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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predicting Li-ion Battery Performance for Impurity-doped NMC Cathodes Using Deep Learning

With the electric vehicle (EV) market expansion and the energy sector's shift towards electrification, the demand for battery metals, including lithium (Li), cobalt (Co), and nickel (Ni), is set to surpass supply. A critical knowledge gap exists in the purity standards for battery precursors and the impact of impurities on battery performance. Addressing this, our study employs a Deep Machine Learning (DL) based multi-objective optimization approach to interpret the relationship between metal impurities in domestic battery resources and their effects on battery performance. We analyze experimental data from Li-ion batteries with NMC (Nickel-Manganese-Cobalt oxide) cathodes over 1000 cycles, representing approximately ~6-8 months of operation, to establish a baseline of performance without impurities. Leveraging this data, we develop a Physics-Informed Deep Learning (PIDL) framework to extend our findings to cases that include metal impurities (e.g., Fe, Cu, Al) ranging from (0.001 - 0.01) %, respectively. By incorporating physics-based features, our PIDL model can accurately estimate the performance of NMC cathodes doped with various metal impurities to provide rapid design decisions. This research paves the way for informed decisions in Li-ion battery material design and optimization, ensuring the sustainable growth of the EV market and the broader energy sector.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Power Generation Impacts of Spacecraft Albedo During the Artemis I Mission

The Orion spacecraft is a deep space, crewed vehicle designed to support NASA’s Artemis exploration campaign. NASA successfully completed an uncrewed test flight of the Orion spacecraft during the 26-day Artemis I mission in November and December 2022. At numerous points during the mission, a small but measurable amount of power was generated by a solar array wing (SAW) while pointed away from the sun. This presentation discusses an analysis of in-flight telemetry data to characterize this condition. Various potential sources of reflected light were examined, with self-reflection off the spacecraft itself having the largest impact. Different array and attitude configurations were studied to characterize the array response to this spacecraft albedo.

Albedo↗
NASA NTRS2005

Sulfate Deposition in Regolith Exposed in Trenches on the Plains Between the Spirit Landing Site and Columbia Hills in Gusev Crater, Mars

During its exploration within Gusev crater between sol 01 and sol 158, the Spirit rover dug three trenches (Fig. 1) to expose the subsurface regolith [1, 2, 9]. Laguna trench (approx. 6 cm deep, approx.203 m from the rim of Bonneville crater) was dug in Laguna Hollow at the boundary of the impact ejecta from Bonneville crater and the surrounding plains. The Big Hole trench (approx. 6-7 cm deep) and The Boroughs trench (approx. 11 cm deep) were dug in the plains between the Bonneville crater and the Columbia Hills (approx.556 m and approx.1698 m from the rim of Bonneville crater respectively). The top, wall and floor regolith of the three trenches were investigated using the entire set of Athena scientific instruments [10].

Wang, Alian↗
DOE OSTI2025

Resolution dependence of the turbulent atmospheric boundary layer in global storm-resolving climate simulations

The current generation of state-of-the-art global climate models are being run at increasingly higher horizontal resolutions, with the goal of resolving organised deep convection explicitly. How a kilometre-scale resolution impacts the representation of the atmospheric boundary layer is, however, not well known. Using statistical analysis on global fields as well as high-frequency data at selected locations, produced with the Integrated Forecasting System (IFS) model for the Next Generation Earth-system Models (nextGEMS) project, we investigate the horizontal resolution dependence of some boundary-layer processes. We find that a change in resolution from 9 to 2.8 km causes no substantial changes to boundary-layer properties and processes at most of the locations studied, although some global changes are detected that indicate circulation changes. Small changes to the boundary-layer depth and structure are found in the Tropics. The short simulation length and lack of data for optimal boundary-layer analysis limits the conclusions, especially in relation to the connection between the boundary layer and the atmosphere general circulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Transition of Large-Scale Environmental Conditions and Characteristics of Four Rainfall Types Observed by S-PolKa During the MJO-1 Active Phase of DYNAMO/CINDY/AMIE

Analyses of National Center for Atmospheric Research (NCAR) S-PolKa dual-polarization radar data and ERA5 reanalysis fields indicate gradual changes in convection characteristics and large-scale environmental conditions during a central Indian Ocean Madden-Julian Oscillation (MJO) event observed by the DYNAMO/CINDY/AMIE field campaigns in late October 2011 (MJO-1). Examination of four rainfall types (isolated convective cores, convective, mixed, and stratiform) reveals a transition of convection characteristics (i.e., areal coverage and depth) between distinct 5-day environmental periods at the beginning and end of this ~2-week MJO active phase. A shift toward less frequent rainfall covering less of the radar domain for all four rainfall types occurs when large-scale lower-tropospheric dry air advects into the region with the westerly wind burst (WWB). Drier and warmer lower-free-tropospheric conditions associated with the WWB contribute to increased large-scale surface-based convective inhibition (CIN), surface-based convective available potential energy (CAPE), and cloud base heights. A thermodynamic budget analysis indicates reduced surface heat fluxes contribute to the increased surface-based CAPE. Greater CAPE at the end of MJO-1 coincides with deeper 50-dBZ convective echoes, while decreased 10-dBZ depth for all rainfall types corresponds in time with WWB-related dry-air advection. Increased (decreased) reflectivity values in the lower-level vertical reflectivity distribution of convective (stratiform) precipitation indicate increased (decreased) convective (stratiform) intensities when the WWB is present. The opposite depth changes for convective echoes and opposite shifts in convective and stratiform precipitation intensities underscore how the WWB can have differing impacts at different reflectivity thresholds and stages of the deep convection lifecycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Depth dependence of climatic controls on soil microbial community activity and composition

Abstract Subsoil microbiomes play important roles in soil carbon and nutrient cycling, yet our understanding of the controls on subsoil microbial communities is limited. Here, we investigated the direct (mean annual temperature and precipitation) and indirect (soil chemistry) effects of climate on microbiome composition and extracellular enzyme activity throughout the soil profile across two elevation-bioclimatic gradients in central California, USA. We found that microbiome composition changes and activity decreases with depth. Across these sites, the direct influence of climate on microbiome composition and activity was relatively lower at depth. Furthermore, we found that certain microbial taxa change in relative abundance over large temperature and precipitation gradients only in specific soil horizons, highlighting the depth dependence of the climatic controls on microbiome composition. Our finding that the direct impacts of climate are muted at depth suggests that deep soil microbiomes may lag in their acclimation to new temperatures with a changing climate.

16S rRNA↗
DOE OSTI2020

Deep convolutional neural networks for multi-scale time-series classification and application to tokamak disruption prediction using raw, high temporal resolution diagnostic data

In this paper we discuss recent advances in deep convolutional neural networks (CNN) for sequence learning, which allow identifying long-range, multi-scale phenomena in long sequences, such as those found in fusion plasmas. We point out several benefits of these deep CNN architectures, such as not requiring experts such as physicists to hand-craft input data features, the ability to capture longer range dependencies compared to the more common sequence neural networks (recurrent neural networks like long short-term memory (LSTM) networks), and the comparative computational efficiency. We apply this neural network architecture to the popular problem of disruption prediction in fusion energy tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. Initial results trained on a large ECEi dataset show promise, achieving an F 1 -score of ~91% on individual time-slices using only the ECEi data. This indicates the ECEi diagnostic by itself can be sensitive to a number of pre-disruption markers useful for predicting disruptions on timescales not only for mitigation but also avoidance. Future opportunities for utilizing these deep CNN architectures with fusion data are outlined, including impact of recent upgrades to the ECEi diagnostic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1979

Initial observations of the nightside ionosphere of Venus from Pioneer Venus Orbiter radio occultations

Results of radio occultation measurements of electron density profiles of the nightside ionosphere of Venus at solar zenith angles from 90 to 164 deg, obtained from the Pioneer Venus Orbiter, are reported. Data were derived from closed-loop S- and X-band signals received by the Deep Space Network upon ionospheric entry and exit of the spacecraft. Nightside electron density profiles are found to be rather uniform in the solar zenith angle range of from 95 to 107 deg, with peak electron densities ranging from 23,000 to 40,000/cu cm, while between 110 and 164 deg, profiles exhibit a high degree of variability and peak electron densities vary from 7,600 to 31,800/cu cm. A possible mechanism for the maintenance of the nightside Venus ionosphere during the long Venus night, which is consistent with the observed spatial and temporal variability of deep ionospheric electron density profiles, is proposed to be impact ionization by precipitating particles, although transport processes from the dayside may also be important.

Kliore, A. J.↗
NASA NTRS2005

Planetary Geophysics and Tectonics

The broad objective of this work is to improve understanding of the internal structures and thermal and stress histories of the solid planets by combining results from analytical and computational modeling, and geophysical data analysis of gravity, topography and tectonic surface structures. During the past year we performed two quite independent studies in the attempt to explain the Mariner 10 magnetic observations of Mercury. In the first we revisited the possibility of crustal remanence by studying the conditions under which one could break symmetry inherent in Runcorn's model of a uniformly magnetized shell to produce a remanent signal with a dipolar form. In the second we applied a thin shell dynamo model to evaluate the range of intensity/structure for which such a planetary configuration can produce a dipole field consistent with Mariner 10 results. In the next full proposal cycle we will: (1) develop numerical and analytical and models of thin shell dynamos to address the possible nature of Mercury s present-day magnetic field and the demise of Mars magnetic field; (2) study the effect of degree-1 mantle convection on a core dynamo as relevant to the early magnetic field of Mars; (3) develop models of how the deep mantles of terrestrial planets are perturbed by large impacts and address the consequences for mantle evolution; (4) study the structure, compensation, state of stress, and viscous relaxation of lunar basins, and address implications for the Moon s state of stress and thermal history by modeling and gravity/topography analysis; and (5) use a three-dimensional viscous relaxation model for a planet with generalized vertical viscosity distribution to study the degree-two components of the Moon's topography and gravity fields to constrain the primordial stress state and spatial heterogeneity of the crust and mantle.

Zuber, Maria↗
NASA NTRS2012

Materials in NASA's Space Launch System: The Stuff Dreams are Made of

Mr. Todd May, Program Manager for NASA's Space Launch System, will showcase plans and progress the nation s new super-heavy-lift launch vehicle, which is on track for a first flight to launch an Orion Multi-Purpose Crew Vehicle around the Moon in 2017. Mr. May s keynote address will share NASA's vision for future human and scientific space exploration and how SLS will advance those plans. Using new, in-development, and existing assets from the Space Shuttle and other programs, SLS will provide safe, affordable, and sustainable space launch capabilities for exploration payloads starting at 70 metric tons (t) and evolving through 130 t for entirely new deep-space missions. Mr. May will also highlight the impact of material selection, development, and manufacturing as they contribute to reducing risk and cost while simultaneously supporting the nation s exploration goals.

May, Todd A.↗
NASA NTRS2015

Opportunity In Situ Geologic Context of Aqueous Alteration Along Offsets in the Rim of Endeavour Crater

Mars Exploration Rover Opportunity traversed 7.9 km and 27 degrees of arc along the rim of the 22 km-diameter Noachian "Endeavour" impact crater since its arrival 1200 sols ago. Areas of aqueous and low-grade thermal alteration, and changes in structure, attitude, and macroscopic texture of outcrops are notable across several discontinuities between segments of the crater rim. The discontinuities and other post-impact joints and fractures coincide with sites of apparent deep fluid circulation processes responsible for thermal and chemical alteration of local outcrops.

Crumpler, L. S.↗
NASA NTRS2012

Autonomous Mission Operations

NASA's Advanced Exploration Systems Autonomous Mission Operations (AMO) project conducted an empirical investigation of the impact of time-delay on todays mission operations, and of the effect of processes and mission support tools designed to mitigate time-delay related impacts. Mission operation scenarios were designed for NASA's Deep Space Habitat (DSH), an analog spacecraft habitat, covering a range of activities including nominal objectives, DSH system failures, and crew medical emergencies. The scenarios were simulated at time-delay values representative of Lunar (1.2-5 sec), Near Earth Object (NEO) (50 sec) and Mars (300 sec) missions. Each combination of operational scenario and time-delay was tested in a Baseline configuration, designed to reflect present-day operations of the International Space Station, and a Mitigation configuration in which a variety of software tools, information displays, and crew-ground communications protocols were employed to assist both crews and Flight Control Team (FCT) members with the long-delay conditions. Preliminary findings indicate: 1) Workload of both crew members and FCT members generally increased along with increasing time delay. 2) Advanced procedure execution viewers, caution and warning tools, and communications protocols such as text messaging decreased the workload of both flight controllers and crew, and decreased the difficulty of coordinating activities. 3) Whereas crew workload ratings increased between 50 sec and 300 sec of time-delay in the Baseline configuration, workload ratings decreased (or remained flat) in the Mitigation configuration.

Mission Operations↗
NASA NTRS2020

MODIS TEB Calibration Algorithm Improvements for Future L1B Collection

Terra and Aqua MODIS have provided continuous global observations for scientific applications for more than 20 and 18 years, respectively. The radiometric calibration of the MODIS thermal emissive bands (TEB) is based on a quadratic approximation of the instrument response. The calibration coefficients look-up tables (LUTs) are updated using the response of the MODIS on-board blackbody (BB)with the response background subtracted by space view. The quarterly on-board BB warm-up and cool-down activity temperature ranges from 270 K to 315 K, and the derived offset has a relatively large uncertainty. Electronic cross-talk, an artifact that affects both instrument calibration and Earth view (EV) radiance retrievals, is corrected based on lunar observations. Calibration assessments using EV observations (e.g. ocean, desert, Antarctic Dome Concordia, and deep convective clouds) provide useful information to evaluate the impact of the Terra safe mode (February 2016) and Aqua MODIS formatter reset (January 2018) events on both MODIS instruments. This study focuses on the TEB radiometric calibration algorithm improvements for future collections based on calibration assessments using EV measurements and analytical modeling. Measurement stability and consistency over specific Earth scenes with a wide temperature range, as well as their brightness temperature (BT) dependency, are used for bias estimations in the calibration coefficients. Calibration coefficients are derived and updated after adjusting the current fitting algorithm. Thereafter, using the test LUTs, their impact on the Level 1B (L1B) data for different EV scenes is analyzed.

MODIS↗
NASA NTRSDate not supplied

Seeing the Future of Spaceflight: Applications of Extended Reality (XR) Technologies

INTRODUCTION Advances in Earth Independent Medical Operations (EIMO) focused capabilities will be crucial for completing successful beyond low-earth-orbit (LEO) missions, where traditional Earth-based medical support and near real-time communication are limited, intermittent, or absent. In such restricted or limited communication environments, emerging extended reality (ER or XR) technologies may play a vital role in ensuring crew health and safety. Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) are common terms used to describe technologies that "generate or modify" while “extended reality” (ER or XR) is often used as an umbrella term for these technologies. This review explores how such cutting-edge “extended reality” information delivery systems are currently applied across various disciplines within NASA. The review focuses on their capabilities, limitations, and prospective future applications as they pertain to Earth-Independent Medical Operations and its components of pre-mission planning, medical decision making, resource management, and task load management. METHODS/DESIGN The review began with a literature search to identify relevant disciplines (e.g., medical education, austere environments) where XR technologies have been studied to highlight areas where evidence is lacking. Previous and current NASA XR projects and applications, as well as commercial partnerships, such as those with Small Business Innovation Research (SBIR), were identified. Discussions with technical experts involved in the design, development, and application of these technologies allowed for classification based on their respective spaceflight applications. RESULTS AND CONCLUSION This review highlights current and emerging XR technologies that have been developed, tested, and implemented both terrestrially and in spaceflight by NASA, its international partners, the U.S. Armed Forces, and various relevant commercial entities. While these novel information delivery systems vary in their respective technology readiness levels (TRL), they have the potential to be implemented on Earth, in LEO, and during deep space exploration. These systems have the potential for impacting and optimizing many aspects of EIMO.

Yevgeniy Zhivotovskiy↗
DOE OSTI2022

Generative adversarial networks for ensemble projections of future urban morphology

As city planners design and adapt cities for future resilience and intelligence, interactions among neighborhood morphological development with respect to changes in population and resultant built infrastructure's impact on the natural environment must be considered. For deep understanding of these interactions, explicit representation of future neighborhoods is necessary for future city modeling. Generative Adversarial Networks (GANs) have been shown to produce spatially accurate urban forms at scales representing entire cities to those at neighborhood and single building scale. Here we demonstrate a GAN method for generating an ensemble of possible new neighborhoods given land use characteristics and designated neighborhood type.

Dumas, Melissa↗
DOE OSTI2025

Quantum AI Based Enhanced Detection of Dementia

Quantum computing has the potential to significantly improve the early detection of Alzheimer's Disease and Related Dementias (ADRD). Quantum-enhanced machine learning can be used to perform an early screening of Alzheimer's disease using brain imaging data based on dataset of MRI scans from both healthy individuals and those diagnosed with Alzheimer's. This study aims to demonstrate the potential of quantum transfer learning to enhance the performance of the classical deep learning model for dementia detection. Using the MRI sagittal images available in the OASIS-2 (64 demented and 72 non-demented subjects between 60 and 96 years), we show how quantum techniques can transform a suboptimal classical model into a more effective solution for dementia detection, highlighting their potential impact on advancing healthcare technology. We begin with a simple classical deep learning model with a significantly smaller number of parameters, which gives suboptimal performance on the problem. Then, we apply different configurations of quantum transfer learning based on the pre-trained weak classifier (Figure 1). We fix the weak classifier's initial convolutional layers at their fixed pre-trained parameters and replace the last set of dense layers with a dressed quantum circuit (DQN), which we train to enhance performance. We performed 4-fold cross-validation for both the classical and the hybrid quantum models and trained them using Pennylane's `default.qubit' simulator and IonQ's Aria-1 simulator (noisy simulation). We showed that with significantly fewer parameters, the quantum transfer learning-based hybrid models showed significant performance enhancement over the base weak classical deep learning model for dementia detection. To classify between a demented and non-demented subject, the accuracy of quantum-based AI methods improved by 6 to 14% compared to classical methods. The sensitivity of the models improved by 4 to 17%. This shows that there are fewer chances of misclassifying demented patients. Figure 2 compares the performance of the hybrid quantum models and their base classical model, and Table 1 summarizes the results. We illustrated that with assistance from quantum machine learning, it is possible to enhance detection for dementia based on brain images. This shows the potential for practical utility of quantum computing in ADRD research.

Bhowmik, Sounak [University of Tennessee, Knoxvill↗
DOE OSTI2026

The Role of Subcloud Mesoscale Convergence in Sculpting Convective Updraft Width and Depth

The initiation of deep moist convection is governed in part by the horizontal width of updrafts near cloud base, which limits the deleterious effects of entrainment-driven dilution on buoyant thermals ascending through the free troposphere. However, the factors controlling cloud-base updraft width, which in turn dictates cloud depth, are not well understood. We track the evolving three-dimensional structure of the mesoscale subcloud forcing for vertical motion and near-cloud thermodynamic ingredients within a high-resolution ensemble of simulations of seven realistic daytime orographic convection initiation events to determine their relative roles in controlling cloud width and depth. Statistical analysis of approximately 5000 cloudy updraft samples indicates that the most important contributors to the width of cloudy updrafts across the ensemble are the depth and magnitude of the subcloud mesoscale ascent. However, the depth achieved by clouds is more consistently predicted by the near-cloud ambient relative humidity within the lower to middle free troposphere and convective available potential energy. Therefore, although the width of cloudy updrafts may be partly set at low levels by the mesoscale vertical mass and moisture flux, the likelihood of deep moist convection is governed by the generation of positive buoyancy within cumulus thermals and entrainment-driven dilution that reduces it. The persistence of the low-level mesoscale vertical forcing locally consolidates and vertically transports boundary layer moisture, helping to reduce updraft dilution. However, these factors vary in relative impacts on cloudy updrafts across individual cases, indicating multiple pathways for deep convection initiation.

Convective storms↗
NASA NTRS2018

Impact of a Cold Pool Parameterization on the Diurnal Cycle and Intraseasonal Variability in the GEOS AGCM

A gradual transition from shallow to deep convection may be important both to the continental diurnal cycle of precipitation and to the tropical Madden-Julian Oscillation. However, many existing convection parameterizations transition too readily, with corresponding diurnal and intraseasonal biases. High entrainment rates can be used to delay deep convection, but typically produce mean state biases; this is the "entrainment dilemma." Cold pools and sub-grid organization offer a potential solution to this dilemma, and recent work shows parameterized cold pools can effectively modulate deep convection, with improvements to the diurnal cycle and intraseasonal variability. Here we investigate the effects of a simple prognostic cold pool scheme coupled to the Grell-Freitas convection parameterization, in a set of global simulations with the NASA GEOS model. Air detrained from parameterized downdrafts is maintained in vertically resolved cold pools, which evolve with simplified dynamics. We test several options for cold pool feedbacks on convection, including modifications to deep convective entrainment rates, convective source air properties, and thermodynamic profiles, based on the level of cold pool activity. Cold pool impacts on the diurnal cycle are evaluated against TRMM, and moisture and moist static energy budgets are used to understand changes in tropical intraseasonal variability. Preliminary results show delays in the diurnal cycle of precipitation.

Arnold, Nathan↗