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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Observed Sensitivity of Low-Cloud Radiative Effects to Meteorological Perturbations over the Global Oceans

Understanding how marine low clouds and their radiative effects respond to changing meteorological conditions is crucial to constrain low-cloud feedbacks to greenhouse warming and internal climate variability. In this paper, we use observations to quantify the low-cloud radiative response to meteorological perturbations over the global oceans to shed light on physical processes governing low-cloud and planetary radiation budget variability in different climate regimes. We assess the independent effect of perturbations in sea surface temperature, estimated inversion strength, horizontal surface temperature advection, 700-hPa relative humidity, 700-hPa vertical velocity, and near-surface wind speed. Stronger inversions and stronger cold advection greatly enhance low-level cloudiness and planetary albedo in eastern ocean stratocumulus and midlatitude regimes. Warming of the sea surface drives pronounced reductions of eastern ocean stratocumulus cloud amount and optical depth, and hence reflectivity, but has a weaker and more variable impact on low clouds in the tropics and middle latitudes. By reducing entrainment drying, higher free-tropospheric relative humidity enhances low-level cloudiness. At low latitudes, where cold advection destabilizes the boundary layer, stronger winds enhance low-level cloudiness; by contrast, wind speed variations have weak influence at midlatitudes where warm advection frequently stabilizes the marine boundary layer, thus inhibiting vertical mixing. These observational constraints provide a framework for understanding and evaluating marine low-cloud feedbacks and their simulation by models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Understanding the Roles of Convective Trigger Functions in the Diurnal Cycle of Precipitation in the NCAR CAM5

The wrong diurnal cycle of precipitation is a common weakness of current global climate models (GCMs). To improve the simulation of the diurnal cycle of precipitation and understand what physical processes control it, we test a convective trigger function described in Xie et al. (2019) with additional optimizations in the NCAR Community Atmosphere Model version 5 (CAM5). The revised trigger function consists of three modifications: 1) replacing the Convective Available Potential Energy (CAPE) trigger with a dynamic CAPE (dCAPE) trigger, 2) allowing convection to originate above the top of planetary boundary layer (i.e., the unrestricted air parcel launch level - ULL), and 3) optimizing the entrainment rate and threshold value of the dynamic CAPE generation rate for convection onset based on observations. Results from 1°-resolution simulations show that the revised trigger can alleviate the long-standing GCM problem of too early maximum precipitation during the day and missing the nocturnal precipitation peak that is observed in many regions, including the U.S. southern Great Plains (SGP). The revised trigger also improves the simulation of the propagation of precipitation systems downstream of the Rockies and the Amazon region. A further composite analysis over the SGP unravels the mechanisms through which the revised trigger affects convection. Additional sensitivity tests show that both the peak time and the amplitude of the diurnal cycle of precipitation are sensitive to the entrainment rate and dCAPE threshold values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Robust Anthropogenic Signal Identified in the Seasonal Cycle of Tropospheric Temperature

Previous work identified an anthropogenic fingerprint pattern in T AC (x, t), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite T AC (x, t) data could have been influenced by real-world multidecadal internal variability (MIV). Here we address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their T AC (x, t) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3–4) intermodel and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal T AC (x, t) variability associated with the Atlantic multidecadal oscillation and El Niño–Southern Oscillation. The robustness of the seasonal cycle detection and attribution results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced T AC (x, t) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

West African Monsoon System’s Responses to Global Ocean–Regional Atmosphere Coupling

This study explores the added value (AV) of a regional Earth system model (ESM) compared to an atmosphere-only regional climate model (RCM) in simulating West African monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean–atmosphere coupling’s influence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM, low resolution (MPI-ESM-LR), by two RCMs, atmosphere only (REMO) and REMO coupled with Max Planck Institute Ocean Model (MPIOM) (ROM), at ~25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fluxes. Contrastingly, as intended, coupling improves SSTs and monsoon fluxes’ relationships under ESM-forced conditions. In this latter case, the coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinea Coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara–Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Diurnal Variation of the Planetary Boundary Layer Height Observed from GNSS Radio Occultation and Radiosonde Soundings over the Southern Great Plains

>The planetary boundary layer (PBL) height (PBLH) is a key physical parameter of the PBL affected by numerous physical processes within the boundary layer. Specifically, the PBLH over land exhibits large spatial and temporal variation across different geographical regions. In this study, the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation (RO) profiles and high-resolution radiosonde profiles from 2007 to 2013 were analyzed to estimate the diurnal cycle of the PBLH over the Southern Great Plains (SGP) in the United States. Large variations in PBLH derived from radiosonde temperature, moisture, and refractivity are observed on seasonal scales. COSMIC RO is capable of observing diurnal and seasonal variations in the terrestrial PBLH over the SGP region. Annual mean diurnal amplitude of approximately 250 m in the terrestrial PBLH was observed, with maxima occurring at around 1500 local solar time (LST) in both the collocated radiosondes and COSMIC RO profiles. Seasonal changes in the PBLH diurnal cycles ranging from approximately 100 to 400 m were also observed. Such PBL diurnal and seasonal changes can be further incorporated into PBL parameterizations to help improve weather and climate model prediction. Significance Statement. The atmospheric planetary boundary layer (PBL) and its height (PBLH) control many atmospheric processes that affect our everyday lives. Observations of the PBL are usually limited to radiosondes at limited time intervals. GNSS radio occultation (RO) provide high-vertical-resolution atmospheric observations that are ideal for PBL study. This study demonstrates that the GNSS RO is capable of capturing the diurnal and seasonal variations of the PBLH over the southern Great Plains (SGP) well as compared to the collocated radiosonde observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models

Abstract While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model’s vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a single-column model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of an SCM against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rainwater from large-eddy simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the covariability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine scales often used in parameterization development and large-eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ∼5 when vertical grid spacing is improved from 120 to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement. Significance Statement In successive generations of computer models that simulate Earth’s atmosphere, improvements have been mainly accomplished by reducing the horizontal sizes of discretized grid boxes, while the vertical grid spacing has seen comparatively lesser refinements. Here we advocate for additional attention to be paid to the number of vertical layers in these models, especially in the model layers closest to Earth’s surface where climatologically important marine stratocumulus and shallow cumulus clouds reside. Our experiments show that the ability of a one-dimensional model to represent physical processes important to these clouds is strongly dependent on the model’s vertical grid spacing.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

GEFSv12 High- and Low-Skill Day-10 Tornado Forecasts

Abstract On average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes because of their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the United States were exploited while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). There were 88 high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden–Julian oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific decadal oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 overforecast the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters. Significance Statement This research provides a framework for the anticipation of a more (or less) skillful 10-day tornado forecast in an operational numerical weather prediction system. High-skill forecasts were associated with substantial tropical convection and warm sea surface temperature throughout the Pacific Ocean and Gulf of Mexico, whereas the underlying cause of low-skill forecasts were typically associated with a blocking anticyclone over eastern Russia. These findings are important because they permit increased or decreased confidence in a long-range forecast of tornado occurrence based on a dynamical prediction system.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

The influence of intake flow and coolant temperature on gasoline spray morphology during early-injection DISI engine operation

Multi-hole gasoline injectors operating at conditions spanning throttled early-intake stroke operation produce spray plumes that either remained separated or merge and collapse due to flash boiling. Flash boiling occurs due to the sudden expansion of gas bubbles in the liquid fuel at high fuel temperature and low ambient pressure. This study records high-speed images of spray-morphology changes due to in-cylinder flow, thereby revealing operating conditions that do and do not affect the self-induced morphology observed in quiescent vessels. Specifically, in a central-injection, four-valve, high-tumble engine, where the thermodynamic state and in-cylinder cross flow are dynamic. Motivated by cold start and hot restart operation, the fuel pressure, coolant temperature, in-cylinder air pressure, and engine rpm were systematically varied over relevant operating conditions, which bracketed the range from non- to flash-boiling sprays. The results reveal the operating conditions at which the in-cylinder cross flow disrupts the spray morphology as well as the extent of the disruption. At 650 rpm, the spray morphology was similar to that observed in quiescent vessels at nominally equivalent fuel temperature and in-cylinder pressure, indicating that the spray’s self-induced entrainment flow dominated the in-cylinder flow. However, for fuel temperature and ambient pressure near the transition between non- and flash-boiling, the intake cross flow at higher engine speed (1950 rpm) significantly disrupted the spray morphology. The high cross-flow velocity appears to induce plume merging and collapse, whereas none was evident at low rpm (650 rpm). This study led to the postulate that the spray merging and collapse are governed by the rate of atomization near the nozzle exit, presumed to be controlled by either or both aerodynamic atomization and flash-boiling intensity. It would then follow that spray modeling in CFD requires atomization models that blend the effects of both physical processes.

42 ENGINEERING↗
DOE OSTI2023

Realistic fuel spray modeling for gasoline direct injection engine applications

Fuel spray modeling plays a critical role during modern gasoline direct injection (GDI) engine development due to fuel injection’s dominant impact on engine performance and emissions as well as the complex physical processes involved. In engineering three-dimensional (3D) computational fluid dynamics (CFD) simulations, the liquid-phase fuel atomization, evaporation, and mixing are usually modeled with the discrete droplet model (DDM) adopting a Lagrangian approach for multiphase CFD simulations. To this end, general practices heavily depend on the reduced order characterization of the injector nozzle flow. However, such simplified injector modeling may lead to insufficient representations of the complex spray dynamics. To tackle this problem, this study proposes a novel workflow to numerically evaluate GDI sub-cooled and flash-boiling sprays under engine-relevant conditions using a side-mounted GDI injector together with real gasoline fuel properties. The workflow introduces a one-way coupling (OWC) method leveraging high-fidelity nozzle flow simulations to provide realistic boundary conditions to the Lagrangian injector model. The proposed workflow was first verified in a constant volume chamber (CVC) environment and then implemented in a practical GDI engine setup to study spray morphology, fuel-air mixing, and wall-wetting propensity. In addition, detailed comparison was performed between the OWC method and the conventional rate of injection (ROI) routine. In conclusion, quantitative analysis of spray characteristics was conducted to highlight possible source of discrepancies of the conventional ROI method.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable optimized scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins (DTs) are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. DTs for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. A DT’s goal is to provide additional insights by combining and interpreting various sources of information for preventative maintenance scheduling optimization or early fault detection. DTs for condition monitoring are projected to be valuable for meeting requirements under 10 CFR 50.55a, “Codes and Standards,” and 10 CFR 50.65, “Requirements for Monitoring the Effectiveness of Maintenance at Nuclear Power Plants”. However, DT technologies are still under significant development, and the process for developing a DT for condition monitoring has not been formalized. Therefore, in this work, we present an initial framework for developing a DT, discuss and review the various challenges and considerations for DT deployment, and identify the opportunities that a DT can improve. The presented framework is intended to help developers formulate a strategy when approaching DT development for condition monitoring. In conclusion, a DT use case for a reactor coolant pump is presented to demonstrate the proposed framework.

advanced sensor instrumentation↗
DOE OSTI2022

Development of a triple-moment ice-phase cloud microphysics scheme and its application to the Single Column Atmosphere Model

Parameterization of cloud microphysics is critical for accurate simulation of weather and climate, in which the characteristics of cloud particle spectrum inevitably further affect climate simulation by changing the cloud evolution and cloud radiation effects. The popular currently used double-moment cloud microphysics schemes in numerical models can predict the intercept (N 0 ) and slope (λ) parameters of cloud particle spectrum but cannot predict the spectral shape parameter (μ), which hinders accurate description of cloud physical processes in climate models. Therefore, in the present study, we built upon the ideas of previously developed triple-moment cloud microphysics scheme, considered radar reflectivity factor as the third predictor in addition to number and mass concentration, and introduced its related prediction equation to the Single Column Atmosphere Model Version 5.3 (SCAM5.3). Moreover, the relevant microphysical process formulas in the model were revised, and a triple-moment ice-cloud microphysics scheme was constructed to predict the μ of ice particle spectrum. Based on this model, a 29-day case of the Atmospheric Radiation Measurement Program in the summer of 1997 (ARM97) was simulated, and the differences in cloud fraction and radiation simulations between the double- and triple-moment schemes were analysed. The μ of ice particle spectrum predicted by the triple-moment scheme mainly ranged from 0 to 4; the peak value was around 2, and at least 85% of the μ values were greater than the default 0. Therefore, the μ=0 setting in the double-moment scheme is unreasonable. Moreover, the developed triple-moment ice-cloud microphysics scheme yielded a narrower ice particle spectrum, which was closer to the observation results of previous studies, than the double-moment cloud microphysics scheme (e.g., height=233 hPa). Furthermore, compared with the double-moment scheme, the triple-moment scheme achieved closer simulations of the cloud fraction observations, particularly for ice clouds in the upper levels. Considering the close association between cloud fraction and radiation, the error with the triple-moment scheme was smaller than that with the double-moment scheme regardless of the shortwave (surface downward shortwave radiation, net downward shortwave radiation at the top of the atmosphere, and net shortwave radiation at the surface) or longwave (surface downward longwave radiation and net longwave radiation at the surface) flux density. Finally, the improvement mechanism of the triple-moment scheme on cloud fraction and radiation simulations was explored. The major reason is that the triple-moment scheme weakens the autoconversion of ice crystal to form snow and enhances the growth process of ice crystal deposition, thereby increasing the mass concentration of ice crystals and ice cloud fraction. Overall, the developed triple-moment ice-cloud microphysics scheme can help improve the simulation ability of models for cloud-climate feedback and other processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Non-contact imaging of terahertz surface currents with aperture-type near-field microscopy

Terahertz (THz) near-field imaging and spectroscopy provide valuable insights into the fundamental physical processes occurring in THz resonators and metasurfaces on the subwavelength scale. However, so far, the mapping of THz surface currents has remained outside the scope of THz near-field techniques. In this study, we demonstrate that aperture-type scanning near-field microscopy enables non-contact imaging of THz surface currents in subwavelength resonators. Through extensive near-field mapping of an asymmetric D-split-ring THz resonator and full electromagnetic simulations of the resonator and the probe, we demonstrate the correlation between the measured near-field images and the THz surface currents. The observed current dynamics in the interval of several picoseconds reveal the interplay between several excited modes, including dark modes, whereas broadband THz near-field spectroscopy analysis enables the characterization of electromagnetic resonances defined by the resonator geometry.

Norman, Sarah↗
DOE OSTI2024

Bridging gaps in permafrost-shrub understanding

Permafrost, permanently frozen ground which underlies much of the Arctic and sub-Arctic, is influenced by deciduous shrubs, yet our understanding of permafrost-shrub interactions is limited. This is largely due to a lack of widespread, long-term, high-quality observations across Arctic and sub-Arctic systems, which are difficult to study due to their remote locations. Shrubs are rapidly expanding in many areas of Arctic tundra and can either amplify or inhibit permafrost thaw, making it crucial that we can understand and predict permafrost-shrub interactions. As we have limited time and resources to make observations, we must design our field campaigns to be as impactful as possible. Below we outline the current state of knowledge and give suggestions about how we can maximize our fieldwork’s impact. From field studies conducted around the Arctic, we know that shrubs generally have a cooling effect on permafrost in the summer, largely caused by the shrub canopy shading the soil. However, summertime cooling can be counteracted by a warming effect in winter, caused by the trapping of blowing snow by shrubs, which leads to increased snow depths. In addition to these commonly observed effects, both observations and models show that other local factors such as climate, soil, snow, and disturbances can interact to cause contrasting dominant effects on permafrost temperatures. For example, shrubs that protrude through the snowpack have been observed to cool permafrost in winter via thermal bridging between the air above the snow and the soil below. However, at other research sites, protruding shrubs lower the surface albedo and cause earlier snowmelt in spring, amplifying permafrost thaw by exposing the soil to thawing earlier. Protruding shrubs have also been observed to induce snow melt in autumn, creating ice layers at the snow surface that prevent further snow accumulation and eliminate the ability of shrubs to trap blowing snow, thereby reducing the winter warming effect. While we understand the physical processes that lead to these effects, we cannot explain why we observe different effects between sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Utah FORGE: Neubrex Well 16B(78)-32 DAS Data - April, 2024

This dataset comprises Distributed Acoustic Sensing (DAS) data collected from the Utah FORGE monitoring well 16B(78)-32 (the producer well) during hydraulic fracture stimulation operations conducted in April 2024. The data were acquired continuously over the stimulation period at a temporal sampling rate of 10,000 Hz (10 kS/s) and a spatial resolution of approximately 3.35 feet (1.02109 meters). The measurements were captured using a Neubrex NBX-S4100 Time Gated Digital DAS interrogator unit connected to a single-mode fiber optic cable, which was permanently installed within the casing string. All recorded channels correspond to downhole segments of the fiber optic cable, from a measured depth (MD) of 5,369.35 feet to 10,352.11 feet. The DAS data reflect raw acoustic energy generated by physical processes within and surrounding the well during stimulation activities at wells 16A(78)-32 and 16B(78)-32. These data have potential applications in analyzing cross-well strain, far-field strain rates (including microseismic activity), induced seismicity, and seismic imaging. Metadata embedded in the attributes of the HDF5 files include detailed information on the measured depths of the channels, interrogation parameters, and other acquisition details. The dataset also includes a recording of a seminar held on September 19, 2024, where Neubrex's Chief Operating Officer presented insights into the data collection, analysis, and preliminary findings. The raw data files, stored in HDF5 format, are organized chronologically according to the recording intervals from April 9 to April 24, 2024, with each file corresponding to a 12-second recording interval.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Marine aerosol generation experiments in the High Arctic during summertime

The rapidly warming Arctic has transitioned to thinner sea ice which fractures, producing leads. Few studies have investigated Arctic sea spray aerosol (SSA) produced from open ocean, leads, and melt ponds, which vary in salinity and organic and microbial community composition. A marine aerosol reference tank was deployed aboard an icebreaker to the Arctic Ocean during August–September 2018 to study SSA generated from locally collected surface waters. Aerosol generation experiments were carried out using water collected from the marginal ice zone, a human-made hole in sea ice near the North Pole, and both lead and melt pond water during an ice floe drift period. Salinity, chlorophyll a, organic carbon, nitrogen, and microbial community composition were measured. Eukaryotic plankton and bacterial abundance were elevated in experimental water from the marginal ice zone, but the relative contributions from major eukaryotic taxonomic groups varied little across the experiments. The chemical composition of individual SSA particles was analyzed using Raman microspectroscopy and computer-controlled scanning electron microscopy with energy-dispersive X-ray spectroscopy. Individual sea salt aerosol, primary organic aerosol, and mineral dust particles were observed. Sea salt aerosol constituted 44–95% of individual submicrometer and 68–100% of supermicrometer particles, by number, generated during each experiment. Carbon was detected in 85%, by number, of the individual sea salt particles, with visible organic coatings. Carbohydrates were detected in 72% of particles, by number, with smaller contributions from long-chain fatty acids (13%) and siliceous material (15%). SSA generated from melt pond water contained only long-chain fatty acids and siliceous material. Quantification of the ice-nucleating activity showed that locally produced SSA may define the High Arctic background ice-nucleating particle population, but cannot account for the peak atmospheric concentrations observed. As the Arctic warms, the increasing SSA emissions have a complex dependence on changing biological and physical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

From material properties to multiscale modeling to improve lithium-ion energy storage safety

Energy storage using lithium-ion cells dominates consumer electronics and is rapidly becoming predominant in electric vehicles and grid-scale energy storage, but the high energy densities attained lead to the potential for release of this stored chemical energy. This article introduces some of the paths by which this energy might be unintentionally released, relating cell material properties to the physical processes associated with this potential release. The selected paths focus on the anode–electrolyte and cathode–electrolyte interactions that are of typical concern for current and near-future systems. Relevant material processes include bulk phase transformations, bulk diffusion, surface reactions, transport limitations across insulating passivation layers, and the potential for more complex material structures to enhance safety. We also discuss the development, parameterization, and application of predictive models for this energy release and give examples of the application of these models to gain further insight into the development of safer energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2024

Elucidating the complex interplay between thermodynamics, kinetics, and electrochemistry in battery electrodes through phase-field modeling

Abstract This article highlights applications of phase-field modeling to electrochemical systems, with a focus on battery electrodes. We first provide an overview on the physical processes involved in electrochemical systems and applications of the phase-field approach to understand the thermodynamic and kinetic mechanisms underlying these processes. We employ two examples to highlight how realistic thermodynamics and kinetics can naturally be incorporated into phase-field modeling of electrochemical processes. One is a composite battery cathode with an intercalation compound (Li x FePO 4 ) as the electrochemically active material, and the other is a displacement reaction compound (Li–Cu–TiS 2 ). With the input parameters mostly from atomistic calculations and experimental measurements, phase-field simulations allowed us to untangle the interactions among transport, reaction, electricity, chemistry, and thermodynamics that lead to highly complex evolution of the materials within battery electrodes. The implications of these observations for battery performance and degradation are discussed. Graphical abstract

Andrews, W. Beck (ORCID:0000000287824621)↗
DOE OSTI2023

Combined Data and Deep Learning Model Uncertainties: An Application to the Measurement of Solid Fuel Regression Rate

In complex physical process characterization, such as the measurement of the regression rate for solid hybrid rocket fuels, where both the observation data and the model used have uncertainties originating from multiple sources, combining these in a systematic way for quantities of interest (QoI) remains a challenge. In this paper, we present a forward propagation uncertainty quantification (UQ) process to produce a probabilistic distribution for the observed regression rate r. We characterized two input data uncertainty sources from the experiment (the distortion from the camera U c and the non-zero-angle fuel placement U Y ), the prediction and model form uncertainty from the deep neural network (U m ), as well as the variability from the manually segmented images used for training it (U s ). Here, we conducted seven case studies on combinations of these uncertainty sources with the model form uncertainty. The main contribution of this paper is the investigation and inclusion of the experimental image data uncertainties involved, and how to include them in a workflow when the QoI is the result of multiple sequential processes.

42 ENGINEERING↗