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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Monitoring agroecosystem productivity and phenology at a national scale: A metric assessment framework

Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, GCC) from tower-mounted PhenoCams for 2017 and 2018. Overall, our analysis compared production dynamics estimated from three independent ground and remote platforms using data for 34 agricultural sites constituting 51 site-years of co-located time series. Pairwise sensor comparisons across all four metrics revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazing land sites where estimating SOS can be challenging. Growing season length estimates derived from 16-day satellite GPP (179.1 days) were significantly longer than those from PhenoCam G CC (70.4 days, p adj < 0.0001) and EC GPP (79.6 days, p adj < 0.0001). Landscape heterogeneity did not explain differences in SOS and EOS estimates. Annual integrated estimates of productivity from EC GPP and PhenoCam G CC diverged from those estimated by Landsat GPP and NDVI at sites where annual production exceeds 1000 gC/m –2 yr –1 . Based on our results, we developed a “metric assessment framework” that articulates where and how metrics from satellite, eddy covariance and PhenoCams complement, diverge from, or are redundant with one another. The framework was designed to optimize instrumentation selection for monitoring, modeling, and forecasting ecosystem functioning with the ultimate goal of informing decision-making by land managers, policy-makers, and industry leaders working at multiple scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Plasticity of irradiated materials at the nano and micro-scales

Here, we review here our recent work on plastic deformation in irradiated materials at the nano- and micro-scales, as revealed by Discrete Dislocation Dynamics (DDD) simulations. Two methods of including irradiation effects in the DDD framework are presented. The first directly captures the atomistic interaction mechanisms, while the second can effectively study high-dose irradiation. Computer simulations lead to new understanding of the dynamics of collective dislocation-irradiation defect interactions, as well as the quantitative analysis of the temporal and spatial characteristics associated with plastic instabilities. Based on these insights, theoretical models are developed to predict the critical conditions for dislocation channel formation. A simple probability model is proposed and demonstrated to predict the width of dislocation channels in bulk irradiated materials with good agreement with experimental data. The fundamental understanding of the origins of plastic flow localization in irradiated materials sheds light on the design of future generations of radiation-resistant materials.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Effect of Satellite Formations and Imaging Modes on Global Albedo Estimation

We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static reference case. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/sq m or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than 70% ground spot overlap between the satellites is possible with 0.5deg of pointing accuracy, 2 Km of GPS accuracy and commands uplinked once a day. The formations can be maintained at less than 1 m/s of monthly (Delta)V per satellite.

BRDF↗
DOE OSTI2023

High-Resolution Synthetic Solar Irradiance Sequence Generation: An LSTM-Based Generative Adversarial Network

The rapid growth of renewable energy resources penetration is bringing more challenges to power system planning and operation. Relevant renewable energy integration studies, such as the capability and dynamic performance of inverter-based resources' primary frequency response and fast frequency response, require high-resolution renewable generation output data that are representative of renewable energy resources. This paper focuses on creating synthetic but realistic solar irradiance data and proposes a long short-term memory-based generative adversarial network to generate high-resolution (second-level) solar irradiance sequences from low-resolution (minute-level) measurements. Combined with a classifier to recognize the solar irradiance patterns, the proposed model is trained using multi-loss functions to accurately capture the temporal correlations among both high-resolution and low-resolution sequences. Verification of the proposed approach is performed on the data set of the Oahu Solar Measurement Grid collected through the National Renewable Energy Laboratory. The results of the case studies demonstrate the proposed approach's capability to capture the statistical characteristics of different solar irradiance patterns and to generate high-quality synthetic solar irradiance sequences in high resolution.

dynamic scheduling↗
NASA NTRS2016

Space Launch System Vibration Analysis Support

The ultimate goal for my efforts during this internship was to help prepare for the Space Launch System (SLS) integrated modal test (IMT) with Rodney Rocha. In 2018, the Structural Engineering Loads and Dynamics Team will have 10 days to perform the IMT on the SLS Integrated Launch Vehicle. After that 10 day period, we will have about two months to analyze the test data and determine whether the integrated vehicle modes/frequencies are adequate for launching the vehicle. Because of the time constraints, NASA must have newly developed post-test analysis methods proven well and with technical confidence before testing. NASA civil servants along with help from rotational interns are working with novel techniques developed and applied external to Johnson Space Center (JSC) to uncover issues in applying this technique to much larger scales than ever before. We intend to use modal decoupling methods to separate the entangled vibrations coming from the SLS and its support structure during the IMT. This new approach is still under development. The primary goal of my internship was to learn the basics of structural dynamics and physical vibrations. I was able to accomplish this by working on two experimental test set ups, the Simple Beam and TAURUS-T, and by doing some light analytical and post-processing work. Within the Simple Beam project, my role involves changing the data acquisition system, reconfiguration of the test set up, transducer calibration, data collection, data file recovery, and post-processing analysis. Within the TAURUS-T project, my duties included cataloging and removing the 30+ triaxial accelerometers, coordinating the removal of the structure from the current rolling cart to a sturdy billet for further testing, preparing the accelerometers for remounting, accurately calibrating, mounting, and mapping of all accelerometer channels, and some testing. Hammer and shaker tests will be performed to easily visualize mode shapes at low frequencies. Short analytical projects using MATLAB were also assigned to aid in research efforts. These included integration of acceleration data for comparison to measured displacement data. Laplace and Fourier transforms were also investigated to determine viability as a method of modal decoupling. In addition to these projects, I was also able contribute work that would benefit future interns and the division as a whole. I gave a short presentation and answered questions to aid in the recruitment of subsequent interns and co-ops for the division. I also assisted in revisions and additions to Intern/Co-Op Handbook to provide incoming employees with background information on the organization they are about to work for. I further developed tutorial on Pulse software, which was used for data acquisition for both experiments and will be helpful to interns and engineers that may be unfamiliar to the software. I gained a diverse range of experience throughout my internship. I was introduced to advanced dynamics and analytical techniques. This was through new experience with both hands on experimentation and analytical post processing methods. I was exposed to the benefits of interdepartmental collaboration and developed stronger skills in time management by coordinating two different tests at once. This internship provided an excellent opportunity to see how engineering theories applied to real life scenarios, and an introduction to how NASA/JSC solves technical problems.

Johnson, Katie↗
DOE OSTI2022

A multi-stage stochastic programming model for adaptive biomass processing operation under uncertainty

Variations of physical and chemical characteristics of biomass reduce equipment utilization and increase operational costs of biomass processing. Biomass processing facilities use sensors to monitor the changes in biomass characteristics. Integrating sensory data into the operational decisions in biomass processing will increase its flexibility to the changing biomass conditions. In this paper, we propose a multi-stage stochastic programming model that minimizes the expected operational costs by identifying the initial inventory level and creating an operational decision policy for equipment speed settings. These policies take the sensory information data and the current biomass inventory level as inputs to dynamically adjust inventory levels and equipment settings according to the changes in the biomass' characteristics. We ensure that a prescribed target reactor utilization is consistently achieved by penalizing the violation of the target reactor feeding rate. A case study is developed using real-world data collected at Idaho National Laboratory's biomass processing facility. We show the value of multi-stage stochastic programming from an extensive computational experiment. Our sensitivity analysis indicates that updating the infeed rate of the system, the processing speed of equipment, and bale sequencing based on the moisture level of biomass improves the processing rate of the reactor and reduces operating costs.

09 BIOMASS FUELS↗
DOE OSTI2018

First-principles calculations of lattice dynamics and thermodynamic properties for Yb 14 MnSb 11

Systematic first-principles calculations were performed to study the lattice dynamics of Yb 14 MnSb 11 and hence to obtain a wide range of its thermodynamic properties at high temperatures. Here, the calculated results were analyzed in terms of the lattice contribution and the electronic contribution, together with a comparison with a collection of experimental thermochemical data. At 0 K, the electronic density of states showed the typical feature of a p-type semiconductor—a small amount of unoccupied electronic states exclusively made of the major spin by a range of ~0.6 eV above the Fermi energy. It showed that the Mn atom had a ferromagnetic spin moment of ~4 μ B . Lastly, as a semiconductor, it was found that the electronic contribution to the heat capacity was substantial, with an electronic heat capacity coefficient of ~0.0006 J/mole-atom/K 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2013

THE OPEN CLUSTER CHEMICAL ANALYSIS AND MAPPING SURVEY: LOCAL GALACTIC METALLICITY GRADIENT WITH APOGEE USING SDSS DR10

The Open Cluster Chemical Analysis and Mapping (OCCAM) survey aims to produce a comprehensive, uniform, infrared-based data set for hundreds of open clusters, and constrain key Galactic dynamical and chemical parameters from this sample. This first contribution from the OCCAM survey presents analysis of 141 members stars in 28 open clusters with high-resolution metallicities derived from a large uniform sample collected as part of the Sloan Digital Sky Survey III/Apache Point Observatory Galactic Evolution Experiment. This sample includes the first high-resolution metallicity measurements for 22 open clusters. With this largest ever uniformly observed sample of open cluster stars we investigate the Galactic disk gradients of both [M/H] and [α/M]. We find basically no gradient in [α/M] across 7.9 kpc ≤ R {sub GC} ≤ 14.5 kpc, but [M/H] does show a gradient for R {sub GC} < 10 kpc and a significant flattening beyond R {sub GC} = 10 kpc. In particular, whereas fitting a single linear trend yields an [M/H] gradient of –0.09 ± 0.03 dex kpc{sup –1}—similar to previously measure gradients inside 13 kpc—by independently fitting inside and outside 10 kpc separately we find a significantly steeper gradient near the Sun (7.9 ≤ R {sub GC} ≤ 10) than previously found (–0.20 ± 0.08 dex kpc{sup –1}) and a nearly flat trend beyond 10 kpc (–0.02 ± 0.09 dex kpc{sup –1})

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗
DOE OSTI2021

Portuguese Wood Pellets Market: Organization, Production and Consumption Analysis

Wood pellets are a form of energy that can be seen as an alternative to fossil fuels, thus contributing to the reduction of greenhouse gas emissions. In other words, wood pellets can be considered a solution contributing to the mitigation of climate change. The use of wood pellets has grown significantly in recent years, with different markets emerging, such as Portugal, both from production and consumption perspectives. The wood pellet industry in Portugal began its development about 15 years ago, with the companies installed in the country initially almost exclusively dedicated to the production of wood pellets for export to central and northern European markets. However, over the years, the domestic market, initially considered insignificant, began to develop; it recently reached a considerable consuming share of the national production. This study presents an analysis of the Portuguese wood pellet market using data collected on the sector, and specifically on producers and consumers. The information was gathered using surveys presented directly to consumers and producers and through interviews with other stakeholders in the sector. From the analysis of the information, it was possible to understand the market’s dynamics, its current evolution and its prospects for the upcoming years, since it can already be considered mature and consolidated.

Nunes, Leonel J. R. (ORCID:0000000154048163)↗
NASA NTRS1988

Effects of El Chichon volcanic effluents on stratospheric aerosol dynamics

The effects of El Chichon's April 1982 eruption on stratospheric aerosol dynamics are presently discussed in terms of log-normal size distributions over 15-20 km sample altitudes between 30 and 45 deg N over the contiguous U.S. After collection, samples were studied by SEM, and log-normal size distributions were fitted to the data-points obtained. It is found that stratospheric aerosol behavior is explainable by the laws of aerosol mechanics more easily than has been the case for tropospheric aerosol, for which the source-sink relationship is much more complex.

Pueschel, R. F.↗
NASA NTRS1994

Photospheric origins of chromospheric and coronal activity

This contract is for a two-year research study of the origins of activity in the upper atmosphere of the sun. The approach is to collect high resolution images of the lower atmosphere on observing runs at the Swedish Solar Observatory on La Palma, Canary Islands, Spain. The best observations are analyzed and compared with data from other telescopes and/or theoretical models, to study magnetic flux emergence, coronal heating, and various dynamic phenomena and transients. Software for analysis and visualization of the data is developed as needed. The contract is being performed by the Solar and Astrophysics Laboratory, part of the Lockheed Palo Alto Research Laboratory (LPARL) of the Research and Development Division (RDD) of Lockheed Missiles and Space Co., Inc. (LMSC).

Tarbell, Theodore↗
NASA NTRS2023

Sea Ice Drift Tracks From Autonomous Buoys in the MOSAiC Distributed Network

A network of autonomous, ice-tethered buoys was deployed around the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment in late September 2019 for a year-long drift in the Arctic Transpolar Drift Stream. The buoys were deployed as part of the MOSAiC distributed network (DN) which included 12 multi-instrumented ice stations and an additional 116 GPS buoys distributed primarily within a 40 km radius of the MOSAiC Central Observatory. Buoy coverage within the DN was maintained with additional deployments throughout the year-long drift allowing for collection of data over a full sea ice growth and melt cycle. All GPS position data from buoys deployed within the DN have been assembled and processed into the collection of 216 quality-controlled buoy drift tracks presented in this dataset covering the period 26 September 2019 – 23 May 2021. The drift tracks in this collection are ideal for studies of dynamic sea ice motion around the MOSAiC experiment at cascading spatial scales ranging from 100s of meters to 100s of km.

Angela C. Bliss↗
DOE OSTI2019

A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT 2A and D2 subtypes of class-A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Aggregation and data driven identification of building thermal dynamic model and unmeasured disturbance

An aggregate model is a single-zone equivalent of a multi-zone building, and is useful for many purposes, including model based control of large heating, ventilation and air conditioning (HVAC) equipment. This paper deals with the problem of simultaneously identifying an aggregate thermal dynamic model and unknown disturbances from input–output data of multi-zone buildings. The unknown disturbance is a key challenge since it is not measurable but non-negligible. In this paper, we first present a principled method to aggregate a multi-zone building model into a single zone model, and show the aggregation is not as trivial as it has been assumed in the prior art. We then provide a method to identify the parameters of the model and the unknown disturbance for this aggregate (single-zone) model. Finally, we test our proposed identification algorithm to data collected from a multi-zone building testbed in Oak Ridge National Laboratory. A key insight provided by the aggregation method allows us to recognize under what conditions the estimation of the disturbance signal will be necessarily poor and uncertain, even in the case of a specially designed test in which the disturbances affecting each zone are known (as the case of our experimental testbed). This insight is used to provide a heuristic that can be used to assess when the identification results are likely to have high or low accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Modeling of the Coral Microbiome: the Influence of Temperature and Microbial Network

Host-associated microbial communities are shaped by extrinsic and intrinsic factors to the holobiont organism. Environmental factors and microbe-microbe interactions act simultaneously on the microbial community structure, making the microbiome dynamics challenging to predict. The coral microbiome is essential to the health of coral reefs and sensitive to environmental changes. Here, we develop a dynamic model to determine the microbial community structure associated with the surface mucus layer (SML) of corals using temperature as an extrinsic factor and microbial network as an intrinsic factor. The model was validated by comparing the predicted relative abundances of microbial taxa to the relative abundances of microbial taxa from the sample data. The SML microbiome from Pseudodiploria strigosa was collected across reef zones in Bermuda, where inner and outer reefs are exposed to distinct thermal profiles. A shotgun metagenomics approach was used to describe the taxonomic composition and the microbial network of the coral SML microbiome. By simulating the annual temperature fluctuations at each reef zone, the model output is statistically identical to the observed data. The model was further applied to six scenarios that combined different profiles of temperature and microbial network to investigate the influence of each of these two factors on the model accuracy. The SML microbiome was best predicted by model scenarios with the temperature profile that was closest to the local thermal environment, regardless of the microbial network profile. Our model shows that the SML microbiome of P. strigosa in Bermuda is primarily structured by seasonal fluctuations in temperature at a reef scale, while the microbial network is a secondary driver. Coral microbiome dysbiosis (i.e., shifts in the microbial community structure or complete loss of microbial symbionts) caused by environmental changes is a key player in the decline of coral health worldwide. Multiple factors in the water column and the surrounding biological community influence the dynamics of the coral microbiome. However, by including only temperature as an external factor, our model proved to be successful in describing the microbial community associated with the surface mucus layer (SML) of the coral P. strigosa. The dynamic model developed and validated in this study is a potential tool to predict the coral microbiome under different temperature conditions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

A mathematical force and moment model of a UH-1H helicopter for flight dynamics simulations

A model of a UH-1H helicopter was developed to support flight simulations and for developmental work on an avionics system known as V/STOLAND system. Equations and numerical values of constants used to represent the helicopter are presented. Responses to stop inputs of the cyclic and collective controls are shown and compared with flight test data for a UH-1H. The model coefficients were adjusted in an attempt to get a consistant match with the flight time histories at hover and 60 knots. Response matching was obtained at 60 knots, but the matching at hover was not as successful. Pilot evaluations of the model, both fixed and moving base, were made.

Talbot, P. D.↗
NASA NTRS2011

Quantification of Asian Dust Plume Seasonal Dynamics and Regional Features

Dust is but one of many aerosols that are analyzed at the Jet Propulsion Laboratory in Pasadena. The purpose of this paper is to describe the process in analyzing and digitizing dust within a source region to better explain the work achieved by my internship. This paper will go over how to view collected data by Multi-angle Imaging SpectroRadiometer (MISR) [1] and the procedure of downloading data to be analyzed. With this data, one can digitize dust plumes using two methods called plume lines and plume polygons with the help of the software MISR INteractive eXplorer (MINX)[3]; thus, the theory of MINX's[3] algorithm and these methods are discussed in detail. Research was gathered from these techniques and emphasis is also focused on the obtained data and results.

aerosols↗