An investigation of polyurethane foam filled with known flame retardant fillers including hydroxides, melamine, phosphate-containing compounds, and melamine phosphates was carried out to produce a low-cost material with high flame retardant efficiency. The impact of flame retardant fillers on the physical properties such a s composite foam density, glass transition temperature, storage modulus, and thermal expansion of composite foams was investigated with the goal of synthesizing a robust rigid foam with excellent flame retardant properties.
Simulating HPC systems is a difficult task and the emergence of “Beyond CMOS” architectures and execution models will increase that difficulty. This document presents a “tutorial” on some of the simulation challenges faced by conventional and non-conventional architectures (Section 1) and goals and requirements for simulating Beyond CMOS systems (Section 2). These provide background for proposed short- and long-term roadmaps for simulation efforts at Sandia (Sections 3 and 4). Additionally, a brief explanation of a proof-of-concept integration of a Beyond CMOS architectural simulator is presented (Section 2.3).
The goal of this session is to introduce five security system design concepts that will enable the development of an integrated security system and will increase the likelihood of effective security management. As a regulator, it’s important to be aware of these design concepts so that when you inspect or evaluate a facility’s security system, you can ensure that these concepts have been applied.
DOE Fellow, Andres Cremisini, completed a 10-week internship with Sandia National Laboratories (SNL) in Albuquerque, New Mexico. Under the management of Kristopher Klingler and the mentorship of Jon Bradley, he was tasked with conceiving and coding a realistic weather model for use in physical security applications. The objective was to make a weather model that could use real data to accurately predict wind and precipitation conditions at any location of interest on the globe at any user-determined time. The intern received guidance on software design, the C++ programming language and clear communication of project goals and ongoing progress. In addition, Mr. Cremisini was given license to structure the program however he best saw fit, an experience that will benefit ongoing research endeavors.
The objective of this report is to determine the feasibility of a combined pulsed - power accelerator machine, similar to HERMES - III, with the Annular Core Research Reactor (ACRR) Fueled - Ring External Cavity (FREC - II) in a new facility. The document is conceptual in nature, and includes some neutronic analysis that i llustrates that that the physics of such a concept would be feasible. There would still be many engineering design considerations and issues that would need to be investigated in order to determine the true viability of such a concept. This report does n ot address engineering design details, the cost of such a facility, or what would be required to develop the safety authorization of the concept. The radiation requirements for the "on - target" gamma - ray dose and dose rate are not addressed in this report . It is assumed that if the same general on - target specifications for a HERMES - III type machine could be met with the proposed concept, that the machine would b e considered highly useful as a radiation effects sciences platform. In general, the combined accelerator/ACRR reactor concept can be shown to be feasible with no major issues that would preclude the usefulness of such a facility. The new facility would provide a capability that currently does not exist in the radiation testing complex.
The International Biological and Chemical Threat Reduction Program at Sandia National Laboratories is developing a 15 - year technology road map in support the United States Government efforts to reduce international chemical and biological dangers . In 2017, the program leadership chartered an analysis team to explore dangers in the future international chemical and biological landscape through engagements with national security experts within and beyond Sandia to gain a multidisciplinary perspective on the future . This report offers a hi gh level landscape of future chemical and biological dangers based upon analysis of those engagements and provides support for further technology road map development.
We study the optimization of an energy function used by the meshing community to measure and improve mesh quality. This energy is non-traditional because it is dependent on both the primal triangulation and its dual Voronoi (power) diagram. The energy is a measure of the mesh's quality for usage in Discrete Exterior Calculus (DEC), a method for numerically solving PDEs. In DEC, the PDE domain is triangulated and this mesh is used to obtain discrete approximations of the continuous operators in the PDE. The energy of a mesh gives an upper bound on the error of the discrete diagonal approximation of the Hodge star operator. In practice, one begins with an initial mesh and then makes adjustments to produce a mesh of lower energy. However, we have discovered several shortcomings in directly optimizing this energy, e.g. its non-convexity, and we show that the search for an optimized mesh may lead to mesh inversion (malformed triangles). We propose a new energy function to address some of these issues.
The FY18Q1 milestone of the ECP/VTK-m project includes the implementation of a multiblock data set, the completion of a gradients filtering operation, and the release of version 1.1 of the VTK-m software. With the completion of this milestone, the new multiblock data set allows us to iteratively schedule algorithms on composite data structures such as assemblies or hierarchies like AMR. The new gradient algorithms approximate derivatives of fields in 3D structures with finite differences. Finally, the release of VTK-m version 1.1 tags a stable release of the software that can more easily be incorporated into external projects.
We propose a porous materials analysis pipeline using persistent homology. We rst compute persistent homology of binarized 3D images of sampled material subvolumes. For each image we compute sets of homology intervals, which are represented as summary graphics called persistence diagrams. We convert persistence diagrams into image vectors in order to analyze the similarity of the homology of the material images using the mature tools for image analysis. Each image is treated as a vector and we compute its principal components to extract features. We t a statistical model using the loadings of principal components to estimate material porosity, permeability, anisotropy, and tortuosity. We also propose an adaptive version of the structural similarity index (SSIM), a similarity metric for images, as a measure to determine the statistical representative elementary volumes (sREV) for persistence homology. Thus we provide a capability for making a statistical inference of the uid ow and transport properties of porous materials based on their geometry and connectivity.
To support more rigorous analysis on global security issues at Sandia National Laboratories (SNL), there is a need to develop realistic data sets without using "real" data or identifying "real" vulnerabilities, hazards or geopolitically embarrassing shortcomings. In response, an interdisciplinary team led by subject matter experts in SNL's Center for Global Security and Cooperation (CGSC) developed a hypothetical case description. This hypothetical case description assigns various attributes related to international SNF transportation that are representative, illustrative and indicative of "real" characteristics of "real" countries. There is no intent to identify any particular country and any similarity with specific real-world events is purely coincidental. To support the goal of this report to provide a case description (and set of scenarios of concern) for international SNF transportation inclusive of as much "real-world" complexity as possible -- without crossing over into politically sensitive or classified information -- this SAND report provides a subject matter expert-validated (and detailed) description of both technical and political influences on the international transportation of spent nuclear fuel.
Sandia National Laboratories is the largest of the Department of Energy national laboratories with more than 13,000 staff spread across its two main campuses in New Mexico and California. For more than 60 years, the Sandia National Laboratories campus in Livermore, California has delivered cutting-edge science and technology solutions to resolve the nation’s most challenging and complex problems. As a multidisciplinary laboratory, Sandia draws from virtually every science and engineering discipline to address challenges in energy, homeland security, cybersecurity, climate, and biosecurity. Today, collaboration is vital to ensuring that the Lab stays at the forefront of science and technology innovation. Partnerships with industry, state, and local governments, and California universities help drive innovation and economic growth in the region. Sandia contributed to California’s regional and statewide economy with more than $145 million in contracts to California companies, $92 million of which goes to California small businesses. In addition, Sandia engages the community directly by running robust STEM education programs for local schools and administering community giving programs. Meanwhile, investments like the Livermore Valley Open Campus (LVOC), an innovation hub supported by LLNL and Sandia, help catalyze the local economy.
This milestone was focused on deploying and verifying a “sliding-mesh interface,” and establishing baseline timings for blade-resolved simulations of a sub-MW-scale turbine. In the ExaWind project, we are developing both sliding-mesh and overset-mesh approaches for handling the rotating blades in an operating wind turbine. In the sliding-mesh approach, the turbine rotor and its immediate surrounding fluid are captured in a “disk” that is embedded in the larger fluid domain. The embedded fluid is simulated in a coordinate system that rotates with the rotor. It is important that the coupling algorithm (and its implementation) between the rotating and inertial discrete models maintains the accuracy of the numerical methods on either side of the interface, i.e., the interface is “design order.”
This workplan addresses filler attributes (i.e., possible requirements), assumptions needed for analysis, selection of filler materials, testing needs, and a long-range perspective on R&D activities leading to filler demonstration and a safety basis for implementation.
Purpose: Water vapor trapped in encapsulation materials or enclosed volumes leads to corrosion issues for critical NW components. Sandia National Laboratories has created a new diagnostic to indicate the presence of water in weapon systems. Impact: Component exposure to water now can be determined instantly, without need for costly, time-consuming analytical methods.
The experimental breeder reactor (EBR-II) used fuel with a layer of sodium surrounding the uranium-zirconium fuel to improve heat transfer. Disposing of EBR-II fuel in a geologic repository without treatment is not prudent because of the potentially energetic reaction of the sodium with water. In 2000, the US Department of Energy (DOE) decided to treat the sodium-bonded fuel with an electrorefiner (ER), which produces metallic uranium product, a metallic waste, mostly from the cladding, and the salt waste in the ER, which contains most of the actinides and fission products. Two waste forms were proposed for disposal in a mined repository; the metallic waste, which was to be cast into ingots, and the ER salt waste, which was to be further treated to produce a ceramic waste form. However, alternative disposal pathways for metallic and salt waste streams may reduce the complexity. For example, performance assessments show that geologic repositories can easily accommodate the ER salt waste without treating it to form a ceramic waste form. Because EBR-II was used for atomic energy defense activities, the treated waste likely meets the definition of transuranic waste. Hence, disposal at the Waste Isolation Pilot Plant (WIPP) in southern New Mexico, may be feasible. This report reviews the direct disposal pathway for ER salt waste and describes eleven tasks necessary for implementing disposal at WIPP, provided space is available, DOE decides to use this alternative disposal pathway in an updated environmental impact statement, and the State of New Mexico grants permission.
The Sandia Analysis Workbench (SAW) project has developed and deployed a production capability for SIERRA computational mechanics analysis workflows. However, the electrical analysis workflow capability requirements have only been demonstrated in early prototype states, with no real capability deployed for analysts’ use. This milestone aims to improve the electrical analysis workflow capability (via SAW and related tools) and deploy it for ongoing use. We propose to focus on a QASPR electrical analysis calibration workflow use case. We will include a number of new capabilities (versus today’s SAW), such as: 1) support for the XYCE code workflow component, 2) data management coupled to electrical workflow, 3) human-in-theloop workflow capability, and 4) electrical analysis workflow capability deployed on the restricted (and possibly classified) network at Sandia. While far from the complete set of capabilities required for electrical analysis workflow over the long term, this is a substantial first step toward full production support for the electrical analysts.
This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.
Kaneshige, Michael J.; Rabbi, Md F.; Mach, Robert; Catzin, Carlos A.; Stewart, Calvin M.
Simulant polymer bonded explosives are widely used to simulate the mechanical response of real energetic materials. In this paper, the fracture resistance of a simulant polymer bo nded explosive (PBX) is experimentally investigated. The simulant is composed of 80 wt.% soda lime glass beads (SLGB) and 20 wt.% high impact Polystyrene 825 (HIPS). Brazilian disk tests are performed to characterize the tensile and compressive properties. Fracture toughness and energy tests are performed in the semi - circular bending (SCB) configuration on 80, 81, 82, and 83 wt % SLGB compositions. Digital image correlation is performed to record the surface displacements and calculate surface strains during testing. The m icromechanical behavior of ductile and brittle fracture are evaluated using digital microscopy and scanning electron microscopy of the fracture surface. It is determined that (i) the manufacturing process produces a credible simulant of PBX properties, and (ii) the SCB test measures fracture resistance with a reasonable coefficient of variation.
This paper describes versions of OPAL, the Occam-Plausibility Algorithm (Farrell et al. in J Comput Phys 295:189–208, 2015) in which the use of Bayesian model plausibilities is replaced with information-theoretic methods, such as the Akaike information criterion and the Bayesian information criterion. Applications to complex systems of coarse-grained molecular models approximating atomistic models of polyethylene materials are described. All of these model selection methods take into account uncertainties in the model, the observational data, the model parameters, and the predicted quantities of interest. A comparison of the models chosen by Bayesian model selection criteria and those chosen by the information-theoretic criteria is given.
Quark nuggets are theoretical objects composed of approximately equal numbers of up, down, and strange quarks and are also called strangelets and nuclearites. They have been proposed as a candidate for dark matter, which constitutes ~85% of the universe's mass and which has been a mystery for decades. Previous efforts to detect quark nuggets assumed that the nuclear-density core interacts directly with the surrounding matter so the stopping power is minimal. Tatsumi found that quark nuggets could well exist as a ferromagnetic liquid with a ∼1012-T magnetic field. We find that the magnetic field produces a magnetopause with surrounding plasma, as the earth's magnetic field produces a magnetopause with the solar wind, and substantially increases their energy deposition rate in matter. We use the magnetopause model to compute the energy deposition as a function of quark-nugget mass and to analyze testing the quark-nugget hypothesis for dark matter by observations in air, water, and land. We conclude the water option is most promising.
Quantum Hall ferromagnetic transitions are typically achieved by increasing the Zeeman energy through in-situ sample rotation, while transitions in systems with pseudo-spin indices can be induced by gate control. We report here a gate-controlled quantum Hall ferromagnetic transition between two real spin states in a conventional two-dimensional system without any in-plane magnetic field. We show that the ratio of the Zeeman splitting to the cyclotron gap in a Ge two-dimensional hole system increases with decreasing density owing to inter-carrier interactions. Below a critical density of ~2.4 × 1010 cm-2, this ratio grows greater than 1, resulting in a ferromagnetic ground state at filling factor ν = 2. At the critical density, a resistance peak due to the formation of microscopic domains of opposite spin orientations is observed. Such gate-controlled spin-polarizations in the quantum Hall regime opens the door to realizing Majorana modes using two-dimensional systems in conventional, low-spin-orbit-coupling semiconductors.
Liu, Sheng L.; Shcherbakov, Maxim R.; Zubyuk, Varvara V.; Vaskin, Aleksandr; Vabishchevich, Polina P.; Keeler, Gordon A.; Pertsch, Thomas; Dolgova, Tatyana V.; Staude, Isabelle; Brener, Igal B.; Fedyanin, Andrey A.
Optical metasurfaces are regular quasi-planar nanopatterns that can apply diverse spatial and spectral transformations to light waves. However, metasurfaces are no longer adjustable after fabrication, and a critical challenge is to realise a technique of tuning their optical properties that is both fast and efficient. We experimentally realise an ultrafast tunable metasurface consisting of subwavelength gallium arsenide nanoparticles supporting Mie-type resonances in the near infrared. Using transient reflectance spectroscopy, we demonstrate a picosecond-scale absolute reflectance modulation of up to 0.35 at the magnetic dipole resonance of the metasurfaces and a spectral shift of the resonance by 30 nm, both achieved at unprecedentedly low pump fluences of less than 400 μJ cm-2. Our findings thereby enable a versatile tool for ultrafast and efficient control of light using light.
Optical nonlinearities are intimately related to the spatial symmetry of the nonlinear media. For example, the second order susceptibility vanishes for centrosymmetric materials under the dipole approximation. The latter concept has been naturally extended to the metamaterials' realm, sometimes leading to the (erroneous) hypothesis that second harmonic (SH) generation is negligible in highly symmetric meta-atoms. In this work we aim to show that such symmetric meta-atoms can radiate SH light efficiently. In particular, we investigate in-plane centrosymmetric meta-atom designs where the approximation for meta-atoms breaks down. In a periodic array this building block allows us to control the directionality of the SH radiation. We conclude by showing that the use of symmetry considerations alone allows for the manipulation of the nonlinear multipolar response of a meta-atom, resulting in e.g. dipolar, quadrupolar, or multipolar emission on demand. This is because the size of the meta-atom is comparable with the free-space wavelength, thus invalidating the dipolar approximation for meta-atoms.
The removal of silica, ubiquitous in produced and industrial waters, by novel mixed oxides is investigated in this present study. We have combined the advantage of high selectivity hydrotalcite (HTC, (Mg6Al2(OH)16(CO3)·4H2O)), with large surface area of active alumina (AA, (Al2O3)) for effective removing of the dissolved silica from cooling tower water. The batch test results indicated the combined HTC/AA is a more effective method for removing silica from CTW than using each of HTC or AA separately. The silica uptake was confirmed by Fourier transform infrared (FTIR), and Energy dispersive spectroscopy (EDS). Results indicate HTC/AA effectively removes silica from cooling tower water (CTW), even in the presence of large concentrations of competing anions, such as Cl−, NO3− HCO3−, CO32− and SO42−. The Single Path Flow Through (SPFT) tests confirmed to rapid uptake of silica by combined HTC/AA during column filtration. The experimental data of silica adsorption fit best to Freundlich isotherm model.
For synthetic aperture radar systems, missing data samples can cause severe image distortion. When multiple, coherent data collections exist and the missing data samples do not overlap between collections, there exists the possibility of replacing data samples between collections. For airborne radar, the known and unknown motions of the aircraft prevent direct data sample replacement to repair image features. This paper presents a method to calculate the necessary phase corrections to enable data sample replacement using only the collected radar data.
All grain boundaries are not equal in their predisposition for fracture due to the complex coupling between lattice geometry, interfacial structure, and mechanical properties. The ability to understand these relationships is crucial to engineer materials resilient to grain boundary fracture. Here, a methodology is presented to isolate the role of grain boundary structure on interfacial fracture properties, such as the tensile strength and work of separation, using atomistic simulations. Instead of constructing sets of grain boundary models within the misorientation/structure space by simply varying the misorientation angle around a fixed misorientation axis, the proposed method creates sets of grain boundary models by means of isocurves associated with important fracture-related properties of the adjoining lattices. Such properties may include anisotropic elastic moduli, the Schmid factor for primary slip, and the propensity for simultaneous slip on multiple slip systems. This approach eliminates the effect of lattice properties from the comparative analysis of interfacial fracture properties and thus enables the identification of structure-property relationships for grain boundaries. As an example, this methodology is implemented to study crack propagation along Ni grain boundaries. Segregated H is used as a means to emphasize differences in the selected grain boundary structures while keeping lattice properties fixed.
Computer simulations at the atomistic scale play an increasing important role in understanding the structure features, and the structure–property relationships of glass and amorphous materials. In this paper, we reviewed atomistic simulation methods ranging from first principles calculations and ab initio molecular dynamics (AIMD) simulations, to classical molecular dynamics (MD), and meso-scale kinetic Monte Carlo (KMC) simulations and their applications to study the reactions and interactions of inorganic glasses with water and the dissolution behaviors of inorganic glasses. Particularly, the use of these simulation methods in understanding the reaction mechanisms of water with oxide glasses, water–glass interfaces, hydrated porous silica gels formation, the structure and properties of multicomponent glasses, and microstructure evolution are reviewed. The advantages and disadvantageous of these simulation methods are discussed and the current challenges and future direction of atomistic simulations in glass dissolution presented.
Units Under Tests (UUTs) will be serviced from a "countertop" that's located on the uppermost side of a new temperature chamber. An ergonomic assessment was performed to determine a working height that ensures the technicians will be able to reach the components inside the UUT in a safe and reliable manner. A review of the anthropometric data relative to elbow height was used to make this determination. Nominal work height was 41.89 inches for the population of interest, ranging from 5th to 95th percentile. After adjusting for the height and centerline dimensions of the UUT, the "countertop" was defined to be ~26.0 inches. Next, a range of working heights was defined to accommodate the tasks involved with servicing the UUTs: from 38.0 to 45.8 inches. These values were compared with design guidelines from the general literature. The results were found to converge relatively well with the external references.
Atomic motion at grain boundaries is essential to microstructure development, growth and stability of catalysts and other nanostructured materials. However, boundary atomic motion is often too fast to observe in a conventional transmission electron microscope (TEM) and too slow for ultrafast electron microscopy. Here, we report on the entire transformation process of strained Pt icosahedral nanoparticles (ICNPs) into larger FCC crystals, captured at 2.5 ms time resolution using a fast electron camera. Results show slow diffusive dislocation motion at nm/s inside ICNPs and fast surface transformation at μm/s. By characterizing nanoparticle strain, we show that the fast transformation is driven by inhomogeneous surface stress. And interaction with pre-existing defects led to the slowdown of the transformation front inside the nanoparticles. Particle coalescence, assisted by oxygen-induced surface migration at T ≥ 300 °C, also played a critical role. Thus by studying transformation in the Pt ICNPs at high time and spatial resolution, we obtain critical insights into the transformation mechanisms in strained Pt nanoparticles.
An experimental study of migration of tungsten in the DIII-D divertor is described, in which the outer strike point of L-mode plasmas was positioned on a toroidal ring of tungsten-coated metal inserts. Net deposition of tungsten on the divertor just outside the strike point was measured on graphite samples exposed to various plasma durations using the divertor materials evaluation system. Tungsten coverage, measured by Rutherford backscattering spectroscopy (RBS), was found to be low and nearly independent of both radius and exposure time closer to the strike point, whereas farther from the strike point the W coverage was much larger and increased with exposure time. Depth profiles from RBS show this was due to accumulation of thicker mixedmaterial deposits farther from the strike point where the plasma temperature is lower. These results are consistent with a low near-surface steady-state coverage on graphite undergoing net erosion, and continuing accumulation in regions of net deposition. This experiment provides data needed to validate, and further improve computational simulations of erosion and deposition of material on plasma-facing components and transport of impurities in magnetic fusion devices. Such simulations are underway and will be reported later.
Maintaining Continuity of Knowledge (CoK) of spent fuel throughout its life cycle is a key objective of the International Atomic Energy Agency (IAEA). This report describes a project in which two specific technologies, cameras with infrared (IR) imaging capabilities and imaging sonar, were tested to determine their effectiveness in augmenting optical surveillance cameras currently used for maintaining CoK for spent nuclear fuel (SNF) staged in spent fuel pools. Furthermore, the project identifies any modifications required to the technologies to facilitate deployment for international safeguards purposes. This report presents results for the imaging sonar tested at Sandia National Laboratories (SNL) in a mockup spent nuclear fuel pool and for the IR-capable cameras tested by Pacific Northwest National Laboratory (PNNL) in the Oregon State University Training, Research, Isotopes, General Atomics (TRIGA) research reactor.
With the end of Dennard scaling and the ever-increasing need for more efficient, faster computation, resistive switching devices (ReRAM), often referred to as memristors, are a promising candidate for next generation computer hardware. These devices show particular promise for use in an analog neuromorphic computing accelerator as they can be tuned to multiple states and be updated like the weights in neuromorphic algorithms. Modeling a ReRAM-based neuromorphic computing accelerator requires a compact model capable of correctly simulating the small weight update behavior associated with neuromorphic training. These small updates have a nonlinear dependence on the initial state, which has a significant impact on neural network training. Consequently, we propose the piecewise empirical model (PEM), an empirically derived general purpose compact model that can accurately capture the nonlinearity of an arbitrary two-terminal device to match pulse measurements important for neuromorphic computing applications. By defining the state of the device to be proportional to its current, the model parameters can be extracted from a series of voltages pulses that mimic the behavior of a device in an analog neuromorphic computing accelerator. This allows for a general, accurate, and intuitive compact circuit model that is applicable to different resistance-switching device technologies. In this work, we explain the details of the model, implement the model in the circuit simulator Xyce, and give an example of its usage to model a specific Ta / TaO x device.
We have developed and built a small porous-plug burner based on the original McKenna burner design. The new burner generates a laminar premixed flat flame for use in studies of combustion chemistry and soot formation. The size is particularly relevant for space-constrained, synchrotron-based X-ray diagnostics. In this paper, we present details of the design, construction, operation, and supporting infrastructure for this burner, including engineering attributes that enable its small size. We also present data for charactering the flames produced by this burner. These data include temperature profiles for three premixed sooting ethylene/air flames (equivalence ratios of 1.5, 1.8, and 2.1); temperatures were recorded using direct one-dimensional coherent Raman imaging. We include calculated temperature profiles, and, for one of these ethylene/air flames, we show the carbon and hydrogen content of heavy hydrocarbon species measured using an aerosol mass spectrometer coupled with vacuum ultraviolet photoionization (VUV-AMS) and soot-volume-fraction measurements obtained using laser-induced incandescence. In addition, we provide calculated mole-fraction profiles of selected gas-phase species and characteristic profiles for seven mass peaks from AMS measurements. Using these experimental and calculated results, we discuss the differences between standard McKenna burners and the new miniature porous-plug burner introduced here.
Individual donors in silicon chips are used as quantum bits with extremely low error rates. However, physical realizations have been limited to one donor because their atomic size causes fabrication challenges. Quantum dot qubits, in contrast, are highly adjustable using electrical gate voltages. This adjustability could be leveraged to deterministically couple donors to quantum dots in arrays of qubits. In this work, we demonstrate the coherent interaction of a 31P donor electron with the electron of a metal-oxide-semiconductor quantum dot. We form a logical qubit encoded in the spin singlet and triplet states of the two-electron system. We show that the donor nuclear spin drives coherent rotations between the electronic qubit states through the contact hyperfine interaction. This provides every key element for compact two-electron spin qubits requiring only a single dot and no additional magnetic field gradients, as well as a means to interact with the nuclear spin qubit.
Methods developed to reduce interference in a noisy environment, be it radar target responses or effective communications in the presence of noise for mobile phone users, are vital in delivering a clear usable signal. The methods used to render a cleaner signal can also be used to combine signals of various frequencies. Ground Penetrating Radar (GPR) scans over the same area are no exception. This paper explores using an optimization problem solver, the Expectation Maximization (EM) Algorithm, to define the weights to use to combine multiple GPR scans at different frequencies over the same target area. This approach exploits the Gaussian Mixture Model (GMM) feature of the EM algorithm to produce a cleaner image at depth. Our method demonstrates a measured improvement toward producing a cleaner image.
A sample of natural quartzite rock was submerged in deionized water and illuminated with 1.8-J pulses of 527- nm light with 15-ns duration over an area of 3 cm2 [fluence = 0.6 J/cm2]. This relatively low fluence and intensity [40 MW/cm2] were far below the threshold needed for direct ablation via plasma formation or thermal evaporation. With each laser pulse, a small cloud of sub-μm particles was released from the surface and dispersed into the submerging water, forming a long-lived suspension. After one hundred laser pulses, the processing was terminated and the surface of the originally colored quartzite was rendered colorless. The quartzite rock was cut in cross section and the colorless material on the surface was examined with X-ray fluorescence. We report that the transition element Fe was found to be significantly depleted in this colorless layer. This supports the hypothesis that the laser exposure lead to a transient hydrothermal dissolution of the material, followed by a recrystallization process of the SiO2 that preferentially released iron oxides into the submerging water.
The Accelerator Driven System (ADS) as a reactor to produce fissile material, or for partitioning & transmutation purposes, has potential as an inherently safe reactor since it can be shut down by simply turning off the accelerator. Multiple studies have focused on the intranuclear and internuclear physics involved in the spallation process for high-energy projectiles impacting high-Z targets relevant to ADS applications. To quantify spallation neutronics, and thereby fissile material production, generally requires numerical methods such as MCNP, and such calculations are specific to the geometry under consideration. This study uses published cross sections from the ENDF database and an assumed generic cylindrical geometry for the ADS target and fertile blanket to derive analytic expressions for the production of Pu-239 and U-233, without needing to run MCNP codes, yet matching published data.
This paper explores the viability of neural-networkbased classification of ground surface for vehicles. By classifying road surface in near realtime, improvements in vehicle performance (e.g. braking and cornering) may be possible. Classification performance for many combinations of feature encoding and neural network types are compared. The vehicle used here was an An Audi “S3” with a magnetic suspension system on the sport mode. An NI CompactRIO (or cDAQ) module was used to record from a lowing the cDAQ to communicate with the PCB 352C03 one-axis accelerometer. The accelerometer was firmly attached to the windshield of the car. This work focuses on the classification of four road surfaces (asphalt, dirt, concrete, and sand), though larger target sets were also considered. The most accurate method involved a MATLAB feature extraction package with a back-propagation neural network, yielding an overall accuracy of 97%. Lessons learned from this wide exploration of options may extend to other related classification problems.
This supplementary material complements the article and provides additional information to the chemical mechanism used in this work, boundary conditions for the LES con guration and table generation, comparisons of axial velocities, results from a LES/ nite-rate chemistry (FRC) approach, and results from the LES/DTF/SPF approach with a particular chemistry table that is generated using a single strained premixed amelet solution.
Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.
Process efficiency is a crucial parameter for inertia friction welding (IFW) that is largely unknown at the present time. A new method has been developed to determine the transient profile of the IFW process efficiency by comparing the workpiece torque used to heat and deform the joint region to the total torque. Particularly, the former is measured by a torque load cell attached to the non-rotating workpiece while the latter is calculated from the deceleration rate of flywheel rotation. The experimentally-measured process efficiency for IFW of AISI 1018 steel rods is validated independently by the upset length estimated from an analytical equation of heat balance and the flash profile calculated from a finite element based thermal stress model. The transient behaviors of torque and efficiency during IFW are discussed based on the energy loss to machine bearings and the bond formation at the joint interface.
Previous observation of EPDM and FEPM materials aged in thermo-oxidative and thermo-oxidative plus hydrolytic environments revealed an unusual trend: the degradation and disintegration of these polymers in the former case but the ability to maintain mechanical performance and shape in the latter [1]. No abnormalities were observed in the chemical (oxidation rates, FTIR spectra, solvent uptake, gel content, and weight loss vs. temperature) or physical (modulus profile) measurements that could explain these empirically observed aging differences. A second controlled aging test was conducted to verify this trend using only EPDM. Once again it was shown that thermo-oxidative conditions appear to cause more degradative damage (enhanced embrittlement) than observed for the combined thermo-oxidative plus hydrolytic environments. From these data we conclude that water may favorably interfere with normal thermo-oxidative degradation processes. This interference may occur via some combination of chemical and physical property changes in the presence of steam such as: oxidation rate and O2 permeability changes, additional sensitivity to hydrolytic damage, and/or mechanistic changes in relation to pH and hydroperoxide formation.
Harmon, Brooke N.; Chylek, Lily A.; Liu, Yanli; Mitra, Eshan D.; Mahajan, Avanika; Saada, Edwin A.; Schudel, Benjamin R.; Holowka, David A.; Baird, Barbara A.; Wilson, Bridget S.; Hlavacek, William S.; Singh, Anup K.
The high-Affinity receptor for IgE expressed on the surface of mast cells and basophils interacts with antigens, via bound IgE antibody, and triggers secretion of inflammatory mediators that contribute to allergic reactions. To understand how past inputs (memory) influence future inflammatory responses in mast cells, a microfluidic device was used to precisely control exposure of cells to alternating stimulatory and non-stimulatory inputs. We determined that the response to subsequent stimulation depends on the interval of signaling quiescence. For shorter intervals of signaling quiescence, the second response is blunted relative to the first response, whereas longer intervals of quiescence induce an enhanced second response. Through an iterative process of computational modeling and experimental tests, we found that these memory-like phenomena arise from a confluence of rapid, short-lived positive signals driven by the protein tyrosine kinase Syk; slow, long-lived negative signals driven by the lipid phosphatase Ship1; and slower degradation of Ship1 co-factors. This work advances our understanding of mast cell signaling and represents a generalizable approach for investigating the dynamics of signaling systems.
An experiment was conducted in DIII-D to compare gross tungsten (W) erosion on samples exposed to outer strike point (OSP) sweeps in L-mode plasmas for three conditions. These included two phases of resonant magnetic perturbations (RMPs), and a set with no perturbations. Upon RMP application, lobe structures indicative of strike point splitting of the OSP were evident in divertor camera data and on Langmuir probes. Gross W erosion flux, GW, inferred spectroscopically using the S/XB method applied to the 400.9 nm W-I line, was generally in the range ΓW/ΓD +,⊥ = 2 × 10-4 referenced to incident deuterium ion flux ΓD+,⊥, and was increased in the RMP cases by no more than 30% of the level observed in unperturbed discharges. A large reduction in gross erosion (50%) was observed in the private flux region at the W sample for one specific toroidal phase of the RMP field.
Design and construct a high-bay facility with penthouse mechanical area that meets the physical and functional requirements as described in this document. Using the Modular High Bay Programming Plan, contractor shall validate programming requirements including equipment to be installed; room sizes and quantities; heating, ventilation, and air- conditioning (HVAC) and electrical requirements, including sizing of equipment based on heat load; and other specific needs. Contractor shall provide the design development, engineering, construction drawings, construction and construction administration services required to completely define, document, and construct the facility to the requirements described in the Building XXX Programming Plan and those referenced herein.
Strong stability preserving (SSP) time discretizations preserve the monotonicity properties satisfied by the spatial discretization when coupled with the first order forward Euler, under a certain time-step restriction. The search for high order strong stability preserving time-stepping methods with high order and large allowable time-step has been an active area of research. It is known that implicit SSP Runge–Kutta methods exist only up to sixth order; however, if we restrict ourselves to solving only linear autonomous problems, the order conditions simplify and we can find implicit SSP Runge–Kutta methods of any linear order. In the current work we find implicit SSP Runge–Kutta methods with high linear order pl i n≤ 9 and nonlinear orders p= 2, 3, 4, that are optimal in terms of allowable SSP time-step. Next, we formulate a novel optimization problem for implicit–explicit (IMEX) SSP Runge–Kutta methods and find optimized IMEX SSP Runge–Kutta pairs that have high linear order pl i n≤ 7 and nonlinear orders up to p= 4. We also find implicit methods with large linear stability regions that pair with known explicit SSP Runge–Kutta methods. These methods are then tested on sample problems to demonstrate the sharpness of the SSP coefficient and the typical behavior of these methods on test problems.
Threaded joints are a common fastening method in applications where disassembly may be required. With a fair amount of investigation of static behavior of threaded joints, less emphasis has been placed on the behavior of threaded joints subjected to transient impact loads. Understanding how energy is transferred across threaded joints under impact loading conditions is critical for improved design and optimization for extreme mechanical environments. Many factors, such as pre - torque, pre - tension load, and impact speed can affect how energy is transferred or dissipated across threaded joins. In addition, high-fidelity numerical simulation of mechanical response of threaded components under blast or impact loading requires reliable experiments and subsequent analyses. In this study, the energy dissipation behavior through a threaded joint under impact loading conditions is investigated using a Kolsky tension bar. The aim is to study possible energy dissipation behavior in both time and frequency domains while the threaded joint remains intact. New analytical methods to understand both time-and frequency-domain behavior of threaded joints are presented. Energy dissipation characteristics through steel-to-steel and steel-to-aluminum threaded joints were then investigated with varying parameters such as pre-torque and impact velocity.
Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials coefficients of thermal expansion as well as the shrinkage upon cure exhibited by most thermoset polymer matrix materials. Depending upon the specific geometric details of the composite structure and the materials curing parameters, it is possible that these residual stresses can result in interlaminar delamination and fracture within the composite as well as plastic deformation in the structures metallic materials. It is important to consider potential residual stresses when designing composite parts and their manufacturing processes. However, the experimental determination of residual stresses in prototype parts can be prohibitive, both in terms of financial and temporal costs. As an alternative to physical measurement, it is possible for computational tools to be used to quantify potential residual stresses in composite prototype parts. A simplified method for simulating residual stresses was previously validated with two simple bi-material structures. Continuing on, the objective of this study is to further validate the simplified method for simulating residual stresses for bi-material split rings of different composites and layup variations. The validation process uses uncertainty quantification to develop a distribution of possible simulated residual stress states that are compared to experimentally measured residual stress states of fabricated structures similar to those simulated. The results of the comparisons indicate that the proposed finite element modeling approach is capable of accurately simulating the formation of residual stresses in composite structures and a temperature independent material model is adequate within the composites glassy region.
We generate a wide range of models of proppant-packed fractures using discrete element simulations, and measure fracture conductivity using finite element flow simulations. This allows for a controlled computational study of proppant structure and its relationship to fracture conductivity and stress in the proppant pack. For homogeneous multi-layered packings, we observe the expected increase in fracture conductivity with increasing fracture aperture, while the stress on the proppant pack remains nearly constant. This is consistent with the expected behavior in conventional proppant-packed fractures, but the present work offers a novel quantitative analysis with an explicit geometric representation of the proppant particles. In single-layered packings (i.e. proppant monolayers), there is a drastic increase in fracture conductivity as the proppant volume fraction decreases and open flow channels form. However, this also corresponds to a sharp increase in the mechanical stress on the proppant pack, as measured by the maximum normal stress relative to the side crushing strength of typical proppant particles. We also generate a variety of computational geometries that resemble highly heterogeneous proppant packings hypothesized to form during channel fracturing. In some cases, these heterogeneous packings show drastic improvements in conductivity with only moderate increase in the stress on the proppant particles, suggesting that in certain applications these structures are indeed optimal. We also compare our computer-generated structures to micro computed tomography imaging of a manually fractured laboratory-scale shale specimen, and find reasonable agreement in the geometric characteristics.
Analog quantum simulators (AQS) will likely be the first nontrivial application of quantum technology for predictive simulation. However, there remain questions regarding the degree of confidence that can be placed in the results of AQS since they do not naturally incorporate error correction. Specifically, how do we know whether an analog simulation of a quantum model will produce predictions that agree with the ideal model in the presence of inevitable imperfections? At the same time there is a widely held expectation that certain quantum simulation questions will be robust to errors and perturbations in the underlying hardware. Resolving these two points of view is a critical step in making the most of this promising technology. In this work we formalize the notion of AQS reliability by determining sensitivity of AQS outputs to underlying parameters, and formulate conditions for robust simulation. Our approach naturally reveals the importance of model symmetries in dictating the robust properties. To demonstrate the approach, we characterize the robust features of a variety of quantum many-body models.
In this study, the experimental results from long-term solubility experiments up to 1146 days on micro-crystalline neodymium hydroxide, Nd(OH)3(micro-cr), in high ionic strength solutions at 298.15 K under well-constrained conditions, are presented. Hydrogen ion concentrations in our experiments are controlled by the dissolution of Nd(OH)3(micro-cr) without artificial adjustment with addition of either an acid or a base, preventing the possibility of phase change that could be induced especially by addition of a base. Such an experimental design also provides the information about the hydrogen ion concentrations buffered by the dissolution of Nd(OH)3, which is currently lacking. The solubility data produced in this work, applicable to geological repositories in high ionic strength environments, are compared with the solubilities of Am(OH)3(s) predicted by using the Waste Isolation Pilot Plant (WIPP) thermodynamic model. The predicted values for Am(OH)3(s) are in good agreement with the experimental values for Nd(OH)3(micro-cr) obtained in this work. Our experimental data indicate that the pHm (negative logarithm of hydrogen ion concentration on a molal scale) buffered by dissolution of Nd(OH)3(micro-cr) ranges from ~ 9.5 to ~ 9.9. As the equilibrium constant for amorphous neodymium hydroxide, Nd(OH)3(am), is useful for several fields, the equilibrium constant regarding the dissolution of Nd(OH)3(am) for the following reaction, Nd(OH)3(am)+3H+=Nd3++3H2O(l)is also obtained by evaluating the experimental data in a wide range of ionic strengths from the literature by using the WIPP thermodynamic model. The log10Ks00 at 298.15 K for the above reaction obtained in this work is 16.85 ± 0.20 (2σ), which is similar to, but slightly lower than, the values in the literature evaluated in the low ionic strength range. This value can be applied to amorphous americium hydroxide, Am(OH)3(am), using Nd(III) as an analog to Am(III).
Algebraic multigrid (AMG) preconditioners are considered for discretized systems of partial differential equations (PDEs) where unknowns associated with different physical quantities are not necessarily colocated at mesh points. Specifically, we investigate a Q2−Q1 mixed finite element discretization of the incompressible Navier–Stokes equations where the number of velocity nodes is much greater than the number of pressure nodes. Consequently, some velocity degrees of freedom (DOFs) are defined at spatial locations where there are no corresponding pressure DOFs. Thus, AMG approaches leveraging this colocated structure are not applicable. This paper instead proposes an automatic AMG coarsening that mimics certain pressure/velocity DOF relationships of the Q2−Q1 discretization. The main idea is to first automatically define coarse pressures in a somewhat standard AMG fashion and then to carefully (but automatically) choose coarse velocity unknowns so that the spatial location relationship between pressure and velocity DOFs resembles that on the finest grid. To define coefficients within the intergrid transfers, an energy minimization AMG (EMIN-AMG) is utilized. EMIN-AMG is not tied to specific coarsening schemes and grid transfer sparsity patterns, and so it is applicable to the proposed coarsening. Numerical results highlighting solver performance are given on Stokes and incompressible Navier–Stokes problems.
A large body of experimental work has established that athermal colloid/polymer mixtures undergo a sequence of transitions from a disordered fluid state to a colloidal crystal to a second disordered phase with increasing polymer concentration. These transitions are driven by polymer-mediated interparticle attraction, which is a function of both the polymer density and size. It has been posited that the disordered state at high polymer density is a consequence of strong interparticle attractions that kinetically inhibit the formation of the colloidal crystal, i.e., the formation of a non-equilibrium gel phase interferes with crystallization. Here we use molecular dynamics simulations and density functional theory on polymers and nanoparticles (NPs) of comparable size and show that the crystal-disordered phase coexistence at high polymer density for sufficiently long chains corresponds to an equilibrium thermodynamic phase transition. While the crystal is, indeed, stabilized at intermediate polymer density by polymer-induced intercolloid attractions, it is destabilized at higher densities because long chains lose significant configurational entropy when they are forced to occupy all of the crystal voids. Our results are in quantitative agreement with existing experimental data and show that, at least in the nanoparticle limit of sufficiently small colloidal particles, the crystal phase only has a modest range of thermodynamic stability.
Molecular structures of kerogen control hydrocarbon production in unconventional reservoirs. Significant progress has been made in developing model representations of various kerogen structures. These models have been widely used for the prediction of gas adsorption and migration in shale matrix. However, using density functional perturbation theory (DFPT) calculations and vibrational spectroscopic measurements, we here show that a large gap may still remain between the existing model representations and actual kerogen structures, therefore calling for new model development. Using DFPT, we calculated Fourier transform infrared (FTIR) spectra for six most widely used kerogen structure models. The computed spectra were then systematically compared to the FTIR absorption spectra collected for kerogen samples isolated from Mancos, Woodford and Marcellus formations representing a wide range of kerogen origin and maturation conditions. Limited agreement between the model predictions and the measurements highlights that the existing kerogen models may still miss some key features in structural representation. A combination of DFPT calculations with spectroscopic measurements may provide a useful diagnostic tool for assessing the adequacy of a proposed structural model as well as for future model development. This approach may eventually help develop comprehensive infrared (IR)-fingerprints for tracing kerogen evolution.
A system is presented that is capable of measuring subnanosecond reverse recovery times of diodes in wide-bandgap materials over a wide range of forward biases (0 - 1 A) and reverse voltages (0 - 10 kV). The system utilizes the step recovery technique and comprises a cable pulser based on a silicon (Si) Photoconductive Semiconductor Switch (PCSS) triggered with an Ultrashort Pulse Laser, a pulse charging circuit, a diode biasing circuit, and resistive and capacitive voltage monitors. The PCSS-based cable pulser transmits a 130 ps rise time pulse down a transmission line to a capacitively coupled diode, which acts as the terminating element of the transmission line. The temporal nature of the pulse reflected by the diode provides the reverse recovery characteristics of the diode, measured with a high bandwidth capacitive probe integrated into the cable pulser. This system was used to measure the reverse recovery times (including the creation and charging of the depletion region) for two Avogy gallium nitride diodes; the initial reverse recovery time was found to be 4 ns and varied minimally over reverse biases of 50-100 V and forward current of 1-100 mA.
In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic Amplitude Versus Angle and Controlled-Source Electromagnetic data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis and Adaptive Metropolis samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and Controlled-Source Electromagnetic data. The multi-chain Markov-chain Monte Carlo is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic Amplitude Versus Angle and Controlled-Source Electromagnetic joint inversion provides better estimation of reservoir saturations than the seismic Amplitude Versus Angle only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated — reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.
We demonstrate a capability of deterministic doping at the single atom level using a combination of direct write focused ion beam and solid-state ion detectors. The focused ion beam system can position a single ion to within 35 nm of a targeted location and the detection system is sensitive to single low energy heavy ions. This platform can be used to deterministically fabricate single atom devices in materials where the nanostructure and ion detectors can be integrated, including donor-based qubits in Si and color centers in diamond.
The porosity of clay aggregates is an important property governing chemical reactions and fluid flow in low-permeability geologic formations and clay-based engineered barrier systems. Pore spaces in clays include interlayer and interparticle pores. Under compaction and dewatering, the size and geometry of such pore spaces may vary significantly (sub-nanometer to microns) depending on ambient physical and chemical conditions. Here we report a molecular dynamics simulation method to construct a complex and realistic clay-like nanoparticle aggregate with interparticle pores and grain boundaries. The model structure is then used to investigate the effect of dewatering and water content on micro-porosity of the aggregates. The results suggest that slow dewatering would create more compact aggregates compared to fast dewatering. Furthermore, the amount of water present in the aggregates strongly affects the particle-particle interactions and hence the aggregate structure. Detailed analyses of particle-particle and water-particle interactions provide a molecular-scale view of porosity and texture development of the aggregates. The simulation method developed here may also aid in modeling the synthesis of nanostructured materials through self-assembly of nanoparticles.
This paper presents a review of the main electrical components that are expected to be present in marine renewable energy arrays. The review is put in context by appraising the current needs of the industry and identifying the key components required in both device and array-scale developments. For each component, electrical, mechanical and cost considerations are discussed; with quantitative data collected during the review made freely available for use by the community via an open access online repository. This data collection updates previous research and addresses gaps specific to emerging offshore technologies, such as marine and floating wind, and provides a comprehensive resource for the techno-economic assessment of offshore energy arrays.
Image processing and stereological techniques were used to characterize the heterogeneity of composite propellant and inform a predictive burn rate model. Composite propellant samples made up of ammonium perchlorate (AP), hydroxyl-terminated polybutadiene (HTPB), and aluminum (Al) were faced with an ion mill and imaged with a scanning electron microscope (SEM) and x-ray tomography (micro-CT). Properties of both the bulk and individual components of the composite propellant were determined from a variety of image processing tools. An algebraic model, based on the improved Beckstead-Derr-Price model developed by Cohen and Strand, was used to predict the steady-state burning of the aluminized composite propellant. In the presented model the presence of aluminum particles within the propellant was introduced. The thermal effects of aluminum particles are accounted for at the solid-gas propellant surface interface and aluminum combustion is considered in the gas phase using a single global reaction. Properties derived from image processing were used directly as model inputs, leading to a sample-specific predictive combustion model.
Anodic stripping voltammetry (ASV) is an analysis technique that permits the selective and quantitative analysis of metal ion species in solution. It is most commonly applied in neutral to acidic electrolyte largely due to inherent metal ion solubility. Bismuth (Bi) is a common film used for ASV due to its good sensitivity, overall stability and insensitivity to O2. ASV, utilizing a Bi film, along with cadmium (Cd) and lead (Pb) as the plating mediators, has recently been adapted to determine zinc (Zn) concentrations in highly alkaline environments (30 % NaOH or 35 % M KOH). Successful analysis of Zn in alkaline relies on the ability of the hydroxide to form soluble metal anion species, such as Bi(OH)4 − and Zn(OH)4 2−. Here, we look to extend this technique to detect and quantify copper (Cu) ions in these highly basic electrolytes. However, in general, the use of ASV to detect and quantify Cu ion concentrations is notoriously difficult as the Cu stripping peak potential overlays with that of Bi from the common Bi film electrode. Here, an ASV method for determining Cu concentration in alkaline solutions is developed utilizing Pb as a deposition mediator. As such, it was found that when analyzing Cu solutions in the presence of Pb, the stripping voltammetry curves present separate and defined Cu stripping peaks. Different analyzes were made to find the best stripping voltammetry performance conditions. As such, an accumulation time of 5 minutes, an accumulation potential of≤−1.45 V vs. Hg/HgO, and a concentration of 35 wt% KOH were determined to be the conditions that presented the best ASV results. Utilizing these conditions, calibration curves in the presence of 5.0 ppm Pb showed the best linear stripping signal correlation with an r-squared value of 0.991 and a limit of detection (LOD) of 0.67 ppm. These results give way to evaluating Cu concentrations using ASV in aqueous alkaline solutions.
We have developed an ambient temperature, SiO2/Si wafer - scale process for Josephson junctions based on Nb electrodes and Ta x N barriers with tunable electronic properties. The films are fabricated by magnetron sputtering. The electronic properties of the TaxN barriers are controlled by adjusting the nitrogen flow during sputtering. This technology offers a scalable alternative to the more traditional junctions based on AlOx barriers for low - power, high - performance computing.
This report assesses seismic interference generated by a tethered aerostat. The study was motivated by a planned aerostat deployment within the footprint of the Dry Alluvium Geology seismic network. No evidence was found for seismic interference generated by the aerostat, and thus the e ects on the Dry Alluvium Geology sensors will be negligible.
Supercritical CO2 (sCO2) is a fluid of interest for advanced power cycles that can reach thermal to electric energy conversion efficiencies of 50% or higher. Of particular interest for fossil-fired natural gas is the Allam cycle that captures nearly all CO2 emissions and exports it as a fluid stream where it may be of value. The combustion process conditions are unlike any before realized with 90-95% CO2 concentration, temperatures around 1000°C, and pressures near 300 bar. This work outlines the experimental feasibility of flow measurements to acquire the first known data in pure sCO2 at similar but reduced temperature and pressure conditions.
The Aquifer Pumping Test Report for the Burn Site Groundwater (BSG) Area of Concern is being submitted by National Technology and Engineering Solutions of Sandia, LLC and the U.S. Department of Energy (DOE)/National Nuclear Security Administration to describe the results of the aquifer pumping test program and related field activities that were completed at the BSG Area of Concern. This report summarizes the results of the field work and data analyses, and is being submitted to the New Mexico Environment Department (NMED) Hazardous Waste Bureau, as required by the April 14, 2016 letter, Summary of Agreements and Proposed Milestones Pursuant to the Meeting of July 20, 2015, (NMED April 2016).
The purpose of the work presented in this memo was to calibrate the Sierra material model Multilinear Elastic-Plastic Hardening Model with Failure, (MLEP-Fail), for 1/8 inch thick plate of 13-8 PH steel in the H1150 condition. Material testing was pursued first, followed by the actual calibration.