We present scenario and parametric analyses of the US light duty vehicle (LDV) stock, sim- ulating the evolution of the stock in order to assess the potential role and impacts of fuel cell electric vehicles (FCEVs). The analysis probes the competition of FCEVs with other LDVs and the effects of FCEV adoption on LDV fuel use and emissions. We parameterize commodity and technology prices in order to explore the sensitivities of FCEV sales and emissions to oil, natural gas, battery technology, fuel cell technology, and hydrogen produc- tion prices. We additionally explore the effects of vehicle purchasing incentives for FCEVs, identifying potential impacts and tipping points. Our analyses lead to the following conclu- sions: (1) In the business as usual scenario, FCEVs comprise 7% of all new LDV sales by 2050. (2) FCEV adoption will not substantially impact green house gas emissions without either policy intervention, significant increases in natural gas prices, or technology improve- ments that motivate low carbon hydrogen production. (3) FCEV technology cost reductions have a much greater potential for impact on FCEV sales than hydrogen fuel cost reductions. (4) FCEV purchasing incentives must be both substantial and sustained in order to motivate lasting changes to FCEV adoption.
Unprecedented amounts of data are continuously being generated by sensors (“hard” data) and by humans (“soft” data), and this data needs to be exploited to its full potential. The first step in exploiting this data is determine how the hard and soft data are related to each other. In this project we fuse hard and soft data, using the attributes of each (e.g., time and space), to gain more information about interesting events. Next, we attempt to use social networking textual data to predict the present (i.e., predict that an interesting event is occurring and details about the event) using data mining, machine learning, natural language processing, and text analysis techniques.
A dual-particle imager (DPI) has been designed that is capable of detecting gamma-ray and neutron signatures from shielded SNM. The system combines liquid organic and NaI(Tl) scintillators to form a combined Compton and neutron scatter camera. Effective image reconstruction of detected particles is a crucial component for maximizing the performance of the system; however, a key deficiency exists in the widely used iterative list-mode maximum-likelihood estimation-maximization (MLEM) image reconstruction technique. For MLEM a stopping condition is required to achieve a good quality solution but these conditions fail to achieve maximum image quality. Stochastic origin ensembles (SOE) imaging is a good candidate to address this problem as it uses Markov chain Monte Carlo to reach a stochastic steady-state solution. The application of SOE to the DPI is presented in this work.
Cochran, John R.; Bennett, David G.; Degnan, Paul; Grout, Chris; Liebenberg, Gert; Little, Richard; Ramsey, Jack; Van Blerk, Japie; Van Marcke, Philippe
The community of Cordova, Alaska currently uses diesel and run-of-river hydro generation for its electricity needs. In the past, 60% of the Cordova summer load was supplied by the run-of-river generation. The majority of the time, the load was supplied only by the run-of-river generation. The bulk of generated electricity is delivered to Cordova's industrial fish processing plants and to other industrial loads. With the expansion of Cordova's fishing industry, the run-of-river generation is less often able to supply 100% of the load demand. When the run-of-river generation is not able to supply 100% of the load demand it has to be supplemented by diesel generation. There are also many times when the load demand is low and the available run-of-river generation has to be curtailed by spilling water which could be stored in an energy storage system. Sandia National Laboratories and Alaska Center for Energy and Power collaborated to evaluate how an energy storage system can be used to capture the spilled water and how it can economically and technically benefit Cordova during the fishing season and other times throughout the year. Results from this study are summarized in this report.
Trumbo, Michael C.; Leshikar, Eric D.; Leach, Ryan C.; Mccurdy, Matthew P.; Sklenar, Allison M.; Frankenstein, Andrea N.; Matzen, Laura E.
Prior work demonstrates that application of transcranial direct current stimulation (tDCS) improves memory. In this study, we investigated tDCS effects on face-name associative memory using both recall and recognition tests. Participants encoded face-name pairs under either active (1.5 mA) or sham (.1 mA) stimulation applied to the scalp adjacent to the left dorsolateral prefrontal cortex (dlPFC), an area known to support associative memory. Participants’ memory was then tested after study (day one) and then again after a 24-h delay (day two), to assess both immediate and delayed stimulation effects on memory. Results indicated that active relative to sham stimulation led to substantially improved recall (more than 50%) at both day one and day two. Recognition memory performance did not differ between stimulation groups at either time point. These results suggest that stimulation at encoding improves memory performance by enhancing memory for details that enable a rich recollective experience, but that these improvements are evident only under some testing conditions, especially those that rely on recollection. Overall, stimulation of the dlPFC could have led to recall improvement through enhanced encoding from stimulation or from carryover effects of stimulation that influenced retrieval processes, or both.
The three-dimensional finite element mesh capturing realistic geometries of the Bayou Choctaw site has been constructed using the sonar and seismic survey data obtained from the field. The mesh consists of hexahedral elements because the salt constitutive model is coded using hexahedral elements. Various ideas and techniques to construct finite element mesh capturing artificially and naturally formed geometries are provided. The techniques to reduce the number of elements as much as possible to save on computer run time while maintaining the computational accuracy is also introduced. The steps and methodologies could be applied to construct the meshes of Big Hill, Bryan Mound, and West Hackberry strategic petroleum reserve sites. The methodology could be applied to the complicated shape masses for various civil and geological structures.
Controlling the traffic of molecules and ions across membranes is a critical feature in a number of biologically relevant processes and highly desirable for the development of technologies based on membrane materials. In this paper, ion transport behavior of hybrid lipid/polymer membranes was studied in the absence and presence of ion transfer agents. A pH-sensitive fluorophore was used to investigate ion (H+/OH−) permeability across hybrid lipid/polymer membranes as a function of the fraction of amphiphilic block copolymer. It was observed that vesicles with intermediate lipid/polymer ratios tend to be surprisingly more permeable to ion transport than the pure lipid or pure polymer vesicles. Hybrid vesicle permeability could be further modulated with valinomycin, nigericin, or gramicidin A, which significantly expedite the dissipation of externally-imposed pH gradients by facilitating the transport of the rate-limiting co-ions (e.g. K+) ions across the membrane. For gramicidin A, ion permeability decreased with increasing polymer mole fraction, and the method of introduction of gramicidin A into the membrane played an important role. Strategies to incorporate biofunctional molecules and facilitate their activity in synthetic systems are highly desirable for developing artificial organelles or other synthetic compartmentalized structures requiring control over molecular traffic across biomimetic membranes.
We use helium released during mechanical deformation of shales as a signal to explore the effects of deformation and failure on material transport properties. A dynamic dual-permeability model with evolving pore and fracture networks is used to simulate gases released from shale during deformation and failure. Changes in material properties required to reproduce experimentally observed gas signals are explored. We model two different experiments of 4He flow rate measured from shale undergoing mechanical deformation, a core parallel to bedding and a core perpendicular to bedding. We find that the helium signal is sensitive to fracture development and evolution as well as changes in the matrix transport properties. We constrain the timing and effective fracture aperture, as well as the increase in matrix porosity and permeability. Increases in matrix permeability are required to explain gas flow prior to macroscopic failure, and the short-term gas flow postfailure. Increased matrix porosity is required to match the long-term, postfailure gas flow. Our model provides the first quantitative interpretation of helium release as a result of mechanical deformation. The sensitivity of this model to changes in the fracture network, as well as to matrix properties during deformation, indicates that helium release can be used as a quantitative tool to evaluate the state of stress and strain in earth materials.
Cyanobacterial phycobilisome (PBS) pigment-protein complexes harvest light and transfer the energy to reaction centers. Previous ensemble studies have shown that cyanobacteria respond to changes in nutrient availability by modifying the structure of PBS complexes, but this process has not been visualized for individual pigments at the single-cell level due to spectral overlap. We characterized the response of four key photosynthetic pigments to nitrogen depletion and repletion at the subcellular level in individual, live Synechocystis sp. PCC 6803 cells using hyperspectral confocal fluorescence microscopy and multivariate image analysis. Our results revealed that PBS degradation and re-synthesis comprise a rapid response to nitrogen fluctuations, with coordinated populations of cells undergoing pigment modifications. Chlorophyll fluorescence originating from photosystem I and II decreased during nitrogen starvation, but no alteration in subcellular chlorophyll localization was found. We observed differential rod and core pigment responses to nitrogen deprivation, suggesting that PBS complexes undergo a stepwise degradation process.
For nearly a century, global power systems have focused on three key functions: Generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.
When electrodes are biased above the plasma potential, electrons accelerated through the associated electron sheath can dramatically increase the ionization rate of neutrals near the electrode surface. It has previously been observed that if the ionization rate is great enough, a double layer separates a luminous high-potential plasma attached to the electrode surface (called an anode spot or fireball) from the bulk plasma. Here, results of the first 2D particle-in-cell simulations of anode spot formation are presented along with a theoretical model describing the formation process. It is found that ionization leads to the build-up of an ion-rich layer adjacent to the electrode, forming a narrow potential well near the electrode surface that traps electrons born from ionization. It is shown that anode spot onset occurs when a quasineutral region is established in the potential well and the density in this region becomes large enough to violate the steady-state Langmuir condition, which is a balance between electron and ion fluxes across the double layer. A model for steady-state properties of the anode spot is also presented, which predicts values for the anode spot size, double layer potential drop, and form of the sheath at the electrode by considering particle, power, and current balance. These predictions are found to be consistent with the presented simulation and previous experiments.
We conducted computational macroscale simulations predicting blast-induced intracranial fluid cavitation possibly leading to brain injury. To further understanding of this problem, we developed microscale models investigating the effects of blast-induced cavitation bubble collapse within white matter axonal fiber bundles of the brain. We model fiber tracks of myelinated axons whose diameters are statistically representative of white matter. Nodes of Ranvier are modeled as unmyelinated sections of axon. Extracellular matrix envelops the axon fiber bundle, and gray matter is placed adjacent to the bundle. Cavitation bubbles are initially placed assuming an intracranial wave has already produced them. Pressure pulses, of varied strengths, are applied to the upper boundary of the gray matter and propagate through the model, inducing bubble collapse. Simulations, conducted using the shock wave physics code CTH, predict an increase in pressure and von Mises stress in axons downstream of the bubbles after collapse. This appears to be the result of hydrodynamic jetting produced during bubble collapse. Interestingly, results predict axon cores suffer significantly lower shear stresses from proximal bubble collapse than does their myelin sheathing. Simulations also predict damage to myelin sheathing, which, if true, degrades axonal electrical transmissibility and general health of the white matter structures in the brain.
Photos in each group are in chronological order as captured: Group I Tank Platform Setup, November 14, 2017; Group II Tank Setup, November 15, 2017; Group III Aboveground Injestion System (AIS) Setup, November 20, 2017; Group IV Chemical Mixing, November 21, 2017; Group V KB-1 Bacteria Injection, November 27, 2017; Group VI Miscellaneous.
Over the past ten years, the Department of Energy (DOE) has helped to develop components and technologies for the Supercritical Carbon Dioxide (sCO2) power cycle capable of efficient operation at high temperatures and high efficiency. The DOE Offices of Fossil Energy, Nuclear Energy, and Energy Efficiency and Renewable Energy collaborated in the planning and execution of the sCO2 Power Cycle Summit conducted in Albuquerque, NM in November 2017. The summit brought together participants from government, national laboratories, research, and industry to engage in discussions regarding the future of sCO2 Power Cycles Technology. This report summarizes the work involved in summit planning and execution, before, during, and after the event, including the coordination between three DOE offices and technical content presented at the event.
Majumder, Erica L.W.; Wolf, Benjamin M.; Liu, Haijun; Berg, R.H.; Timlin, Jerilyn A.; Chen, Min; Blankenship, Robert E.
Far-Red Light (FRL) acclimation is a process that has been observed in cyanobacteria and algae that can grow solely on light above 700 nm. The acclimation to FRL results in rearrangement and synthesis of new pigments and pigment-protein complexes. In this study, cyanobacteria containing chlorophyll f, Synechococcus sp. PCC 7335 and Halomicronema hongdechloris, were imaged as live cells with confocal microscopy. H. hongdechloris was further studied with hyperspectral confocal fluorescence microscopy (HCFM) and freeze-substituted thin-section transmission electron microscopy (TEM). Under FRL, phycocyanin-containing complexes and chlorophyll-containing complexes were determined to be physically separated and the synthesis of red-form phycobilisome and Chl f was increased. The timing of these responses was observed. The heterogeneity and eco-physiological response of the cells was noted. Additionally, a gliding motility for H. hongdechloris is reported.
In many fields of study, from coherent Raman microscopy on living cells to time-resolved coherent Raman spectroscopy of gas-phase turbulence and combustion reaction dynamics, the need for the capability to time-resolve fast dynamical and nonrepetitive processes has led to the continued development of high-speed coherent Raman methods and new high-repetition rate laser sources, such as pulse-burst laser systems. However, much less emphasis has been placed on our ability to detect shot to shot coherent Raman spectra at equivalently high scan rates, across the kilohertz to megahertz regime. This is beyond the capability of modern scientific charge coupled device (CCD) cameras, for instance, as would be employed with a Czerny-Turner type spectrograph. As an alternative detection strategy with megahertz spectral detection rate, we demonstrate dispersive Fourier transformation detection of pulsed (~90 ps) coherent Raman signals in the time-domain. Instead of reading the frequency domain signal out using a spectrometer and CCD, the signal is transformed into a time-domain waveform through dispersive Fourier transformation in a long single-mode fiber and read-out with a fast sampling photodiode and oscilloscope. Molecular O- and S-branch rotational sideband spectra from both N2 and H2 were acquired employing this scheme, and the waveform is fitted to show highly quantitative agreement with a molecular model. The total detection time for the rotational spectrum was 20 ns, indicating an upper limit to the detection frequency of ~50 MHz, significantly faster than any other reported spectrally-resolved coherent anti-Stokes Raman detection strategy to date.
Accelerated aging of polymers at elevated temperatures often involves the generation of volatiles. These can be formed as the products of oxidative degradation reactions or intrinsic pyrolytic decomposition as part of polymer scission reactions. A simple analytical method for the quantification of water, CO2, and CO as fundamental signatures of degradation kinetics is required. This study describes an analytical framework and develops a rapid mid-IR based gas analysis methodology to quantify volatiles that are contained in small ampoules after aging exposures. The approach requires identification of unique spectral signatures, systematic calibration with known concentrations of volatiles, and a rapid acquisition FTIR spectrometer for time resolved successive spectra. The volatiles are flushed out from the ampoule with dry N2 carrier gas and are then quantified through spectral and time integration. This method is sufficiently sensitive to determine absolute yields of ∼50 μg water or CO2, which relates to probing mass losses of less than 0.01% for a 1 g sample, i.e. the early stages in the degradation process. Such quantitative gas analysis is not easily achieved with other approaches. This approach opens up the possibility of quantitative monitoring of volatile evolution as an avenue to explore polymer degradation kinetics and its dependence on time and temperature.
Fatigued driving contributes to a substantial number of motor vehicle accidents each year. Music listening is often employed as a countermeasure during driving in order to mitigate the effects of fatigue. Though music listening has been established as a distractor in the sense that it increases cognitive load during driving, it is possible that increased cognitive load is desirable under particular circumstances. For instance, during situations that typically result in cognitive underload, such as driving in a low-traffic monotonous stretch of highway, it may be beneficial for cognitive load to increase, thereby necessitating allocation of greater cognitive resources to the task of driving and attenuating fatigue. In the current study, we employed a song-naming game as a countermeasure to fatigued driving in a simulated monotonous environment. During the first driving session, we established that driving performance deteriorates in the absence of an intervention following 30 min of simulated driving. During the second session, we found that a song-naming game employed at the point of fatigue onset was an effective countermeasure, as reflected by simulated driving performance that met or exceeded fresh driving behavior and was significantly better relative to fatigued performance during the first driving session.
The excimer-pumped alkali laser (XPAL) system has recently been demonstrated in several different mixtures of alkali vapor and rare gas. Without special preventive measures, plasma formation during operation of XPAL is unavoidable. Recent advancements in the availability of reliable data for electron impact collisions with atoms and molecules have enabled development of a complete reaction mechanism to investigate XPAL-induced plasmas. We report on pathways leading to plasma formation in an Ar∕C2H6∕Cs XPAL sustained at different cell temperatures. We find that depending on the operating conditions, the contribution of electron impact processes can be as little as bringing the excitation of Cs(2P) states to higher level Cs states, and can be as high as bringing Cs(2P) excited states to a full ionization. Increasing the input pumping power or cell temperature, or decreasing the C2H6 mole fraction leads to electron impact processes dominating in plasma formation over the energy pooling mechanisms previously reported in literature.
Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.; Jensen, Anna M.; Malhotra, Avni; Mcfarlane, Karis J.; Norby, Richard J.; Sargsyan, Khachik S.; Sebestyen, Stephen D.; Shi, Xiaoying; Walker, Anthony P.; Ward, Eric J.; Warren, Jeffrey M.; Weston, David J.
We are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determine if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m-2 yr-1 to a sink of 67 g C m-2 yr-1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO2 treatments.
The advent of fabrication techniques like additive manufacturing has focused attention on the considerable variability of material response due to defects and other micro-structural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. Lastly, we demonstrate that the new method provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.
Here, we develop a method for time-dependent topic tracking and meme trending in social media. Our objective is to identify time periods whose content differs signifcantly from normal, and we utilize two techniques to do so. The first is an information-theoretic analysis of the distributions of terms emitted during different periods of time. In the second, we cluster documents from each time period and analyze the tightness of each clustering. We also discuss a method of combining the scores created by each technique, and we provide ample empirical analysis of our methodology on various Twitter datasets.
Strike difference of the trivalent rare-earth cations from their alkali and alkaline-earth peers is in the presence of localized 4f-electrons and strong spin-orbit coupling. Placing trivalent rare-earth cations inside the fullerene molecules or in between the blocks of itinerant magnetic intermetallics gave rise to plethora of fascinating properties and materials. A long-time missing but hardly desired piece is the semiconducting or metallic compound where rare-earth cations are situated inside the oversized polyhedral cages of three-dimensional framework. In this work we present a synthesis of such compounds, rare-earth containing clathrates Ba8-xRxCu16P30. The unambiguous proofs of their composition and crystal structure were achieved by a combination of synchrotron powder diffraction, time-of-flight neutron powder diffraction, scanning-transmission electron microscopy, and electron energy-loss spectroscopy. Our quantum-mechanical calculations and experimental characterizations show that the incorporation of the rare-earth cations significantly enhances the hole mobility and concentration which results in the drastic increase in the thermoelectric performance.
Here, this study explores the performance and scaling of a GMRES Krylov method employed as a smoother for an algebraic multigrid (AMG) preconditioned Newton- Krylov solution approach applied to a fully-implicit variational multiscale (VMS) nite element (FE) resistive magnetohydrodynamics (MHD) formulation. In this context a Newton iteration is used for the nonlinear system and a Krylov (GMRES) method is employed for the linear subsystems. The efficiency of this approach is critically dependent on the scalability and performance of the AMG preconditioner for the linear solutions and the performance of the smoothers play a critical role. Krylov smoothers are considered in an attempt to reduce the time and memory requirements of existing robust smoothers based on additive Schwarz domain decomposition (DD) with incomplete LU factorization solves on each subdomain. Three time dependent resistive MHD test cases are considered to evaluate the method. The results demonstrate that the GMRES smoother can be faster due to a decrease in the preconditioner setup time and a reduction in outer GMRESR solver iterations, and requires less memory (typically 35% less memory for global GMRES smoother) than the DD ILU smoother.
We present findings on the computational complexity of computing multidimensional persistent homology. We first show that the worst-case computational complexity of multidimensional persistence is exponential. We then present an algorithm for computing multidimensional persistence which extends the algorithm given by Zomorodian and Carlsson for computing one-dimensional persistence. The computational complexity of our algorithm is polynomial in the size of the persistence module and exponential in the persistence dimension.
Miller, Andrew; Bentov, Iddo; Kumaresan, Ranjit; Cordi, Christopher; Mccorry, Patrick
Bitcoin, Ethereum and other blockchain-based cryptocurrencies, as deployed today, cannot scale for wide-spread use. A leading approach for cryptocurrency scaling is a smart contract mechanism called a payment channel which enables two mutually distrustful parties to transact efficiently (and only requires a single transaction in the blockchain to set-up). Payment channels can be linked together to form a payment network, such that payments between any two parties can (usually) be routed through the network along a path that connects them. Crucially, both parties can transact without trusting hops along the route. In this paper, we propose a novel variant of payment channels, called Sprites, that reduces the worst-case “collateral cost” that each hop along the route may incur. The benefits of Sprites are two-fold. 1) In Lightning Network, a payment across a path of ℓ channels requires locking up collateral for Θ(ℓΔ) time, where Δ is the time to commit an on-chain transaction. Sprites reduces this cost to Θ(ℓ+Δ). 2) Unlike prior work, Sprites supports partial withdrawals and deposits, during which the channel can continue to operate without interruption. In evaluating Sprites we make several additional contributions. First, our simulation-based security model is the first formalism to model timing guarantees in payment channels. Our construction is also modular, making use of a generic abstraction from folklore, called the “state channel,” which we are the first to formalize. We also provide a simulation framework for payment network protocols, which we use to confirm that the Sprites construction mitigates against throughput-reducing attacks.
Uncertainty is pervasive in all science and engineering applications. Incorporating uncertainty in physical models is therefore both natural and vital. In doing so, we often arrive at parametric systems of partial differential equations (PDEs). When passing from simulation to optimization, we obtain (typically nonconvex) infinite-dimensional optimization problems that, upon discretization, result in extremely large-scale nonlinear programs. For example, consider a linear elliptic PDE on a two- dimensional domain with a single random coeffcient. If we sampled the random input with 10,000 realizations of the coeffcient, the resulting optimization problem would have 10,000 PDE constraints. Furthermore, discretizing each PDE with piecewise linear finite elements on a 100X100 uni- form quadrilateral mesh results in 100,000,000 degrees of freedom. As a result, the critical components for ensuring mesh-independent performance of numerical optimization methods in the deterministic setting, for example, solution regularity and generalized differentiability, are even more critical in the stochastic setting.
Clays have many positive attributes leading to their use in waste isolation scenarios. One negative of their use is the formation of clay colloids that can transmit otherwise strongly sorbing contaminants long distances. In this work, we introduce a material combining a layered double hydroxide and a montmorillonite clay. This material is functionally characterized in an advective column under conditions where clay colloid formation is extensive. The material is shown to retard clay colloids once formed, and to help limit the initial formation of clay colloids. Adding this material to a waste barrier will help to limit the erosion of the clays in the barrier and limit the colloidal transport of contaminants.
The stability constant of FeB(OH)4+ is expected to find applications in many areas of study. For instance, FeB(OH)4+ may have played an important role in transport of ferrous iron in reducing water bodies at the surface of the primitive Earth. In the nearfield of geological repositories, the formation of FeB(OH)4+ can sequestrate soluble borate, lowering borate concentrations available to the formation of the Am(III)-borate aqueous complex.
Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films
Gerberich, William; Tadmor, Ellad B.; Kysar, Jeffrey; Zimmerman, Jonathan A.; Minor, Andrew M.; Szlufarska, Izabela; Amodeo, Jonathan; Devincre, Benoit; Hintsala, Eric; Ballarini, Roberto
With rapidly increasing numbers of studies of new and exotic material uses for perovskites and quasicrystals, these demand newer instrumentation and simulation developments to resolve the revealed complexities. One such set of observational mechanics at the nanoscale is presented here for somewhat simpler material systems. The expectation is that these approaches will assist those materials scientists and physicists needing to verify atomistic potentials appropriate to the nanomechanical understanding of increasingly complex solids. The five following segments from nine University, National and Industrial Laboratories both review and forecast where some of the important approaches will allow a confirming of how in situ mechanics and nanometric visualization might unravel complex phenomena. These address two-dimensional structures, temporal models for the nanoscale, atomistic and multiscale friction fundamentals, nanoparticle surfaces and interfaces and nanomechanical fracture measurements, all coupled to in situ observational techniques. Rapid future advances in the applicability of such materials science solutions appear guaranteed.
This Federal Radiological Monitoring and Assessment Center (FRMAC) Assessment Manual has been prepared by representatives of those Federal and State agencies that can be expected to play the major roles during a radiological emergency. Federal Agencies include: the National Nuclear Security Administration (NNSA), the Nuclear Regulatory Commission (NRC), the Environmental Protection Agency (EPA), the Department of Agriculture (USDA), the Food and Drug Administration (FDA), and the Centers for Disease Control (CDC). This final manual was reviewed by experts from across the community and their input has been incorporated.
This report provides an introduction to cyber security for distributed energy resources (DER) - such as photovoltaic (PV) inverters and energy storage systems (ESS). This material is motivated by the need to assist DER vendors, aggregators, grid operators, and broader PV industry with cyber security resilience and describe the state-of-the-art for securing DER communications. The report outlines basic principles of cyber security, encryption, communication protocols, DER cyber security recommendations and requirements, and device-, aggregator-, and utility-level security best practices to ensure data confidentiality, integrity, and availability. Example cyber security attacks, including eavesdropping, masquerading, man-in-the-middle, replay attacks, and denial-of-service are also described. A survey of communication protocols and cyber security recommendations used by the DER and power system industry are included to elucidate the cyber security standards landscape. Lastly, a roadmap is presented to harden end-to-end communications for DER with research and industry engagement.
Understanding the interfacial behavior of two materials sliding relative to each other is import ant in computational modeling and simulating impact or shock response of components, subsystems, and even full-scale systems. Although often considered as a constant for different applications, the coefficient of friction may be dependent on a number of factors such as normal force, roughness, material type, temperature, and sliding velocity. In this study, a new method based on a Kolsky tension bar with a custom-made friction fixture was developed for measurement of the dynamic friction coefficient between two metallic materials at high sliding velocities. In this new method, polyvinylidene fluoride (PVDF) thin film force sensors were used to measure the normal force, while a strain gage on the transmission bar was used to measure the friction force. As such, the dynamic friction coefficient is calculated with the normal and friction forces. The impact velocity can be varied to investigate the dependency of friction coefficient on impact velocity. To evaluate the technique, friction coefficients between 4340 steel and 7075-T6 we re measured at three different sliding velocities of 4, 8 and 11 m/s. Effects of surface roughness, normal force, and impact speed were also explored . Decreased static and kinetic friction coefficient s were observed when the normal force was increased at constant sliding velocity. With increasing velocity, the friction coefficient remained fairly constant for the three velocities studied. Higher friction coefficients were measured when the specimen roughness was increased.
This Laboratory Directed Research and Development (LDRD) project focused on understanding the mathematical relationships that can be used in assessing the value of executing various EMP mitigation strategies on the grid. This is referred to as the EMP Resilient Grid Value Model. Because the range of mitigation strategies can contain widely differing characteristics (operational vs. technological), it is necessary to compute functions of many interrelated metrics at varying levels of fidelity that will be used to provide feedback as to the cost/benefit relationship of any proposed strategy. The value model is a hierarchical decomposition of a system of systems (SoS) model down to a grid circuit model. The model is intended to be suitable for use in subsequent decision support optimization for resilience to EMP events. The metric set goes beyond direct, technical impacts on the electrical grid to include ancillary impacts on dependent infrastructure and enterprise concerns (water, DoD, transportation, etc.).
Future nuclear arms - control agreements may place numerical limits on the total number of warheads in the nuclear arsenals of states. Verifying these limits may require inspectors to account for individual warheads, both deployed and non-deployed. This task could be accomplished with unique identifiers, but standard tagging techniques may be unacceptable in this case due to host concerns about safety and intrusiveness. To resolve this dilemma, we revisit the so - called Buddy Tag concept first proposed by Sandia National Laboratories in the early 1990s. The conceptual innovation in the Buddy Tag was to by separate the tag from the treaty limited item itself. Verification of the pairings between tags and limited items would take place during a short-notice inspection, where the host would be required to produce one buddy tag for each item. Sensors on the Buddy Tag would show that it had not been moved to the inspected site after the inspection was declared (e.g., within the last 24-48 hours). If the inspector counted more (or fewer) treaty limited items than Buddy Tags at the inspected site, a treaty violation could be asserted. Using a number of single-site inspections, an inspecting party can hold the host at risk for discovery of violating the treaty at an enterprise level by possessing more treaty limited items than the treaty allows. In this project, we developed a buddy-tag prototype for demonstration and evaluation purposes. This paper summarizes the performance requirements for an advanced Buddy Tag, the proposed conduct of operations, the design choices and functionalities of the different subsystems, and initial testing results. The report also summarizes peer review feedback obtained throughout the project.
Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible. Projections by all models were in close agreement only in the first few years. Although the projections from LVCFlex, MA3T, LAVE-Trans, and ParaChoice were in qualitative agreement, there were significant differences in sales shares given by the different models for individual powertrain types, particularly in later years (2030 and later). For example, projected sales shares of conventional spark-ignition vehicles in 2030 for a given scenario ranged from 35% to 74%. Reasons for such differences are discussed, recognizing that these models were not developed to give quantitatively accurate predictions of future sales shares, but to represent vehicles markets realistically and capture the connections between sales and important influences. Model features were also compared at a high level, and suggestions for further comparison of models are given to enable better understanding of how different features and algorithms used in these models may give different projections.
Quantitative understanding of reactivity and stability for a chemical species is fundamental to chemistry. The concept has undergone many changes and additions throughout the history of chemistry, stemming from the ideas such as Lewis acids and bases. For a given complexing ligand (Lewis base) and a group of isovalent metal cations (Lewis acids), the stability constants of metal-ligand (ML) complexes can simply correlate to the known properties of metal ions [ionic radii (rMn+), Gibbs free energy of formation (ΔG°f, Mn+), and solvation energy (ΔG°s, Mn+)] by 2.303RT log KML = (α∗MLΔG°f, Mn+ - β∗MLrMn+ + γ∗MLΔG°s, Mn+ - ∗ML), where the coefficients (α∗ML, β∗ML, γ∗ML, and intercept δ∗ML) are determined by fitting the equation to the existing experimental data. Coefficients β∗ML and γ∗ML have the same sign and are in a linear relationship through the origin. Gibbs free energies of formation of cations (ΔG°f, Mn+) are found to be natural indices for the softness or hardness of metal cations, with positive values corresponding to soft acids and negative values to hard acids. The coefficient α∗ML is an index for the softness or hardness of a complexing ligand. Proton (H+) with the softness index of zero is a unique acid that has strong interactions with both soft and hard bases. The stability energy resulting from the acid-base interactions is determined by the term α∗MLΔG°f, Mn+; a positive product of α∗ML and ΔG°f, Mn+ indicates that the acid-base interaction between the metal cation and the complexing ligand stabilizes the complex. The terms β∗MLrMn+ and γ∗MLΔG°s, Mn+, which are related to ionic radii of metal cations, represent the steric and solvation effects of the cations. The new softness indices proposed here will help to understand the interactions of ligands (Lewis bases) with metal cations (Lewis acids) and provide guidelines for engineering materials with desired chemical reactivity and selectivity. The new correlation can also enhance our ability for predicting the speciation, mobility, and toxicity of heavy metals in the earth environments and biological systems.
There has recently been a great deal of interest in employing immiscible solutes to stabilize nanocrystalline microstructures. Existing modeling efforts largely rely on mesoscale Monte Carlo approaches that employ a simplified model of the microstructure and result in highly homogeneous segregation to grain boundaries. However, there is ample evidence from experimental and modeling studies that demonstrates segregation to grain boundaries is highly non-uniform and sensitive to boundary character. This work employs a realistic nanocrystalline microstructure with experimentally relevant global solute concentrations to illustrate inhomogeneous boundary segregation. Furthermore, experiments quantifying segregation in thin films are reported that corroborate the prediction that grain boundary segregation is highly inhomogeneous. In addition to grain boundary structure modifying the degree of segregation, the existence of a phase transformation between low and high solute content grain boundaries is predicted. In order to conduct this study, new embedded atom method interatomic potentials are developed for Pt, Au, and the PtAu binary alloy.
Moaseri, Ehsan; Bollinger, Jonathan B.; Changalvaie, Behzad; Johnson, Lindsay; Schroer, Joseph; Johnston, Keith P.; Truskett, Thomas M.
Nanoparticle (NP) clusters with diameters ranging from 20 to 100 nm are reversibly assembled from 5 nm gold (Au) primary particles coated with glutathione (GSH) in aqueous solution as a function of pH in the range of 5.4 to 3.8. As the pH is lowered, the GSH surface ligands become partially zwitterionic and form interparticle hydrogen bonds that drive the self-limited assembly of metastable clusters in <1 min. Whereas clusters up to 20 nm in size are stable against cluster-cluster aggregation for up to 1 day, clusters up to 80 nm in size can be stabilized over this period via the addition of citrate to the solution in equal molarity with GSH molecules. The cluster diameter may be cycled reversibly by tuning pH to manipulate the colloidal interactions; however, modest background cluster-cluster aggregation occurs during cycling. Cluster sizes can be stabilized for at least 1 month via the addition of PEG-thiol as a grafted steric stabilizer, where PEG-grafted clusters dissociate back to starting primary NPs at pH 7 in fewer than 3 days. Whereas the presence of excess citrate has little effect on the initial size of the metastable clusters, it is necessary for both the cycling and dissociation to mediate the GSH-GSH hydrogen bonds. In summary, these metastable clusters exhibit significant characteristics of equilibrium self-limited assembly between primary particles and clusters on time scales where cluster-cluster aggregation is not present.
Triangle counting serves as a key building block for a set of important graph algorithms in network science. In this paper, we address the IEEE HPEC Static Graph Challenge problem of triangle counting, focusing on obtaining the best parallel performance on a single multicore node. Our implementation uses a linear algebra-based approach to triangle counting that has grown out of work related to our miniTri data analytics miniapplication [1] and our efforts to pose graph algorithms in the language of linear algebra. We leverage KokkosKernels to implement this approach efficiently on multicore architectures. Our performance results are competitive with the fastest known graph traversal-based approaches and are significantly faster than the Graph Challenge reference implementations, up to 670,000 times faster than the C++ reference and 10,000 times faster than the Python reference on a single Intel Haswell node.
We use ab initio molecular dynamics (AIMD) calculations and quasi-chemical theory (QCT) to study the inner-shell structure of F-(aq) and to evaluate that single-ion free energy under standard conditions. Following the "no split occupancies" rule, QCT calculations yield a free energy value of -101 kcal/mol under these conditions, in encouraging agreement with tabulated values (-111 kcal/mol). The AIMD calculations served only to guide the definition of an effective inner-shell constraint. QCT naturally includes quantum mechanical effects that can be concerning in more primitive calculations, including electronic polarizability and induction, electron density transfer, electron correlation, molecular/atomic cooperative interactions generally, molecular flexibility, and zero-point motion. No direct assessment of the contribution of dispersion contributions to the internal energies has been attempted here, however. We anticipate that other aqueous halide ions might be treated successfully with QCT, provided that the structure of the underlying statistical mechanical theory is absorbed, i.e., that the "no split occupancies" rule is recognized.
Nanosecond in situ x-ray diffraction and simultaneous velocimetry measurements were used to determine the crystal structure and pressure, respectively, of ramp-compressed aluminum at stress states between 111 and 475 GPa. The solid-solid Al phase transformations, fcc-hcp and hcp-bcc, are observed at 216±9 and 321±12 GPa, respectively, with the bcc phase persisting to 475 GPa. The high-pressure crystallographic texture of the hcp and bcc phases suggests close-packed or nearly close-packed lattice planes remain parallel through both transformations.
In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments. In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.
This paper proposes a method of enabling photovoltaic (PV) power plants to participate in primary frequency response by providing synthetic inertia (SI). This variation, referred to as communication enabled synthetic inertia (CE-SI), utilizes communication capabilities to provide global system frequency information to PV plants to emulate the inertial response of synchronous generators. The performance of CE-SI is analyzed with respect to the challenges associated with communication, such as latency and availability. Results indicate improvements in frequency response over SI using local frequency measurements when communication latency is sufficiently small.
Distribution system analysis with high penetrations of distributed energy resources (DER) requires quasi-static time-series (QSTS) analysis to capture the time-varying and time-dependent aspects of the system, but current QSTS algorithms are prohibitively burdensome and computationally intensive. This paper proposes a novel deviation-based algorithm to calculate the critical time periods when QSTS simulations should be solved at higher or lower time-resolution. This predetermined time-step (PT) solver is a new method of performing variable time-step simulations based solely on the input data. The PT solver demonstrates high accuracy while performing the simulation up to 20 times faster.
A hierarchical control algorithm was developed to utilize photovoltaic system advanced inverter volt-VAr functions to provide distribution system voltage regulation and to mitigate 10-minute average voltages outside of ANSI Range A (0.95-1.05 pu). As with any hierarchical control strategy, the success of the control requires a sufficiently fast and reliable communication infrastructure. The communication requirements for voltage regulation were tested by varying the interval at which the controller monitors and dispatches commands and evaluating the effectiveness to mitigate distribution system over-voltages. The control strategy was demonstrated to perform well for communication intervals equal to the 10-minute ANSI metric definition or faster. The communication reliability impacted the controller performance at levels of 99% and below, depending on the communication interval, where an 8-minute communication interval could be unsuccessful with an 80% reliability. The communication delay, up to 20 seconds, was too small to have an impact on the effectiveness of the communication-based hierarchical voltage control.
The response of associating polymers with oscillatory shear is studied through large-scale simulations. A hybrid molecular dynamics (MD), Monte Carlo (MC) algorithm is employed. Polymer chains are modeled as a coarse-grained bead-spring system. Functionalized end groups, at both ends of the polymer chains, can form reversible bonds according to MC rules. Stress-strain curves shownonlinearities indicated by a non-ellipsoidal shape. We consider two types of nonlinearities. Type I occurs at a strain amplitude much larger than one, type II at a frequency at which the elastic storage modulus dominates the viscous loss modulus. In this last case, the network topology resembles that of the system at rest. The reversible bonds are broken and chains stretch when the system moves away from the zero-strain position. For type I, the chains relax and the number of reversible bonds peaks when the system is near an extreme of the motion. During the movement to the other extreme of the cycle, first a stress overshoot occurs, then a yield accompanied by shear-banding. Finally, the network restructures. Interestingly, the system periodically restores bonds between the same associating groups. Even though major restructuring occurs, the system remembers previous network topologies.
Second order nonlinearity vanishes for centrosymmetric materials in the dipole approximation. For metamaterial this means second-harmonic-generation is negligible in highly symmetric meta-atoms. We show a new type of meta-atom in which the dipolar approximation breaks down.
In this paper, we present an efficient band-to-trap tunneling model based on the Schenk approach, in which an analytic density-of-states (DOS) model is developed based on the open boundary scattering method. The new model explicitly includes the effect of heterojunction band offset, in addition to the well-known field effect. Its analytic form enables straightforward implementation into TCAD device simulators. It is applicable to all one-dimensional potentials, which can be approximated to a good degree such that the approximated potentials lead to piecewise analytic wave functions with open boundary conditions. The model allows for simulating both the electric-field-enhanced and band-offset-enhanced carrier recombination due to the band-to-trap tunneling near the heterojunction in a heterojunction bipolar transistor (HBT). Simulation results of an InGaP/GaAs/GaAs NPN HBT show that the proposed model predicts significantly increased base currents, due to the hole-to-trap tunneling enhanced by the emitter-base junction band offset. Finally, the results compare favorably with experimental observation.
The family of three-dimensional topological insulators opens new avenues to discover novel photophysics and to develop novel types of photodetectors. ZrTe5 has been shown to be a Dirac semimetal possessing unique topological, electronic, and optical properties. Here, we present spatially resolved photocurrent measurements on devices made of nanoplatelets of ZrTe5, demonstrating the photothermoelectric origin of the photoresponse. Because of the high electrical conductivity and good Seebeck coefficient, we obtain noise-equivalent powers as low as 42 pW/Hz1/2, at room temperature for visible light illumination, at zero bias. We also show that these devices suffer from significant ambient reactivity, such as the formation of a Te-rich surface region driven by Zr oxidation as well as severe reactions with the metal contacts. This reactivity results in significant stresses in the devices, leading to unusual geometries that are useful for gaining insight into the photocurrent mechanisms. Our results indicate that both the large photothermoelectric response and reactivity must be considered when designing or interpreting photocurrent measurements in these systems.
Woen, David H.; Chen, Guo P.; Ziller, Joseph W.; Boyle, Timothy J.; Furche, Filipp; Evans, William J.
The first (N=N)2- complex of a rare-earth metal with an end-on dinitrogen bridge, {K(crypt)}2{[(R2N)3Sc]2[μ-η1:η1-N2]} (crypt = 2.2.2-cryptand, R = SiMe3), has been isolated from the reduction of Sc(NR2)3 under dinitrogen at -35 °C and characterized by X-ray crystallography. The structure differs from the characteristic side-on structures previously observed for over 40 crystallographically characterized rare-earth metal (N=N)2- complexes of formula [A2Ln(THF)x]2[μ- η2:η2-N2] (Ln = Sc, Y, and lanthanides; x = 0, 1; A = anionic ligand such as amide, cyclopentadienide, and aryloxide). The 1.221(3) Å N - N distance and the 1644 cm-1 Raman stretch are consistent with the presence of an (N=N)2- bridge. The observed paramagnetism of the complex by Evans method measurements is consistent with DFT calculations that suggest a triplet (3A2) ground state in D3 symmetry involving two degenerate Sc - N2 - Sc bonding orbitals. Upon brief exposure of the orange Sc3+ bridging dinitrogen complex to UV-light, photolysis to form the monomeric Sc2+ complex, [K(crypt)][Sc(NR2)3], was observed. Conversion of the Sc2+ complex to the Sc3+ dinitrogen complex was not observed with this crypt system, but it did occur with the 18-crown-6 (crown) analog which formed {K(crown)}2{[(R2N)3Sc]2[μ- η1:η1-N2]}. This suggests the importance of the alkali metal chelating agent in the reversibility of dinitrogen binding in this scandium system.
We report atomically detailed molecular dynamics simulations of the permeation of the lethal factor (LF) N-terminal segment through the anthrax channel. The N-terminal chain is unstructured and leads the permeation process for the LF protein. The simulations were conducted in explicit solvent with milestoning theory, making it possible to extract kinetic information from nanosecond to millisecond time scales. We illustrate that the initial event is strongly influenced by the protonation states of the permeating amino acids. While the N-terminal segment passes easily at high protonation state through the anthrax channel (and the φ clamp), the initial permeation represents a critical step, which can be irreversible and establishes a hook in the channel mouth.
We investigate carrier transport in silicon-germanium nanowires with an axial p-n junction doping profile by fabricating these wires into transistors that feature separate top gates over each doping segment. By independently biasing each gate, carrier concentrations in the n- and p-side of the wire can be modulated. For these devices, which were fabricated with nickel source-drain electrical contacts, holes are the dominant charge carrier, with more favorable hole injection occurring on the p-side contact. Channel current exhibits greater sensitivity to the n-side gate, and in the reverse biased source-drain configuration, current is limited by the nickel/n-side Schottky contact.
Synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.
A major challenge in the commercialization of additive manufactured (AM) materials and processes is the ability to achieve acceptance of processes and products. There has been some progress towards acceptance has been made by adapting legacy qualification paradigms to match with the very limited process control and monitoring offered by AM machines. The opportunity for in-situ measurement can provide process monitoring and control perhaps changing the way we qualify parts however it is limited by lack of adequate process measurement methods. New measurement techniques, sensors and correlations to relevant phenomena are needed that enable process control and monitoring for consistently producing high quality articles. Beyond process data we need to characterize uncertainties of performance in all aspects of material, process and final part. These are prerequisites to achieving articles that are indeed worthy of materials characterization efforts that establish a microstructural reference of desirable performance through process-structure-property relations. Only then can industry apply physics based understanding of the material, part and process to probabilistically predict performance of an AM part. Our paper provides a brief overview, discussion of hurdles and key areas where R&D investment is needed.
Here, the effect of a linear accelerator’s (LINAC’s) microstructure (i.e., train of narrow pulses) on devices and the associated transient photocurrent models are investigated. The data indicate that the photocurrent response of Si-based RF bipolar junction transistors and RF p-i-n diodes is considerably higher when taking into account the microstructure effects. Similarly, the response of diamond, SiO2, and GaAs photoconductive detectors (standard radiation diagnostics) is higher when taking into account the microstructure. This has obvious hardness assurance implications when assessing the transient response of devices because the measured photocurrent and dose rate levels could be underestimated if microstructure effects are not captured. Indeed, the rate the energy is deposited in a material during the microstructure peaks is much higher than the filtered rate which is traditionally measured. In addition, photocurrent models developed with filtered LINAC data may be inherently inaccurate if a device is able to respond to the microstructure.
Molecular simulations of the adsorption of representative organic molecules onto the basal surfaces of various clay minerals were used to assess the mechanisms of enhanced oil recovery associated with salinity changes and water flooding. Simulations at the density functional theory (DFT) and classical levels provide insights into the molecular structure, binding energy, and interfacial behavior of saturate, aromatic, and resin molecules near clay mineral surfaces. Periodic DFT calculations reveal binding geometries and ion pairing mechanisms at mineral surfaces while also providing a basis for validating the classical force field approach. Through classical molecular dynamics simulations, the influence of aqueous cations at the interface and the role of water solvation are examined to better evaluate the dynamical nature of cation-organic complexes and their coadsorption onto the clay surfaces. The extent of adsorption is controlled by the hydrophilic nature and layer charge of the clay mineral. All organic species studied showed preferential adsorption on hydrophobic mineral surfaces. However, the anionic form of the resin (decahydro-2-naphthoic acid), expected to be prevalent at near-neutral pH conditions in petroleum reservoirs, readily adsorbs to the hydrophilic kaolinite surface through a combination of cation pairing and hydrogen bonding with surface hydroxyl groups. Analysis of cation-organic pairing in both the adsorbed and desorbed states reveals a strong preference for organic anions to coordinate with divalent calcium ions rather than monovalent sodium ions, lending support to current theories regarding low-salinity water flooding.
Low-salinity water flooding, a method of enhanced oil recovery, consists of injecting low ionic strength fluids into an oil reservoir in order to detach oil from mineral surfaces in the underlying formation. Although highly successful in practice, the approach is not completely understood at the molecular scale. Molecular dynamics simulations have been used to investigate the effect of surface protonation on the adsorption of an anionic crude oil component on clay mineral edge surfaces. A set of interatomic potentials appropriate for edge simulations has been applied to the kaolinite (010) surface in contact with an aqueous nanopore. Decahydro-2-napthoic acid in its deprotonated form (DHNA-) was used as a representative resin component of crude oil, with monovalent and divalent counterions, to test the observed trends in low-salinity water flooding experiments. Surface models include fully protonated (neutral) and deprotonated (negative) edge sites, which require implementation of a new deprotonation scheme. The surface adsorptive properties of the kaolinite edge under neutral and deprotonated conditions have been investigated for low and high DHNA- concentrations with Na+ and Ca2+ as counterions. The tendency of DHNA- ions to coordinate with divalent (Ca2+) rather than monovalent (Na+) ions greatly influences adsorption tendencies of the anion. Additionally, the formation of net positively charged surface sites due to Ca2+ at deprotonated sites results in increased DHNA- adsorption. Divalent cations such as Ca2+ are able to efficiently bridge surface sites and organic anions. Replacing those cations with monovalent cations such as Na+ diminishes the bridging mechanism, resulting in reduced adsorption of the organic species. A clear trend of decreased DHNA- adsorption is observed in the simulations as Ca2+ is replaced by Na+ for deprotonated surfaces, as would be expected for oil detachment from reservoir formations following a low-salinity flooding event.
This report develops and documents linear and nonlinear constitutive relations implemented in ALEGRA-FE (ferroelectric). A thermodynamic framework is created to describe the electromechanical system in the form of a free energy functional. Constitutive relations are derived by taking series expansions of the free energy functional with respect to the independent fields. First order expansion terms yield linear constitutive relations and higher order expansion terms yield non-linear constitutive relations. This document serves as supplement to Section 4 of Sandia Report SAND2013-7363, Rev 3. Methods for implementation of kinematic relations of piezoelectric models and rotation of material principal axes are covered in the supplemented report. Additional discussion on phase velocity calculation is also presented.
James Wait was a pioneer in electromagnetic methods in geophysical exploration and wave propagation. In his career, he published more than 860 papers and wrote 8 books on subjects ranging from geo-electromagnetism to lightning. He left an undeniable mark on every subject he has tackled, and his work on layered media, propagation along thin wires and induced polarization are seminal and widely cited throughout the world.
Nanocrystals (NCs) can self-assemble into ordered superlattices with collective properties, but the ability for controlling NC assembly remains poorly understandable toward achievement of desired superlattice. This work regulates several key variables of PbS NC assembly (e.g., NC concentration and solubility, solvent type, evaporation rate, seed mediation and thermal treatment), and thoroughly exploits the nucleation and growth as well as subsequent superlattice transformation of NC assembles and underneath mechanisms. PbS NCs in toluene self-assemble into a single face-centered-cubic (fcc) and body-centered-cubic (bcc) superlattice, respectively, at concentrations ≤17.5 and ≥70 mg/mL, but an intermediate concentration between them causes the coexistence of the two superlattices. Differently, NCs in hexane or chloroform self-assemble into only a single bcc superlattice. Distinct controls of NC assembly in solvent with variable concentrations confirm the NC concentration/solubility mediated nucleation and growth of superlattice, in which an evaporation-induced local gradient of NC concentration causes simultaneous nucleation of the two superlattices. The observation for the dense packing planes of NCs in fast growing fcc rather than bcc reveals the difference of entropic driving forces responsible for the two distinct superlattices. Decelerating the solvent evaporation does not amend the superlattice symmetry, but improves the superlattice crystallinity. In addition to shrinking the superlattice volume, thermal treatment also transforms the bcc to an fcc superlattice at 175 °C. Through a seed-meditated growth, the concentration-dependent superlattice does not change lattice symmetry over the course of continuous growth, whereas the newly nucleated secondary small nuclei through a concentration change have relatively higher surface energy and quickly dissolve in solution, providing additional NC sources for the ripening of the primarily nucleated larger and stable seeds. The observations under multiple controls of assembly parameters not only provide insights into the nucleation and growth as well as transformation of various superlattice polymorphs but also lay foundation for controlled fabrication of desired superlattice with tailored property.
Aryal, Dipak; Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.
Controlling the structure and dynamics of thin films of ionizable polymers at water interfaces is critical to their many applications. As the chemical diversity within one polymer is increased, controlling the structure and dynamics of the polymer, which is a key to their use, becomes a challenge. Here molecular dynamics simulations (MD) are used to obtain molecular insight into the structure and dynamics of thin films of one such macromolecule at the interface with water. The polymer consists of an ABCBA topology with randomly sulfonated polystyrene (C), tethered symmetrically to flexible poly(ethylene-r-propylene) blocks (B), and end-capped by a poly(t-butylstyrene) block (A). The compositions of the interfacial and bulk regions of thin films of the ABCBA polymers are followed as a function of exposure time to water. We find that interfacial rearrangements take place where buried ionic segments migrate toward the water interface. The hydrophobic blocks collapse and rearrange to minimize their exposure to water. The water that initially drives interfacial reengagements breaks the ionic clusters within the film, forming a dynamic hydrophilic internal network within the hydrophobic segments.
This research presents a predictive engine that integrates into an on-line optimal control planner for electrical microgrids. This controller models the behavior of the underlying system over a specified time horizon and then solves for a control over this period. In an electrical microgrid, such predictions are challenging to obtain in the presence of errors in the sensor information. The likelihood of instrumentation errors increases as microgrids become more complex and cyber threats more common. In order to overcome these difficulties, details are provided about a predictive engine robust to errors.
A 6-mm by 6-mm by 50-mm bar of stilbene was coupled on both ends to silicon photomultipliers (SiPMs) to assess the detector's position sensitivity to interactions throughout the bar. A Na-22 gamma ray source was collimated with a pair of lead bricks to produce a source beam that was used to irradiate five positions along the length of the bar. A logarithmic relationship between the ratio of the pulse heights obtained from the two SiPMs and the position of the collimated source was established. The standard deviation of the distribution of ratios from each measurement was propagated through the functional form to determine position resolution. The position resolution along the length of the bar was determined to have an average value of 4.9 mm.
We investigate the feasibility of constructing a data-driven distance metric for use in null-hypothesis testing in the context of arms-control treaty verification. The distance metric is used in testing the hypothesis that the available data are representative of a certain object or otherwise, as opposed to binary-classification tasks studied previously. The metric, being of strictly quadratic form, is essentially computed using projections of the data onto a set of optimal vectors. These projections can be accumulated in list mode. The relatively low number of projections hampers the possible reconstruction of the object and subsequently the access to sensitive information. The projection vectors that channelize the data are optimal in capturing the Mahalanobis squared distance of the data associated with a given object under varying nuisance parameters. The vectors are also chosen such that the resulting metric is insensitive to the difference between the trusted object and another object that is deemed to contain sensitive information. Data used in this study were generated using the GEANT4 toolkit to model gamma transport using a Monte Carlo method. For numerical illustration, the methodology is applied to synthetic data obtained using custom models for plutonium inspection objects. The resulting metric based on a relatively low number of channels shows moderate agreement with the Mahalanobis distance metric for the trusted object but enabling a capability to obscure sensitive information.
Our work uses market analysis and simulation to explore the potential of public charging infrastructure to spur US battery electric vehicle (BEV) sales, increase national electrified mileage, and lower greenhouse gas (GHG) emissions. By employing both scenario and parametric analysis for policy driven injection of public charging stations we find the following: (1) For large deployments of public chargers, DC fast chargers are more effective than level 2 chargers at increasing BEV sales, increasing electrified mileage, and lowering GHG emissions, even if only one DC fast charging station can be built for every ten level 2 charging stations. (2) A national initiative to build DC fast charging infrastructure will see diminishing returns on investment at approximately 30,000 stations. (3) Some infrastructure deployment costs can be defrayed by passing them back to electric vehicle consumers, but once those costs to the consumer reach the equivalent of approximately 12¢/kWh for all miles driven, almost all gains to BEV sales and GHG emissions reductions from infrastructure construction are lost.
The discontinuous Petrov–Galerkin (DPG) methodology of Demkowicz and Gopalakrishnan (2010, 2011) guarantees the optimality of the solution in an energy norm, and provides several features facilitating adaptive schemes. A key question that has not yet been answered in general – though there are some results for Poisson, e.g.– is how best to precondition the DPG system matrix, so that iterative solvers may be used to allow solution of large-scale problems. In this paper, we detail a strategy for preconditioning the DPG system matrix using geometric multigrid which we have implemented as part of Camellia (Roberts, 2014, 2016), and demonstrate through numerical experiments its effectiveness in the context of several variational formulations. We observe that in some of our experiments, the behavior of the preconditioner is closely tied to the discrete test space enrichment. We include experiments involving adaptive meshes with hanging nodes for lid-driven cavity flow, demonstrating that the preconditioners can be applied in the context of challenging problems. We also include a scalability study demonstrating that the approach – and our implementation – scales well to many MPI ranks.
Peste des Petits Ruminants (PPR) is an infectious disease affecting goats and sheep. PPR has a mortality rate of 80% and a morbidity rate of 100% in naïve herds. This disease is currently of concern to Afghani goat and sheep herders as conditions in Afghanistan are conducive to the disease becoming an epidemic. PPR is similar to Rinderpest, but is not as well studied. There is a lack of empirical data on how the disease spreads or effective large-scale mitigation strategies. We developed a herd-level, event-driven model of PPR, using memoryless state transitions, to study how the virus propagates through a herd, and to identify effective control strategies for disparate herd configurations and environments. This model allows us to perform Sensitivity Analyses (SA) on environmental and disease parameters for which we do not have empirical data and to simulate the effectiveness of various control strategies. We find that reducing the amount of time from the identification of PPR in a herd to the vaccination of the herd will radically reduce the number of deaths that result from PPR. The goal of this model is to give policy makers a tool to develop effective containment strategies for managing outbreaks of PPR.
Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high fidelity, validated models used in modal, vibration, static and shock analysis of structural systems. This manual describes the theory behind many of the constructs in Sierra/SD. For a more detailed description of how to use Sierra/SD, we refer the reader to Sierra/SD, Users Notes. Many of the constructs in Sierra/SD are pulled directly from published material. Where possible, these materials are referenced herein. However, certain functions in Sierra/SD are specific to our implementation. We try to be far more complete in those areas. The theory manual was developed from several sources including general notes, a programmer_notes manual, the user's notes and of course the material in the open literature.
The purpose of this appendix is to provide a consistent approach for establishing the hazard category for a nuclear facility as required in 10 CFR 830, Nuclear Safety Management, Subpart B, "Safety Basis Requirements," Section 202 (b)(3). As defined, this approach is consistent with DOE-STD-1027-92 Change Notice No. 1, Hazard Categorization and Accident Analysis Techniques for Compliance with DOE Order 5480.23, Nuclear Safety Analysis Reports (hereafter DOE-STD-1027-92), and facilitates the use of updated dosimetry and release fractions as provided in NNSA SD G 1027 Admin Change 1, Guidance on Using Release Fraction and Modern Dosimetric Information Consistently with DOE STD 1027-92, Hazard Categorization and Accident Analysis Techniques for Compliance with DOE Order 5480.23, Nuclear Safety Analysis Reports, Change Notice No. 1 (hereafter NNSA SD G 1027).
National Technology & Engineering Solutions of Sandia, LLC, manages the facilities and infrastructure of Sandia National Laboratories (SNL) on behalf of the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA). Activities in support of the SNL mission take place at primary facilities located in Albuquerque, New Mexico, and Livermore, California, as well as at supporting facilities located in Nevada, Hawaii, Alaska, Texas, and Washington, D.C. As required by the Management and Operating (M&O) Contract (DE-NA0003525) and DOE orders, standards, and guidance, the M&O contractor maintain a safety basis process, which helps to identify and evaluate hazards related to facilities, operations, and activities at both Sandia-controlled premises (i.e., onsite) and non-Sandia-controlled premises (i.e., offsite) to adequately protect workers, the public, and the environment. This manual describes the SNL safety basis process, which is managed by the Environment, Safety, and Health (ES&H) Planning Department. Safety basis personnel ensure that a centralized and consistent process is implemented for safety basis development, documentation, and evaluation.
The noise performance of infrared detectors can be improved through utilization of thinner detector layers which reduces thermal and generation-recombination noise currents. However, some infrared detector materials suffer from weak optical absorption and thinning the detector layer can lead to incomplete absorption of the incoming infrared photons which reduces detector quantum efficiency. Here, we show how subwavelength metallic nanoantennas can be used to boost the efficiency of photon absorption for thin detector layers, thereby achieving overall enhanced detector performance.
Electrochemistry is necessarily a science of interfacial processes, and understanding electrode/electrolyte interfaces is essential to controlling electrochemical performance and stability. Undesirable interfacial interactions hinder discovery and development of rational materials combinations. By example, we examine an electrolyte, magnesium(II) bis(trifluoromethanesulfonyl)imide (Mg(TFSI)2) dissolved in diglyme, next to the Mg metal anode, which is purported to have a wide window of electrochemical stability. However, even in the absence of any bias, using in situ tender X-ray photoelectron spectroscopy, we discovered an intrinsic interfacial chemical instability of both the solvent and salt, further explained using first-principles calculations as driven by Mg2+ dication chelation and nucleophilic attack by hydroxide ions. The proposed mechanism appears general to the chemistry near or on metal surfaces in hygroscopic environments with chelation of hard cations and indicates possible synthetic strategies to overcome chemical instability within this class of electrolytes.
The Chemistry Science Investigation: Dognapping Workshop was designed to (i) target and inspire fourth grade students to view themselves as Junior Scientists before their career decisions are solidified; (ii) enable hands-on experience in fundamental scientific concepts; (iii) increase public interaction with science, technology, engineering, and mathematical personnel by providing face-to-face opportunities; (iv) give teachers a pathway forward for scientific resources; (v) meet the New Mexico K-5 Science Benchmark Performance Standards; (vi) most importantly, ensure everyone has fun! For this workshop, the students are told they will be going to see a Chemistry Magic Show, but the performance is stopped when the Chemistry Dog is reportedly stolen. The students first clear their names using a series of interactive stations and then apply a number of science experiments to solve the mystery. This report describes the workshop in detail, which is suitable for large (100 students per day) audiences but has flexibility to be modified for much smaller groups. An identical survey was given three times (before, immediately after, and 2 months after the workshop) to determine the impact on the students' perception of science and scientists as well as determine the effectiveness in relaying scientific concepts through retention time. Survey responses indicate that scientific information pertaining to the workshop is retained for up to 2 months.
In situ neutron diffraction measurements were completed for this study during tensile and compressive deformation of stainless steel 304L additively manufactured (AM) using a high power directed energy deposition process. Traditionally produced wrought 304L material was also studied for comparison. The AM material exhibited roughly 200 MPa higher flow stress relative to the wrought material. Crystallite size, crystallographic texture, dislocation density, and lattice strains were all characterized to understand the differences in the macroscopic mechanical behavior. The AM material’s initial dislocation density was about 10 times that of the wrought material, and the flow strength of both materials obeyed the Taylor equation, indicating that the AM material’s increased yield strength was primarily due to greater dislocation density. Finally, a ~50 MPa flow strength tension/compression asymmetry was observed in the AM material, and several potential causes were examined.
Glick, Joseph A.; Khasawneh, Mazin A.; Niedzielski, Bethany M.; Loloee, Reza; Pratt, W.P.; Birge, Norman O.; Gingrich, E.C.; Kotula, Paul G.; Missert, Nancy A.
Josephson junctions containing ferromagnetic layers are of considerable interest for the development of practical cryogenic memory and superconducting qubits. Such junctions exhibit a ground-state phase shift of π for certain ranges of ferromagnetic layer thicknesses. We present studies of Nb based micron-scale elliptically shaped Josephson junctions containing ferromagnetic barriers of Ni81Fe19 or Ni65Fe15Co20. By applying an external magnetic field, the critical current of the junctions is found to follow characteristic Fraunhofer patterns and display sharp switching behavior suggestive of single-domain magnets. The high quality of the Fraunhofer patterns enables us to extract the maximum value of the critical current even when the peak is shifted significantly outside the range of the data due to the magnetic moment of the ferromagnetic layer. The maximum value of the critical current oscillates as a function of the ferromagnetic barrier thickness, indicating transitions in the phase difference across the junction between values of zero and π. We compare the data to previous work and to models of the 0-π transitions based on existing theories.
Solar photovoltaic systems provide cost savings to the property owner in terms of avoided electricity costs that accrue over the system lifetime. From an investment standpoint, the equipment and the value of the energy generated can potentially increase the underlying property value. This first-of-a-kind study presents real market data collected from real estate appraisers using the PV Value® tool to develop a market value for solar as part of a property sale or refinance. Aggregated results at the state level are discussed for California, Arizona and Massachusetts, using 2015 and 2016 data where appraisers used the income capitalization approach to develop a market value for solar. Additional data collection using future transaction data could reveal market-specific trends and insights at the zip code, city and metropolitan statistical area (MSA) levels.
One of the major challenges of simulating flow and transport in the far field of a geologic repository in crystalline host rock is related to reproducing the properties of the fracture network over the large volume of rock with sparse fracture characterization data. Various approaches have been developed to simulate flow and transport through the fractured rock. The approaches can be broadly divided into Discrete Fracture Network (DFN) and Equivalent Continuum Model (ECM). The DFN explicitly represents individual fractures, while the ECM uses fracture properties to determine equivalent continuum parameters. We compare DFN and ECM in terms of upscaled observed transport properties through generic fracture networks. The major effort was directed on making the DFN and ECM approaches similar in their conceptual representations. This allows for separating differences related to the interpretation of the test conditions and parameters from the differences between the DFN and ECM approaches. The two models are compared using a benchmark test problem that is constructed to represent the far field (1 × 1 × 1 km3) of a hypothetical repository in fractured crystalline rock. The test problem setting uses generic fracture properties that can be expected in crystalline rocks. The models are compared in terms of the: 1) effective permeability of the domain, and 2) nonreactive solute breakthrough curves through the domain. The principal differences between the models are mesh size, network connectivity, matrix diffusion and anisotropy. We demonstrate how these differences affect the flow and transport. We identify the factors that should be taken in consideration when selecting an approach most suitable for the site-specific conditions.
Cubic zirconium tungstate (α-ZrW2O8), a notorious negative thermal expansion (NTE) material, has been investigated within the framework of density functional perturbation theory (DFPT), combined with experimental characterization to assess and validate computational results. Spectroscopic, mechanical and thermodynamic properties have been derived from DFPT calculations. A systematic comparison of DFPT-simulated infrared, Raman, and phonon density-of-state spectra with Fourier transform far-/mid-infrared and Raman data collected in this study, as well as with available inelastic neutron scattering measurements, shows the supe-rior accuracy of the PBEsol exchange-correlation functional over standard PBE calculations. The thermal evolution of the Grüneisen parameter computed within the quasi-harmonic approximation exhibits negative values below the Debye temperature, consistent with the observed NTE characteristics of α-ZrW2O8. The standard molar heat capacity is predicted to be C$0\atop{P}$=193.8 and 192.2 J.mol-1.K-1 with PBE and PBEsol, respectively, ca. 7% lower than calorimetric data. In conclusion, these results demonstrate the accuracy of the DFPT/PBEsol approach for studying the spectroscopic, mechanical and thermodynamic properties of materials with anomalous thermal expansion.
Directed energy deposition (DED) and forged austenitic stainless steels possess distinct microstructures, but may exhibit similar mechanical properties. In this study, annealing is used to evolve the microstructures of these materials, and scanning electron microscopy techniques are used to probe the similarities and differences of the microstructure-property relationships. A strong correlation between geometrically necessary dislocation (GND) density and hardness is observed for the forged material. Finally, a more complex relationship is observed in the DED material and is attributed to the thermally driven dissolution of the solidification microstructure.
Woven fiber, laminated composites allow the design engineer to create high strength parts, but the effectiveness of the final processed part is greatly diminished through weak or nonexistent bonds between the composite and the substrate to which it is bonded. Additionally, these layered laminates are commonly made by curing the resin infused carbon fiber fabrics in predefined layers and then bonding them to another composite or a metallic structure using either a pre-cure or a co-cure method. The focus of this study is the identification of the defect caused by a disbond or a delamination located at the interface between a composite laminate stack and the substrate to which it is bonded. We present a nondestructive approach using various ultrasonic methods to identify the existence of the bond between composite and composite-to-metal interface. This paper explores contact and immersion ultrasound methods using pulse-echo for evaluating the composite material and adhesive bondline and the signal attenuation undergone by the wave as it propagates through the composite. Finally, a summary of the detection and analysis techniques developed to identify disbonds, including Fast Fourier Transform analysis of the immersion data, is presented. Lastly, each of the methods evaluated in this study is able to detect the transition from bonded to unbonded sections at the bondline from either side of the bonded part, with the immersion technique providing a significantly higher resolution of the edge of the bondline.
Aerosol Deposition (AD) is a unique thick film deposition technology that is capable of depositing ceramic, metallic, or composite films through the acceleration, impact and consolidation of dry, fine sized (~0.1-1μm) particle feedstock delivered by a carrier gas towards a substrate [akedo]. Additionally, the use of fine particle feedstock is necessary in order for typically brittle materials (i.e., ceramics) to exhibit sufficient plasticity and non-brittle fracturing that is the key mechanism to coating consolidation [Sarobol], resulting in a dense, nano-crystalline grain size deposition.
Titanium alloys such as Ti-6Al-4V and Ti-6Al-7Nb are widely used in the biomedical industry as structural implant materials. The strain-rate sensitivity of tensile strength is now assessed using a modified Kocks-Mecking formulation for hardening. The operative scale of the microstructural strengthening is designated by the coefficieint cb that can be determined from measurements of plastic strain, yield and ultimate strength. It is found that although that strength varies slightly with strain rate, the scale of the microstructure cb remains nearly constant for each material. Finally, a low cb-value of 14 is computed for Ti-6Al-4V that is consistent with the refined twophase microstructure needed to enhance both ductility beyond yielding and its ultimate strength.
In this study, we have made reasonable cookoff predictions of large-scale explosive systems by using pressure-dependent kinetics determined from small-scale experiments. Scale-up is determined by properly accounting for pressure generated from gaseous decomposition products and the volume that these reactive gases occupy, e.g. trapped within the explosive, the system, or vented. The pressure effect on the decomposition rates has been determined for different explosives by using both vented and sealed experiments at low densities. Low-density explosives are usually permeable to decomposition gases and can be used in both vented and sealed configurations to determine pressure-dependent reaction rates. In contrast, explosives that are near the theoretical maximum density (TMD) are not as permeable to decomposition gases, and pressure-dependent kinetics are difficult to determine. Ignition in explosives at high densities can be predicted by using pressure-dependent rates determined from the low-density experiments as long as gas volume changes associated with bulk thermal expansion are also considered. In the current work, cookoff of the plastic-bonded explosives PBX 9501 and PBX 9502 is reviewed and new experimental work on LX-14 is presented. Reactive gases are formed inside these heated explosives causing large internal pressures. The pressure is released differently for each of these explosives. For PBX 9501, permeability is increased and internal pressure is relieved as the nitroplasticizer melts and decomposes. Internal pressure in PBX 9502 is relieved as the material is damaged by cracks and spalling. For LX-14, internal pressure is not relieved until the explosive thermally ignites. The current paper is an extension of work presented at the 26th ICDERS symposium [1].
Abuse tests are designed to determine the safe operating limits of HEV\PHEV energy storage devices. Testing is intended to achieve certain worst-case scenarios to yield quantitative data on cell\module\pack response, allowing for failure mode determination and guiding developers toward improved materials and designs. Standard abuse tests with defined start and end conditions are performed on all devices to provide comparison between technologies. New tests and protocols are developed and evaluated to more closely simulate real-world failure conditions. When scaling from cell to the battery level, a detailed understanding of cell interactions provides insight on safety performance. Single point failures from a cell or group of cells can be initiated by a number of triggers including internal short circuit, misuse or abuse, or component failure at the battery or system level. Propagation of a single failure event (regardless of the initiation trigger) through an entire battery, system, or vehicle is an unacceptable outcome with regards to EV battery safety. In this FY, our work has focused on evaluating the propagation of a single cell thermal runaway event through a battery using a variety of design considerations with an emphasis on passive thermal management impacts. This has been coupled with thermal modeling by NREL for these testing conditions. In addition, alternative failure initiation methods have been evaluated to provide direct comparisons of possible energy injection between modes. This data was compiled to better identify what propagation test method is appropriate given certain battery designs. Expanding the analysis of short circuit current during failure propagation has been done for EV relevant chemistries. Ongoing test development and validation to obtain these values has been achieved. While robust mechanical models for vehicles and vehicle components exist, there is a gap for mechanical modeling of EV batteries. The challenge with developing a mechanical model for a battery is the heterogeneous nature of the materials and components (polymers, metals, metal oxides, liquids). Our work will provide empirical data on the mechanical behavior of batteries under compressive load to understand how a battery may behave in a vehicle crash scenario. This work is performed in collaboration with the U.S. Council for Automotive Research (USCAR) and Computer Aided Engineering of Batteries (CAEBAT). These programs have supported the design and development of a drop tower testing apparatus to close the gap between cell/string level testing and full scale crash testing with true dynamic rate effects.
Miljkovic, Nenad; Pilawa-Podgurski, Robert; Foulkes, Thomas; Oh, Junho; Birbarah, Patrick; Neely, Jason C.
Demand for enhanced cooling technologies within various commercial and consumer applications has increased in recent decades due to electronic devices becoming more energy dense. This study demonstrates jumping-droplet based electric-field-enhanced (EFE) condensation as a potential method to achieve active hot spot cooling in electronic devices. To test the viability of EFE condensation, we developed an experimental setup to remove heat via droplet evaporation from single and multiple high power gallium nitride (GaN) transistors acting as local hot spots (4.6 mm x 2.6 mm). An externally powered circuit was developed to direct jumping droplets from a copper oxide (CuO) nanostructured superhydrophobic surface to the transistor hot spots by applying electric fields between the condensing surface and the transistor. Heat transfer measurements were performed in ambient air (22-25°C air temperature, 20-45% relative humidity) to determine the effects of gap spacing (2-4 mm), electric field (50-250 V/cm), and heat flux (demonstrated to 13 W/cm2). EFE condensation was shown to enhance the heat transfer from the local hot spot by ≈ 200% compared to cooling without jumping and by 20% compared to non-EFE jumping. Dynamic switching of the electric field for a two-GaN system reveals the potential for active cooling of mobile hot spots. The opportunity for further cooling enhancement by the removal of non-condensable gases promises hot spot heat dissipation rates approaching 120 W/cm2. This work provides a framework for the development of active jumping droplet based vapor chambers and heat pipes capable of spatial and temporal thermal dissipation control.
One of the largest transitions in the power system today is the shift to a more sustainable and resilient power system. This is being driven by public opinion, changes in regulatory policies, and advancements in smart grid technologies. The most noticeable changes taking place is the integration of distributed energy sources (DERs); this study uses the term DER in the most general way as a resource that can be manipulated to alter energy delivery and flow in the transmission and distribution networks. Also, here it is preferred to focus on energy as the true need while power is a function of the equipment rating. As such, wind and solar, demand that can be manipulated, electric vehicles, electric energy storage, thermal storage, and storage in water system are all considered DERs. These additions to the distribution system are evolving the operation of distribution feeders into microgrids- communication, computing, and control-enabled resources that produce, transport, and utilize energy in a manner that provides cost, reliability, and resilience benefits. As this evolution progresses, the planning and operational management (scheduling and control) must explicitly include the consideration of risk. The management of system risk is currently in the purview of the utility and will likely remain so in the future. However, as each microgrid, as well as federation of microgrids, sees autonomy in order to provide maximum benefits to their constituents, they must assume responsibility to manage their internal risk. The primary scope of this study is the scheduling of resources in a distribution feeder(s) operating as microgrids. The study explores a distribution algorithm to develop the transactive schedule for the DERs, to minimize cost and risk over a time horizon, and an initial laboratory-scale to conduct implementation on distributed hardware. Results from case studies are presented that show that solutions derived by the distributed algorithm are valid. This study also discusses the continuing work on the expansion of: 1) the distributed algorithm from a deterministic to stochastic optimization formulation, and 2) implementation of the distributed algorithm into real-time simulation within the Power System laboratory at New Mexico State University (NMSU) and expanding to the Southwest Technology Development Institute located at NMSU where actual solar, energy storage, and demand response resources are installed.
This report describes the application of an approach for determining grid modernization investments that can best improve the resilience of communities. Under the direction of the US Department of Energy's Grid Modernization Laboratory Consortium, Sandia National Laboratories (Sandia) and Los Alamos National Laboratory (Los Alamos) collaborated with community stakeholders in New Orleans, Louisiana on grid modernization strategies for resilience. Past disruptions to the electric grid in New Orleans have contributed to an inability to provide citizens with adequate access to a wide range of infrastructure services. Using a performance-based resilience metric, Sandia and Los Alamos performed analysis on how to improve access to infrastructure services across New Orleans after a major disruption using a system of resilience nodes. Resilience nodes rely on a combination of urban planning with grid investment planning for resilience in order to design clustered infrastructure assets with highly resilient electrical supply. Results of the analysis led to suggestion of 22 draft resilience node locations that can provide a wide range of infrastructure services equitably to New Orleans citizens. This report serves as a proof-of-concept for the Urban Resilience Planning Process, and describes several gaps that should be overcome in order to integrate resilience planning between electric utilities and local governments.
This report summarizes the activities that Sandia National Laboratories undertook in support of the Si anode Fundamentals program managed by the Vehicle Technology Office of the Department of Energy. The program is led by the National Renewable Energy Laboratory, and Sandia is one of four laboratories (including Oak Ridge National Laboratories and Berkeley National Laboratories) included in the program. The initial set of activities included establishing the baseline protocols for cell assembly and testing, and executing a number of round robin style tests to compare data collected under nominally identical conditions at each of the participating laboratories to ensure that similar results were obtained and that no extraneous secondary factors were affecting the results. Because the nature of the interface between electrode and electrolyte was in question, as well as how the interface evolved over time and electrochemical cycling, an effort to build “model” interfaces based upon previously observed lithium silicate structures within the native film.
Materials that incorporate hydrogen and helium isotopes are of great interest at Sandia. The Ion Beam Lab at SNL-NM has invented techniques using micron to mm-size MeV ion beams to recoil these light isotopes (Elastic Recoil Detection or ERD) that can very accurately make such measurements. However, there are many measurements that would benefit NW and DOE that require much better resolution. To address these and many other issues, this LDRD demonstrated that neutral H atoms could be recoiled through a thin film by 70 keV electrons and detected with a Channeltron electron multiplier (CEM). The electrons were steered away from the CEM by strong permanent magnets. This proved the feasibility that the high energy electrons from a transmission-electron-microscope-TEM can potentially be used to recoil and subsequently detect (e-ERD), quantify and map the concentration of H and He isotopes with nm resolution.
This the final report of the LDRD project entitled "Realizing the Power of Near-Term Quantum Technologies", which was tasked with laying a theoretical foundation and computational framework for quantum simulation on quantum devices, to support both future Sandia efforts and the broader academic research effort in this area. The unifying theme of the project has been the desire to delineate more clearly the interface between existent classical computing resources that are vast and reliable with emerging quantum computing resources that will be scarce and unreliable for the foreseeable future. We seek to utilize classical computing resources to judge the efficacy of quantum devices for quantum simulation tasks and determine when they exceed the performance of classical devices, thereby achieving "quantum supremacy". This task was initially pursued by adapting the general concept of "parameter space compression" to quantum simulation. An inability to scale this analysis efficiently to large-scale simulations precipitated a shift in focus to assessing quantum supremacy of a specific quantum device, a 1D Bose gas trapped in an optical lattice, that was more amenable to large-scale analysis. We also seek to reconstruct unobserved information from limited observations of a quantum device to enhance their utility. This task was initially pursued as an application of maximum entropy reconstruction. Initial attempts to improve entropy approximations for direct reconstruction by free energy minimization proved to be more difficult than expected, and the focus shifted to the development of a quantum thermostat to facilitate indirect reconstruction by evolving a quantum Markov process. An efficient quantum thermostat is broadly useful for quantum state preparation in almost any quantum simulation task. In the middle of the project, a small opportunistic investment was made in a high-risk experiment to build an analog quantum simulator out of hole quantum dots in Ge/SiGe heterostructures. While a useful simulator was not produced, hole quantum dots at a Ge/SiGe interface have been successfully observed for the first time.
Several jurisdictions with critical tunnel infrastructure have expressed the need to understand the risks and implications of traffic incidents in tunnels involving hydrogen fuel cell vehicles. A risk analysis was performed to estimate what scenarios were most likely to occur in the event of a crash. The results show that the most likely consequence is no additional hazard from the hydrogen, although some factors need additional data and study to validate. This includes minor crashes and scenarios with no release or ignition. When the hydrogen does ignite, it is most likely a jet flame from the pressure relief device release due to a hydrocarbon fire. This scenario was considered in detailed modeling of specific tunnel configurations, as well as discussion of consequence concerns from the Massachusetts Department of Transportation. Localized concrete spalling may result where the jet flame impinges the ceiling, but this is not expected to occur with ventilation. Structural epoxy remains well below the degradation temperature. The total stress on the steel structure was significantly lower than the yield stress of stainless steel at the maximum steel temperature even when the ventilation was not operational. As a result, the steel structure will not be compromised. It is important to note that the study took a conservative approach in several factors, so observed temperatures should be lower than predicted by the models.
The proposed use of the subject property is for the purpose of adding a parking lot to serve the increase in customer vehicles that is occurring as the 9940 Main Complex is more heavily utilized, and as the 2009 Expansion areas come online as operational training facilities. The subject property would be used only for parking, not for testing or training activities. The parking lot would have a gravel surface. Current and future work at the 9940 Main Complex involves arming, fuzing, and firing of explosives and the testing of explosive systems components in both terrestrial and aquatic settings. It also involves specialized training activities for a variety of first responder customers, both DOE and non-DOE agencies.
An assessment of two methodologies used at Sandia National Laboratories to model mechanical interfaces is performed on the Ministack finite element model. One method uses solid mechanics models to model contacting surfaces with Coulomb frictional contact to capture the physics. The other, termed the structural dynamics reduced order model, models the interface with a simplified whole joint model using four-parameter Iwan elements. The solid mechanics model resolves local kinematics at the interface while the simplified structural dynamics model is significantly faster to simulate. One of the current challenges to using the whole joint model is that it requires calibration to data. A novel approach is developed to calibrate the reduced structural dynamics model using data from the solid mechanics model to match the global dynamics of the system. This is achieved by calibrating to amplitude dependent frequency and damping of the system modes, which are estimated using three different approaches.
Ehrmann, Robert S.; Wilcox, Benjamin; White, Edward B.; Maniaci, David C.
Wind farm operators observe production deficits as machines age. Quantifying deterioration on individual components is difficult, but one potential explanation is accumulation of blade surface roughness. Historically, wind turbine airfoils were designed for lift to be insensitive to roughness by simulating roughness with trip strips. However, roughness was still shown to negatively affect performance. Furthermore, experiments illustrated distributed roughness is not properly simulated by trip strips. To understand how real-world roughness affects performance, field measurements of turbine-blade roughness were made and simulated on a NACA 633-418 airfoil in a wind tunnel. Insect roughness and paint chips were characterized and recreated as distributed roughness and a forward-facing step. Distributed roughness was tested in three heights and five density configurations. The model chord Reynolds number was varied between 0.8 to 4.8 x 106. Measurements of lift, drag, pitching moment, and boundary-layer transition were completed. Results indicate minimal effect from paint-chip roughness. As distributed roughness height and density increase, lift-curve slope, maximum lift, and lift-to-drag ratio decrease. As Reynolds number increases, bypass transition occurs earlier. The critical roughness Reynolds number varies between 178 to 318, within the historical range. Little sensitivity to pressure gradient is observed. At a chord Reynolds number of 3.2 x 106, the maximum lift-to-drag ratio decreases 40% for 140 m roughness, corresponding to a 2.3% loss in annual energy production. Simulated performance loss compares well to measured performance loss on an in-service wind turbine.