Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “time resolution data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

North American Vegetation Dynamics Observed with Multi-Resolution Satellite Data

North American vegetation has been discovered to be a net carbon sink, with atypical behavior of drawing down more carbon from the atmosphere during the past century. It has been suggested that the Northern Hemisphere will respond favorably to climate warming by enhancing productivity and reducing the impact of fossil fuel emissions into the atmosphere. Many investigations are currently underway to understand and identify mechanisms of storage so they might be actively managed to offset carbon emissions which have detrimental consequences to the functioning of ecosystems and human well being. This paper used a time series of satellite data from multiple sensors at multiple resolutions over the past thlrty years to identify and understand mechanisms of change to vegetation productivity throughout North America. We found that humans had a marked impact to vegetation growth in half of the six selected study regions which cover greater than two million km2. We found climatic influences of increasing temperatures, and longer growing seasons with reduced snow cover in the northern regions of North America with forest fire recovery in the Northern coniferous forests of Canada. The Mid-latitudes had more direct land cover changes induced by humans coupled with climatic influences such as severe drought and altered production strategies of rain-fed agriculture in the upper Midwest, expansion of irrigated agriculture in the lower Midwest, and insect outbreaks followed by subsequent logging in the upper Northeast. Vegetation growth over long time periods (20+ years) in North America appears to be associated with long term climate change but most of the marked changes appear to be associated with climate variability on decadal and shorter time scales along with direct human land cover conversions. Our results document regional land cover land use change and climatic influences that have altered continental scale vegetation dynamics in North America.

Neigh, Christopher S. R.↗
DOE OSTI2023

Strictly Enforcing Invertibility and Conservation in CNN-Based Super Resolution for Scientific Datasets

Abstract Recently, deep convolutional neural networks (CNNs) have revolutionized image “super resolution” (SR), dramatically outperforming past methods for enhancing image resolution. They could be a boon for the many scientific fields that involve imaging or any regularly gridded datasets: satellite remote sensing, radar meteorology, medical imaging, numerical modeling, and so on. Unfortunately, while SR-CNNs produce visually compelling results, they do not necessarily conserve physical quantities between their low-resolution inputs and high-resolution outputs when applied to scientific datasets. Here, a method for “downsampling enforcement” in SR-CNNs is proposed. A differentiable operator is derived that, when applied as the final transfer function of a CNN, ensures the high-resolution outputs exactly reproduce the low-resolution inputs under 2D-average downsampling while improving performance of the SR schemes. The method is demonstrated across seven modern CNN-based SR schemes on several benchmark image datasets, and applications to weather radar, satellite imager, and climate model data are shown. The approach improves training time and performance while ensuring physical consistency between the super-resolved and low-resolution data. Significance Statement Recent advancements in using deep learning to increase the resolution of images have substantial potential across the many scientific fields that use images and image-like data. Most image super-resolution research has focused on the visual quality of outputs, however, and is not necessarily well suited for use with scientific data where known physics constraints may need to be enforced. Here, we introduce a method to modify existing deep neural network architectures so that they strictly conserve physical quantities in the input field when “super resolving” scientific data and find that the method can improve performance across a wide range of datasets and neural networks. Integration of known physics and adherence to established physical constraints into deep neural networks will be a critical step before their potential can be fully realized in the physical sciences.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Inflight lightning characteristics measurement system

A research data-gathering system being developed for inflight measurement of direct and nearby lightning strike characteristics is described. Wideband analog recorders used to record the lightning scenario are supplemented with high-sample-rate digital transient recorders with augmented memory capacity for increased time resolution of specific times of interest. The endless-loop data storage technique employed by the transient recorders circumvents problems associated with oscilloscopic techniques and allows unattended operation. System integrity and immunity from induced effects is accomplished by fiber-optics signal-transmission links, shielded system enclosures, and the use of a dynamotor for power system isolation.

Pitts, F. L.↗
NASA NTRS2010

Interplanetary Magnetic Field Power Spectrum Variations: A VHO Enabled Study

The newly reprocessed high time resolution (11/22 vectors/sec) Wind mission interplanetary magnetic field data and the solar wind key parameter search capability of the Virtual Heliospheric Observatory (VHO) affords an opportunity to study magnetic field power spectral density variations as a function of solar wind conditions. In the reprocessed Wind Magnetic Field Investigation (MFI) data, the spin tone and its harmonics are greatly reduced that allows the meaningful fitting of power spectra to the approx.2 Hz limit above which digitization noise becomes apparent. The power spectral density is computed and the spectral index is fitted for the MHD and ion inertial regime separately along with the break point between the two for various solar wind conditions . The time periods of fixed solar wind conditions are obtained from VHO searches that greatly simplify the process. The functional dependence of the ion inertial spectral index and break point on solar wind plasma and magnetic field conditions will be discussed

Szabo, A.↗
NASA NTRS2011

Interplanetary Magnetic Field Power Spectrum Variations: A VHO Enabled Study

The newly reprocessed high time resolution (11/22 vectors/sec) Wind mission interplanetary magnetic field data and the solar wind key parameter search capability of the Virtual Heliospheric Observatory (VHO) affords an opportunity to study magnetic field power spectral density variations as a function of solar wind conditions. In the reprocessed Wind Magnetic Field Investigation (MFI) data, the spin tone and its harmonics are greatly reduced that allows the meaningful fitting of power spectra to the ~2 Hz limit above which digitization noise becomes apparent. The power spectral density is computed and the spectral index is fitted for the MHD and ion inertial regime separately along with the break point between the two for various solar wind conditions. The time periods of fixed solar wind conditions are obtained from VHO searches that greatly simplify the process. The functional dependence of the ion inertial spectral index and break point on solar wind plasma and magnetic field conditions will be discussed

Szabo, A.↗
DOE OSTI2020

Water Withdrawal and Consumption Data from McManamay et al. 2020

This dataset contains estimations of water withdrawal and consumption (for electricity production only) at the county resolution on an annual time step from 1950 to 2016. Water withdrawal and consumption for electricity production are also provided at the electric generating unit resolution. Additionally, water use for irrigation was calculated at a daily time step. Data are associated with McManamay et al. 2020 in WRR.

13 HYDRO ENERGY↗
NASA NTRS2010

Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

Limaye, Ashutosh S.↗
NASA NTRS2011

Interplanetary Magnetic Field Power Spectrum Variations in the Inner Heliosphere: A Wind and MESSENGER Study

The newly reprocessed high time resolution (11/22 vectors/sec) Wind mission interplanetary magnetic field data and the similar observations made by the MESSENGER spacecraft in the inner heliosphere affords an opportunity to compare magnetic field power spectral density variations as a function of radial distance from the Sun under different solar wind conditions. In the reprocessed Wind Magnetic Field Investigation (MFI) data, the spin tone and its harmonics are greatly reduced that allows the meaningful fitting of power spectra to the approx.2 Hz limit above which digitization noise becomes apparent. The powe'r spectral density is computed and the spectral index is fitted for the MHD and ion inertial regime separately along with the break point between the two for various solar wind conditions. Wind and MESSENGER magnetic fluctuations are compared for times when the two spacecraft are close to radial and Parker field alignment. The functional dependence of the ion inertial spectral index and break point on solar wind plasma and magnetic field conditions will be discussed.

Szabo, Adam↗
NASA NTRS2012

Advances in the RXTE Proportional Counter Array Calibration: Nearing the Statistical Limit

During its 16 years of service Rossi X-ray Timing Explorer (RXTE) mission has provided an extensive archive of data, which will serve as a primary source of high cadence observation of variable X-ray sources for fast timing studies. It is, therefore, very important to have the most reliable calibration of RXTE instruments. The Proportional Counter Array (PCA) is the primary instrument on-board RXTE which provides data in 2-50 keY with higher than millisecond time resolution in up to 256 energy channels. In 2009 RXTE team revised the response residual minimization method used to derive the parameters of the PCA physical model. The procedure is now based on the residual minimization between the model spectrum for Crab nebula emission and a calibration data set consisting of a number of spectra from the Crab and the on-board Am241 calibration source, uniformly covering a whole RXTE span. The new method led to a much more effective model convergence and allowed for better understanding of the behavior of the PCA energy-to-channel relationship. It greatly improved the response matrix performance. We describe the new version of the RXTE/PCA response generator PCARMF vll.7 along with the corresponding energy-to-channel conversion table (version e05v04) and their difference from the previous releases of PCA calibration. The new PCA response adequately represents the spectrum of the calibration sources and successfully predicts the energy of the narrow iron emission line in Cas-A throughout the RXTE mission.

Shaposhnikov, Nikolai↗
NASA NTRS2023

Spatiotemporal Characterization of Droughts and Vegetation Response in Northwest Africa From 1981 to 2020

Drought has become one of the most devastating natural risks of agricultural production and the environment in almost all climate regions. Thus, understanding the spatiotemporal characteristics of drought and its associated impacts is crucial in drought early warning management and adaptation efforts. In this study, we used the 3-month Standardized Precipitation Index (SPI-3) obtained from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) to investigate the space–time characteristics of drought conditions. Also, this study examined the impact of the SPI-based drought on vegetation health conditions using the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time-series data from 1981 to 2020. The results revealed that the region experiences drought primarily between July and September, with the most prolonged drought events lasting up to five months. Morocco suffered from more frequent droughts than other countries in the region. The Mann-Kendall test showed that the trend of drought became drier over the last decade, whereas the period from 1981 to 2010 witnessed either wetting or no trends. This study also found that the response of crops and grasslands showed higher correlation with the SPI-3 and that the response of vegetation to droughts was higher during the dry season. The findings of this study provide useful information to support local and regional drought planning and adaptation programs and enhance the understanding of drought development in the region.

Nguyen Quang Thi↗
NASA NTRS2009

Synthetic Foveal Imaging Technology

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Hoenk, Michael↗
NASA NTRS1989

Periodic behaviors in the observed vertical column abundances of atmospheric hydroxyl

The data base for the vertical column abundance of atmospheric hydroxyl (OH) for Fritz Peak Observatory, Colorado (40 N, 105 W), now extends from 1976 through 1988 and is composed of 8849 independent data sets, averaging about 15 percent uncertainty and 20-minute time resolution each. The dominant solar zenith angle (chi) dependence of the OH abundance is characterized by an empirical curve, N(88), which has been updated from N(82) to include all valid data from 1980 through 1988. The chi-dependence of the OH abundance has been, to a first order, removed from the data base by a normalization procedure in which each data point is divided by the N(88,AM) value for the corresponding solar zenith angle. The resulting normalized OH values may then be examined for other systematic effects, particularly for periodic variations. Observations have also been made at Boca Raton, Florida (26 N, 80 W) and at Truk, Federated States of Micronesia (7 N, 152 E). These data bases are much less extensive and, as such, are less amenable to analysis for periodic behaviors. Some comparisons with the Colorado data may be made, however.

Burnett, Elizabeth Beaver↗
NASA NTRS1999

Pulse Profiles, Accretion Column Dips and a Flare in GX 1+4 During a Faint State

The Rossi X-ray Timing Explorer (RXTE) spacecraft observed the X-ray GX 1+4 for it period of 34 hours on July 19/20 1996. The source faded front an intensity of approximately 20 mcrab to a minimum of <= 0.7 mcrab and then partially recovered towards the end of the observation. This extended minimum lasted approximately 40,000 seconds. Phase folded light curves at a barycentric rotation period of 124.36568 +/- 0.00020 seconds show that near the center of the extended minimum the source stopped pulsing in the traditional sense but retained a weak dip feature at the rotation period. Away from the extended minimum the dips are progressively narrower at higher energies and may be interpreted as obscurations or eclipses of the hot spot by the accretion column. The pulse profile changed from leading-edge bright before the extended minimum to trailing-edge bright after it. Data from the Burst and Transient Source Experiment (BATSE) show that a torque reversal occurred < 10 days after our observation. Our data indicate that the observed rotation departs from a constant period with a P/P value of approximately -1.5% per year at a 4.5sigma significance. We infer that we may have serendipitously obtained data, with high sensitivity and temporal resolution about the time of an accretion disk spin reversal. We also observed a rapid flare which had some precursor activity close to the center of the extended minimum.

Giles, A. B.↗
NASA NTRS1999

Pulse Profiles, Accretion Column and a flare in Gx 1+4 During a Faint State

The Rossi X-ray Timing Explorer (RXTE) spacecraft observed the X-ray pulsar GX 1+4 for a period of 34 hours on July 19/20 1996. The source faded from an intensity of approx. 20 mcrab to a minimum of less than or equal to 0.7 mcrab and then partially recovered towards the end of the observation. This extended minimum lasted approx. 40,000 seconds. Phase folded light curves at a barycentric rotation period of 124.36568 +/- 0.00020 seconds show that near the center of the extended minimum the source stopped pulsing in the traditional sense but retained a weak dip feature at the rotation period. Away from the extended minimum the dips are progressively narrower at higher energies and may be interpreted as obscurations or eclipses of the hot spot by the accretion column. The pulse profile changed from leading-edge bright before the extended minimum to trailing-edge bright after it. Data from the Burst and Transz'ent Source Experiment (BATSE) show that a torque reversal occurred less than 10 days after our observation. Our data indicate that the observed rotation departs from a constant period with a P/P value off approx. -5% per year at a 4.5(sigma) significance. We infer that we may have serendipitously obtained data. with high sensitivity and temporal resolution about the time of an accretion disk spin reversal. We also observed a rapid flare which had some precursor activity close to the center of the extended minimum.

Giles, A. B.↗
NASA NTRS2012

Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the other uses the daily SPoRT/MODIS GVFs. Finally, snapshots of the LIS land surface fields are used to initialize two different simulations of the NU-WRF, one running with climatology LIS and GVFs, and the other running with experimental LIS and NASA/SPoRT GVFs. In this paper/presentation, case study results will be highlighted in regions with significant differences in GVF between the NCEP climatology and SPoRT product during severe weather episodes.

Case, Jonathan L.↗
DOE OSTI2024

High-Resolution Meteorology with Climate Change Impacts from Global Climate Model Data Using Generative Machine Learning

As renewable energy generation increases, the impacts of weather and climate on energy generation and demand become critical to the reliability of the energy system. However, these impacts are often overlooked. Global climate models (GCMs) can be used to understand possible changes to our climate, but their coarse resolution makes them difficult to use in energy system modelling. Here we present open-source generative machine learning methods that produce meteorological data at a nominal spatial resolution of 4 km at an hourly frequency based on inputs from 100 km daily-average GCM data. These methods run 40 times faster than traditional downscaling methods and produce data that have high-resolution spatial and temporal attributes similar to historical datasets. We demonstrate that these methods can be used to downscale projected changes in wind, solar and temperature variables across multiple GCMs including projections for more frequent low-wind and high-temperature events in the Eastern United States.

climate change↗
DOE OSTI2023

FTR for: Reducing plug-load electricity footprint of residential buildings through low-cost, non-intrusive sub-metering and personalized feedback technology

The project started in October 2016 and ended in December 2022. The project's principal goals and achievements were: (i) Measure real and reactive electric power consumption in ~400 apartments in multifamily settings of varying size and vintage and publish the data; data was published according to New York State's recommended 15x15 rule continuously from Jan 2019 through December 2022 (10 second time resolution); with the combination of large number of apartments, real and reactive power, as well as high time resolution (10-seconds), the dataset is first of its kind worldwide; because the dataset New York City apartment consumption pre, during, and post pandemic, it further offers unique insights into changes in residential electricity consumption during lockdowns and after modified work from home schedules. (ii) Measure effectiveness of different feedback types to prompt residents to lower their electricity consumption; achieved 11% (kWh-weighted) reduction versus baseline consumption; confirmed previous studies that social comparisons elicit above average responses; showed, for the first time, that the so called boomerang effect in power consumption feedback projects can be explained by a previously hypothesized norm-conforming "magnet effect" (rather than a non-conforming defiance effect), thus substantially advancing the research in the field. (iii) Disaggregate apartment-level consumption to appliance level; because the hardware for electricity consumption unexpectedly allowed only for 10-second time resolution (rather than the 1-second resolution we had planned on), the disaggregation algorithms we developed on sample data could not be applied to the actual field data we collected. The project has yielded high visibility, with a total of 17 publications, from peer reviewed journals, published data sets (free access), blog posts, NY Times, National Public Radio, and CNN.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination

Abstract Synchrotron X‐ray‐based in situ metrology is advantageous for monitoring the synthesis of battery materials, offering high throughput, high spatial and temporal resolution, and chemical sensitivity. However, the rapid generation of massive data poses a challenge to on‐site, on‐the‐fly analysis needed for real‐time process monitoring. Here, a weighted lagged cross‐correlation (WLCC) similarity approach is presented for automated data analysis, which merges with in situ synchrotron X‐ray diffraction metrology to monitor the calcination process of the archetypal nickel‐based cathode, LiNiO 2 . The WLCC approach, incorporating variables that account for peak shifts and width changes associated with structural transformations, enables rapid extraction of phase progression within 10 seconds from tens of diffraction patterns. Details are captured, from initial precursors to intermediates and the final layered LiNiO 2 , providing information for agile on‐site adjustments during experiments and complementing post hoc diffraction analysis by offering insights into early‐stage phase nucleation and growth. Expanding this data‐powered platform paves the way for real time calcination process monitoring and control, which is pivotal to quality control in battery cathode manufacturing.

36 MATERIALS SCIENCE↗