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At least 577 records · Page 32

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NASA NTRS2020

Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R(exp 2), RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year (p < 0.01), and harvesting dates were delayed by 0.78 days/year (p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.

North America↗

DOE OSTI2021

Disentangling Rotational Dynamics and Ordering Transitions in a System of Self-Organizing Protein Nanorods via Rotationally Invariant Latent Representations

The dynamics of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally invariant variational autoencoder-based analysis of orientation and shape evolution. The latter allows for disentanglement of the particle orientation from other degrees of freedom and compensates for lateral shifts. The disentangled representations in the latent space encode the rich spectrum of local transitions that can now be visualized and explored via continuous variables. The time dependence of ensemble averages allows insight into the time dynamics of the system and, in particular, illustrates the presence of the potential ordering transition. Finally, analysis of the latent variables along the single-particle trajectory allows tracing these parameters on a single-particle level. The proposed approach is expected to be universally applicable for the description of the imaging data in optical, scanning probe, and electron microscopy seeking to understand the dynamics of complex systems where rotations are a significant part of the process.

representation learning↗

DOE OSTI2019

High throughput crystal structure and composition mapping of crystalline nanoprecipitates in alloys by transmission Kikuchi diffraction and analytical electron microscopy

Statistically significant crystal structure and composition identification of nanocrystalline features such as nanoparticles/nanoprecipitates in materials chemistry and alloy designing using electron microscopy remains a grand challenge. In this paper, we reveal that differing crystallographic phases of nanoprecipitates in alloys can be mapped with unprecedented statistics using transmission Kikuchi diffraction (TKD), on typical carbon-based electron-transparent samples. Using a case of multiphase, multicomponent nanoprecipitates extracted from an improved version of 9% chromium Eurofer-97 reduced-activation ferritic-martensitic steel we show that TKD successfully identified more than thousand M 23 C 6 , MX, M 7 C 3 , and M 2 X ( M =Fe, Cr, W, V, Ta; X = C, N) nanoprecipitates in a single scan, something that is currently unachievable using a transmission electron microscope (TEM) without incorporating a precision electron diffraction (PED) system. Precipitates as small as ~20–25 nm were successfully phase identified by TKD. We verified the TKD phase identification using high-resolution transmission electron microscopy (HRTEM) and convergent beam electron diffraction (CBED) pattern analysis of a few precipitates that were identified by TKD on same sample. TKD study was combined with state-of-art analytical scanning transmission electron microscopy (STEM)-energy dispersive X-ray (EDX) spectroscopy and multivariate statistical analysis (MVSA) which provided the complete crystal structure and distinct chemistries of the precipitates in the steel in a high throughput automated way. This technique should be applicable to characterizing any multiphase crystalline nanoparticles or nanomaterials. Furthermore the results highlight that combining phase identification by TKD with analytical STEM and modern data analytics may open new pathways in big data material characterization at nanoscale that may be highly beneficial for characterizing existing materials and in designing new materials.

36 MATERIALS SCIENCE↗

NASA NTRS1990

The spatial variation of vegetation changes at very coarse scales

Previous analysis (Townshend and Justice 1988) is extended to examine the spatial variations in images of the normalized difference vegetation index (NDVI) of seven areas. These images were derived by subtracting corresponding pixel values from pairs of registered MSS images. The changes depicted by these derived images were analyzed by scale variance analysis for pixel sizes between 4 km and 64 km. It is shown that for some areas substantial changes are detectable at these very coarse scales, although there is less contrast between the areas than at finer spatial resolutions below 1 km. In all the areas the total spatial variability of the images is contributed at a wide variety of spatial scales.

Townshend, John R. G.↗

NASA NTRS1994

Specific features of space-time variations of ozone during the development of intensive tropical disturbances

An analysis of specific features of space-time variations of ozone in the tropical areas which has been performed on the basis of processing of the results of special expedition studies in the Atlantic and Pacific in 1987-1990 and the data of observations at the stations of the world ozonometric network over the 25-year period. The existence of a cause-and-effect relation has been revealed between the processes determining tropical cyclone (TC) development, and specific features of variations of the total content of ozone (TCO) and the vertical distribution of ozone (VDO) in the regions of TC action. Characteristic features of day-to-day and daily variations of TCO during TC development have been found. On the periphery of a developing TC, 1-4 days before it reaches the stage of storm, TCO increases, on average, by 5-8 percent, and a substantial increase in the concentration of ozone occurs in the middle and upper troposphere. The most probable physical mechanisms relating the observed specific features of ozone variations to TC evolution have been suggested. A hypothesis of the possibility of using ozone as an indicator for early prediction of TC development has been substantiated.

Nerushev, Alexander F.↗

NASA NTRS2005

Aerocapture Performance Analysis of A Venus Exploration Mission

A performance analysis of a Discovery Class Venus Exploration Mission in which aerocapture is used to capture a spacecraft into a 300km polar orbit for a two year science mission has been conducted to quantify its performance. A preliminary performance assessment determined that a high heritage 70 sphere-cone rigid aeroshell with a 0.25 lift to drag ratio has adequate control authority to provide an entry flight path angle corridor large enough for the mission s aerocapture maneuver. A 114 kilograms per square meter ballistic coefficient reference vehicle was developed from the science requirements and the preliminary assessment s heating indicators and deceleration loads. Performance analyses were conducted for the reference vehicle and for sensitivity studies on vehicle ballistic coefficient and maximum bank rate. The performance analyses used a high fidelity flight simulation within a Monte Carlo executive to define the aerocapture heating environment and deceleration loads and to determine mission success statistics. The simulation utilized the Program to Optimize Simulated Trajectories (POST) that was modified to include Venus specific atmospheric and planet models, aerodynamic characteristics, and interplanetary trajectory models. In addition to Venus specific models, an autonomous guidance system, HYPAS, and a pseudo flight controller were incorporated in the simulation. The Monte Carlo analyses incorporated a reference set of approach trajectory delivery errors, aerodynamic uncertainties, and atmospheric density variations. The reference performance analysis determined the reference vehicle achieves 100% successful capture and has a 99.87% probability of attaining the science orbit with a 90 meters per second delta V budget for post aerocapture orbital adjustments. A ballistic coefficient trade study conducted with reference uncertainties determined that the 0.25 L/D vehicle can achieve 100% successful capture with a ballistic coefficient of 228 kilograms per square meter and that the increased ballistic coefficient increases post aerocapture V budget to 134 meters per second for a 99.87% probability of attaining the science orbit. A trade study on vehicle bank rate determined that the 0.25 L/D vehicle can achieve 100% successful capture when the maximum bank rate is decreased from 30 deg/s to 20 deg/s. The decreased bank rate increases post aerocapture delta V budget to 102 meters per second for a 99.87% probability of attaining the science orbit.

Starr, Brett R.↗

DOE OSTI2025

The examination of the spatial and contextual disparities of determinant factors of adult obesity among communities in Chicago

The issue of adult obesity has multiple complexes contributing factors and is becoming a significant public health concern worldwide, including in the neighborhoods of Chicago. This study utilized data on nineteen demographic, environmental, socioeconomic, and behavioral characteristics of community neighborhoods in Chicago to analyze the interplay and impact of these complex factors, which is essential for understanding and addressing the issue. The analysis revealed significant geographic variations in the prevalence of adult obesity across Chicago neighborhoods, with associations of these patterns found significant in 17 out of 19 determinant factors studied. Notably, strong associations were found between obesity and the percentage of the White population, the quality of sidewalks and walkability, the economic hardship index, and the unemployment rate. Identifying high-risk adult obesity communities and understanding the multifaceted contributing factors is crucial for developing evidence-based interventions and policy initiatives to reduce obesity and create healthier, more equitable urban neighborhoods for a city such as Chicago and beyond.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1984

Search for solar signals in GOES imagery and cloud climatology analysis

The digitization and analysis of 16mm GOES IR imagery to identify spatial and temporal variation in clouds is discussed, along with a cloud climatology analysis. Recently added to the Interactive Graphics Package was a Computer Image Analysis System. This system allows many new imaging techniques. One of the possibilities is the analysis of overall light intensity variations in six 10 degree square boxes across the intertropical convergence zone. This technique is discussed, as is a preliminary analysis of unnormalized data.

Markson, R. J.↗

NASA NTRS2017

Assimilation of AERONET and MODIS AOT Observations Using Variational and Ensemble Data Assimilation Methods and Its Impact on Aerosol Forecasting Skill

Data assimilation of Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness (AOT) for aerosol forecasting was tested within the Navy Aerosol Analysis Prediction System (NAAPS) framework, using variational and ensemble data assimilation methods. Navy aerosol forecasting currently makes use of a deterministic NAAPS simulation coupled to Navy Variational Data Assimilation System for aerosol optical depth, a two-dimensional variational data assimilation system, for MODIS AOT assimilation. An ensemble version of NAAPS (ENAAPS) coupled to an ensemble adjustment Kalman filter (EAKF) from the Data Assimilation Research Testbed was recently developed, allowing for a range of data assimilation and forecasting experiments to be run with deterministic NAAPS and ENAAPS. The main findings are that the EAKF, with its flow-dependent error covariances, makes better use of sparse observations such as AERONET AOT. Assimilating individual AERONET observations in the two-dimensional variational system can increase the analysis errors when observations are located in high AOT gradient regions. By including AERONET with MODIS AOT assimilation, the magnitudes of peak aerosol events (AOT> 1) were better captured with improved temporal variability, especially in India and Asia where aerosol prediction is a challenge. Assimilating AERONET AOT with MODIS had little impact on the 24 h forecast skill compared to MODIS assimilation only, but differences were found downwind of AERONET sites. The 24 h forecast skill was approximately the same for forecasts initialized with analyses from AERONET AOT assimilation alone compared to MODIS assimilation, particularly in regions where the AERONET network is dense; including the United States and Europe, indicating that AERONET could serve as a backup observation network for over-land synoptic-scale aerosol events.

Rubin, Juli I.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-26160-DND

The structural performance of two advanced composite tow-steered shells is assessed using experiments and analyses. The fiber angles vary continuously around the shell circumference, and one shell has all 24 tows applied during fabrication, while the second shell uses the fiber placement systems tow drop/add capability to achieve a uniform wall thickness. The shells are tested in compression, and their axial stiffnesses and buckling loads are estimated using linear finite element analyses. Scaled passenger and cargo door cutouts are machined into one side of each shell. Axial stiffnesses and buckling loads of the shells with cutouts are computed using linear finite element analyses. The retested shells carry over 90 percent of the axial stiffness, and 85 percent of the buckling loads, of the shells without cutouts. These small reductions demonstrate the potential of tow steering to mitigate adverse effects of cutouts on the structural performance. The good correlation between experimental buckling loads and linear buckling analyses noted here may result from their circumferential stiffness variation, reducing geometric imperfection sensitivity. Analysis models of both shells were evaluated without and with measured geometric imperfections superposed in different longitudinal orientations. Small variations in prebuckling stiffness and buckling load of the shells are observed.

K C Wu↗

NASA NTRS2013

Neutron Absorption Measurements Constrain Eucrite-Diogenite Mixing in Vesta's Regolith

The NASA Dawn Mission s Gamma Ray and Neutron Detector (GRaND) [1] acquired mapping data during 5 months in a polar, low altitude mapping orbit (LAMO) with approx.460-km mean radius around main-belt asteroid Vesta (264-km mean radius) [2]. Neutrons and gamma rays are produced by galactic cosmic ray interactions and by the decay of natural radioelements (K, Th, U), providing information about the elemental composition of Vesta s regolith to depths of a few decimeters beneath the surface. From the data acquired in LAMO, maps of vestan neutron and gamma ray signatures were determined with a spatial resolution of approx.300 km full-width-at-half-maximum (FWHM), comparable in scale to the Rheasilvia impact basin (approx.500 km diameter). The data from Vesta encounter are available from the NASA Planetary Data System. Based on an analysis of gamma-ray spectra, Vesta s global-average regolith composition was found to be consistent with the Howardite, Eucrite, and Diogenite (HED) meteorites, reinforcing the HED-Vesta connection [2-7]. Further, an analysis of epithermal neutrons revealed variations in the abundance of hydrogen on Vesta s surface, reaching values up to 400 micro-g/g [2]. The association of high concentrations of hydrogen with equatorial, low-albedo surface regions indicated exogenic delivery of hydrogen by the infall of carbonaceous chondrite (CC) materials. This finding was buttressed by the presence of minimally-altered CC clasts in howardites, with inferred bulk hydrogen abundances similar to that found by GRaND, and by studies using data from Dawn s Framing Camera (FC) and VIR instruments [8-10]. In addition, from an analysis of neutron absorption, spatial-variations in the abundance of elements other than hydrogen were detected [2].

Prettyman, T. H.↗

DOE OSTI2020

A novel CMB component separation method: hierarchical generalized morphological component analysis

ABSTRACT We present a novel technique for cosmic microwave background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to generalized morphological component analysis (GMCA), we introduce hierarchical GMCA (HGMCA), a Bayesian hierarchical graphical model for source separation. We test our method on Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25{{\ \rm per\ cent}}$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the 0.02–0.03 per cent level at ℓ > 200 (and $\lt 0.26{{\ \rm per\ cent}}$ for all ℓ), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art internal linear combination type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Impact of battery cell imbalance on electric vehicle range

Due to manufacturing variation, battery cells often possess heterogeneous characteristics, leading to battery state-of-charge variation in real-time. Since the lowest cell state-of-charge determines the useful life of battery pack, such variation can negatively impact the battery performance and electric vehicles range. Existing research has been focused on control design to mitigate cell imbalance. However, it is yet unclear how much impacts the cell imbalance can have on electric vehicle range. This paper closes this knowledge gap by using a simulation environment consisting of real-world driving speed data, vehicle longitudinal control, propulsion and vehicle dynamics, and cell level battery modeling. In particular, each battery cell is modeled as an equivalent circuit model, and variations among cell parameters are introduced to assess their impact on electric vehicles range and to identify the most influential parameter variations. Simulation results and analysis can be used to assist balancing control design and to benchmark control performance.

25 ENERGY STORAGE↗

DOE OSTI2026

Elastic-wave sensitivity-guided adaptive seismic survey design for cost-effective monitoring of geological carbon storage

Effective seismic monitoring is essential for verifying CO₂ containment, detecting potential leakage, and optimizing operational decisions in geologic carbon storage. Here, this study presents a time-adaptive, elastic-wave sensitivity-guided framework for designing cost-effective seismic monitoring layouts for tracking CO₂ plume migration. The method is based on elastic-wave sensitivity analysis, which quantifies how variations in subsurface properties impact seismic wavefields. Two complementary design strategies are developed: one based on selecting a fixed number of seismic sources (Method A), and the other based on selecting source–receiver pairs contributing to a fixed fraction of cumulative elastic-wave sensitivity energy (Method B). The optimization workflow to identify source–receiver configurations with the highest detection potential is demonstrated using a hypothetical GCS scenario at the Kimberlina site in California using simulations of elastic-wave sensitivity data at multiple post-injection timesteps. Results show that both strategies adapt to evolving plume geometries and wavefield sensitivities, with Method B offering broader spatial coverage and Method A ensuring simpler deployment. This framework enables site-specific, cost-effective, and risk-informed seismic survey designs, enhancing the ability to monitor CO₂ migration over time in evolving geological environments

58 GEOSCIENCES↗

DOE OSTI2020

High-throughput synthesis and corrosion behavior of sputter-deposited nanocrystalline Al x (CoCrFeNi) 100-x combinatorial high-entropy alloys

High-entropy alloys (HEAs) are inherently complex and potentially span a vast composition space, making their research and discovery challenging. In the present study, high-throughput synthesis of an Al x (CoCrFeNi) 100-x combinatorial material library covering x = 4.5–40 atomic percent Al is achieved, using magnetron cosputtering. The effects of Al on the microstructure and corrosion behavior are investigated. With the increased amount of Al, crystal-structures of thin films transform from face-centered cubic (FCC) to body-centered cubic (BCC). Both the FCC and BCC thin films demonstrate a uniform elemental distribution. Corrosion characteristics of combinatorial samples immersed in the 3.5 wt% (wt%) NaCl solution are evaluated via electrochemical tests. Complementary X-ray photoelectron spectroscopy analysis reveals the compositional variation of passivated films formed on the sample surface after immersion. The results show that the Al x (CoCrFeNi) 100-x HEA thin films possess outstanding corrosion-resistant properties, but the resistance diminishes with the increasing Al content. The decreased corrosion resistance is revealed to be directly related to the constituents of passivated films.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Thermodynamic control on the decomposition of organic matter across different electron acceptors

The increasing availability of high-resolution characterization of natural organic matter (OM) data has shifted the paradigm of lumped descriptions of OM components and potential microbial activities. Our recent development of a substrate-explicit thermodynamic model uniquely enables incorporating complex OM pools to formulate biogeochemical reaction models based on their elemental compositions. While this previous work facilitates prediction of aerobic respiration of complex OM, it is equally imperative to consider the role of non-oxygenic electron acceptors in regulating OM turnover and the fate of carbon. In this study, we significantly expand our previous model by flexibly incorporating both detailed OM chemistry and electron acceptors other than oxygen. Here, our modeling analysis has revealed substantial variations in the energy status of OM molecules across different soils, which drive the co-occurrence of different electron-accepting processes. We demonstrated the effectiveness of the proposed model using a consistency check with experimental data. Through systematic evaluation of the impact of diverse chemical inputs (both electron donors and acceptors) on OM decomposition, the new model also revealed how key microbial growth parameters such as carbon use efficiency (CUE) and reaction rates vary across different electron-accepting processes. Our model provides a unified framework integrating thermodynamic and kinetic constraints on microbial metabolic activities. It complements traditional kinetic models, which are often designed solely to capture mass fluxes. We conclude that thermodynamic modeling emerges as a powerful tool for describing the mechanisms underlying the interplay between microbial growth and OM chemistry and cycling across different electron acceptors, enhancing our ability to project complex ecosystem behaviors in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

How Do Ionic Liquids “Fold” Ionenes? Computational and Experimental Analysis of Imidazolium Polymers Based on Ether and Alkyl Chain Variations Dissolved in an Ionic Liquid

Molecular dynamics (MD) simulations and complementary experiments are used here to understand the inter- and intramolecular structure and conformational properties of ionenes (i.e., cationic polymers formed from condensation reactions) dissolved in an ionic liquid (IL), 1-ethyl-3-methylimidazolium bistriflimide [C 2 mim + ][Tf 2 N - ]. The simulated structural properties are benchmarked against experimental analyses of these same polymers, mainly using dynamic light scattering (DLS) experiments. Four different imidazolium ionenes are considered, corresponding to variations in the chemistry and structure of the repeat units including: (1) poly (decylimidazolium) (PD 10 ); (2) poly (tetraethyleneglycolimidazolium) (PE 10 ); (3) alternating copolymer (P(ED) 5 ); and (4) a block copolymer (PE 5 D 5 ). Detailed computational analyses of the polymer structure and conformational properties were performed, including the radius of gyration, end-to-end distance, torsional distributions, and site-site and spatial distribution functions. Overall, there is a competition between intramolecular associations between the imidazolium groups and the ether sites in the polymers versus the intermolecular interactions of the polymer imidazolium groups with the surrounding anion molecules. The polymer with only ether linkages (PE 10 ) results in the most intramolecular interactions, leading to significant coiling behavior and chain contraction. These strong interactions reduce chain flexibility, but they also result in much more linear chain configurations and alignment of the imidazolium groups. The polymer structure is strongly affected as the concentration of alkyl groups is increased, and we find that the polymer architecture (alternating versus block copolymer) also has an important influence. Furthermore, these detailed observations are important for understanding the connection between the molecular design of imidazolium polymers and their emergent structural properties, which could lead to unique opportunities for creating polymer composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Estimating the Electric Fields Driving Lightning Dart Leader Development With BIMAP‐3D Observations

Abstract In this paper, a numerical dart leader model has been implemented to understand the leader's development and the corresponding electric field changes observed by the 3D broadband mapping and polarization (BIMAP‐3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre‐dart‐leader channel has a significant temperature of 3,000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well‐defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

3D lightning mapping↗