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Detecting hidden transient events in noisy nonlinear time-series

Chaos

Montoya, Angela C.; Habtour, E.; Moreu, F.

The information impulse function (IIF), running Variance, and local Hölder Exponent are three conceptually different time-series evaluation techniques. These techniques examine time-series for local changes in information content, statistical variation, and point-wise smoothness, respectively. Using simulated data emulating a randomly excited nonlinear dynamical system, this study interrogates the utility of each method to correctly differentiate a transient event from the background while simultaneously locating it in time. Computational experiments are designed and conducted to evaluate the efficacy of each technique by varying pulse size, time location, and noise level in time-series. Our findings reveal that, in most cases, the first instance of a transient event is more easily observed with the information-based approach of IIF than with the Variance and local Hölder Exponent methods. While our study highlights the unique strengths of each technique, the results suggest that very robust and reliable event detection for nonlinear systems producing noisy time-series data can be obtained by incorporating the IIF into the analysis.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Magnesium- and intermetallic alloys-based hydrides for energy storage: Modelling, synthesis and properties

Progress in Energy

Pasquini, Luca; Sakaki, Kouji; Akiba, Etsuo; Allendorf, Mark; Alvares, Ebert; Ares, Jose R.; Babai, Dotan; Baricco, Marcello; Bellosta Von Colbe, Jose; Bereznitsky, Matvey; Buckley, Craig E.; Cho, Young W.; Cuevas, Fermin; De Rango, Patricia; Dematteis, Erika M.; Denys, Roman V.; Dornheim, Martin; Fernandez, J.F.; Hariyadi, Arif; Hauback, Bjorn C.; Heo, Tae W.; Hirscher, Michael; Humphries, Terry D.; Huot, Jacques; Jacob, Isaac; Jensen, Torben R.; Jerabek, Paul; Kang, Shin Y.; Keilbart, Nathan; Kim, Hyunjeong; Latroche, Michel; Leardini, F.; Li, Haiwen; Ling, Sanliang; Lototskyy, Mykhaylo V.; Mullen, Ryan; Orimo, Shin I.; Pistidda, Claudio; Polanski, Marek; Puszkiel, Julian; Rabkin, Eugen; Sahlberg, Martin; Sartori, Sabrina; Santhosh, Archa; Sato, Toyoto; Shneck, Roni Z.; Sorby, Magnus H.; Shang, Yuanyuan; Stavila, Vitalie; Suh, Jin Y.; Suwarno, Suwarno; Le Thi ThuLe T.; Wan, Liwen F.; Webb, Colin J.; Witman, Matthew D.; Wan, Chubin; Wood, Brandon C.; Yartys, Volodymyr A.

Hydrides based on magnesium and intermetallic compounds provide a viable solution to the challenge of energy storage from renewable sources, thanks to their ability to absorb and desorb hydrogen in a reversible way with a proper tuning of pressure and temperature conditions. Therefore, they are expected to play an important role in the clean energy transition and in the deployment of hydrogen as an efficient energy vector. This review, by experts of Task 40 'Energy Storage and Conversion based on Hydrogen' of the Hydrogen Technology Collaboration Programme of the International Energy Agency, reports on the latest activities of the working group 'Magnesium- and Intermetallic alloys-based Hydrides for Energy Storage'. The following topics are covered by the review: multiscale modelling of hydrides and hydrogen sorption mechanisms; synthesis and processing techniques; catalysts for hydrogen sorption in Mg; Mg-based nanostructures and new compounds; hydrides based on intermetallic TiFe alloys, high entropy alloys, Laves phases, and Pd-containing alloys. Finally, an outlook is presented on current worldwide investments and future research directions for hydrogen-based energy storage.

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TYPE Journal Article YEAR 2022
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Classification of Intensity Distributions of Transmission Eigenchannels of Disordered Nanophotonic Structures Using Machine Learning

Applied Sciences (Switzerland)

Sarma, Raktim S.; Pribisova, Abigail; Sumner, Bjorn; Briscoe, Jayson

Light-matter interaction optimization in complex nanophotonic structures is a critical step towards the tailored performance of photonic devices. The increasing complexity of such systems requires new optimization strategies beyond intuitive methods. For example, in disordered photonic structures, the spatial distribution of energy densities has large random fluctuations due to the interference of multiply scattered electromagnetic waves, even though the statistically averaged spatial profiles of the transmission eigenchannels are universal. Classification of these eigenchannels for a single configuration based on visualization of intensity distributions is difficult. However, successful classification could provide vital information about disordered nanophotonic structures. Emerging methods in machine learning have enabled new investigations into optimized photonic structures. In this work, we combine intensity distributions of the transmission eigenchannels and the transmitted speckle-like intensity patterns to classify the eigenchannels of a single configuration of disordered photonic structures using machine learning techniques. Specifically, we leverage supervised learning methods, such as decision trees and fully connected neural networks, to achieve classification of these transmission eigenchannels based on their intensity distributions with an accuracy greater than 99%, even with a dataset including photonic devices of various disorder strengths. Simultaneous classification of the transmission eigenchannels and the relative disorder strength of the nanophotonic structure is also possible. Our results open new directions for machine learning assisted speckle-based metrology and demonstrate a novel approach to classifying nanophotonic structures based on their electromagnetic field distributions. These insights can be of paramount importance for optimizing light-matter interactions at the nanoscale.

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TYPE Journal Article YEAR 2022
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Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1

Geoscientific Model Development

Xu, Donghui; Bisht, Gautam; Sargsyan, Khachik; Liao, Chang; Ruby Leung, L.

Runoff is a critical component of the terrestrial water cycle, and Earth system models (ESMs) are essential tools to study its spatiotemporal variability. Runoff schemes in ESMs typically include many parameters so that model calibration is necessary to improve the accuracy of simulated runoff. However, runoff calibration at a global scale is challenging because of the high computational cost and the lack of reliable observational datasets. In this study, we calibrated 11 runoff relevant parameters in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) using a surrogate-assisted Bayesian framework. First, the polynomial chaos expansion machinery with Bayesian compressed sensing is used to construct computationally inexpensive surrogate models for ELM-simulated runoff at 0.5 × 0.5 for 1991-2010. The error metric between the ELM simulations and the benchmark data is selected to construct the surrogates, which facilitates efficient calibration and avoids the more conventional, but challenging, construction of high-dimensional surrogates for the ELM simulated runoff. Second, the Sobol' index sensitivity analysis is performed using the surrogate models to identify the most sensitive parameters, and our results show that, in most regions, ELM-simulated runoff is strongly sensitive to 3 of the 11 uncertain parameters. Third, a Bayesian method is used to infer the optimal values of the most sensitive parameters using an observation-based global runoff dataset as the benchmark. Our results show that model performance is significantly improved with the inferred parameter values. Although the parametric uncertainty of simulated runoff is reduced after the parameter inference, it remains comparable to the multimodel ensemble uncertainty represented by the global hydrological models in ISMIP2a. Additionally, the annual global runoff trend during the simulation period is not well constrained by the inferred parameter values, suggesting the importance of including parametric uncertainty in future runoff projections.

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TYPE Journal Article YEAR 2022
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Evaluation of Binders and Plasticizers in Kollidon VA 64-PEG Binder Systems

Colletti, Catherine A.; Neuman, Eric W.

The binders, plasticizers, and dispersants in a polyvinylpyrrolidone/polyethylene glycol/glycerin binder system for PZT were evaluated. Kollidon VA 64 was investigated as a possible alternative binder to Kollidon 25 in a PZT powder system. The target amount of PEG300 in a Kollidon VA 64 system was predicted to be 15 to 30 wt.% PEG300 based on Tganalysis by DSC. The compaction properties (slide coefficient, cohesiveness, green strength, etc.) were analyzed for Kollidon VA 64 – x PEG300 – glycerin systems. The properties in the range of x = 0 to 20 for systems without glycerin and x = 5 to 20 for systems with glycerin all exceeded the performance of the baseline Kollidon 25 system, of which VA 64 – 10 wt.% PEG300 – 5 wt.% glycerin with adsorbed moisture was the most promising composition due to a compact cohesiveness of 0.84 at 40 kpsi compared to a baseline of 0.44. The effect of dispersants on the compaction properties of a Kollidon 25 – PEG300 binder system was also analyzed, and the compaction properties were also compared to that of a Aquazol 200 – PEG6000 binder system. The powders with dispersant exhibited comparabl e per formance to the baseline, suggesting good compatibility. The compacts produce with the Aquazol 200 – PEG6000 binder exhibited decreased performance when compared to the baseline .

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TYPE SAND Report YEAR 2022
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Ensuring a Nuclear Power Plant Safe State Following an EMP Event - Task 7 Deliverable: EMP Testing of Secondary Coupling to Instrumentation Cables

Bowman, Tyler C.; Guttromson, Ross; San Martin, Luis

Sandia National Laboratories performed tests to address the potential vulnerability concerns of a coupled High-Altitude Electromagnetic Pulse (HEMP) inducing secondary coupling onto critical instrumentation and control cables in a nuclear power plant, with specific focus on early-time HEMP. Three types of receiving cables in nine configurations were tested to determine transfer functions between two electrically separated cables referenced to the common mode input current on the transmitting cable. One type of transfer function related the input short circuit current and resulting open circuit voltage on the receiving cable. The other transfer function related the input short circuit current and the resulting short circuit current on the receiving cable. A 500 A standard HEMP waveform was input into the transfer functions to calculate peak coupling values on the receiving cables. The highest level of coupling using the standard waveform occurred when cables were in direct contact, with a peak short circuit current of 85 A and open circuit voltage of 9.8 kV, while configurations with separated cables predicted coupling levels of less than 5 A or 500 V.

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TYPE SAND Report YEAR 2022
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Global wave energy resource classification system for regional energy planning and project development

Renewable and Sustainable Energy Reviews

Ahn, Seongho; Neary, Vincent S.; Haas, Kevin A.

Efforts to streamline and codify wave energy resource characterization and assessment for regional energy planning and wave energy converter (WEC) project development have motivated the recent development of resource classification systems. Given the unique interplay between WEC absorption and resource attributes, viz, available wave power frequency, directionality, and seasonality, various consensus resource classification metrics have been introduced. However, the main international standards body for the wave energy industry has not reached consensus on a wave energy resource classification system designed with clear goals to facilitate resource assessment, regional energy planning, project site selection, project feasibility studies, and selection of WEC concepts or archetypes that are most suitable for a given wave energy climate. A primary consideration of wave energy generation is the available energy that can be captured by WECs with different resonant frequency and directional bandwidths. Therefore, the proposed classification system considers combinations of three different wave power classifications: the total wave power, the frequency-constrained wave power, and the frequency-directionally constrained wave power. The dominant wave period bands containing the most wave power are sub-classification parameters that provide useful information for designing frequency and directionally constrained WECs. The bulk of the global wave energy resource is divided into just 22 resource classes representing distinct wave energy climates that could serve as a common language and reference framework for wave energy resource assessment if codified within international standards.

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TYPE Journal Article YEAR 2022
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Soot and PAH formation in high pressure spray pyrolysis of gasoline and diesel fuels

Combustion and Flame

Wan, Kevin; Manin, Julien L.; Sim, Hyung S.; Karathanassis, Ioannis

Time-resolved soot and PAH formation from gasoline and diesel spray pyrolysis are visualized and quantified using diffuse back illumination (DBI) and laser induced fluorescence (LIF) at 355 nm, respectively, in a constant-volume vessel at 60 bar from 1400 to 1700 K for up to 30 ms. The delay, maximum formation rate, and yield of soot and PAHs are compared across fuels and temperatures and correlated with the yield sooting indices on either the mass or mole basis. The delays generally decrease with increasing temperature, and the formation rates of both PAHs and soot generally increase with temperature. The apparent PAH-LIF yield may decrease with temperature due to PAH growth and conversion into larger species, signal trapping, and thermal quneching. Soot yield generally increases with temperature. The mass-based YSI correlates reasonably well with soot delay, but YSI does not correlate well with soot yield. The mass-based YSI is a more appropriate predictor of sooting propensity than the mole-based YSI.

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TYPE Journal Article YEAR 2022
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Solid particulate mass and number from ducted fuel injection in an optically accessible diesel engine in skip-fired operation

International Journal of Engine Research

Wilmer, Brady M.; Nilsen, Christopher W.; Biles, Drummond E.; Mueller, Charles J.; Northrop, William F.

Ducted fuel injection (DFI) is a novel combustion strategy that has been shown to significantly attenuate soot formation in diesel engines. While previous studies have used optical diagnostics and optical filter smoke number methods to show that DFI reduces in-cylinder soot formation and engine-out soot emissions, respectively, this is the first study to measure solid particle number (PN) emissions in addition to particle mass (PM). Furthermore, this study quantitatively evaluates the use of transient particle instruments for measuring particles from skip-fired operation in an optical single cylinder research engine (SCRE). Engine-out PN was measured using an engine exhaust particle sizer following a catalytic stripper, and PM was measured using a photoacoustic analyzer. The study improves on earlier preliminary emissions studies by clearly showing that DFI reduces overall PM by 76%–79% and PN for particles larger than 23 nm by 77% relative to conventional diesel combustion at a 1200-rpm, 13.3-bar gross indicated mean effective pressure operating condition. The degree of engine-out PM reduction with DFI was similar across both particulate measurement instruments used in the work. Through the use of bimodal distribution fitting, DFI was also shown to reduce the geometric mean diameter of accumulation mode particles by 26%, similar to the effects of increased injection pressure in conventional diesel combustion systems. This work clearly shows the significant solid particulate matter reductions enabled by DFI while also demonstrating that engine-out PN can be accurately measured from an optical SCRE operating in a skip-fired mode. Based on these results, it is believed that DFI has the potential to enable fuel savings when implemented in multi-cylinder engines, both by lowering the required frequency of active diesel particulate filter regeneration, and by reducing the backpressure imposed by exhaust filtration systems.

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TYPE Journal Article YEAR 2022
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Classification of Photovoltaic Failures with Hidden Markov Modeling, an Unsupervised Statistical Approach

Energies

Hopwood, Michael W.; Patel, Lekha; Gunda, Thushara

Failure detection methods are of significant interest for photovoltaic (PV) site operators to help reduce gaps between expected and observed energy generation. Current approaches for field-based fault detection, however, rely on multiple data inputs and can suffer from interpretability issues. In contrast, this work offers an unsupervised statistical approach that leverages hidden Markov models (HMM) to identify failures occurring at PV sites. Using performance index data from 104 sites across the United States, individual PV-HMM models are trained and evaluated for failure detection and transition probabilities. This analysis indicates that the trained PV-HMM models have the highest probability of remaining in their current state (87.1% to 93.5%), whereas the transition probability from normal to failure (6.5%) is lower than the transition from failure to normal (12.9%) states. A comparison of these patterns using both threshold levels and operations and maintenance (O&M) tickets indicate high precision rates of PV-HMMs (median = 82.4%) across all of the sites. Although additional work is needed to assess sensitivities, the PV-HMM methodology demonstrates significant potential for real-time failure detection as well as extensions into predictive maintenance capabilities for PV.

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TYPE Journal Article YEAR 2022
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Molecular dynamics studies of helium bubble effects on grain boundary fracture vulnerabilities in an Fe70Ni11Cr19–1%H austenitic stainless steel

Journal of Nuclear Materials

Zhou, Xiaowang; Foster, Michael E.; Sills, R.B.

Comprehensive molecular dynamics tensile test simulations have been performed to study the delamination processes of seven different grain boundaries / cleavage planes (Σ1{111}, Σ3{111}, Σ5{100}, Σ7{111}, Σ9{411}, Σ11{311}, and R{100}/{411}) containing a helium bubble. Combinations of a variety of conditions are explored including different strain rates, system dimensions, bubble density, bubble radius, bubble pressure, and temperature. We found that in general, grain boundaries absorb less energies with decreasing strain rate but increasing bubble areal density, bubble pressure, bubble radius, and temperature. The propensity of grain boundary delamination is sensitive to grain boundary type: The random grain boundary R{100}/{411} is one of the most brittle boundaries whereas the Σ1{111} cleavage plane and the Σ3{111} twin boundary are two of the toughest boundaries. The sorted list of grain boundary fracture vulnerability obtained from our dynamic tensile test simulations differs from the one obtained from our decohesion energy calculations, confirming the important role of plastic deformation during fracture. Detailed mechanistic analyses are performed to interpret the simulated results.

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TYPE Journal Article YEAR 2022
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Sewer System Management Plan

Manger, Trevor J.

The Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC (NTESS), a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration (DOE/NNSA) under contract DE-NA0003525. In 2008, a Notice of Intent (NOI) was filed for the Sandia National Laboratories, California (SNL/CA) facility to be covered under the State Water Resources Control Board (SWRCB) Order No. 2006-0003-DWQ Statewide General Waste Discharge Requirements (WDR) for Sanitary Sewer Systems (General Permit) and was issued the WDID No. 2SSO11605. The General Permit requires a proactive approach to reduce the number and frequency of sanitary sewer overflows (SSOs) within the State. Provision D.11 of the General Permit requires the development and implementation of a written Sewer System Management Plan (SSMP). This SSMP is prepared according to the mandatory elements required by Provision D.13 and D.14, as well as the schedule for a population less than 2,500 as outlined in Provision D.15.

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TYPE Other Report YEAR 2022
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Unraveling Thermodynamic and Kinetic Contributions to the Stability of Doped Nanocrystalline Alloys using Nanometallic Multilayers

Advanced Materials

Cunningham, W.S.; Riano, J.S.; Wang, Wenbo; Hwang, Sooyeon; Hattar, Khalid M.; Hodge, Andrea M.; Trelewicz, Jason R.

Targeted doping of grain boundaries is widely pursued as a pathway for combating thermal instabilities in nanocrystalline metals. However, certain dopants predicted to produce grain-boundary-segregated nanocrystalline configurations instead form small nanoprecipitates at elevated temperatures that act to kinetically inhibit grain growth. Here, thermodynamic modeling is implemented to select the Mo–Au system for exploring the interplay between thermodynamic and kinetic contributions to nanostructure stability. Using nanoscale multilayers and in situ transmission electron microscopy thermal aging, evolving segregation states and the corresponding phase transitions are mapped with temperature. The microstructure is shown to evolve through a transformation at lower homologous temperatures (<600 °C) where solute atoms cluster and segregate to the grain boundaries, consistent with predictions from thermodynamic models. An increase in temperature to 800 °C is accompanied by coarsening of the grain structure via grain boundary migration but with multiple pinning events uncovered between migrating segments of the grain boundary and local solute clustering. Direct comparison between the thermodynamic predictions and experimental observations of microstructure evolution thus demonstrates a transition from thermodynamically preferred to kinetically inhibited nanocrystalline stability and provides a general framework for decoupling contributions to complex stability transitions while simultaneously targeting a dominant thermal stability regime.

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TYPE Journal Article YEAR 2022
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Automating Component-Level Stress Measurements for Inverter Reliability Estimation

Energies

Flicker, Jack D.; Johnson, Jay; Hacke, Peter; Thiagarajan, Ramanathan

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous operating modes which induce new stresses on the power electronics components. In this work, an experimental and theoretical framework is introduced which couples laboratory-measured component stress with advanced inverter functionality and derives a reduction in useful lifetime based on an applicable reliability model. Multiple DER devices were instrumented to calculate the additional component stress under multiple reactive power setpoints to estimate associated DER lifetime reductions. A clear increase in switch loss was demonstrated as a function of irradiance level and power factor. This is replicated in the system-level efficiency measurements, although magnitudes were different—suggesting other loss mechanisms exist. Using an approximate Arrhenius thermal model for the switches, the experimental data indicate a lifetime reduction of 1.5% when operating the inverter at 0.85 PF—compared to unity PF—assuming the DER failure mechanism thermally driven within the H-bridge. If other failure mechanisms are discovered for a set of power electronics devices, this testing and calculation framework can easily be tailored to those failure mechanisms.

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TYPE Conference Presentation YEAR 2022
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The ultrafast pixel array camera system and its applications in high energy density physics

Review of Scientific Instruments

Looker, Quinn M.; Oberla, Eric J.; Stahoviak, John W.; Mostafanezhad, Isar; Pang, Ryan; Luck, Marcus; Galloway, Benjamin R.; Rambo, Patrick K.; Porter, John L.

Diagnostics in high energy density physics, shock physics, and related fields are primarily driven by a need to record rapidly time-evolving signals in single-shot events. These measurements are often limited by channel count and signal degradation issues on cable links between the detector and digitizer. We present the Ultrafast Pixel Array Camera (UPAC), a compact and flexible detector readout system with 32 waveform-recording channels at up to 10 Gsample/s and 1.8 GHz analog bandwidth. The compact footprint allows the UPAC to be directly embedded in the detector environment. A key enabling technology is the PSEC4A chip, an eight-channel switch-capacitor array sampling device with up to 1056 samples/channel. The UPAC system includes a high-density input connector that can plug directly into an application-specific detector board, programmable control, and serial readout, with less than 5 W of power consumption in full operation. We present the UPAC design and characterization, including a measured timing resolution of ∼20 ps or better on acquisitions of sub-nanosecond pulses with minimal system calibrations. Example applications of the UPAC are also shown to demonstrate operation of a solid-state streak camera, an ultrafast imaging array, and a neutron time-of-flight spectrometer.

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TYPE Journal Article YEAR 2022
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Statistical perspective on embrittling potency for intergranular fracture

Physical Review Materials

Fernandez, M.E.; Dingreville, Remi; Spearot, D.E.

Embrittling potency is a thermodynamic metric that assesses the influence of solute segregation to a grain boundary (GB) on intergranular fracture. Historically, authors of studies have reported embrittling potency as a single scalar value, assuming a single segregation site of importance at a GB and a particular cleavage plane. However, the topography of intergranular fracture surfaces is not generally known a priori. Accordingly, in this paper, we present a statistical ensemble approach to compute embrittling potency, where many free surface (FS) permutations are systematically considered to model fracture of a GB. The result is a statistical description of the thermodynamics of GB embrittlement. As a specific example, embrittling potency distributions are presented for Cr segregation to sites at two Ni (111) symmetric tilt GBs using atomistic simulations. We show that the average embrittling potency for a particular GB site, considering an ensemble of FS permutations, is not equal to the embrittling potency computed using the lowest energy pair of FSs. A mean GB embrittlement is proposed, considering both the likelihood of formation of a particular FS and the probability of solute occupancy at each GB site, to compare the relative embrittling behavior of two distinct GBs.

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TYPE Journal Article YEAR 2022
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FY22 Progress on Multicontinuum Methods in Containment

Kuhlman, Kristopher L.; Mills, Melissa M.; Heath, Jason E.; Paul, Matthew J.

Estimation of two-phase fluid flow properties is important to understand and predict water and gas movement through the vadose zone for agricultural, hydrogeological, and engineering applications, such as containment transport and/or containment of gases in the subsurface. To estimate rock fluid flow properties and subsequently predict physically realistic processes such as patterns and timing of water, gas, and energy (e.g., heat) movement in the subsurface, laboratory spontaneous water imbibition with simultaneous temperature measurement and numerical modeling methods are presented in the FY22 progress report. A multiple-overlapping-continua conceptual model is used to explain and predict observed complex multi-phenomenological laboratory test behavior during spontaneous imbibition experiments. This report primarily addresses two complexities that arise during the experiments: 1) capturing the late-time behavior of spontaneous imbibition tests with dual porosity; and 2) understanding the thermal perturbation observed at or ahead of the imbibing wetting front, which are associated with adsorption of water in initially dry samples. We use numerical approaches to explore some of these issues, but also lay out a plan for further laboratory experimentation and modeling to best understand and leverage these unique observations.

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TYPE SAND Report YEAR 2022
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Internal energy balance and aerodynamic heating predictions for hypersonic turbulent boundary layers

Physical Review Fluids

Barone, Matthew F.; Nicholson, Gary L.; Duan, Lian

The elemental equation governing heat transfer in aerodynamic flows is the internal energy equation. For a boundary layer flow, a double integration of the Reynolds-averaged form of this equation provides an expression of the wall heat flux in terms of the integrated effects, over the boundary layer, of various physical processes: turbulent dissipation, mean dissipation, turbulent heat flux, etc. Recently available direct numerical simulation data for a Mach 11 cold-wall turbulent boundary layer allows a comparison of the exact contributions of these terms in the energy equation to the wall heat flux with their counterparts modeled in the Reynolds-averaged Navier-Stokes (RANS) framework. Various approximations involved in RANS, both closure models as well as approximations involved in adapting incompressible RANS models to a compressible form, are assessed through examination of the internal energy balance. There are a number of potentially problematic assumptions and terms identified through this analysis. The effect of compressibility corrections of the dilatational dissipation type is explored, as is the role of the modeled turbulent dissipation, in the context of wall heat flux predictions. The results indicate several potential avenues for RANS model improvement for hypersonic cold-wall boundary-layer flows.

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TYPE Journal Article YEAR 2022
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Cybersecurity for Electric Vehicle Charging Infrastructure

Johnson, Jay; Anderson, Benjamin; Wright, Brian J.; Quiroz, Jimmy E.; Berg, Timothy M.; Graves, Russell; Daley, Josh; Phan, Kandy; Kunz, Michael; Pratt, Rick; Carroll, Tom; Oneil, Lori R.; Dindlebeck, Brian; Maloney, Patrick; Brien, David'; Gotthold, David; Varriale, Roland; Bohn, Ted; Hardy, Keith

As the U.S. electrifies the transportation sector, cyberattacks targeting vehicle charging could impact several critical infrastructure sectors including power systems, manufacturing, medical services, and agriculture. This is a growing area of concern as charging stations increase power delivery capabilities and must communicate to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid operator communication systems could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks — or public perception of such — would ripple across the industry and produce lasting effects. Unfortunately, there is currently no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured inter faces. Comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project provided the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team created a cybersecurity threat model and performed a technical risk assessment of EVSE assets across multiple manufacturers and vendors, so that automotive, charging, and utility stakeholders could better protect customers, vehicles, and power systems in the face of new cyber threats.

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TYPE SAND Report YEAR 2022
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Results 6201–6400 of 99,299
Results 6201–6400 of 99,299