Babiniec, Sean M.; Reinholz, Emilee L.; Coker, Eric N.; Larsen, Marin E.
Intumescent materials are in wide use as protective coatings in fire protection or thermal management applications. These materials undergo chemical reactions occurring from approximately 300°C to 900°C, which outgas and expand the material, providing an appreciable increase in insulative performance. However, the complicated chemical mechanisms and large changes in materials properties complicate the incorporation of these materials into predictive thermal models. This document serves to outline the thermochemical characterization of select intumescent materials, the extraction of relevant parameters, and the incorporation of these parameters into the ChemEQ reaction model implemented in Aria. This work was performed in 2016 and documented in a draft SAND report in March 2017. In 2022, the draft SAND report was discovered and put through R&A.
Worldwide growth in electric vehicle use is prompting new installations of private and public electric vehicle supply equipment (EVSE). EVSE devices support the electrification of the transportation industry but also represent a linchpin for power systems and transportation infras-tructures. Cybersecurity researchers have recently identified several vulnerabilities that exist in EVSE devices, communications to electric vehicles (EVs), and upstream services, such as EVSE vendor cloud services, third party systems, and grid operators. The potential impact of attacks on these systems stretches from localized, relatively minor effects to long-term national disruptions. Fortunately, there is a strong and expanding collection of information technology (IT) and operational technology (OT) cybersecurity best practices that may be applied to the EVSE environment to secure this equipment. In this paper, we survey publicly disclosed EVSE vulnerabilities, the impact of EV charger cyberattacks, and proposed security protections for EV charging technologies.
Sjoberg, Carl M.; Killingsworth, Nick; Kolodziej, Christopher; Majumdar, Sreshtha S.; Szybist, James
In total, light-duty vehicles in the United States travel on the order of 3 trillion miles annually, providing tremendous societal and personal benefits. However, the environmental burden is excessive, prompting Co-Optimization of Fuel and Engines (Co-Optima) program efforts to provide the science needed to increase engine efficiency and produce non-fossil fuels with reduced greenhouse gas emissions. Boosted spark-ignition (SI) engines provide high power density by offering high loads and engine speeds, making them light-weight and attractive for light-duty vehicles. Unfortunately, the engine efficiency drops off at lower loads and speeds, where the engine spends most time during typical driving. Multimode SI engines can use a more efficient advanced lean combustion mode at lower loads and speeds, while reverting to boosted SI under high-load conditions. Within Co-Optima, multiple advanced lean combustion modes have been explored; these include stratified-charge SI, pre-chamber lean SI, and advanced compression ignition (ACI) techniques such as spark-assisted compression ignition (SACI). For these combustion modes, focus has been on determining fuel properties that enable higher engine efficiency, clean and stable combustion, and effective exhaust aftertreatment. This report highlights recent efforts funded by the Vehicle Technologies Office at multiple National Laboratories that supported the multimode project in Co-Optima. It also includes a brief summary of biofuel production research funded by the Bioenergy Technologies Office.
Metals subjected to irradiation environments undergo microstructural evolution and concomitant degradation, yet the nanoscale mechanisms for such evolution remain elusive. Here, we combine in situ heavy ion irradiation, atomic resolution microscopy, and atomistic simulation to elucidate how radiation damage and interfacial defects interplay to control grain boundary (GB) motion. While classical notions of boundary evolution under irradiation rest on simple ideas of curvature-driven motion, the reality is far more complex. Focusing on an ion-irradiated Pt Σ3 GB, we show how this boundary evolves by the motion of 120° facet junctions separating nanoscale {112} facets. Our analysis considers the short- and mid-range ion interactions, which roughen the facets and induce local motion, and longer-range interactions associated with interfacial disconnections, which accommodate the intergranular misorientation. We suggest how climb of these disconnections could drive coordinated facet junction motion. These findings emphasize that both local and longer-range, collective interactions are important to understanding irradiation-induced interfacial evolution.
This report presents a specification for the Portals 4 network programming interface. Portals 4 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4 is well suited to massively parallel processing and embedded systems. Portals 4 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4 is targeted to the next generation of machines employing advanced network interface architectures that support enhanced offload capabilities.
Although mass spectrometry is a widely used analytical tool, age-appropriate, interactive outreach activities for laboratory visitors, especially children, are lacking. The presented interactive demonstration, "Did you eat a MOLEcule today?", introduces all ages to molecular weight concepts and mass spectrometry in a research laboratory, while connecting the concepts to real-world applications. Through real-time breath analysis, participants explore the concepts of molecular weight, electrostatic field manipulation of charged molecules, and analyte identification by mass analysis. This module is rapid and highly adaptable for outreach activities but also includes age- or classroom-appropriate variations to decrease or increase difficulty levels. The presented interactive demonstration has repeatedly been implemented, with over 2300 participants during six annual "Take Our Daughters & Sons to Work Day" and two corporate "Family Day" outreach activities, successfully engaging, exciting, and educating both kids and parents.
We present a combination of machine-learned models that predicts the surface elastic properties of general free surfaces in face-centered cubic (FCC) metals. These models are built by combining a semi-analytical method based on atomistic simulations to calculate surface properties with the artificial neural network (ANN) method or the boosted regression tree (BRT) method. The latter is also used to link bulk properties and surface orientation to surface properties. The surface elastic properties are represented by their invariants considering plane elasticity within a polar method. The resulting models are shown to accurately predict the surface elastic properties of seven pure FCC metals (Cu, Ni, Ag, Au, Al, Pd, Pt). The BRT model reveals the correlations between bulk and corresponding surface properties in terms of invariants, which can be used to guide the design of complex nano-sized particles, wires and films. Finally, by expressing the surface excess energy density as a function of surface elastic invariants, fast predictions of surface energy as a function of in-plane deformations can be made from these model constructs.
Over the past few years, the CTH multiphysics hydrocode has overhauled its software quality and testing processes, implementing current best practices in software quality and building a robust V&V test suite comprised of traditional hydrocode verification problems, including ASC Tri-Lab Test Suite and Enhanced Tri-Lab Test Suite problems, as well as validation problems for some of CTH’s most frequently used equations of state, materials models, and other key capabilities. Substantial progress towards building this new test suite was made in FY19 and FY20. In FY21, the test suite has been expanded to include verification and validation tests of the Steinberg-Guinan-Lund (ST) viscoplastic model and the Johnson Cook (JFRAC) fracture model. Additionally, two new verification tests were added, covering hydrodynamics and high explosive (HE) modeling capabilities: the Kidder Gaussian density problem and the Escape of HE Products (EHEP) problem from the Tri-Lab Test Suite. This report discusses each of these test problems in detail. Verification test results are compared to analytic solutions. Validation test results are compared to experimental data. Wherever possible, convergence or mesh refinement studies are included. Additionally, while implementing the Kidder verification problem, a bug was identified that affects the use of tables to initialize pressure or density in 1D or 2D calculations. A brief discussion of the bug and its fix is included. CTH demonstrates good performance overall on the new test suite problems. Simulation results showed good agreement with analytic solutions for the Kidder problem, with convergence rates ranging between 1.8 and sub-linear, and relatively good agreement for the EHEP problem, though convergence rates for pressure and density were nearly 0. The ST and JFRAC strain rate loading verification tests show good agreement with analytic solutions. Likewise, CTH simulation results show good agreement with experimental validation data, including Taylor rod impact testing, for the materials tested. Future V&V work will focus on adding 2D and 3D versions of existing verification tests as well as adding validation tests of other frequently used capabilities such as other fracture models.
This user’s guide documents capabilities in Sierra/SolidMechanics which remain “in-development” and thus are not tested and hardened to the standards of capabilities listed in Sierra/SM 5.8 User’s Guide. Capabilities documented herein are available in Sierra/SM for experimental use only until their official release. These capabilities include, but are not limited to, novel discretization approaches such as the conforming reproducing kernel (CRK) method, numerical fracture and failure modeling aids such as the extended finite element method (XFEM) and J-integral, explicit time step control techniques, dynamic mesh rebalancing, as well as a variety of new material models and finite element formulations.
Aims: High-resolution information on soils’ vulnerability to climate-induced soil organic carbon (SOC) loss can enable environmental scientists, land managers, and policy makers to develop targeted mitigation strategies. This study aims to estimate baseline and decadal changes in continental US surface SOC stocks under future emission scenarios. Location: Continental United States. Time period: 2014–2100. Methods: We used recent SOC field observations (n = 6,213 sites), environmental factors (n = 32), and an ensemble machine learning (ML) approach to estimate baseline SOC stocks in surface soils across the continental United States at 100-m spatial resolution, and decadal changes under the projected climate scenarios of Coupled Model Intercomparison Project Phase Six (CMIP6) earth system models (ESMs). Results: Baseline SOC projections from ML approaches captured more than 50% of variability in SOC observations, whereas ESMs represented only 6–16% of observed SOC variability. ML estimates showed a mean total loss of 1.8 Pg C from US surface soils under the high-emission scenario by 2100, whereas ESMs showed no significant change in SOC stocks with wide variation among ESMs. Both ML and ESM predictions agree on the direction of SOC change (net emissions or sequestration) across 46–51% of continental US land area. These differences are attributable to the high-resolution site-specific data used in the ML models compared to the relatively coarse grid represented in CMIP6 ESMs. Main conclusions: Our high-resolution estimates of baseline SOC stocks, identification of key environmental controllers, and projection of SOC changes from US land cover types under future climate scenarios suggest the need for high-resolution simulations of SOC in ESMs to represent the heterogeneity of SOC. We found that the SOC change is sensitive to key soil related factors (e.g. soil drainage and soil order) that have not been historically considered as input parameters in ESMs, because currently more than 95% variability in the SOC of CMIP6 ESMs is controlled by net primary productivity, temperature, and precipitation. Using additional environmental factors to estimate the baseline SOC stocks and predict the future trajectory of SOC change can provide more accurate results.
Electrochemical characteristics and semiconducting behavior of additively manufactured electron beam melted (EBM) and wrought (WR) Ti–6Al–4V (Ti-G5) are compared in Ringer’s physiological solution. X-ray diffraction (XRD) and field emission scanning electron microscopy (FE-SEM) confirmed the α + β structure of the tested materials, with two different microstructure types of “bimodal” and “basket-weave” for WR and EBM, respectively. Potentiodynamic polarization (PDP) revealed that the corrosion current density for EBM (icorr = 0.27 ± 0.06 μA cm−2) is less than the WR (icorr = 0.70 ± 0.05 μA cm−2). Moreover, potentiostatic polarization (PS) that was employed to form the passive layers at three different potentials of 300, 500, and 700 mVAg/AgCl, showed that the passive films on the EBM sample are thinner. This finding was confirmed by electrochemical impedance spectroscopy (EIS). Furthermore, through Mott–Schottky (M–S) analysis, donor densities on WR passive films were found to be ~ 1.5 times larger than EBM. Although PS and EIS confirmed that the passive layer on EBM is thinner, it provides higher corrosion resistance than WR. The passive layer on both samples were found to have n-type characteristics with a duplex structure. Graphical abstract: [Figure not available: see fulltext.]
