitchford, Leanne
Technologies based on non-equilibrium, low-temperature plasmas are ubiquitous in today’s society. Plasma modeling plays an essential role in their understanding, development and optimization. An accurate description of electron and ion collisions with neutrals and their transport is required to correctly describe plasma properties as a function of external parameters. LXCat is an open-access, web-based platform for storing, exchangig and manipulating data needed for modeling the electron and ion components of non-equilibrium, low-temperature plasmas. The data types supported by LXCat are electron- and ion-scattering cross-sections with neutrals (total and differential), interaction potentials, oscillator strengths, and electron- and ion-swarm/transport parameters. Online tools allow users to identify and compare the data through plotting routines, and use the data to generate swarm parameters and reaction rates with the integrated electron Boltzmann solver. In this review, the historical evolution of the project and some perspectives on its future are discussed together with a tutorial review for using data from LXCat.
De Marcos, Luis V.R.; Boris, David R.; Gray, Emrold; Del Hoyo, Javier G.; Kozen, Alexander C.; Richardson, Joseph G.; Rosenberg, Samantha G.; Walton, Scott G.; Wheeler, Virginia; Wollack, Edward J.; Woodward, Jeffre E.M.; Quijada, Manuel A.
The development of optical systems operating in the far ultraviolet range (FUV, X= 100-200 nm) is limited by the efficiency of passivated aluminum (Al) mirrors. Although it is presently possible to obtain high-reflectivity FUV mirrors through physical vapor deposition, the process involves deposition with substrates at high temperatures, which is technically challenging for large optical elements. A novel passivation procedure for bare Al mirrors is reported. The treatment consisted of using a low-temperature electron-beam generated plasma produced in a gas mixture of Ar and SF6 to etch away the native oxide layer from the Al flm, while simultaneously promoting the generation of a thin aluminum tri-fuoride (AlF3) layer on the Al surface. In the first section we analyze the effect of varying both ion energy and SF6 concentration on the FUV reflectance, thickness, composition, and surface morphology of the resulting AlF3 protective layers. In the second section, the reflectivity of samples is optimized at selected important FUV wavelengths for astronomical observations. Notably, samples attained state-of-the-art reflectances of 75% at 108.5 nm (He Lyman y), 91% at 121.6nm(HLyman a), 90% at 130.4nm (OI), and of 95% at 155.0 nm (C IV). The stability over time of these passivated mirrors is also investigated.
Abstract: Multimodal in-situ experiments are the wave of the future, as this approach will permit multispectral data collection and analysis during real-time nanoscale observation. In contrast, the evolution of technique development in the electron microscopy field has generally trended toward specialization and subsequent bifurcation into more and more niche instruments, creating a challenge for reintegration and backward compatibility for in-situ experiments on state-of-the-art microscopes. We do not believe this to be a requirement in the field; therefore, we propose an adaptive instrument that is designed to allow nearly simultaneous collection of data from aberration-corrected transmission electron microscopy (TEM), probe-corrected scanning transmission electron microscopy, ultrafast TEM, and dynamic TEM with a flexible in-situ testing chamber, where the entire instrument can be modified as future technologies are developed. The value would be to obtain a holistic understanding of the underlying physics and chemistry of the process-structure–property relationships in materials exposed to controlled extreme environments. Such a tool would permit the ability to explore, in-situ, the active reaction mechanisms in a controlled manner emulating those of real-world applications with nanometer and nanosecond resolution. If such a powerful tool is developed, it has the potential to revolutionize our materials understanding of nanoscale mechanisms and transients. Graphical Abstract: [Figure not available: see fulltext.].
The choice of model form used to represent the anisotropic yield response of metals can depend strongly on the type and amount of data available for calibration. This two-part contribution considers the calibration (part I) of three yield functions: von Mises, Hill-48 and Yld2004-18p by Barlat and co-workers. This is followed by model verification exercises (part II). The material used was a 7079 aluminum alloy extruded tube. The calibration data were measurements of yield stress and Lankford ratio from uniaxial tension specimens cut along 12 orientations. Given that the tube was relatively thick-walled, some of the orientations included through-thickness components. This allowed the calibrations to be based exclusively on test data, without the need for parameter assumptions or supplemental crystal plasticity calculations. The Yld2004-18p function provided the best fit to the data available due to its 18 anisotropy parameters plus an unspecified exponent, compared to the quadratic Hill function with 6 anisotropy parameters and to the isotropic von Mises function. Whereas the Yld2004-18p function did not warrant further exploration due to the excellent fit it provided, the results showed that care must be taken when using Hill’s function. Finally, due to its parametrization with only 6 anisotropy parameters, it can significantly misrepresent the yield behavior depending on the calibration data used, possibly rendering it less desirable than a simple isotropic function in some applications.
Anodic stripping voltammetry (ASV) has been widely used for the detection of several heavy metal ions in neutral and acidic solution, in many cases employing electrodes and/or solutions incorporating Bi. In this work we demonstrate that Bi(OH)4− ion concentration can be measured in highly alkaline 8.5 M KOH solution using ASV. The addition of Pb in similar concentrations to the Bi(OH)4− being measured is shown to improve both the sensitivity and precision of the method. When the Pb additive is employed, a formal limit of detection of 8.5 ppb is achieved, compared to 17.3 ppb when the Pb additive is not used. Due to the use of Bi additives in alkaline battery chemistries, it follows that separators which limit Bi(OH)4− diffusion into the bulk electrolyte and away from the electrodes are of interest. For this purpose, we utilize ASV to determine Bi(OH)4− diffusion rates through Celgard 3501, cellophane 350P00, and Nafion 211. Bi(OH)4− crossover rates, as determined by ASV, are shown to be repeatable and consistent with expectations from the known separator structure.
Shortages of N95 respirators for use by medical personnel have driven consideration of novel conservation strategies, including decontamination for reuse and extended use. Decontamination methods listed as promising by the Centers for Disease Control and Prevention (CDC) (vaporous hydrogen peroxide (VHP), wet heat, ultraviolet irradiation (UVI)) and several methods considered for low resource environments (bleach, isopropyl alcohol and detergent/soap) were studied for two commonly used surgical N95 respirators (3M™ 1860 and 1870+ Aura™). Although N95 filtration performance depends on the electrostatically charged electret filtration layer, the impact of decontamination on this layer is largely unexplored. As such, respirator performance following decontamination was assessed based on the fit, filtration efficiency, and pressure drop, along with the relationship between (1) surface charge of the electret layer, and (2) elastic properties of the straps. Decontamination with VHP, wet heat, UVI, and bleach did not degrade fit and filtration performance or electret charge. Isopropyl alcohol and soap significantly degraded fit, filtration performance, and electret charge. Pressure drop across the respirators was unchanged. Modest degradation of N95 strap elasticity was observed in mechanical fatigue testing, a model for repeated donnings and doffings. CDC recommended decontamination methods including VHP, wet heat, and UV light did not degrade N95 respirator fit or filtration performance in these tests. Extended use of N95 respirators may degrade strap elasticity, but a loss of face seal integrity should be apparent during user seal checks. NIOSH recommends performing user seal checks after every donning to detect loss of appropriate fit. Decontamination methods which degrade electret charge such as alcohols or detergents should not be used on N95 respirators. The loss of N95 performance due to electret degradation would not be apparent to a respirator user or evident during a negative pressure user seal check.
Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for pure components in liquid, gas and super critical phases. The ANNs were tested on an experimental database of 6625 self-diffusion constants for 118 different chemical compounds. The presence of multiple phases results in a heavy skew in the distribution of diffusion constants and multiple approaches were used to address this challenge. First, an ANN was developed with the raw diffusion values to assess what the main drawbacks of this direct method were. The first approach for improving the predictions involved taking the log 10 of diffusion to provide a more uniform distribution and reduce the range of target output values used to develop the ANN. The second approach involved developing individual ANNs for each phase using the raw diffusion values. Results show that the log transformation leads to a model with the best self-diffusion constant predictions and an overall average absolute deviation (AAD) of 6.56%. The resultant ANN is a generalized model that can be used to predict diffusion across all three phases and over a diverse group of compounds. The importance of each input feature was ranked using a feature addition method revealing that the density of the compound has the largest impact on the ANN prediction of self-diffusion constants in pure compounds.
The effects of internal hydrogen on the deformation microstructures of 304L austenitic stainless steel have been characterized using electron backscattered diffraction (EBSD), transmission Kikuchi diffraction (TKD), high-resolution scanning transmission electron microscopy (HRSTEM), and nanoprobe diffraction. Samples, both thermally precharged with hydrogen and without thermal precharging, were subjected to tensile deformation of 5 and 20 pct true strain followed by multiple microscopic interrogations. Internal hydrogen produced widespread stacking faults within the as-forged initially unstrained material. While planar deformation bands developed with tensile strain in both the hydrogen-precharged and non-precharged material, the character of these bands changed with the presence of internal hydrogen. As shown by nanobeam diffraction and HRSTEM observations, in the absence of internal hydrogen, the bands were predominantly composed of twins, whereas for samples deformed in the presence of internal hydrogen, ε-martensite became more pronounced and the density of deformation bands increased. For the 20 pct strain condition, α'-martensite was observed at the intersection of ε-martensite bands in hydrogen-precharged samples, whereas in non-precharged samples α'-martensite was only observed along grain boundaries. We hypothesize that the increased prevalence of α'-martensite is a secondary effect of increased ε-martensite and deformation band density due to internal hydrogen and is not a signature of internal hydrogen itself.
Sandia National Laboratories (SNL) Employee Health Services (EHS) program believes that good health is essential to getting the most out of life, which is why we offer a variety of worksite wellness programs that put employees in control of their own health. These programs are based on current research and strategies that are proven to minimize risk and decrease the impact of illness through early detection and treatment. Services includes Health Assessments, the Virgin Pulse (VP) online wellness platform, and Health Action Plans (HAP) which include one-on-one education, organizational health initiatives, a video library, an events calendar, onsite fitness facilities, and group fitness classes. Participation in these programs help employees and their spouses earn funding for their Health Reimbursement Accounts (HRAs). The EHS Health Action Plan (HAP) initiative targets the key health risks identified through the 8-15-80 model by engaging employees to change their own healthcare story. EHS identified the most prevalent of the health risks amongst our population through Health Risk Assessment (HRA) and used that data to build Health Action Plans (HAPs). The 2020 Health Action Plans addressed improving upon inadequate sleep, lack of energy, stress, weight, physical inactivity, cardiometabolic issues (hypertension, high cholesterol, diabetes), low back pain, allergies, asthma, digestive health, tobacco use, and living well to maintaining low risk for those individuals who do not have a chronic condition to manage. These plans connect employees with our onsite registered dietitians, fitness professionals, health coaches, physical therapists, and physicians as appropriate. In addition to addressing the physical aspects of health, the plans also emphasized pre/post-assessments to encourage building behavioral and emotional skills that promote health and facilitate lifestyle changes over a minimum of three months. Just one risk reduction or behavior change can make an impact on the health of the participant’s Division as well as Sandia’s overall risk levels and ultimately its healthcare costs. Sandia employees achieved an Overall Wellness Score of 69 based on the WellSource Health Assessment (the same as last year). A score of 70-100 is considered “Doing Well”, and a score of 40-69 is in the “Caution” category. Overall in CY 2019, Sandia saw a 34% participation rate in Health Action Plan (HAP) programs (up from 33% in CY 2019) with an 89% completion rate (4% lower than CY 2019). Overall, 5,039 (347 more than CY 2019) individuals participated in 8,329 HAPs, which is 1,005 more than the last calendar year (7,324).
Priest, Chad P.; Greathouse, Jeffery A.; Kinnan, Mark K.; Burton, Patrick D.; Rempe, Susan B.
Here, we performed ab initio molecular dynamics (AIMD) simulations to benchmark bulk liquid structures and to evaluate results from all-atom force field molecular dynamics (FFMD) simulations with the generalized Amber force field (GAFF) for organophosphorus (OP) and organochlorine (OC) compounds. Our work also addresses the current and important topic of force field validation, applied here to a set of nonaqueous organic liquids. Our approach differs from standard treatments, which validate force fields based on thermodynamic data. Utilizing radial distribution functions (RDFs), our results show that GAFF reproduces the AIMD-predicted asymmetric liquid structures moderately well for OP compounds that contain bulky alkyl groups. Among the OCs, RDFs obtained from FFMD overlap well with AIMD results, with some offsets in position and peak structuring. However, re-parameterization of GAFF for some OCs is needed to reproduce fully the liquid structures predicted by AIMD. The offsets between AIMD and FFMD peak positions suggest inconsistencies in the developed force fields, but, in general, GAFF is able to capture short-ranged and long-ranged interactions of OPs and OCs observed in AIMD. Along with the local coordination structure, we also compared enthalpies of vaporization. Overall, calculated bulk properties from FFMD compared reasonably well with experimental values, suggesting that small improvements within the FF should focus on parameters that adjust the bulk liquid structures of these compounds.
The peridynamic theory of solid mechanics is applied to modeling the deformation and fracture of micrometer-sized particles made of organic crystalline material. A new peridynamic material model is proposed to reproduce the elastic–plastic response, creep, and fracture that are observed in experiments. The model is implemented in a three-dimensional, meshless Lagrangian simulation code. In the small deformation, elastic regime, the model agrees well with classical Hertzian contact analysis for a sphere compressed between rigid plates. Under higher load, material and geometrical nonlinearity is predicted, leading to fracture. Finally, the material parameters for the energetic material CL-20 are evaluated from nanoindentation test data on the cyclic compression and failure of micrometer-sized grains.
Helium is frequently used as a working medium for the generation of plasmas and is capable of energetic photon emissions. These energetic photon emissions are often attributed to the formation of helium excimer and subsequent photon emission. When the plasma device is exposed to another gas, such as nitrogen, this energetic photon emission can cause photoionization and further ionization wave penetration into the additional gas. Often ignored are the helium resonance emissions that are assumed to be radiation trapped and therefore not pertinent to photoionization. Here, experimental evidence for the presence of helium atomic emission in a pulsed discharge at ten's of Torr is shown. Simulations of a discharge in similar conditions agree with the experimental measurements. In this context, the role of atomic and molecular helium light emission on photoionization of molecular nitrogen in an ionization wave is studied using a kinetic modeling approach that accounts for radiation dynamics in a developing low-temperature plasma. Three different mixtures of helium at a total pressure of 250 Torr are studied in simulation. Photoionization of the nitrogen molecule by vacuum ultraviolet helium emission is used as the only seed source ahead of the ionization front. It is found that even though radiation trapped, the atomic helium emission lines are the significant source of photoionization of nitrogen. The significant effect of radiation trapped photon emission on ionization wave dynamics demonstrates the need to consider these radiation dynamics in plasma reactors where self-absorbed radiation is ignored.
A small number of associating groups incorporated onto a polymer backbone have dramatic effects on the mobility and viscoelastic response of the macromolecules in melts. These associating groups assemble, driving the formation of clusters, whose lifetime affects the properties of the polymers. Here, we probe the effects of the interaction strength on the structure and dynamics of two topologies, linear and star polymer melts, and further investigate blends of associative and non-associating polymers using molecular dynamics simulations. Polymer chains of approximately one entanglement length are described by a bead-spring model, and the associating groups are incorporated in the form of interacting beads with an interaction strength between them that is varied from 1 to 20 kBT. We find that, for all melts and blends, interaction of a few kBT between the associating groups drives cluster formation, where the size of the clusters increases with increasing interaction strength. These clusters act as physical crosslinkers, which slow the chain mobility. Blends of chains with and without associating groups macroscopically phase separate for interaction strength between the associating groups of a few kBT and above. For weakly interacting associating groups, the static structure function S(q) is well fit by functional form predicted by the random phase approximation where a clear deviation occurs as phase segregation takes place, providing a quantitative assessment of phase segregation.
Wire X-pinches (WXPs) have been studied comprehensively as fast (∼ 1 ns pulse width), small (∼ 1 μm) x-ray sources, created by twisting two or more fine wires into an "X"to produce a localized region of extreme magnetic pressure at the cross-point. Recently, two alternatives to the traditional WXP have arisen: The hybrid X-pinch (HXP), composed of two conical electrodes bridged by a thin wire or capillary, and the laser-cut foil X-pinch (LCXP), cut from a thin foil using a laser. We present a comparison of copper wire, hybrid, and laser-cut foil X-pinches on a single experimental platform: UC San Diego's ∼ 200 kA, 150 ns rise time GenASIS driver. All configurations produced 1-2 ns pulse width, ≤ 5 μm soft x-ray (Cu L-shell, ∼ 1 keV) sources (resolutions diagnostically limited) with comparable fluxes. WXP results varied with linear mass and wire count, but consistently showed separate pinch and electron-beam-driven sources. LCXPs produced the brightest (∼ 1 MW), smallest (≤ 5 μm) Cu K-shell sources, and spectroscopic data showed both H-like Cu K α lines indicative of source temperatures ≥ 2 keV, and cold K α (∼ 8050 eV) characteristic of electron beam generated sources, which were not separately resolved on other diagnostics (within 1-2 ns and ≤ 200 μm). HXPs produced minimal K-shell emission and reliably single, bright, and small L-shell sources after modifications to shape the early current pulse through them. Benefits and drawbacks for each configuration are discussed to provide potential X-pinch users with the information required to choose the configuration best suited to their needs.
Addamane, Sadhvikas J.; Laurain, Alexandre; Baker, Caleb W.; Rotter, Thomas J.; Watt, John; Reno, J.L.; Balakrishnan, Ganesh; Moloney, Jerome V.
Semiconductor saturable absorber mirrors (SESAMs) enable passive modelocking of several ultrafast solid-state lasers. Conventionally, SESAMs in the 1-µm wavelength range have employed InGaAs quantum wells (QWs) as absorbers. Here we demonstrate a SESAM based on InAs/GaAs submonolayer quantum dots (SML QDs) capable of generating femtosecond pulses by passively modelocking a vertical-external-cavity surface-emitting laser (VECSEL). Structural measurements are carried out to verify the quality and composition of the QDs. Modelocking experiments with a VECSEL and the QD SESAM in a ring cavity configuration yield pulses as short as 185 fs at 1025 nm. Compared to a traditional QW absorber, SML QD SESAMs exhibit ~ 25% faster recovery times. This also translates to slower power degradation rates or higher damage thresholds in SML QD SESAMs.
Maximum pit sizes were predicted for dilute and concentrated NaCl and MgCl2 solutions as well as sea-salt brine solutions corresponding to 40% relative humidity (RH) (MgCl2-rich) and 76% RH (NaCl-rich) at 25 °C. A quantitative method was developed to capture the effects of various cathode evolution phenomena including precipitation and dehydration reactions. Additionally, the sensitivity of the model to input parameters was explored. Despite one's intuition, the highest chloride concentration (roughly 10.3 M Cl−) did not produce the largest predicted pit size as the ohmic drop was more severe in concentrated MgCl2 solutions. Therefore, the largest predicted pits were calculated for saturated NaCl (roughly 5 M Cl−). Next, it was determined that pit size predictions are most sensitive to model input parameters for concentrated brines. However, when the effects of cathodic reactions on brine chemistry are considered, the sensitivity to input parameters is decreased. Although there was not one main input parameter that influenced pit size predictions, two main categories were identified. Under similar chloride concentrations (similar RH), the water layer thickness (WL), and pit stability product, (i·x)sf, are the most influential factors. When varying chloride concentrations (RH), changes in WL, the brine specific cathodic kinetics on the external surface (captured in the equivalent current density (ieq)), and conductivity (κo) are the most influential parameters. Finally, it was noted that dehydration reactions coupled with precipitation in the cathode will have the largest effect on predicted pit size, and cause the most significant inhibition of corrosion damage.
Ryder, Landen D.; Ryder, Kaitlyn L.; Sternberg, Andrew L.; Kozub, John A.; Zhang, En X.; Linten, Dimitri; Croes, Kristof; Weller, Robert A.; Schrimpf, Ronald D.; Weiss, Sharon M.; Reed, Robert A.
Pulsed-laser induced single event current measurements on two geometries of waveguide-integrated germanium photodiodes were conducted over a range of operating voltages to examine the impact of photodiode geometry on the transient response. Vertical PIN photodiodes exhibit transients with a duration that is relatively independent of the operating voltage while the transient duration in lateral PIN photodiodes depends on operating voltage. Furthermore, the experimental measurements facilitate identification of device dimensions that impact the transient response. In this work, these results can be used to identify potential radiation mitigation strategies for photodiodes operating in a radiation environment. Understanding the implications of design choices is critical for designing integrated photonic systems that balance system performance with tolerance for radiation degradation.
Ryder, Kaitlyn L.; Ryder, Landen D.; Sternberg, Andrew L.; Kozub, John A.; Zhang, En X.; Lalumondiere, Stephen D.; Khachatrian, Ani; Buchner, Steven P.; Mcmorrow, Dale P.; Hales, Joel M.; Zhao, Yuanfu; Wang, Liang; Wang, Chuanmin; Weller, Robert A.; Schrimpf, Ronald D.; Weiss, Sharon M.; Reed, Robert A.
Heavy ion, focused x-ray, and pulsed laser single event transient experiments are performed on a silicon epitaxial diode. Collected charge, transient rise times, and transient fall times are calculated and compared between the different sources. It is observed that these transient shape characteristics depend on the source (ion, x-ray, or laser), even when similar amounts of charge are generated. Finally, the observed differences are examined and explained in terms of basic charge collection mechanisms.
Epitaxial lithium niobate (LNO) thin films are an attractive material for devices across a broad range of fields, including optics, acoustics, and electronics. These applications demand high-quality thin films without in-plane growth domains to reduce the optical/acoustical losses and optimize efficiency. Twin-free single-domain-like growth has been achieved previously, but it requires specific growth conditions that might be hard to replicate. In this work, a versatile nanocomposite-seeded approach is demonstrated as an effective approach to grow single-domain epitaxial lithium niobate thin films. Films are grown through a pulsed laser deposition method and growth conditions are optimized to achieve high-quality epitaxial film. A comprehensive microstructure characterization is performed and optical properties are measured. A piezoelectric acoustic resonator device is developed to demonstrate the future potential of the nanocomposite-seeded approach for high-quality LNO growth for radio frequency (RF) applications.
Industrial accidents, such as the Fukushima and Chernobyl disasters, release harmful chemicals into the environment, covering large geographical areas. Natural flora may serve as biological sensors for detecting metal contamination, such as cesium. Spectral detection of plant stresses typically employs a few select wavelengths and often cannot distinguish between different stress phenotypes. In this study, we apply hyperspectral reflectance imaging in the visible and near-infrared along with multivariate curve resolution (MCR) analysis to identify unique spectral signatures of three stresses in Arabidopsis thaliana: salt, copper, and cesium. While all stress conditions result in common stress physiology, hyperspectral reflectance imaging and MCR analysis produced unique spectral signatures that enabled classification of each stress. As the level of potassium was previously shown to affect cesium stress in plants, the response of A. thaliana to cesium stress under variable levels of potassium was also investigated. Increased levels of potassium reduced the spectral response of A. thaliana to cesium and prevented changes to chloroplast cellular organization. While metal stress mechanisms may vary under different environmental conditions, this study demonstrates that hyperspectral reflectance imaging with MCR analysis can distinguish metal stress phenotypes, providing the potential to detect metal contamination across large geographical areas.
In this position paper we will address challenges and opportunities relating to the design and codesign of application specific circuits. Given our background as computational scientists, our perspective is from the viewpoint of a highly motivated application developer as opposed to career computer architects
In this work, we present modal-based methods for model calibration in structural dynamics, and address several key challenges in the solution of gradient-based optimization problems with eigenvalues and eigenvectors, including the solution of singular Helmholtz problems encountered in sensitivity calculations, non-differentiable objective functions caused by mode swapping during optimization, and cases with repeated eigenvalues. Unlike previous literature that relied on direct solution of the eigenvector adjoint equations, we present a parallel iterative domain decomposition strategy (Adjoint Computation via Modal Superposition with Truncation Augmentation) for the solution of the singular Helmholtz problems. For problems with repeated eigenvalues we present a novel Mode Separation via Projection algorithm, and in order to address mode swapping between inverse iterations we present a novel Injective mode ordering metric. We present the implementation of these methods in a massively parallel finite element framework with the ability to use measured modal data to extract unknown structural model parameters from large complex problems. A series of increasingly complex numerical examples are presented that demonstrate the implementation and performance of the methods in a massively parallel finite element framework [7,5], using gradient-based optimization techniques in the Rapid Optimization Library (ROL) [21].
Powell, Amy; Acquesta, Erin C.S.; Davis, Warren L.; Nichol, Jefferey J.; Tezaur, Irina; Peterson, Kara; Rempe, Susan; Huerta, Jose G.
We propose a novel synthesis of observational and simulated data (climatological and biological) to enhance understanding of the real-world interplay between climate (here, the water cycle) and the epidemiology of water cycle-driven infectious disease. Aligning with Focal Area 2, predictive modeling using AI techniques, we will develop systems of hierarchical models to discover latent features of the water cycle. Our approach will leverage state-of-the-art in Artificial Intelligence (AI) to measure the degree to which climate change-driven shifts in water cycle can be predicted by supplementing sparse and irregular climate data with water cycle-driven infectious disease resources.
Grain boundaries in metallic materials can exist in a wide range of stable and metastable structures. In addition, the properties of a grain boundary may be altered through solute segregation. In this work, we present a formulation that combines the spectrum of embrittling potencies associated with solute segregation with site-occupancy statistics. As a prototype problem, we illustrate the relation between segregation and embrittlement in the case of S segregation to grain boundaries in Ni. To obtain a population of site segregation energies, we perform molecular statics calculations on 378 different symmetric-tilt grain boundaries and their free surface equivalents, using an embedded-atom method interatomic potential developed specifically for studying embrittlement. Our results show that it is important to consider both the energies associated with embrittlement and the probability of occupancy to describe the general embrittling nature of a grain boundary. When analyzed in isolation, certain grain boundaries show large embrittling potencies; however, that effect is diminished when the probability of S segregation to that grain boundary is considered within a polycrystal. We propose a new quantity, the embrittling estimator, which not only categorizes grain boundaries as embrittling or strengthening, but also considers site occupancy probabilities, so that the embrittlement behavior of grain boundaries within a network of grain boundaries can be compared. Finally, we examine the relationship between embrittlement behavior and innate grain boundary properties, such as the free volume, and find statistical evidence that the complex nature of embrittlement cannot be explained by linear correlations with excess volumes or energies. Ultimately, this combined approach provides a theoretical tool to assist grain boundary engineering of metastable alloys.
Here we examine approximate geometrically self-similar solutions to a parabolic free boundary value problem applied to alluvial fan surface morphology and growth. Alluvial fans are fan- or cone-shaped sedimentary deposits caused by the rapid deposition of sediment from a canyon discharging onto a flatter plain. Longitudinal, topographic profiles of fans can be readily described by a seemingly time independent dimensionless profile (DeChant et al., 1999). However, because an alluvial fan can be expected to grow over time, it is clear that this “steady” profile is certainly time dependent and can be described using a space-time self-similar solution. In an experimental and theory-based study, Guerit et al. (2014) developed a self-similar (or as they describe it a self-affine) linear solution based upon an approximate first order small parameter expansion solution for a 1-d homogeneous nonlinear diffusion equation. Direct substitution of this result into a linear diffusion equation suggests that this first order expression may not fully satisfy the associated governing equation. In contrast, we develop a more complete solution based upon a modeled approximation for the axi-symmetric formulation such that the associated temporal behavior is consistent with a 1/3 time power-law as described by Reitz and Jerolmack (2014). The resulting expression is an exact solution to a linear heat equation. We emphasize that a small parameter is not inherent to the resulting profile result and is not included in our model development. Though developed using rather different approaches, the formal solution developed here is in good agreement with the simple polynomial described by DeChant et al. (1999) suggesting that this self-similar solution is a suitable time dependent representation of alluvial fan longitudinal profile form and improves on earlier work.
Nanocrystalline (NC) metals suffer from an intrinsic thermal instability; their crystalline grains undergo rapid coarsening during processing treatments or under service conditions. Grain boundary (GB) solute segregation has been proposed to mitigate grain growth and thermally stabilize the grain structures of NC metals. However, the role of GB character in solute segregation and thermal stability of NC metals remains poorly understood. Herein, we employ high resolution microscopy techniques, atomistic simulations, and theoretical analysis to investigate and characterize the impact of GB character on segregation behavior and thermal stability in a model NC Pt-Au alloy. High resolution electron microscopy along with X-ray energy dispersive spectroscopy and automated crystallographic orientation mapping is used to obtain spatially correlated Pt crystal orientation, GB misorientation, and Au solute concentration data. Atomistic simulations of polycrystalline Pt-Au systems are used to reveal the plethora of GB segregation profiles as a function of GB misorientation and the corresponding impact on grain growth processes. With the aid of theoretical models of interface segregation, the experimental data for GB concentration profiles are used to extract GB segregation energies, which are then used to elucidate the impact of GB character on solute drag effects. Our results highlight the paramount role of GB character in solute segregation behavior. In broad terms, our approach provides future avenues to employ GB segregation as a microstructure design strategy to develop NC metallic alloys with tailored microstructures. This journal is
Coronal mass ejections (CMEs) occur when long-lived magnetic flux ropes (MFRs) anchored to the solar surface destabilize and erupt away from the Sun. This destabilization is often described in terms of an ideal magnetohydrodynamic instability called the torus instability. It occurs when the external magnetic field decreases sufficiently fast such that its decay index, n = -z θ(ln B) θz, is larger than a critical value, n > ncr, where ncr = 1.5 for a full, large aspect ratio torus. However, when this is applied to solar MFRs, a range of conflicting values for ncr is found in the literature. To investigate this discrepancy, we have conducted laboratory experiments on arched, line-tied flux ropes and applied a theoretical model of the torus instability. Our model describes an MFR as a partial torus with foot points anchored in a conducting surface and numerically calculates various magnetic forces on it. This calculation yields better predictions of ncr that take into account the specific parameters of the MFR. We describe a systematic methodology to properly translate laboratory results to their solar counterparts, provided that the MFRs have a sufficiently small edge safety factor or, equivalently, a large enough twist. After this translation, our model predicts that ncr in solar conditions falls near ncr ~ 0.9 solar and within a larger range of ncr ~ (0.7, 1.2) solar, depending on the parameters. The methodology of translating laboratory MFRs to their solar counterparts enables quantitative investigations of CME initiation through laboratory experiments. These experiments allow for new physics insights that are required for better predictions of space weather events but are difficult to obtain otherwise.
Dynamic interface instabilities such as Rayleigh–Taylor, Kelvin–Helmholtz, and Richtmyer–Meshkov are important in a number of physical phenomena. Besides meriting study because of their role in natural events and man-made applications, they can also be used to study constitutive properties of materials in extreme conditions. Both RTI and RMI configurations have been used to study the strength of solids at high strain rates, though RMI has largely been limited to zero or ambient pressure. Recently, advances in imaging have allowed tamped RMI experiments to be performed in which the pressure is maintained above ambient. In this study, we examine the tamped RMI for determining material strength. Through simulation, we explore the behavior of the jetting material and examine the sensitivity of jetting to material properties. We identify simple scaling laws that relate the key physical parameters controlling jetting, which are compared to previous results from the literature. We use these scaling law and other considerations to examine issues associated with tamped RMI experiments.
Objectives: Introduce a sensor selection approach to assist test engineers with MIMO test design. Demonstrate the capability of the approach. Approach: Define a desired response from a field model. Supply the sensor selection technique to two lab models, with different boundary conditions than the “field” model. Compare the laboratory response to the field response using sensors selected from the approach.
Summary: Sensor selection approach for MIMO testing was defined and demonstrated on a model of a practical system. Laboratory response obtained using the approach matched the field response well. Information about how many control sensors, and where to locate sensors can be gleaned from the approach.
Fracture resistance of pipeline welds from a range of strength grades and welding techniques was measured in air and 21 MPa hydrogen gas, including electric resistance weld of X52, friction stir weld of X100 and gas metal arc welds (GMAW) of X52, X65 and X100. Welds exhibited a decrease in fracture resistance in hydrogen compared to complementary tests in air. A general trend was observed that fracture resistance in 21 MPa hydrogen gas decreased with increasing yield strength. To accommodate material constraints, two different fracture coupon geometries were used in this study, which were shown to yield similar fracture resistance values in air and 21 MPa hydrogen gas; values using different coupons resulted in less than 15% difference. In addition, fracture coupons were removed from controlled locations in select welds to examine the potential influence of orientation and residual stress. The two orientations examined in the X100 GMAW exhibited negligible differences in fracture resistance in air and, similarly, negligible differences in hydrogen. Residual stress exhibited a modest influence on fracture resistance; however, a consistent trend was not observed between tests in air and hydrogen, suggesting further studies are necessary to better understand the influence of residual stress. A comparison of welds and base metals tested in hydrogen gas showed similar susceptibility to hydrogen-assisted fracture. The overall dominant factor in determining the susceptibility to fracture resistance in hydrogen is the yield strength.