Determination of ellipsoidal surface mass change from GRACE time-variable gravity data
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Khosro Ghobadi-Far↗
SEARCH · Engineering Papers
Results for “Data Variables”
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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Salinity stress on three representative species from Mediterranean semifixed dunes: Assessment of salinity exposure and substrate conductivity data reveal variable response strategies and tolerance between species
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M.D. Cerrato↗
Cloud encounter and particle density variabilities from GASP data
Summary statistics and variability studies are presented for cloud encounter and particle number density data as part of the NASA Global Atmospheric Sampling Program (GASP) aboard commercial Boeing 747 airliners. On the average, cloud encounter is shown on about 15% of the 52,164 data samples available; this value varies with season, latitude, synoptic weather situation, and distance from the tropopause. The number density of particles (diameter greater than 3 microns) also varies with time and location, and depends on the horizontal extent of cloudiness.
Nastrom, G. D.↗
Hourly gap-filled meteorological data from PIE LTER measurements (2004-2023) used as drivers to run ELM PFLOTRAN simulations
This dataset contains continuous gap-filled precipitation, solar radiation, photosynthetically active radiation (PAR), air temperature, relative humidity, wind speed, and barometric pressure data recorded primarily at the Marshview Farm weather station within the Plum Island Long Term Ecosystems Research (PIE LTER) in Newbury Massachusetts (MA) from 2004 to 2023. We compiled the data set from published annual data packages in 15min resolution available on DataOne. Gaps were filled using different statistical techniques or available observations from the vicinity, e.g. the US-PLo and the US-PHM Ameriflux sites, also located within the PIE LTER. Flags are included in this dataset to indicate the origin of each data point. Metadata files ELMPFLOTRAN_met_dd.csv and ELMPFLOTRAN_met_flmd.csv contain more information on site locations, gap filling protocols, data variables, flags, and QA/QC methods. The data set was used in the spin up and simulations of a land surface model coupled to a biogeochemical reaction network (ELM PFLOTRAN) assessing impacts of hydrology and salinity input on methane fluxes in 2022 and 2023 (Sulman et al., 2024).
54 ENVIRONMENTAL SCIENCES↗
Metrics and Methods for Radiation Detection Algorithm Characterization for Nuclear/Radiological Source Search
This report presents a series of recommendations for data to train and evaluate radiation detection algorithms and performance metrics to evaluate these algorithms. These recommendations were formed through a community consensus approach through the Detection Radiation Algorithms Group (DRAG), a multi-institution collaboration spanning eight Department of Energy laboratories and John Hopkins Applied Physics Laboratory. This report includes recommendations on background data variability, and metrics to quantify variability, sources and shielding configurations to include in data collection campaigns and detector response variability. In addition, this report describes several anomaly detection and identification algorithms and recommends metrics to report their performance. Finally, this report ends with a discussion on machine learning algorithms.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
GES DISC Datalist Enables Easy Data Selection For Natural Phenomena Studies
In order to investigate and assess natural hazards such as tropical storms, winter storms, volcanic eruptions, floods, and drought in a timely manner, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been developing an efficient data search and access service. Called "Datalist," this service enables users to acquire their data of interest "all at once," with minimum effort. A Datalist is a virtual collection of predefined or user-defined data variables from one or more archived data sets. Datalists are more than just data. Datalists effectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services (e.g., subset and OPeNDAP), all available from one-stop shopping. The predefined Datalists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend. The Datalist service is an extension of the new GES DISC website, which is completely data-driven. A Datalist, also known as "data bundle," is treated just as any other data set. Being a virtual collection, a Datalist requires no extra storage space.
natural hazards↗
GES DISC Datalist Enables Easy Data Selection for Natural Phenomena Studies
In order to investigate and assess natural hazards such as tropical storms, winter storms, volcanic eruptions, floods, and drought in a timely manner, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been developing an efficient data search and access service. Called Datalist, this service enables users to acquire their data of interest all at once, with minimum effort. A Datalistis a virtual collection of predefined or user-defined data variables from one or more archived data sets. Datalistsare more than just data. Datalistseffectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services (e.g., subset and OPeNDAP), all available from one-stop shopping. The predefined Datalists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend. The Datalistservice is an extension of the new GES DISC website, which is completely data-driven. A Datalist, also known as data bundle, is treated just as any other data set. Being a virtual collection, a Datalistrequires no extra storage space.
Earth events↗
Cloud-encounter and particle-concentration variabilities from GASP data
Summary statistics, tabulations, and variability studies are presented for cloud encounter and particle concentration data taken as part of the NASA global atmospheric sampling program. Cloud encounter was experienced in about 15 percent of the data samples; however, the percentage varies with season, latitude, and altitude (particularly distance from the tropopause). In agreement with classical storm models, the data show more clouds in the upper troposphere in anticyclones than in cyclones. The concentration of particles with a diameter greater than 3 micron also varies with time and location, depending primarily on the horizontal extent of cloudiness. Some examples of the application of the statistical data to the estimation of the frequency of cloud encounter and laminar flow loss to be expected on long range airline routes are also presented.
Nastrom, G. D.↗
Sensor data autonomy
'Smart' sensors onboard NASA space missions will require variable data output bandwidth as they respond to phenomena of interest. An Instrument Telemetry Packet (ITP) approach has been developed which encodes experimental instrument data into an autonomous data package, along with pertinent engineering parameters and ancillary data (time, position, attitude, etc.). New requirements for onboard concentration and buffering, as well as for end-to-end error control, arise from this approach. Emphasis is placed on packet protocols compatible with the data link standard ADCCP, to enable one set of ground support equipment to readily support instrument development, launch site checkout and mission operations phases.
Greene, E. P.↗
An Efficient Variable-Length Data-Compression Scheme
Adaptive variable-length coding scheme for compression of stream of independent and identically distributed source data involves either Huffman code or alternating run-length Huffman (ARH) code, depending on characteristics of data. Enables efficient compression of output of lossless or lossy precompression process, with speed and simplicity greater than those of older coding schemes developed for same purpose. In addition, scheme suitable for parallel implementation on hardware with modular structure, provides for rapid adaptation to changing data source, compatible with block orientation to alleviate memory requirements, ensures efficiency over wide range of entropy, and easily combined with such other communication schemes as those for containment of errors and for packetization.
Cheung, Kar-Ming↗
Decoding Golden Eagle Movement Behavior from High-Resolution, Variable-Rate Telemetry Data Through Bayesian Filtering
The recent advances in animal tracking technology have enabled the collection of a vast amount of in situ data regarding the movement of wildlife at high spatiotemporal resolution. These data are usually available at variable time resolutions and contains noise (error) originating from GPS fixes. Decoding movement characteristics, particularly of flying animals, from telemetry data while handling these factors is a challenging yet important task for conservation purposes. Typically, this task is broken into two subtasks: resampling, and model calibration. The resampling subtask converts the variable rate positional data into a constant time interval data, while the model calibration subtask uses the resampled data to tune time-invariant parameters of the proposed models. For telemetry data at high temporal resolutions (order of 1 second), it is very challenging to decouple noise from actual movements using interpolation-based resampling techniques. Any errors introduced during resampling can significantly alter the the calibration and prediction attributes of the movement model. We address this problem through a unified Bayesian state-space framework that can handle both the resampling and calibration tasks in a single step. In addition, we use the speed and heading of the bird from telemetry data to regularize the position information of the bird. We use a Kalman filtering approach to include these nonlinearly related motion parameters within the state space framework. We cross-validated to quantify how this inclusion affects the model performance in estimating true bird movements. The relationship between the true state of the bird and environmental and topographical covariates is then represented parametrically. These parameters are then tuned using stochastic sampling strategies like Markov Chain Monte Carlo (MCMC). We use the telemetry data collected from golden eagles in the western USA to demonstrate the applicability of this approach to build a predictive, probabilistic movement model. Our preliminary results show that this approach provides improved predictive performance in terms of capturing higher-order motion parameters such as angular and horizontal accelerations, which may have simpler and more direct relationships with environmental covariates than corresponding speeds. In this talk, we will demonstrate how this state-space approach benefits the prediction capabilities of a movement model in simulating golden eagle paths through a wind power plant in Wyoming given certain atmospheric conditions. The model outcomes are aimed at informing mitigation strategies that can minimize the potential for collisions of golden eagles with wind turbines.
Bayesian methods↗
Shuttle booster separation aerodynamics
A wind tunnel test program of some complexity was used to define the aerodynamic forces exerted on the space shuttle solid rocket boosters and orbiter/external tank during staging. In these tests, problems associated with the use of up to three models in close proximity and with the need to simulate high pressure separation motor plumes were handled in a unique and effective manner. A new method was developed for efficiently organizing data which is a function of a large number of independent variables. Data derived from the test program drastically reduced previous estimates of aerodynamic uncertainties and allowed certification of the separation system at the design maximum staging dynamic pressure. Reduction of flight data has implicitly verified the staging aerodynamics data base and its associated uncertainties.
Mark K. Craig↗
A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics
In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data post-processing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR (Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. This technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.
Temporal Queries↗
Analysis of variable-head viscometer data
Nonnewtonian mathematical model and plotting method for analyzing variable head viscometer data obtained on pseudo-plastic polymer solutions - Rheology
MATHEMATICAL MODEL↗
Concepts for a theoretical and experimental study of lifting rotor random loads and vibrations (identification of lifting rotor system parameters from transient response data), Phase 7-B
System identification methods have been applied to rotorcraft to estimate stability derivatives from transient flight control response data. While these applications assumed a linear constant coefficient representation of the rotorcraft, the computer experiments used transient responses in flap-bending and torsion of a rotor blade at high advance ratio which is a rapidly time varying periodic system. It was found that a simple system identification method applying a linear sequential estimator also called least square estimator or equation of motion estimator, is suitable for this periodic system and can be used directly if only the acceleration data are noise polluted. In the case of noise being present also in the state variable data the direct application of the estimator gave poor results.
Hohenemser, K. H.↗
Measurement of Cyanobacterial Bloom Magnitude Using Satellite Remote Sensing
Cyanobacterial harmful algal blooms (cyano HABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude,information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatio temporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio (USA) respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Sentinel-3 Ocean Land Color Imager (OLCI) data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision making for recreational and drinking water sources.
Sachidananda Mishra↗
Cardiopulmonary data-acquisition system
Computerized system controls and monitors bicycle and treadmill cardiovascular stress tests. It acquires and reduces stress data and displays heart rate, blood pressure, workload, respiratory rate, exhaled-gas composition, and other variables. Data are printed on hard-copy terminal every 30 seconds for quick operator response to patient. Ergometer workload is controlled in real time according to experimental protocol. Collected data are stored directly on tape in analog form and on floppy disks in digital form for later processing.
Crosier, W. G.↗
Computer experiments on periodic systems identification using rotor blade transient flapping-torsion responses at high advance ratio
Computer experiments are described which used transient responses in flap-bending and torsion of a rotor blade at high advance ratio. It was found that a simple system identification method applying a linear sequential estimator also called equation of motion estimator, is suitable for this periodic system and can be used directly, if only the acceleration data are noise-polluted. In the case where noise is also present in the state-variable data, the direct application of the estimator gave poor results. However after prefiltering the data with a digital Graham filter having a cutoff frequency above the natural blade torsion frequency, the linear sequential estimator successfully recovered the parameters of the periodic coefficient analytical model.
Hohenemser, K. H.↗