This User's Guide serves as a brief introduction to the RAPTURE radiation effects analysis code. It includes an overview of the input format, RAPTURE's error- and consistency-checking of the user-provided input files, the automatic-differentiation and convergce-checking schemes employed by RAPTURE, and the RAPTURE output files. A variety of example problems are included in this Guide which collectively demonstrate RAPTURE's current capabilities and provide a suite of test problems and template input files for the user. This Guide includes, for each problem, the problem description, RAPTURE input files, and comparison of the RAPTURE solution with solutiong generated with the Monte Carlo transport code ITS, the legacy deterministic code ADEPT, and, where possible, published experimental results. An appendix includes a description of all keywords and options in the RAPTURE input file.
The use of gradient-based data-driven models to solve a range of real-world remote sensing problems can in practice be limited by the uniformity of available data. Use of data from disparate sensor types, resolutions, and qualities typically requires compromises based on assumptions that are made prior to model training and may not necessarily be optimal given over-arching objectives. For example, while deep neural networks (NNs) are state-of-the-art in a variety of target detection problems, training them typically requires either limiting the training data to a subset over which uniformity can be enforced or training independent models which subsequently require additional score fusion. The method we introduce here seeks to leverage the benefits of both approaches by allowing correlated inputs from different data sources to co-influence preferred model solutions, while maintaining flexibility over missing and mismatching data. In this work we propose a new data fusion technique for gradient updated models based on entropy minimization and experimentally validate it on a hyperspectral target detection dataset. We demonstrate superior performance compared to currently available techniques using a range of realistic data scenarios, where available data has limited spacial overlap and resolution.
Commercial spent nuclear fuel (SNF) is accumulating at 72 sites across the U.S., at the rate of about 2,000 metric tons of uranium (MTU) per year. There are currently more than 2,700 dualpurpose canisters (DPCs) loaded with SNF, which are designed for storage and transportation but not disposal. If current storage practices continue, about half the eventual total U.S. SNF inventory will be in about 5,500 dry storage systems by 2035, with the entire inventory stored in 10,000 or more by 2060. The quantity of SNF in DPCs is now much greater than that anticipated in the past, leading the DOE to investigate the technical feasibility of direct disposal of SNF in DPCs. Studies in 2013-2015 concluded that the main technical challenges for disposal of SNF in DPCs are thermal management, handling and emplacement of large, heavy waste packages, and postclosure criticality control (Hardin et al. 2015). Of these, postclosure criticality control is the most challenging, and the R&D needed for this aspect of DPC direct disposal is the primary focus of this report.
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 SPR's 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. 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 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 cavern's 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 includes an update to the baseline drawdowns for each cavern, and provides an initial assessment of the evolution of drawdown expenditure for several caverns
We are assessing the efficacy and integrity of Personal Protective Equipment (PPE) after irradiating the PPE with gamma radiation over a three-week sprint (report should be available before April 17th)
This report describes a proof-of-concept method of seismic source discrimination using seismic gradiometry and a common machine learning technique. The tests described here are purely numerical, using synthetic seismic data and well understood mathematical techniques. The primary innovation described here is the application of a richer seismic data set derived from seismic gradiometry. Seismic gradiometry is a method to estimate the time variable spatial gradient of the wavefield to compute various wavefield attributes such as slowness, dynamic strain, and rotational motions. With the addition of these wavefield attributes, we are afforded up to twenty "compo- nents" of time series data measured at a single point on, or in, the Earth. This is in direct contrast to conventional three-component seismic data collected at several locations using a seismic network. Using the gradiometrically-derived wavefield components directly in a single-layer neural network, I show that it is possible to discriminate between three common seismic source types (earthquakes, explosions, and opening fractures) for various noise conditions and gradiometry configurations.
The Recorded Information Management (RIM) training and guidance materials were originally evaluated to determine the current status of the training program. Specifically, how and where are training materials implemented and are members of the workforce (MOWs) regularly accessing them. The evaluation highlighted that there is a breadth of training materials and guidance available; however, the materials are often outdated, point to old Sandia Policies, and/or are in outdated templates. Additionally, there is currently no single-entry point for training, meaning that training is available via the RIM homepage, TEDs, etc. This means that MOWs must search in various webpages or systems for training. To ensure RIM training materials are regularly updated and are accessible for MOWs it is recommended to assign one staff member to manage the program training materials.
This report presents work performed in 2017 and is a reissue of the end-of-year report SAND2018-0240, A Proof-of-Concept Approach to DevOps and Microservices, January 2018, modified for unlimited release. This report describes the approach, investigation, and prototyping efforts to create an API management solution and automated deployment pipeline for REST-based microservices. Additionally, it reviews: the microservices created for testing purposes; our experiences and results in using an open-source API management tool; and future plans.
Practical applications of nanocrystalline metallic thin films are often limited by instabilities. In addition to grain growth, the thin film itself can become unstable and collapse into islands through solid-state dewetting. Selective alloying can improve nanocrystalline stability, but the impact of this approach on dewetting is not clear. In this study, two alloys that exhibit nanocrystalline thermal stability as ball milled powders are evaluated as thin films. While both alloys demonstrated dewetting behavior following annealing, the severity decreased in more dilute compositions. Ultimately, a balance may be struck between nanocrystalline stability and thin film structural stability by tuning dopant concentration.
Nanocrystalline metals are promising radiation tolerant materials due to their large interfacial volume fraction, but irradiation-induced grain growth can eventually degrade any improvement in radiation tolerance. Therefore, methods to limit grain growth and simultaneously improve the radiation tolerance of nanocrystalline metals are needed. Amorphous intergranular films are unique grain boundary structures that are predicted to have improved sink efficiencies due to their increased thickness and amorphous structure, while also improving grain size stability. In this study, ball milled nanocrystalline Cu-Zr alloys are heat treated to either have only ordered grain boundaries or to contain amorphous intergranular films distributed within the grain boundary network, and are then subjected to in situ transmission electron microscopy irradiation and ex situ irradiation. Differences in defect density and grain growth due to grain boundary complexion type are then investigated. When amorphous intergranular films are incorporated within the material, fewer and smaller defect clusters are observed while grain growth is also limited, leading to nanocrystalline alloys with improved radiation tolerance.
Harris, Zachary D.; Bhattacharyya, Jishnu J.; Ronevich, Joseph A.; Agnew, Sean R.; Burns, James T.
The effect of hydrogen (H) on the deformation behavior of Monel K-500 in various isothermal heat treatment conditions (non-aged, under-aged, peak-aged, and over-aged) was assessed via uniaxial mechanical testing. H-charged and non-charged specimens were strained to failure to facilitate a comparison of ductility, fracture surface morphology, strength, and work hardening behavior. For all examined heat treatment conditions, H charging leads to a significant reduction in ductility, which is accompanied by a consistent change in fracture surface morphology from ductile microvoid coalescence to brittle intergranular fracture. While H charging led to a systematic enhancement in the yield strength of all heat treatments, the three age-hardened conditions exhibited a more than 2-fold increase relative to the non-aged heat treatment. This suggests that H modifies the dislocation–precipitate interactions, which also manifest themselves through changes in work hardening metrics related to the dislocation storage and recovery rates. In particular, the H-charged peak-aged specimen exhibited a significant increase in initial hardening (dislocation storage) rate relative to the H-charged under-aged specimen. Transmission electron microscopy of these samples revealed the onset of widespread dislocation looping in the H-charged peak-aged sample, in addition to the planar slip bands characteristic of the non-charged condition. This result suggests that hydrogen induces the particle shearing-to-looping transition at smaller particle sizes. Possible mechanistic explanations for this observed behavior are presented.
In many experiments on microscopic quantum systems, it is implicitly assumed that when a macroscopic procedure or “instruction” is repeated many times – perhaps in different contexts – each application results in the same microscopic quantum operation. But in practice, the microscopic effect of a single macroscopic instruction can easily depend on its context. If undetected, this can lead to unexpected behavior and unreliable results. Here, we design and analyze several tests to detect context-dependence. They are based on invariants of matrix products, and while they can be as data intensive as quantum process tomography, they do not require tomographic reconstruction, and are insensitive to imperfect knowledge about the experiments. We also construct a measure of how unitary (reversible) an operation is, and show how to estimate the volume of physical states accessible by a quantum operation.
Nolen, J.R.; Runnerstrom, Evan L.; Kelley, Kyle P.; Luk, Ting S.; Folland, Thomas G.; Cleri, Angela; Maria, Jon P.; Caldwell, Joshua D.
Spectroscopic ellipsometry and Fourier transform infrared spectroscopy were applied to extract the ultraviolet to far-infrared (150-33333cm-1) complex dielectric functions of high-quality, sputtered indium-doped cadmium oxide (In:CdO) thin crystalline films on MgO substrates possessing carrier densities (Nd) ranging from 1.1×1019cm-3 to 4.1×1020cm-3. A multiple oscillator fit model was used to identify and analyze the three major contributors to the dielectric function and their dependence on doping density: interband transitions in the visible, free-carrier excitations (Drude response) in the near- to far-infrared, and IR-active optic phonons in the far-infrared. More specifically, values pertinent to the complex dielectric function such as the optical band gap (Eg), are shown here to be dependent upon carrier density, increasing from approximately 2.5-3 eV, while the high-frequency permittivity (ϵ∞) decreases from 5.6 to 5.1 with increasing carrier density. The plasma frequency (ωp) scales as Nd, resulting in ωp values occurring within the mid- to near-IR, and the effective mass (m∗) was also observed to exhibit doping density-dependent changes, reaching a minimum of 0.11mo in unintentionally doped films (1.1×1019cm-3). Good quantitative agreement with prior work on polycrystalline, higher-doped CdO films is also demonstrated, illustrating the generality of the results. The analysis presented here will aid in predictive calculations for CdO-based next-generation nanophotonic and optoelectronic devices, while also providing an underlying physical description of the key properties dictating the dielectric response in this atypical semiconductor system.
The generation 3 concentrating solar power, or Gen3CSP, campaign seeks to de-risk and deploy a CSP pilot plant through three parallel project tracks focused on solid, liquid, and gas-phase primary heat transfer fluids. Although the components between the sun and the primary heat exchanger from the thermal storage system differ with each track, the supercritical carbon dioxide (sCO2) coolant system required to cool the primary heat exchanger in place of a complete power conversion system has very similar requirements regardless of the primary heat transfer fluid. In order to avoid duplicative efforts, this project will design, assemble, perform acceptance testing, and deploy a single sCO2 coolant system design meeting the needs of any Gen3CSP topic 1 pathway pilot plant design.
Ring-enlargement reactions can provide a fast route towards the formation of six-membered single-ring or polycyclic aromatic hydrocarbons (PAHs). To investigate the participation of the cyclopentadienyl (C5H5) radical in ring-enlargement reactions in high-temperature environments, a mass-spectrometric study was conducted. Experimental access to the C5H5 high-temperature chemistry was provided by two counterflow diffusion flames. Cyclopentene was chosen as a primary fuel given the large amount of resonantly stabilized cyclopentadienyl radicals produced by its decomposition and its high tendency to form PAHs. In a second experiment, methane was added to the fuel stream to promote methyl addition pathways and to assess the importance of ring-enlargement reactions for PAH growth. The experimental dataset includes mole fraction profiles of small intermediate hydrocarbons and of several larger species featuring up to four condensed aromatic rings. Results show that, while the addition of methane enhances the production of methylcyclopentadiene and benzene, the concentration of larger polycyclic hydrocarbons is reduced. The increase of benzene is probably attributable to the interaction between the methyl and the cyclopentadienyl radicals. However, the formation of larger aromatics seems to be dominated only by the cyclopentadienyl driven molecular-growth routes which are hampered by the addition of methane. In addition to the experimental work, two chemical mechanisms were tested and newly calculated reaction rates for cyclopentadiene reactions were included. In an attempt to assess the impact of cyclopentadienyl ring-enlargement chemistry on the mechanisms' predictivity, pathways to form benzene, toluene, and ethylbenzene were investigated. Results show that the updated mechanism provides an improved agreement between the computed and measured aromatics concentrations. Nevertheless, a detailed study of the single reaction steps leading to toluene, styrene, and ethylbenzene would be certainly beneficial.
Contact instability may occur during discharging because of void formation. Xin Zhang et al. suggested a method to predict the conditions leading to instability. The development of solid-state batteries has encountered a number of problems due to the complex interfacial contact conditions between lithium (Li) metal and solid electrolytes (SEs). Recent experiments have shown that applying stack pressure can ameliorate these problems. Here, we report a multi-scale three-dimensional time-dependent contact model for describing the Li-SE interface evolution under stack pressure. Our simulation considers the surface roughness of the Li and SEs, Li elastoplasticity, Li creep, and the Li metal plating/stripping process. Consistency between the very recent experiments from two different research groups indicates effective yield strength of the Li used in those experiments of 16 ± 2 MPa. We suggest that the preferred stack pressure be at least 20 MPa to maintain a relatively small interface resistance while reducing void volume.
Jorgensen, Mathias; Shea, Patrick T.; Tomich, Anton W.; Varley, Joel B.; Bercx, Marnik; Laros, James H.; Cerny, Radovan; Erny; Zhou, Wei; Udovic, Terrence J.; Lavallo, Vincent; Fortune, Torben R.; Wood, Brandon C.; Stavila, Vitalie S.
Solid-state ion conductors based on closo-polyborate anions combine high ionic conductivity with a rich array of tunable properties. Cation mobility in these systems is intimately related to the strength of the interaction with the neighboring anionic network and the energy for reorganizing the coordination polyhedra. Here, we explore such factors in solid electrolytes with two anions of the weakest coordinating ability, [HCB11H5Cl6]- and [HCB11H5Br6]-, and a total of 11 polymorphs are identified for their lithium and sodium salts. Our approach combines ab initio molecular dynamics, synchrotron X-ray powder diffraction, differential scanning calorimetry, and AC impedance measurements to investigate their structures, phase-transition behavior, anion orientational mobilities, and ionic conductivities. We find that M(HCB11H5X6) (M = Li, Na, X = Cl, Br) compounds exhibit order-disorder polymorphic transitions between 203 and 305 °C and display Li and Na superionic conductivity in the disordered state. Through detailed analysis, we illustrate how cation disordering in these compounds originates from a competitive interplay among the lattice symmetry, the anion reorientational mobility, the geometric and electronic asymmetry of the anion, and the polarizability of the halogen atoms. These factors are compared to other closo-polyborate-based ion conductors to suggest guidelines for optimizing the cation-anion interaction for fast ion mobility. This study expands the known solid-state poly(carba)borate-based materials capable of liquid-like ionic conductivities, unravels the mechanisms responsible for fast ion transport, and provides insights into the development of practical superionic solid electrolytes.
Magnesium borohydride (Mg(BH4)2, abbreviated here MBH) has received tremendous attention as a promising onboard hydrogen storage medium due to its excellent gravimetric and volumetric hydrogen storage capacities. While the polymorphs of MBH - alpha (α), beta (β), and gamma (γ) - have distinct properties, their synthetic homogeneity can be difficult to control, mainly due to their structural complexity and similar thermodynamic properties. Here, we describe an effective approach for obtaining pure polymorphic phases of MBH nanomaterials within a reduced graphene oxide support (abbreviated MBHg) under mild conditions (60-190 °C under mild vacuum, 2 Torr), starting from two distinct samples initially dried under Ar and vacuum. Specifically, we selectively synthesize the thermodynamically stable α phase and metastable β phase from the γ-phase within the temperature range of 150-180 °C. The relevant underlying phase evolution mechanism is elucidated by theoretical thermodynamics and kinetic nucleation modeling. The resulting MBHg composites exhibit structural stability, resistance to oxidation, and partially reversible formation of diverse [BH4]- species during de- and rehydrogenation processes, rendering them intriguing candidates for further optimization toward hydrogen storage applications.
GaN p-n diodes were formed by selective area regrowth on freestanding GaN substrates using a dry etch, followed by post-etch surface treatment to reduce etch-induced defects, and subsequent regrowth into wells. Etched-and-regrown diodes with a 150 μm diameter achieved 840 V operation at 0.5 A/cm2 reverse current leakage and a specific on-resistance of 1.2 mΩ·cm2. Etched-and-regrown diodes were compared with planar, regrown diodes without etching on the same wafer. Both types of diodes exhibited similar forward and reverse electrical characteristics, which indicate that etch-induced defectivity of the junction was sufficiently mitigated so as not to be the primary cause for leakage. An area dependence for forward and reverse leakage current density was observed, suggesting that the mesa sidewall provided a leakage path.
Three-dimensional (3D) strain induced in self-assembled vertically aligned nanocomposite (VAN) epitaxial films provides an unrivaled method to induce very large strains in thin films. Here, by growing VAN films of EuTiO3 (ETO)-Eu2O3 (EO) with different EO fractions, the vertical strain was systematically increased in ETO, up to 3.15%, and the Eu-Ti-Eu bond angle along ⟨111»decreased by up to 1°, leading to a weakening of the antiferromagnetic interactions and switching from antiferromagnetic to ferromagnetic behavior. Our work has shown for the first time that Eu-Ti-Eu superexchange interactions play a key role in determining the magnetic ground state of ETO. More broadly, our work serves as an exemplar to show that multifunctionalities in strong spin-lattice coupling perovskite oxides can be uniquely tuned at the atomic scale using simple VAN structures.
Magnesium oxide (MgO) can convert to different magnesium-containing compounds depending on exposure and environmental conditions. Many MgO-based phases contain hydrated species allowing 1H-nuclear magnetic resonance (NMR) spectroscopy to be used in the characterization and quantification of proton-containing phases; however, surprisingly limited examples have been reported. Here, 1H-magic angle spinning (MAS) NMR spectra of select Mg-based minerals are presented and assigned. These experimental results are combined with computational NMR density functional theory (DFT) periodic calculations to calibrate the predicted chemical shielding results. This correlation is then used to predict the NMR shielding for a series of different MgO hydroxide, magnesium chloride hydrate, magnesium perchlorate, and magnesium cement compounds to aid in the future assignment of 1H-NMR spectra for complex Mg phases.
Fink, D.R.; Lee, S.; Kodati, S.H.; Rogers, V.; Ronningen, T.J.; Winslow, M.; Grein, C.H.; Jones, A.H.; Campbell, J.C.; Klem, John F.; Krishna, S.
We present a method of determining the background doping type in semiconductors using capacitance-voltage measurements on overetched double mesa p-i-n or n-i-p structures. Unlike Hall measurements, this method is not limited by the conductivity of the substrate. By measuring the capacitance of devices with varying top and bottom mesa sizes, we were able to conclusively determine which mesa contained the p-n junction, revealing the polarity of the intrinsic layer. This method, when demonstrated on GaSb p-i-n and n-i-p structures, concluded that the material is residually doped p-type, which is well established by other sources. The method was then applied to a 10 monolayer InAs/10 monolayer AlSb superlattice, for which the doping polarity was unknown, and indicated that this material is also p-type.
Zeolite-supported Ag0 clusters have broad applications from catalysis to medicine, necessitating a mechanistic understanding of the formation of Ag0 clusters in situ. Density functional theory (DFT) simulations have been performed on silver, water, and silver–water clusters in silica mordenite (Si-MOR), to identify the role of the confinement on the structure and energetics of Ag0 cluster formation. The most favorable binding energy in the 12-membered ring (MR) pore of the Si-MOR is a 10–15-atom Ag0 cluster. Computational pair distribution function (PDF) data indicates that the Ag0 and Ag0–H2O clusters formed in vacuum versus in Si-MOR exhibit structural differences. Additionally, when the Ag0 cluster is confined, the density decreases and the surface area increases, hypothesized to be due to the limiting geometry of the 12-MR main channel. An energetic drive toward formation of larger Ag0 clusters was also identified, with hydrated silver atoms generating higher energy structures. In conclusion, this work identifies mechanistic and structural insight into the role of nanoconfinement on formation of Ag0 clusters in mordenite.
A custom designed and manufactured set of ion guns has been in use at the University of Wisconsin Inertial Electrostatic Confinement Laboratory for both beam fusion experiments and materials implantation experiments. For the first time, direct measurements have been made on the spatial profiles and the mass compositions of He and D ion beams produced by these guns. The results validate assumptions about the circular Gaussian spatial profiles for both He and D ion beams. Mass composition measurements of the He beam identified a pressure-dependent minimum impurity content of 15% N+. The D beam contained relative molecular ion fractions of 58% D3 +, 32% D2 +, and 10% D+ with impurities of 15% to 20% D2O+. A new experimental platform, the Ion Beam and Source Analyzer was developed to perform these experiments on the ion guns used to irradiate candidate fusion materials.
We develop a method for constructing tolerance bounds for functional data with random warping variability. In particular, we define a generative, probabilistic model for the amplitude and phase components of such observations, which parsimoniously characterizes variability in the baseline data. Based on the proposed model, we define two different types of tolerance bounds that are able to measure both types of variability, and as a result, identify when the data has gone beyond the bounds of amplitude and/or phase. The first functional tolerance bounds are computed via a bootstrap procedure on the geometric space of amplitude and phase functions. The second functional tolerance bounds utilize functional Principal Component Analysis to construct a tolerance factor. This work is motivated by two main applications: process control and disease monitoring. The problem of statistical analysis and modeling of functional data in process control is important in determining when a production has moved beyond a baseline. Similarly, in biomedical applications, doctors use long, approximately periodic signals (such as the electrocardiogram) to diagnose and monitor diseases. In this context, it is desirable to identify abnormalities in these signals. We additionally consider a simulated example to assess our approach and compare it to two existing methods.
We investigate the thermoelectric transport properties of the half-filled lowest Landau level v=1/2 in a gated two-dimensional hole system in a strained Ge/SiGe heterostructure. The electron-diffusion dominated regime is achieved below 600 mK, where the diffusion thermopower Sxxd at v=1/2 shows a linear temperature dependence. In contrast, the diffusion-dominated Nernst signal Sxyd of v=1/2 is found to approach zero, which is independent of the measurement configuration (sweeping magnetic field at a fixed hole density or sweeping the density by a gate at a fixed magnetic field).
We describe here the immersion corrosion resistance of multilayer polymer-clay nanocomposite (PCN) barrier thin films coated on low carbon steel. Deposited using a Layer-by-Layer (LbL) self-assembly process and only a few hundred nanometers thick, the thin film polymer clay nanocomposites (PCN) exhibited excellent corrosion barrier properties, comparable to coatings that are orders of magnitude thicker. PCN barrier thin films comprising up to 60 “bilayers” of polyethyleneimine and exfoliated montmorillonite were coated onto steel coupons and immersed in high salinity water for up to 7 days to evaluate barrier film corrosion resistance. PCN film performance is shown to be influenced by the number of coated bilayers and, critically, a post-coating crosslinking treatment. Covalently crosslinking the polyethyleneimine components of the films resulted in a significant improvement in corrosion resistance. PCN films that were not crosslinked showed nearly identical electrochemical impedance compared to bare steel, failing rapidly and leading to large areas of visible corrosion. Impedance behavior of the corroding samples was analyzed with a precise model, which allowed the determination of the PCN film properties separate from the substrate and solution. The resistivity through the PCN thin films was very high, even after 7 days of immersion. Though increasing PCN thickness led to increased charge transfer resistance, chemical crosslinking most significantly increased charge transfer resistance by several orders of magnitude. The combined influences of PCN film resistivity and very high charge transfer resistances led to the outstanding corrosion barrier properties. These PCN films show promise toward a new class of low-cost highly applicable anticorrosion coatings.
In 2010, the U.S. Department of Energy created its first Energy Innovation Hub, which focuses on improving Light Water Reactors (LWRs) through Modeling and Simulation. This hub, named the Consortium for the Advanced Simulation of LWRs (CASL), attempts to characterize and understand LWR behavior under normal operating conditions and use any gained insights to improve their efficiency. In collaboration with North Carolina State University (NCSU), CASL has worked extensively on the thermal-hydraulic subchannel code Coolant Boiling in Rod Arrays—Three Field (COBRA-TF). The NCSU/CASL version of COBRA-TF has been rebranded as CTF. This document focuses on code verification test problems that ensure CTF converges to the correct answer for the intended application. The suite of code verification tests are mapped to the underlying conservation equations of CTF, and significant gaps are addressed. Convergence behavior and numerical errors are quantified for each of the tests. Tests that converge at the correct rate to the corresponding analytic solution are incorporated into the CTF automated regression suite. A new verification utility is created for this purpose, which enables code verification by generalizing the process. For problems that do not behave correctly, the results are reported but the problem is not included in the regression suite. In addition to verification studies, this document also quantifies the existing tests of constitutive models. A few existing gaps are addressed by adding new unit tests.
The sea level contribution of the Antarctic ice sheet constitutes a large uncertainty in future sea level projections. Here we apply a linear response theory approach to 16 state-of-the-art ice sheet models to estimate the Antarctic ice sheet contribution from basal ice shelf melting within the 21st century. The purpose of this computation is to estimate the uncertainty of Antarctica's future contribution to global sea level rise that arises from large uncertainty in the oceanic forcing and the associated ice shelf melting. Ice shelf melting is considered to be a major if not the largest perturbation of the ice sheet's flow into the ocean. However, by computing only the sea level contribution in response to ice shelf melting, our study is neglecting a number of processes such as surface-mass-balance-related contributions. In assuming linear response theory, we are able to capture complex temporal responses of the ice sheets, but we neglect any self-dampening or self-amplifying processes. This is particularly relevant in situations in which an instability is dominating the ice loss. The results obtained here are thus relevant, in particular wherever the ice loss is dominated by the forcing as opposed to an internal instability, for example in strong ocean warming scenarios. In order to allow for comparison the methodology was chosen to be exactly the same as in an earlier study (Levermann et al., 2014) but with 16 instead of 5 ice sheet models. We include uncertainty in the atmospheric warming response to carbon emissions (full range of CMIP5 climate model sensitivities), uncertainty in the oceanic transport to the Southern Ocean (obtained from the time-delayed and scaled oceanic subsurface warming in CMIP5 models in relation to the global mean surface warming), and the observed range of responses of basal ice shelf melting to oceanic warming outside the ice shelf cavity. This uncertainty in basal ice shelf melting is then convoluted with the linear response functions of each of the 16 ice sheet models to obtain the ice flow response to the individual global warming path. The model median for the observational period from 1992 to 2017 of the ice loss due to basal ice shelf melting is 10.2 mm, with a likely range between 5.2 and 21.3 mm. For the same period the Antarctic ice sheet lost mass equivalent to 7.4mm of global sea level rise, with a standard deviation of 3.7mm (Shepherd et al., 2018) including all processes, especially surface-mass-balance changes. For the unabated warming path, Representative Concentration Pathway 8.5 (RCP8.5), we obtain a median contribution of the Antarctic ice sheet to global mean sea level rise from basal ice shelf melting within the 21st century of 17 cm, with a likely range (66th percentile around the mean) between 9 and 36 cm and a very likely range (90th percentile around the mean) between 6 and 58 cm. For the RCP2.6 warming path, which will keep the global mean temperature below 2 °C of global warming and is thus consistent with the Paris Climate Agreement, the procedure yields a median of 13 cm of global mean sea level contribution. The likely range for the RCP2.6 scenario is between 7 and 24 cm, and the very likely range is between 4 and 37 cm. The structural uncertainties in the method do not allow for an interpretation of any higher uncertainty percentiles.We provide projections for the five Antarctic regions and for each model and each scenario separately. The rate of sea level contribution is highest under the RCP8.5 scenario. The maximum within the 21st century of the median value is 4 cm per decade, with a likely range between 2 and 9 cm per decade and a very likely range between 1 and 14 cm per decade.
The trapped 171Yb+ ion is a promising candidate for portable atomic clock applications. However, with buffer-gas cooled ytterbium ions, the ions can be pumped into a low-lying 2F7 / 2 state or form YbH+ molecules. These dark states reduce the fluorescence signal from the ions and can degrade the clock stability. In this work, we study the dynamics of the populations of the 2F7 / 2 state and YbH+ molecules under different operating conditions of our 171 Yb+ ion system. Our study indicates that 2F7 / 2-state ions can form YbH+ molecules through interactions with hydrogen gas. As observed previously, dissociation of YbH+ is observed at wavelengths around 369 nm. We also demonstrate YbH+ dissociation using 405 nm light. Moreover, we show that the population in the dark states can be limited by using a single repump laser at 935 nm. Our study provides insights into the molecular formation in a trapped ion system.
Grosso, Robson L.; Muccillo, Eliana N.S.; Muche, Dereck N.F.; Jawaharram, Gowtham S.; Barr, Christopher M.; Monterrosa, Anthony M.; Castro, Ricardo H.R.; Hattar, Khalid M.; Dillon, Shen J.
This work demonstrates a novel approach to ultrahigherature mechanical testing using a combination of in situ nanomechanical testing and localized laser heating. The methodology is applied to characterizing and testing initially nanograined 10 mol % Sc2O3-stabilized ZrO2 up to its melting temperature. The results suggest that the lowerature strength of nanograined, d < 50 nm, oxides is not influenced by creep. Tensile fracture of ZrO2 bicrystals produce a weakerature dependence suggesting that grain boundary energy dominates brittle fracture of grain boundaries even at high homologous temperatures; for example, T = 2050 °C or T ≈ 77% Tmelt. The maximum temperature for mechanical testing in this work is primarily limited by the instability of the sample, due to evaporation or melting, enabling a host of new opportunities for testing materials in the ultrahigherature regime.
Ongoing work at the Z Machine on the development of warm x-ray sources in support of national security missions requires fast x-ray diagnostics with sensitivities significantly higher than what is commercially available. Our team represents a collaborative effort between MESA and Z to fabricate GaAs x-ray detectors that meet this need. The delivered detectors have now been fielded in several Z shot series and are providing hard x-ray data to physicists at Z. In addition to improved time response and hard x-ray sensitivity compared to commercial detectors, the devices fabricated at MESA show much more consistent device-to-device signal levels. This improved repeatability gives researchers at Z new quantitative data for source development efforts.
Accurately predicting power generation for PV sites is critical for prioritizing relevant operations & maintenance activities, thereby extending the lifetime of a system and improving profit margins. A number of factors influence power generation at PV sites, including local weather, shading and soiling losses, design of modules, DC mismatches, and degradation over time. Other external factors such as curtailment and grid outages can also have a notable impact on power generation. Machine learning techniques can be used to provide more accurate predictions of PV power production by accounting for important weather and climate information neglected by current industry methods. This article will cover the deficiencies of those methods and will show how machine learning can dramatically improve power generation predictions.
We report on the energy, timing, and pulse-shape discrimination performance of cylindrical 5.08 cm diameter × 5.08 cm thick and 7.62 cm diameter × 7.62 cm thick trans-stilbene crystals read out with the passively summed output of three different commercial silicon photo-multiplier arrays. Our results indicate that using the summed output of an 8 × 8 array of SiPMs provides performance competitive with photo-multiplier tubes for many neutron imaging and correlated particle measurements. For a 5.08 cm diameter × 5.08 cm thick crystal read out with SensL's ArrayJ-60035_64P-PCB, which had the best overall properties, we measure the energy resolution as 17.8 ± 0.8% at 341 keVee (σ/E), the timing resolution in the 180–400 keVee range as 236 ± 61 ps (σ), and the pulse-shape discrimination figure-of-merit as 2.21 ± 0.03 in the 230–260 keVee energy range. For a 7.62 cm diameter × 7.62 cm thick crystal read out with SensL's ArrayJ-60035_64P-PCB, we measure the energy resolution as 21.9 ± 2.3% at 341 keVee, the timing resolution in the 180–400 keVee range as 518 ± 42 ps, and the pulse-shape discrimination figure-of-merit as 1.49 ± 0.01 in the 230–260 keVee energy range. These results enable many scintillator-based instruments to enjoy the size, robustness, and power benefits of silicon photo-multiplier arrays as replacement for the photo-multiplier tubes that are predominantly used today.
As we approach exascale, computational parallelism will have to drastically increase in order to meet throughput targets. Many-core architectures have exacerbated this problem by trading reduced clock speeds, core complexity, and computation throughput for increasing parallelism. This presents two major challenges for communication libraries such as MPI: the library must leverage the performance advantages of thread level parallelism and avoid the scalability problems associated with increasing the number of processes to that scale. Hybrid programming models, such as MPI+X, have been proposed to address these challenges. MPI THREAD MULTIPLE is MPI's thread safe mode. While there has been work to optimize it, it largely remains non-performant in most implementations. While current applications avoid MPI multithreading due to performance concerns, it is expected to be utilized in future applications. One of the major synchronous data structures required by MPI is the matching engine. In this paper, we present a parallel matching algorithm that can improve MPI matching for multithreaded applications. We then perform a feasibility study to demonstrate the performance benefit of the technique.
Geomechanics experiments were used to assess mechanical alteration of Boise Sandstone promoted by reactions with supercritical carbon dioxide (scCO2) and water vapor. During geologic carbon storage, scCO2 is injected into subsurface reservoirs, forming buoyant plumes. At brine-plume interfaces, scCO2 can dissolve into native brines, and water from brines can partition into scCO2, forming hydrous scCO2. This study investigates the effect of hydrous scCO2 on the strength of Boise Sandstone. Samples are first exposed to recirculating hydrous scCO2 for 24 h at 70 °C and 13.8 MPa scCO2 pressure. Samples are reacted with scCO2 with added water contents up to 500 mL. After scCO2 exposure, samples are deformed at room temperature under confining pressures of 3.4, 6.9, and 10.3 MPa. The results demonstrate that hydrous scCO2 induces chemical reactions in Boise Sandstone, with ions migrating from the solid into the hydrous scCO2 phase. At the longer time-scales, these reactions could lead to mechanical weakening in the samples; however, on the scale of our experiments, the strength changes are within sample variability. Because the solubility of water in scCO2 is extremely low (0.008 mol H2O per 1 mol CO2), the mineral dissolution of Boise Sandstone was under 0.002 wt.%. Additionally, mineral grains and pore throats in Boise Sandstone are cemented with quartz, which is not susceptible to dissolution at these conditions. Our results indicate that humidity in scCO2 plumes is unlikely to sustain chemical reactions and induce long term strength changes in quartz cemented sandstones due to resistant mineralogies and low water solubility.
Global Security delivers innovative engineering solutions to protect the nation from strategic threats home and abroad. Global Security programs focus on developing and implementing technical solutions to address global security challenges through three enduring missions: Global Monitoring, Preventing Proliferation, and Nuclear Weapon Security.
This short report documents the review of the XSEL for September 1st, 2019. The XSEL process created 318 events overall. Seventy-two of those events were matched in the Standard Event List (SEL) and eleven of the events were matched in the Reviewed Event Bulletin (REB). There an addition 235 events, purported to be "NEW" events, not appearing in either SEL or REB. The NEW events were the major focus of this review, along with confirmation of the events listed in SEL and REB.
Gunther, Stefanie; Ruthotto, Lars; Schroder, Jacob B.; Cyr, Eric C.; Gauger, Nicolas R.
Residual neural networks (ResNets) are a promising class of deep neural networks that have shown excellent performance for a number of learning tasks, e.g., image classification and recognition. Mathematically, ResNet architectures can be interpreted as forward Euler discretizations of a nonlinear initial value problem whose time-dependent control variables represent the weights of the neural network. Hence, training a ResNet can be cast as an optimal control problem of the associated dynamical system. For similar time-dependent optimal control problems arising in engineering applications, parallel-in-time methods have shown notable improvements in scalability. This paper demonstrates the use of those techniques for efficient and effective training of ResNets. The proposed algorithms replace the classical (sequential) forward and backward propagation through the network layers with a parallel nonlinear multigrid iteration applied to the layer domain. This adds a new dimension of parallelism across layers that is attractive when training very deep networks. From this basic idea, we derive multiple layer-parallel methods. The most efficient version employs a simultaneous optimization approach where updates to the network parameters are based on inexact gradient information in order to speed up the training process. Finally, using numerical examples from supervised classification, we demonstrate that the new approach achieves a training performance similar to that of traditional methods, but enables layer-parallelism and thus provides speedup over layer-serial methods through greater concurrency.
Interfacial toughness quantifies resistance to crack growth along an interface and in this investigation the toughness of an aluminum/epoxy interface was measured as a function of surface roughness and test temperature. The large strain response of the relatively ductile epoxy adhesive used in this study was also characterized. This epoxy adhesive exhibits intrinsic strain-softening after initial compressive yield and then deforms plastically at a roughly constant flow stress until it rapidly hardens at large compressive strains. Here, we find that interface toughness scales as the product of the temperature dependent epoxy yield strength and a length scale that characterizes surface roughness. The proposed scaling is based upon dimensional considerations of a model problem that assumes that the characteristic length scale of both the roughness and the crack-tip yield zone is small relative to the region dominated by the linear elastic asymptotic crack-tip stress field. Furthermore, the model assumes that interfacial failure occurs only after the epoxy begins to harden at large strains. The proposed relationship is validated by our interfacial toughness measurements.
Xie, Bing; Oral, Sarp; Zimmer, Christopher; Choi, Jong Y.; Dillow, David; Klasky, Scott A.; Lofstead, Gerald F.; Chase, Jeffrey
This article studies the I/O write behaviors of the Titan supercomputer and its Lustre parallel file stores under production load. The results can inform the design, deployment, and configuration of file systems along with the design of I/O software in the application, operating system, and adaptive I/O libraries.We propose a statistical benchmarking methodology to measure write performance across I/O configurations, hardware settings, and system conditions. Moreover, we introduce two relative measures to quantify the write-performance behaviors of hardware components under production load. In addition to designing experiments and benchmarking on Titan, we verify the experimental results on one real application and one real application I/O kernel, XGC and HACC IO, respectively. These two are representative and widely used to address the typical I/O behaviors of applications.In summary, we find that Titan’s I/O system is variable across the machine at fine time scales. This variability has two major implications. First, stragglers lessen the benefit of coupled I/O parallelism (striping). Peak median output bandwidths are obtained with parallel writes to many independent files, with no striping or write sharing of files across clients (compute nodes). I/O parallelism is most effective when the application—or its I/O libraries—distributes the I/O load so that each target stores files for multiple clients and each client writes files on multiple targets in a balanced way with minimal contention. Second, our results suggest that the potential benefit of dynamic adaptation is limited. In particular, it is not fruitful to attempt to identify “good locations” in the machine or in the file system: component performance is driven by transient load conditions and past performance is not a useful predictor of future performance. For example, we do not observe diurnal load patterns that are predictable.
Rechargeable alkaline Zn/MnO2 batteries are an attractive solution for large-scale energy storage applications. Recently, Bi and Cu additives have been used to increase the cycle life and capacity of rechargeable Zn/MnO2 batteries, with an equivalent of the full two-electron capacity realized for many cycles, in the absence of zinc. However, the mechanism of the effect of Bi and Cu on the performance of rechargeable Zn/MnO2 batteries has not been investigated in detail. We apply first-principles density functional computational methods to study the discharge mechanisms of the unmodified and Bi/Cu-modified γ-MnO2 electrodes in rechargeable alkaline Zn/MnO2 batteries. Using the results of our calculations, we analyze the possible redox reaction pathways in the γ-MnO2 electrode and identify the electrochemical processes leading to the formation of irreversible discharge reaction products, such as hausmannite and hetaerolite. Our study demonstrates the possibility of formation of intermediate Bi-Mn and Cu-Mn oxides in deep-cycled Bi/Cu-modified MnO2 electrodes. The formation of intermediate Bi-Mn and Cu-Mn oxides could reduce the rate of accumulation of irreversible reaction products in the MnO2 electrode and improve the rechargeability and cyclability of Zn/MnO2 batteries.
Accurate calculation of spectral line broadening is important for many hot, dense plasma applications. However, calculated line widths have significantly underestimated measured widths for Δn=0 lines of Li-like ions, which is known as the isolated-line problem. In this Letter, scrutinization of the line-width derivation reveals that the commonly used expression neglects a potentially important contribution from electron-capture. Line-width calculations including this process are performed with two independent codes, both of which removed the discrepancies at temperatures below 10 eV. The revised calculations also suggest the remaining discrepancy scales more strongly with electron temperature than the atomic number as was previously suggested.
In the California lndustrial General Permit (IGP) 2014-0057-DWQ for storm water monitoring, effective July 1, 2015, there are 21 contaminants that have been assigned NAL (Numeric Action Level) values, both annual and instantaneous. For annual NALs, an exceedance occurs when the average of all analytical results from all samples taken at a facility during a reporting year for a given parameter exceeds an annual NAL value listed in Table 2 of the General Permit. For instantaneous maximum NALs, an exceedance occurs when two or more analytical results from samples taken for any parameter within a reporting year exceed the instantaneous maximum NAL value (for TSS and O&G), or are outside of the instantaneous maximum NAL range (for pH) listed in Table 2.
In the present research, a new method for simulation of rarefied gas flows is proposed, a velocity-space hybrid of both a DSMC representation of particles and a discrete velocity quasi-particle representation of the distribution function. The hybridization scheme is discussed in detail, and is numerically verified for two test-cases: the BKW relaxation problem and a stationary Maxwellian distribution. It is demonstrated that such a velocity-space hybridization can provide computational benefits when compared to a pure discrete velocity method or pure DSMC approach, while retaining some of the more attractive properties of discrete velocity methods. Further possible improvements to the velocity-space hybrid approach are discussed.
We study the solution of block-structured linear algebra systems arising in optimization by using iterative solution techniques. These systems are the core computational bottleneck of many problems of interest such as parameter estimation, optimal control, network optimization, and stochastic programming. Our approach uses a Krylov solver (GMRES) that is preconditioned with an alternating method of multipliers (ADMM). We show that this ADMM-GMRES approach overcomes well-known scalability issues of Schur complement decomposition in problems that exhibit a high degree of coupling. The effectiveness of the approach is demonstrated using linear systems that arise in stochastic optimal power flow problems and that contain up to 2 million total variables and 4000 coupling variables. We find that ADMM-GMRES is nearly an order of magnitude faster than Schur complement decomposition. Moreover, we demonstrate that the approach is robust to the selection of the augmented Lagrangian penalty parameter, which is a key advantage over the direct use of ADMM.
In radiobiology, predicting the evolution of irradiated biological matter is nowadays an active field of research to identify DNA lesions or to adapt the radiotherapeutic protocols in radiation oncology. In this context, the numerical methods, based on Monte Carlo track-structure simulations, represent the most suitable and powerful tools for understanding the radiobiological damages induced by ionizing particles. In the present work, we report the theoretical differential and total cross sections, computed within the quantum mechanical continuum distorted wave-eikonal initial state (CDW-EIS) approach, for ion impact on water vapor and DNA nucleobases. These cross sections have been used to build up the input database for the homemade Monte Carlo track-structure TILDA-V. A comparison between the theoretical predictions and the available experimental data is presented. Micro-dosimetry results obtained with TILDA-V are also reported.
As a part of the series of Source Physics Experiments (SPE) conducted on the Nevada National Security Site in southern Nevada, we have developed a local-to-regional scale seismic velocity model of the site and surrounding area. Accurate earth models are critical for modeling sources like the SPE to investigate the role of earth structure on the propagation and scattering of seismic waves. We combine seismic body waves, surface waves, and gravity data in a joint inversion procedure to solve for the optimal 3D seismic compres-sional and shear-wave velocity structures and earthquake locations subject to model smoothness constraints. Earthquakes, which are relocated as part of the inversion, provide P-and S-body-wave absolute and differential travel times. Active source experiments in the region augment this dataset with P-body-wave absolute times and surface-wave dispersion data. Dense ground-based gravity observations and surface-wave dispersion derived from ambient noise in the region fill in many areas where body-wave data are sparse. In general, the top 1–2 km of the surface is relatively poorly sampled by the body waves alone. However, the addition of gravity and surface waves to the body-wave data-set greatly enhances structural resolvability in the near surface. We discuss the method-ology we developed for simultaneous inversion of these disparate data types and briefly describe results of the inversion in the context of previous work in the region.
Digital image correlation (DIC) is an optical metrology method widely used in experimental mechanics for full-field shape, displacement and strain measurements. The required strain resolution for engineering applications of interest mandates DIC to have a high image displacement matching accuracy, on the order of 1/100th of a pixel, which necessitates an understanding of DIC errors. In this paper, we examine two spatial bias terms that have been almost completely overlooked. They cause a persistent offset in the matching of image intensities and thus corrupt DIC results. We name them pattern-induced bias (PIB), and intensity discretization bias (IDB). We show that the PIB error occurs in the presence of an undermatched shape function and is primarily dictated by the underlying intensity pattern for a fixed displacement field and DIC settings. The IDB error is due to the quantization of the gray level intensity values in the digital camera. In this paper we demonstrate these errors and quantify their magnitudes both experimentally and with synthetic images.
Modern programming languages have effects and mix multiple calling conventions, and their core calculi should too. We characterize calling conventions by their “substitution discipline” that says what variables stand for, and design calculi for mixing disciplines in a single program. Building on variations of the reducibility candidates method, including biorthogonality and symmetric candidates which are both specialized for one discipline, we develop a single uniform framework for strong normalization encompassing call-by-name, call-by-value, call-by-need, call-by-push-value, non-deterministic disciplines, and any others satisfying some simple criteria. We explicate commonalities of previous methods and show they are special cases of the uniform framework and they extend to multi-discipline programs.
Transparent conducting oxides, such as doped indium oxide, zinc oxide, and cadmium oxide (CdO), have recently attracted attention as tailorable materials for applications in nanophotonic and plasmonic devices such as low-loss modulators and all-optical switches due to their tunable optical properties, fast optical response, and low losses. In this work, optically induced extraordinarily large reflection changes (up to 135%) are demonstrated in bulk CdO films in the mid-infrared wavelength range close to the epsilon near zero (ENZ) point. To develop a better understanding of how doping level affects the static and dynamic optical properties of CdO, the evolution of the optical properties with yttrium (Y) doping is investigated. An increase in the metallicity and a blueshift of the ENZ point with increasing Y-concentrations is observed. Broadband all-optical switching from near-infrared to mid-infrared wavelengths is demonstrated. The major photoexcited carrier relaxation mechanisms in CdO are identified and it is shown that the relaxation times can be significantly reduced by increasing the dopant concentration in the film. This work could pave the way to practical dynamic and passive optical and plasmonic devices with doped CdO spanning wavelengths from the ultraviolet to the mid-infrared region.
We present an approach and relevant models for predicting the probabilistic shock-to-detonation transition (SDT) behavior and Pop plot (PP) of heterogeneous energetic materials (HEM) via mesoscopic microstructure-explicit (ME) and void explicit (VE) simulations at the millimeter (mm) sample size scale. Although the framework here is general, the particular material considered in this paper is pressed Octahydro-1,3,5,7-tetranitro-1,2,3,5-tetrazocine (HMX). To systematically delineate the effects of material heterogeneities, four material cases are considered. These cases are homogeneous material, material with granular microstructure but no voids, homogeneous material with voids, and material with both granular microstructure and voids. Statistically equivalent microstructure sample sets (SEMSS) are generated and used. Eulerian hydrocode simulations explicitly resolve the material heterogeneities, voids, and the coupled mechanical-thermal-chemical processes. In particular, it is found that both microstructure and voids strongly influence the SDT behavior and PP. The effects of different combinations of microstructure heterogeneity and voids on the SDT process and PP are quantified and rank-ordered. The overall framework uses the Mie–Grüneisen equation of state and a history variable reactive burn model (HVRB). A novel probabilistic representation for quantifying the PP is developed, allowing the calculation of (1) the probability of observing SDT at a given combination of shock pressure and run distance, (2) the run-distance to detonation under a given combination of shock pressure and prescribed probability, and (3) the shock pressure required for achieving SDT at a given run distance with a prescribed probability. The results are in agreement with general trends in experimental data in the literature.
Ductile rupture or tearing usually involves structural degradation from the nucleation and growth of voids and their coalescence into cracks. Although some materials contain preexisting pores, the first step in failure is often the formation of voids. Because this step can govern both the failure strain and the fracture mechanism, it is critical to understand the mechanisms of void nucleation and the enabling microstructural configurations which give rise to nucleation. To understand the role of dislocations during void nucleation, the present study presents ex-situ cross-sectional observations of interrupted deformation experiments revealing incipient, subsurface voids in a copper material containing copper oxide inclusions. The local microstructural state was evaluated using electron backscatter diffraction (EBSD), electron channeling contrast (ECC), transmission electron microscopy (TEM), and transmission kikuchi diffraction (TKD). Surprisingly, before substantial growth and coalescence had occurred, the deformation process had resulted in the nucleation of a high density of nanoscale (≈50 nm) voids in the deeply deformed neck region where strains were on the order of 1.5. Such a proliferation of nucleation sites immediately suggests that the rupture process is limited by void growth, not nucleation. With regard to void growth, analysis of more than 20 microscale voids suggests that dislocation boundaries facilitate the growth process. The present observations call into question prior assumptions on the role of dislocation pile-ups and provide new context for the formulation of revised ductile rupture models. While the focus of this study is on damage accumulation in a highly ductile metal containing small, well-dispersed particles, these results are also applicable to understanding void nucleation in engineering alloys.
Kittell, David E.; Yarrington, Cole D.; Lechman, Jeremy B.; Damm, David L.; Baer, Melvin R.
While current phenomenological burn models are useful for describing the average or bulk reactive flow behaviour of heterogeneous explosives, one fundamental weakness inherent to these models is the loss of detailed microstructural information at the scale of the calculation. In order to include the effects of the microstructure, and in particular the underlying material heterogeneities that influence the build-up to detonation, a new paradigm is put forth for modelling sub-grid, reaction-induced fluctuations (i. e. “hot spots”) at the continuum level. This modelling approach assumes that the reaction rate is stochastic, rather than deterministic, and it uses Langevin-type equations with a mathematical framework built upon Itô calculus and Lambourn's CIM model for shocked heterogeneous explosives. This approach follows directly from our previous letter, Ref. [1], and is inspired by the probability density function (pdf) methods used in turbulent reactive flows. Here, the stochastic burn model is derived, implemented, and exercised far beyond what has been shown in previous work. New hydrocode simulation results demonstrate the role of stochastic fluctuations during shock initiation; these fluctuations are approximated by collections of discrete particles, that evolve with drift (i. e. deterministic) and diffusion (i. e. stochastic) coefficients. Additionally, the particle values are propagated and averaged to calculate the heat release, yield strength, and material impedance in each computational cell. Hydrocode simulation results further show how the fluctuating hot spot energy may or may not be transmitted to the wave front, and result in a detonation wave-like structure. The fundamental stochastic nature of this model permits simulations to have varying outcomes with the same initial conditions; this allows for go/no-go estimation (e. g., marginal or failed detonations), which might possibly be calibrated using the statistical distributions from real materials. Mesoscale calculations of shocked heterogeneous explosives also show that these fluctuations are physically justified (i. e., Ref. [2]), and it is hypothesized that the pdf functions provide a link between the meso(grain) and continuum scales for practical engineering calculations. Thus, our approach is a paradigm shift for building efficient, reduced order continuum burn models, that represent the sub-grid stochastic behaviour of shocked heterogeneous solid explosives.
General polyhedral discretizations offer several advantages over classical approaches consisting of standard tetrahedra and hexahedra. These include increased flexibility and robustness in the meshing of geometrically complex domains and higher-quality solutions for both finite element and finite volume schemes. Currently, the use of general polyhedra is hampered by the lack of general-purpose polyhedral meshing algorithms and software. One approach for generating polyhedral meshes is the use of tetrahedral subdivisions and dual-cell aggregation. In this approach, each tetrahedron of an existing tetrahedral mesh is subdivided using one of several subdivision schemes. Polyhedral-dual cells may then be formed and formulated as finite elements with shape functions obtained through the use of generalized barycentric coordinates. We explore the use of dual-cell discretizations for applications in nonlinear solid mechanics using a displacement-based finite element formulation. Verification examples are presented that yield optimal rates of convergence. Accuracy of the methodology is demonstrated via several nonlinear examples that include large deformation and plasticity.
Forced oscillations in power systems are of particular interest when they interact and reinforce inter-area oscillations. This paper determines how a previously proposed inter-area damping controller mitigates forced oscillations. The damping controller modulates active power on the Pacific DC Intertie (PDCI) based on phasor measurement units (PMU) frequency measurements. The primary goal of the controller is to improve the small signal stability of the north south B mode in the North American Western Interconnection (WI). The paper presents small signal stability analysis in a reduced order system, time-domain simulations of a detailed representation of the WI and actual system test results to demonstrate that the PDCI damping controller provides effective damping to forced oscillations in the frequency range below 1 Hz.
Reducing the risk of cyber-attacks that affect the confidentiality, integrity, and availability of distributed Photovoltaic (PV) inverters requires the implementation of an Intrusion Detection System (IDS) at the grid-edge. Often, IDSs use signature or behavior-based analytics to identify potentially harmful anomalies. In this work, the two approaches are deployed and tested on a small, single-board computer; the computer is setup to monitor and detect malevolent traffic in-between an aggregator and a single PV inverter. The Snort, signature-based, analysis tool detected three of the five attack scenarios. The behavior-based analysis, which used an Adaptive Resonance Theory Artificial Neural Network, successfully identified four out of the five attacks. Each of the approaches ran on the single-board computer and decreased the chances of an undetected breach in the PV inverters control system.