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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Simulation of the Universal-Time Diurnal Variation of the Global Electric Circuit Charging Rate

A global lightning model that includes diurnal and annual lightning variation, and total flash density versus latitude for each major land and ocean, has been used as the basis for simulating the global electric circuit charging rate. A particular objective has been to reconcile the difference in amplitude ratios [AR=(max-min)/mean] between global lightning diurnal variation (AR approximately equals 0.8) and the diurnal variation of typical atmospheric potential gradient curves (AR approximately equals 0.35). A constraint on the simulation is that the annual mean charging current should be about 1000 A. The global lightning model shows that negative ground flashes can contribute, at most, about 10-15% of the required current. For the purpose of the charging rate simulation, it was assumed that each ground flash contributes 5 C to the charging process. It was necessary to assume that all electrified clouds contribute to charging by means other than lightning, that the total flash rate can serve as an indirect indicator of the rate of charge transfer, and that oceanic electrified clouds contribute to charging even though they are relatively inefficient in producing lightning. It was also found necessary to add a diurnally invariant charging current component. By trial and error it was found that charging rate diurnal variation curves could be produced with amplitude ratios and general shapes similar to those of the potential gradient diurnal variation curves measured over ocean and arctic regions during voyages of the Carnegie Institute research vessels. The comparisons were made for the northern winter (Nov.-Feb.), the equinox (Mar., Apr., Sept., Oct.), the northern summer (May-Aug.), and the whole year.

Mackerras, David↗
DOE OSTI2025

Dual-season thermal energy storage-integrated heat pump system for load shifting: experiments, modeling and nationwide analysis

Here, this paper proposes and validates a dual-season thermal energy storage-integrated heat pump (TES-HP) system that shifts building electric load in both cooling and heating modes using a single phase-change TES. The design uses the TES as a heat sink for the condenser in summer and a heat source for the evaporator in winter, thereby reducing on-peak electric demand while ensuring compatible with existing air-distribution systems. A 14-kW TES-HP prototype with six operating modes and novel refrigerant charge management strategies was experimentally tested under varied conditions. Subsequently, data-driven polynomial performance curves were developed and validated against experiments, then coupled with a phase change material (PCM) model and a calibrated building model within a rule-based controller. Single-day case studies demonstrated effective on-peak demand reduction while maintaining thermal comfort. During cooling, hourly power was lowered by up to 1.5 kW; in heating, average hourly power decreased from over 3.5 kW to 1.8 kW, compared to an HP-only system, achieving 64.5 % load shifting, and the need for resistance heating was eliminated. Seasonal simulations showed typical on-peak electricity savings of 25–35 % in cooling and 40–65 % in heating, with the largest benefits on the hottest and coldest days. Extended response-surface analysis and nationwide mapping quantified load shifting as functions of ambient and TES temperatures, revealing a seasonal trade-off in TES phase-change temperature. These results demonstrate the TES-HP system as a practical and scalable solution for grid-interactive buildings that reduces on-peak demand and electricity use while maintaining thermal comfort and enhancing grid flexibility and reliability.

Grid-interactive buildings↗
NASA NTRS1988

CAMELOT 2: Personnel transport between Earth and Mars

A summary of the second phase of a design study fo a cycling spacecraft for regular and frequency personnel transport between Earth and a Mars base is presented. The first-phase study, called project CAMELOT, was a mission analysis and configuration design and was completed by the Space Systems Design class at the University of Michigan in the winter term, 1987. In the second phase, the configuration and component design has been developed by the Space Systems Design class in the winter term, 1988, beyond the initial configuration study. Analysis has led to numerous design modifications and improvements, as well as providing more detailed system definition. Major components of the second phase study include innovative detailed designs such as an interface between the rotating and non-rotating portions of the spacecraft, an elevator system that changes orientation to eliminate Coriolis forces, an electromagnetic radiation shield that significantly reduces the mass of the spacecraft, and a detailed assembly sequence and cost analysis. In addition, modifications to the propulsion and the power generation subsystems, taxi-docking facilities, and internal layout design have led to a more efficient, more reliable, and more comfortable vehicle. Finite-element stress and dynamic analysis has verified much of the system and indicates the validity of the design. Computer simulation of many moving components, including torus rotation, elevator and interface operations, and attitude control mechanisms further validate and support the various systems.

Source record↗
DOE OSTI2023

Anthropogenic Aerosols Contribute to the Recent Decline in Precipitation Over the U.S. Southwest

Abstract The winter‐spring precipitation over the Southwestern United States (SWUS) decreased since 1980. It is frequently attributed to Pacific internal decadal variability, but recent studies found anthropogenic aerosols (AA) can also induce a transition to a negative Pacific Decadal Variability (PDV) phase. We revisit the attribution of SWUS drying by quantifying the contributions of anthropogenically forced decadal Pacific Sea Surface Temperatures (SSTs). Applying a low‐frequency component analysis to observations, Community Earth System Model version 2 (CESM2) all‐forcings and single‐forcing large ensembles, we find up to 42% of the observed precipitation trend to be related to the AA‐induced negative PDV‐like pattern, which is driven by the emission shift from the Western to the Eastern Hemisphere. In CESM2, other radiative forcings counteract the influence of AA, but it remains unclear whether the model correctly simulates this balance. This implies that the near‐future trajectories of these forcings, in particular Asian aerosols, are important for projections of SWUS precipitation.

Geology↗
NASA NTRS2018

Satellite Remote Sensing Estimation of River Discharge: Application to the Yukon River Alaska

A methodology based on general hydraulic relations for rivers has been developed to estimate the discharge (flow rate) of rivers using satellite remote sensing observations. The estimates of discharge, flow depth, and flow velocity are derived from remotely observed water surface area, water surface slope, and water surface height, and demonstrated for two reaches of the Yukon River in Alaska, at Eagle (reach length 34.7 km) and near Stevens Village (reach length 38.3 km). The method is based on fundamental equations of hydraulic flow resistance in rivers, including the Manning equation and the Prandtl-von Karman universal velocity distribution equation. The method employs some new hydraulic relations to help define flow resistance and height of the zero flow boundary in the channel. Estimates are made both with and without calibration. The water surface area of the river reach is measured by using a provisional version of the U.S. Geological Survey (USGS) Landsat based product named Dynamic Surface Water Extent (DSWE). The water surface height and slope measurements require a self-consistent datum, and are derived from observations from the Jason-2 satellite altimeter mission. At both reach locations, the Jason-2 radar altimeter non-winter heights consistently tracked the stage recorded at USGS streamgages with a standard deviation of differences (error) during the non-winter periods of less than 7%. Part of the error may be due to differences in the gage and altimeter crossing locations with respect to the range of stage change and the response to changes in discharge at the upstream and downstream locations. For the non-winter periods, the radar derived slope estimates (mean = 0.0003) were constant over the mission lifetime, and in agreement with previously measured USGS water surface slopes and slopes determined from USGS topographic maps. The accuracy of the mean of the uncalibrated daily estimates of discharge varied between reaches, ranging from 13% near Stevens Village (N = 90) to −21% at Eagle (N = 246) based on the absolute error, and 5% to −6% based on the error of the log of the estimates. Calibrating to the mean of USGS daily discharge estimates from the streamflow rating for the same period of record at each streamgage resulted in mean absolute errors ranging from 1% to 2%, and log errors ranging from 1% or less. The error pattern of the estimates shows that without calibration, even though the mean is well simulated, the high and low end values over the range of estimates may have significant bias.

Bjerklie, David M.↗
DOE OSTI2026

Theory uncertainties of the irreducible background to VBF Higgs production

Higgs boson production through gluon fusion in association with two jets is an irreducible background to Higgs boson production through vector boson fusion, one of the most important channels for analyzing and understanding the Higgs boson properties at the Large Hadron Collider. Despite a range of available simulation tools, precise predictions for the corresponding final states are notoriously hard to achieve. Using state-of-the-art fixed-order calculations as the baseline for a comparison, we perform a detailed study of similarities and differences in existing event generators. We provide consistent setups for the simulations that can be used to obtain identical parametric precision in various programs used by experiments. We find that NLO calculations for the two-jet final state are essential to achieve reliable predictions.

Chen, Xuan [Shandong U.] (ORCID:0000000167722196)↗
NASA NTRS2023

Importance of Atmospheric Feedbacks in Simulating the Seasonal Cycle of the Antarctic Sea Ice and Its Response to Perturbations

The seasonal cycle of the Antarctic sea ice extent is largely controlled by the evolution of the insolation received at the top of the atmosphere. However, sea ice processes and feedbacks with the ocean and the atmosphere can modulate this seasonal cycle. Here, the atmospheric feedbacks are quantified in a series of idealized sensitivity experiments performed with an eddy-permitting (1/4°) NEMO-LIM3 Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM 2 regional atmospheric model. In these experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake/release upon sea ice growth/melt, ice dynamics and surface albedo. We show that the changes in surface heat fluxes are very different between the configurations driven by the reanalysis and those coupled to the atmosphere. Atmospheric feedbacks enhance the response of the modelled winter ice extent to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere. By contrast, the atmospheric feedbacks can damp the impact of the perturbations affecting the heat conductivity through sea ice.

Atmospheric feedbacks↗
DOE OSTI2021

Seasonal Cycle of Idealized Polar Clouds: Large Eddy Simulations Driven by a GCM

The uncertainty in polar cloud feedbacks calls for process understanding of the cloud response to climate warming. As an initial step toward improved process understanding, we investigate the seasonal cycle of polar clouds in the current climate by adopting a novel modeling framework using large eddy simulations (LES), which explicitly resolve cloud dynamics. Resolved horizontal and vertical advection of heat and moisture from an idealized GCM are prescribed as forcing in the LES. The LES are also forced with prescribed sea ice thickness, but surface temperature, atmospheric temperature, and moisture evolve freely without nudging. A semigray radiative transfer scheme without water vapor and cloud feedbacks allows the GCM and LES to achieve closed energy budgets more easily than would be possible with more complex schemes. This enables the mean states in the two models to be consistently compared, without the added complications from interaction with more comprehensive radiation. Furthermore, we show that the LES closely follow the GCM seasonal cycle, and the seasonal cycle of low-level clouds in the LES resembles observations: maximum cloud liquid occurs in late summer and early autumn, and winter clouds are dominated by ice in the upper troposphere. Large-scale advection of moisture provides the main source of water vapor for the liquid-containing clouds in summer, while a temperature advection peak in winter makes the atmosphere relatively dry and reduces cloud condensate. The framework we develop and employ can be used broadly for studying cloud processes and the response of polar clouds to climate warming.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Mercury Conditions for the MESSENGER Mission Simulated in High- Solar-Radiation Vacuum Tests

The MESSENGER (Mercury Surface, Space Environment, Geochemistry, and Ranging) spacecraft, planned for launch in March 2004, will perform two flybys of Mercury before entering a year-long orbit of the planet in September 2009. The mission will provide opportunities for detailed characterization of the surface, interior, atmosphere, and magnetosphere of the closest planet to the Sun. The NASA Glenn Research Center and the MESSENGER spacecraft integrator, the Johns Hopkins University Applied Physics Laboratory, have partnered under a Space Act Agreement to characterize a variety of critical components and materials under simulated conditions expected near Mercury. Glenn's Vacuum Facility 6, which is equipped with a solar simulator, can simulate the vacuum and high solar radiation anticipated in Mercury orbit. The MESSENGER test hardware includes a variety of materials and components that are being characterized during the Tank 6 vacuum tests, where the hardware will be exposed to up to 11 suns insolation, simulating conditions expected in Mercury orbit. In 2002, ten solar vacuum tests were conducted, including beginning of life, end of life, backside exposure, and solar panel thermal shock cycling tests. Components tested include candidate solar array panels, sensors, thermal shielding materials, and communication devices. As an example, for the solar panel thermal shock cycling test, two candidate solar array panels were suspended on a lift mechanism that lowered the panels into a liquid-nitrogen-cooled box. After reaching -140 C, the panels were then lifted out of the box and exposed to the equivalent of 6 suns (8.1 kilowatts per square meters). After five cold soak/heating cycles were completed successfully, there was no apparent degradation in panel performance. An anticipated 100-hr thermal shield life test is planned for autumn, followed by solar panel flight qualification tests in winter. Glenn's ongoing support to the MESSENGER program has been instrumental in identifying design solutions and validating thermal performance models under a very aggressive development schedule. The test data have assisted Johns Hopkins engineers in selecting a flight solar array vendor and a thermal shield design. MESSENGER is one in a series of missions in NASA's Discovery Program. Infrared thermography provides data on the thermal gradients in the MESSENGER components during high solar insolation vacuum testing.

Wong, Wayne A.↗
DOE OSTI2020

MJO Teleconnections over the PNA Region in Climate Models. Part II: Impacts of the MJO and Basic State

In an assessment of 29 global climate models (GCMs), Part I of this study identified biases in boreal winter MJO teleconnections in anomalous 500-hPa geopotential height over the Pacific–North America (PNA) region that are common to many models: an eastward shift, a longer persistence, and a larger amplitude. In Part II, we explore the relationships of the teleconnection metrics developed in Part I with several existing and newly developed MJO and basic state (the mean subtropical westerly jet) metrics. The MJO and basic state diagnostics indicate that the MJO is generally weaker and less coherent and propagates faster in models compared to observations. The mean subtropical jet also exhibits notable biases such as too strong amplitude, excessive eastward extension, or southward shift. The following relationships are found to be robust among the models: 1) models with a faster MJO propagation tend to produce weaker teleconnections; 2) models with a less coherent eastward MJO propagation tend to simulate more persistent MJO teleconnections; 3) models with a stronger westerly jet produce stronger and eastward shifted MJO teleconnections; 4) models with an eastward extended jet produce an eastward shift in MJO teleconnections; and 5) models with a southward shifted jet produce stronger MJO teleconnections. The results are supported by linear baroclinic model experiments. Our results suggest that the larger amplitude and eastward shift biases in GCM MJO teleconnections can be attributed to the biases in the westerly jet, and that the longer persistence bias is likely due to the lack of coherent eastward MJO propagation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Diagnosing Near-Surface Model Errors with Candidate Physics Parameterization Schemes for the Multiphysics Rapid Refresh Forecast System (RRFS) Ensemble during Winter over the Northeastern United States and Southern Great Plains

Abstract During the winter of 2020/21 an ensemble of FV3-LAM forecasts was produced over the contiguous United States for the Winter Weather Experiment using five physics suites. These forecasts are evaluated with the goal of optimizing physics parameterizations within the future operational Rapid Refresh Forecast System (RRFS) in the Unified Forecast System (UFS) realm and for selecting suitable physics suites for a multiphysics RRFS ensemble. The five physics suites have different combinations of land surface models (LSMs), planetary boundary layer (PBL) parameterizations, and surface layer schemes, chosen from those used in current and possible future operational systems and likely to be supported in the operational UFS. Full-season evaluation reveals a persistent near-surface cold bias in the U.S. Northeast from one suite and a nighttime warm bias in the southern Great Plains in another suite, while other suites have smaller biases. A representative case is chosen to diagnose the cause for each of these biases using sensitivity simulations with different physics combinations or modified parameters and verified with additional mesonet observations. The cold bias in the Northeast is attributed to aspects of the Noah-MP LSM over snow cover, where Noah-MP simulates lower soil water content, and thus lower thermal conductivity than other LSMs, leading to less upward ground heat flux during nighttime and consequently lower surface temperature. The nighttime warm bias found in the southern Great Plains is attributed to overestimation of vertical mixing in the K -profile-based eddy-diffusivity mass-flux (K-EDMF) PBL scheme and insufficient land–atmospheric coupling from the GFS surface layer scheme over short vegetation. A few key parameters driving these systematic biases are identified.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models

Annual burned areas in the United States have increased 2-fold during the past decades. With more large fires resulting in more emissions of fine particulate matter, an accurate prediction of fire emissions is critical for quantifying the impacts of fires on air quality, human health, and climate. This study aims to construct a machine learning (ML) model with game-theory interpretation to predict monthly fire emissions over the contiguous US (CONUS) and to understand the controlling factors of fire emissions. The optimized ML model is used to diagnose the process-based models in the Fire Modeling Intercomparison Project (FireMIP) to inform future development. Results show promising performance for the ML model, Community Land Model (CLM), and Joint UK Land Environment Simulator-Interactive Fire And Emission Algorithm For Natural Environments (JULES-INFERNO) in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over the CONUS. Regional analysis shows that only the ML model and CLM simulate the realistic interannual variability of fire emissions for most of the subregions (r >0.95 for ML and r =0.14~0.70 for CLM), except for Mediterranean California, where all the models perform poorly (r =0.74 for ML and r <0.30 for the FireMIP models). Regarding seasonality, most models capture the peak emission in July over the western US. However, all models except for the ML model fail to reproduce the bimodal peaks in July and October over Mediterranean California, which may be explained by the smaller wind speeds of the atmospheric forcing data during Santa Ana wind events and limitations in model parameterizations for capturing the effects of Santa Ana winds on fire activity. Furthermore, most models struggle to capture the spring peak in emissions in the southeastern US, probably due to underrepresentation of human effects and the influences of winter dryness on fires in the models. As for extreme events, both the ML model and CLM successfully reproduce the frequency map of extreme emission occurrence but overestimate the number of months with extremely large fire emissions. Comparing the fire PM 2.5 emissions from the ML model with process-based fire models highlights their strengths and uncertainties for regional analysis and prediction and provides useful insights into future directions for model improvements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

The stratopause semiannual oscillation in the NCAR Community Climate Model

The middle atmospheric version of the NCAR Community Climate Model (CCM2) has been used to study the development of the equatorial semiannual oscillation (SAO) in the stratosphere. The model domain extends from the ground to about 80 km, with a vertical resolution of 1 km. Transport of nitrous oxide (N2O) with simplified photochemistry is included in the calculation to illustrate the influence of tropical circulations on the distribution of trace species. Diagnosis of model output reveals two distinct phases in the evolution of the zonal mean state on the equator. In early December, a strong and broad easterly jet appears near the stratopause in connection with a midlatitude wave event (sudden stratospheric warming) that reverses the winter westerlies of the Northern Hemisphere throughout the upper stratosphere. When the wave forcing dies out, the radiative drive allows the westerlies to recover at midlatitudes, while easterlies persist in the tropics. The resulting strong meridional gradient of the zonal mean wind provides favorable conditions for the development of inertial instability at lower latitudes. The meridional circulation associated with the instability shapes the 'nose' of the easterly jet, reducing the extension of the unstable region. In equinoctial conditions, a jet of westerlies appears in the lower equatorial mesosphere and descends to lower altitudes; positive accelerations associated with the descending westerlies are due primarily to Kelvin waves. The descent of the westerly jet does not reproduce well the observed behavior of the SAO westerly phase, either in amplitude or in the extent of downward propagation. As a consequence, the model does not simulate the 'double peak' observed in the tropical distribution of N2O. Comparison of wave amplitudes in the model with those derived from satellite observations shows that the calculated amplitudes are larger than observed in the upper stratosphere. It follows that inadequate Kelvin wave forcing is not the cause of the weak westerly phase in the model, and that some other mechanism must be responsible for the generation of the strong westerly phase observed.

Sassi, Fabrizio↗
NASA NTRS2017

An Evaluation of Teleconnections Over the United States in an Ensemble of AMIP Simulations with the MERRA-2 Configuration of the GEOS Atmospheric Model

The atmospheric general circulation model that is used in NASA's Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) is evaluated with respect to the relationship between large-scale teleconnection patterns and daily temperature and precipitation over the United States (US) using a ten-member ensemble of simulations, referred to as M2AMIP. A focus is placed on four teleconnection patterns that are known to influence weather and climate in the US: El Nino Southern Oscillation, the Pacific Decadal Oscillation, the North Atlantic Oscillation, and the Pacific-North American Pattern. The monthly and seasonal indices associated with the patterns are correlated with daily temperature and precipitation statistics including: (i) monthly mean 2 m temperature and precipitation, (ii) the frequency of extreme temperature events at the 90th, 95th, and 99th percentiles, and (iii) the frequency and intensity of extreme precipitation events classified at the 90th, 95th, and 99th percentiles.Correlations obtained with M2AMIP data and thus the strength of teleconnections in the free-running model are evaluated through comparison against corresponding correlations computed from observations and from MERRA-2. Overall, the strongest teleconnections in all datasets occur during the winter and coincide with the largest agreement between the observations, MERRA-2, and M2AMIP. When M2AMIP does capture the correlation seen in observations, there is a tendency for the spatial extent to be exaggerated. The weakest agreement between the data sources, for all teleconnection patterns, is in the correlation with extreme precipitation; however there are discrepancies between the datasets in the number of days with at least 1 mm of precipitation: M2AMIP has too few days with precipitation in the Northwest and the Northern Great Plains and too many days in the Northeast. In JJA, M2AMIP has too few days with precipitation in the western two-thirds of the country and too many days with precipitation along the east coast.

JJA↗
DOE OSTI2020

Intra-Annual and Interannual Dynamics of Evaporation Over Western Lake Erie

Evaporation (E) is a critical component of the water and energy budget in lake systems yet is challenging to quantify directly and continuously. We examined the magnitude and changes of E and its drivers over Lake Erie - the shallowest and most southern lake of the Laurentian Great Lakes. We deployed two eddy-covariance tower sites in the western Lake Erie Basin - one located nearshore (CB) and one offshore (LI) - from September 2011 through May 2016. Monthly E varied from 5 to 120 mm, with maximum E occurring in August–October. The annual E was 635 ± 42 (±SD) mm at CB and 604 ± 32 mm at LI. Mean winter (October–March) E was 189 ± 61 mm at CB and 178 ± 25 mm at LI, accounting for 29.8% and 29.4% of annual E. Mean daily E was 1.8 mm during the coldest month (January) and 7.4 mm in the warmest month (July). Monthly E exhibited a strong positive linear relationship to the product of wind speed and vapor pressure deficit. Pronounced seasonal patterns in surface energy fluxes were observed with a 2-month lag in E from R n , due to the lake's heat storage. This lag was shorter than reports regarding other Great Lakes. Difference in E between the offshore and nearshore sites reflected within-lake spatial heterogeneity, likely attributable to climatic and bathymetric differences between them. These findings suggest that predictive models need to consider lake-specific heat storage and spatial heterogeneity in order to accurately simulate lake E and its seasonal dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Enhanced Habitability on High Obliquity Bodies near the Outer Edge of the Habitable Zone of Sun-Like Stars

High obliquity planets represent potentially extreme limits of terrestrial climate, as they exhibit large seasonality, a reversed annual-mean pole-to-equator gradient of stellar heating, and novel cryospheres. A suite of 3D global climate model simulations is performed for low and high obliquity planets with various stellar fluxes, CO2 concentrations, and initial conditions to explore the propensity for high obliquity climates to undergo global glaciation. We also simulate planets with thick CO2 or H2 atmospheres, such as those expected to develop near or beyond the outer edge of the habitable zone. We show that high obliquity planets are hotter than their low obliquity counterparts due to ice-albedo feedbacks for cold climates, and water vapor in warm climates. We suggest that the water vapor greenhouse trapping is greater on high obliquity bodies for a given global-mean temperature due to the different dynamical regimes that occur between the two states. While equatorial ice belts are stable at high obliquity in some climate regimes, it is substantially harder to achieve global glaciation than for a low obliquity planet. Temperate polar conditions can be present at high obliquity at forcings for which low obliquity planets would be in a hard snowball state. Furthermore, open ocean can persist even in the winter hemisphere and when global-mean temperatures are well below freezing. However, the influence of obliquity diminishes for dense atmospheres, in agreement with calculations from 1D energy balance models.

Planet and satellite atmospheres↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Cubespark: A New Satellite-Based 3d Lightning Observing Concept

Legacy and current space-based optical lightning detectors are insensitive to small and dim pulses that make up much of the lightning activity produced by severe storms. Moreover, lightning flashes produced at low altitudes within optically thick clouds are severely under-detected by current optical detectors. Lastly, there is currently no capability to characterize the 3D structure of lightning both day and night at the global scale, yet this information is critical for identifying lightning produced in updraft regions, including lightning occurring in overshooting tops, which is a distinctive signature of severe weather. Global 3D lightning information is also critical for understanding the vertical distribution of NOx production and identifying anomalously electrified storms. Furthermore, the vertical distribution of lightning has implications for how microphysical (e.g., ice-based) and thermodynamical (e.g., latent heat release) processes vary regionally, as well as seasonally – e.g., winter lightning typically occurs at lower altitudes than summer lightning and is often associated with tall, man-made structures. Finally, global-scale 3D lightning observations would directly provide flash type (i.e., CG or IC) information that is very useful in all of the studies mentioned in this paragraph and is fundamental in identifying/documenting deleterious CG-caused impacts (e.g., wildfires, power-outages, crop and property damage, and associated insurance claims). A new, satellite mission concept called CubeSpark is being designed to address these shortcomings and fill this measurement gap by providing novel 3D observations of total lightning activity. CubeSpark will utilize a constellation of low-Earth orbiting small satellites that make radio frequency (RF) and bi-spectral optical measurements of lightning. Two options for combining these measurements to retrieve the 3D location of lightning are considered with corresponding measurement simulators built to understand the level of detail and viability of each approach. Although the level of detail varies for each combined measurement approach, results indicate that a 3D location accuracy of < 1-2 km in each dimension is feasible across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high-latitudes.

lightning↗