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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multitaper Magnitude‐Squared Coherence for Time Series With Missing Data: Understanding Oscillatory Processes Traced by Multiple Observables

To explore the hypothesis of a common source of variability in two time series, observers may estimate the magnitude-squared coherence (MSC), which is a frequency-domain view of the cross correlation. For time series that do not have uniform observing cadence, MSC can be estimated using Welch's overlapping segment averaging. However, multitaper has superior statistical properties to Welch's method in terms of the tradeoff between bias, variance, and bandwidth. The classical multitaper technique has recently been extended to accommodate time series with underlying uniform observing cadence from which some observations are missing. This situation is common for solar and geomagnetic data sets, which may have gaps due to breaks in satellite coverage, instrument downtime, or poor observing conditions. We demonstrate the scientific use of missing-data multitaper magnitude-squared coherence by detecting known solar mid-term oscillations in simultaneous, missing-data time series of solar Lyman α flux and geomagnetic Disturbance Storm Time index. Due to their superior statistical properties, we recommend that multitaper methods be used for all heliospheric time series with underlying uniform observing cadence.

Astro-statistics techniques (1886)↗
NASA NTRSDate not supplied

Identifying Large Transients within ARTEMIS Solar Wind Data for Nightside Time Domain Electromagnetic Sounding

Mysteries regarding the Moon’s internal composition persist. By studying the induced magnetic fields produced by the Moon in response to changes in the magnetic field of the surrounding solar wind, inferences can be made regarding the associated eddy currents and thus regarding the electrical conductivities of the lunar regions hosting these currents. In this manner, a greater understanding of the Moon’s inner geophysical properties can be garnered. This investigative strategy, known as electromagnetic sounding, can be employed using magnetic field data from the ARTEMIS satellites. In particular, data taken from time intervals in which one satellite is within the lunar wake and within 500 km of the surface while the other is relatively far from the surface immersed within the pristine solar wind. Per Faraday’s Law, the steeper the magnetic transient from the solar wind, the greater the current induced within the Moon, and per Ampère’s Law, the greater this induced current, the larger the magnetic field it produces. Larger signals generally feature higher signal-to-noise ratios (SNRs). Thus, larger transients tend to produce more valuable data in terms of sounding. The enhanced separation between source signal and reaction signal via the aforementioned positioning of the probes during time intervals of interest augments the SNRs as well. Here we discuss tools developed in Python (making use of the PySPEDAS package) that expedites the task of identifying large magnetic transients within these time frames of interest. These exceptional changes in magnetic field are then evaluated for use in electromagnetic sounding as described above. We have identified 51 major transient events (during times of interest) from 8/1/2011 to 7/31/2021. One key hurdle we overcame was identifying and navigating data gaps. These data gaps would often interfere with our time intervals of interest, necessitating an algorithm to avoid them.

Moons↗
DOE OSTI2022

Time-lapse seismic data inversion for estimating reservoir parameters using deep learning

Geologic carbon sequestration involves the injection of captured carbon dioxide ([Formula: see text]) into subsurface formations for long-term storage. The movement and fate of the injected [Formula: see text] plume is of great concern to regulators because monitoring helps to identify potential leakage zones and determines the possibility of safe long-term storage. To address this concern, we design a deep-learning framework for [Formula: see text] saturation monitoring to determine the geologic controls on the storage of the injected [Formula: see text]. We use different combinations of porosities and permeabilities for a given reservoir to generate saturation and velocity models. We train the deep-learning model with a few time-lapse seismic images and their corresponding changes in saturation values for a particular [Formula: see text] injection site. The deep-learning model learns the mapping from the change in the time-lapse seismic response to the change in [Formula: see text] saturation during the training phase. We then apply the trained model to data sets comprising different time-lapse seismic image slices (corresponding to different time instances) generated using different porosity and permeability distributions that are not part of the training to estimate the [Formula: see text] saturation values along with the plume extent. Our algorithm provides a deep-learning assisted framework for the direct estimation of [Formula: see text] saturation values and plume migration in heterogeneous formations using the time-lapse seismic data. Our method improves the efficiency of time-lapse inversion by streamlining the large number of intermediate steps in the conventional time-lapse inversion workflow. This method also helps to incorporate the geologic uncertainty for a given reservoir by accounting for the statistical distribution of porosity and permeability during the training phase. Tests on different examples verify the effectiveness of our approach.

Geochemistry & Geophysics↗
NASA NTRS1997

Wavelet Analyses of F/A-18 Aeroelastic and Aeroservoelastic Flight Test Data

Time-frequency signal representations combined with subspace identification methods were used to analyze aeroelastic flight data from the F/A-18 Systems Research Aircraft (SRA) and aeroservoelastic data from the F/A-18 High Alpha Research Vehicle (HARV). The F/A-18 SRA data were produced from a wingtip excitation system that generated linear frequency chirps and logarithmic sweeps. HARV data were acquired from digital Schroeder-phased and sinc pulse excitation signals to actuator commands. Nondilated continuous Morlet wavelets implemented as a filter bank were chosen for the time-frequency analysis to eliminate phase distortion as it occurs with sliding window discrete Fourier transform techniques. Wavelet coefficients were filtered to reduce effects of noise and nonlinear distortions identically in all inputs and outputs. Cleaned reconstructed time domain signals were used to compute improved transfer functions. Time and frequency domain subspace identification methods were applied to enhanced reconstructed time domain data and improved transfer functions, respectively. Time domain subspace performed poorly, even with the enhanced data, compared with frequency domain techniques. A frequency domain subspace method is shown to produce better results with the data processed using the Morlet time-frequency technique.

Martin J Brenner↗
NASA NTRS2016

Analysis of One-Way Laser Ranging Data to LRO, Time Transfer and Clock Characterization

We processed and analyzed one-way laser ranging data from International Laser Ranging Service ground stations to NASA's Lunar Reconnaissance Orbiter (LRO), obtained from June 13, 2009 until September 30, 2014. We pair and analyze the one-way range observables from station laser fire and spacecraft laser arrival times by using nominal LRO orbit models based on the GRAIL gravity field. We apply corrections for instrument range walk, as well as for atmospheric and relativistic effects. In total we derived a tracking data volume of approximately 3000 hours featuring 64 million Full Rate and 1.5 million Normal Point observations. From a statistical analysis of the dataset we evaluate the experiment and the ground station performance. We observe a laser ranging measurement precision of 12.3 centimeters in case of the Full Rate data which surpasses the LOLA (Lunar Orbiting Laser Altimeter) timestamp precision of 15 centimeters. The averaging to Normal Point data further reduces the measurement precision to 5.6 centimeters. We characterized the LRO clock with fits throughout the mission time and estimated the rate to 6.9 times10 (sup -8), the aging to 1.6 times 10 (sup -12) per day and the change of aging to 2.3 times 10 (sup -14) per day squared over all mission phases. The fits also provide referencing of onboard time to the TDB (Barycentric Dynamical Time) time scale at a precision of 166 nanoseconds over two and 256 nanoseconds over all mission phases, representing ground to space time transfer. Furthermore we measure ground station clock differences from the fits as well as from simultaneous passes which we use for ground to ground time transfer from common view observations. We observed relative offsets ranging from 33 to 560 nanoseconds and relative rates ranging from 2 times 10 (sup -13) to 6 times 10 (sup -12) between the ground station clocks during selected mission phases. We study the results from the different methods and discuss their applicability for time transfer.

Bauer, S.↗
DOE OSTI2025

Temperature, Humidity, and Time-Lapse Video Data from the East River Watershed, Water Years 2024 and 2025

This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across the East River basin from 3 October 2023 to 8 August 2025. Instruments were deployed at 19 sites as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. Time-lapse cameras were deployed at three sites. Imagery from sites AP BONUS and AP5 (Avery Picnic) provides insight into large-scale seasonal snow cover variability. Imagery from site EL2 (Emerald Lake) shows smaller-scale snow patterns across a nearby meadow. Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into short videos stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Open-Source Framework for Data Storage and Visualization of Real-Time Experiments

Digital real time simulators (DRTS) are increasingly being used for the evaluation of power hardware and controller hardware in the laboratory prior to field deployment. Although DRTS are capable of simulating large models in real-time, it is challenging to visualize the results of large models without overdrawing or confounding the viewer. This paper provides an open-source framework for users to visualize their DRTS-based hardware-in-the-loop (HIL) experimental results in real-time. This proposed framework can be used by experimental test beds that can push data through an internet protocol based network. The proposed framework includes three main components. First, it includes the DRTS that generates and pushes the data to a relay. Second, it includes an application that serves multiple purposes, from data storage, testing, and translation of the data to a publisher/subscriber protocol. Finally, it includes libraries and applications that can be used to visualize the data by subscribing to the relay. This framework is available in open source, and it is tested using the HIL platform developed for testing advanced distribution management systems.

advanced distribution management systems↗
DOE OSTI2022

Quality Analysis of Baseline Time-Lapse CSEM Data CarbonSAFE Project, North Dakota

Conference presentation at International Meeting for Applied Geoscience & Energy (IMAGE), Houston, TX, August 28 – September 2, 2022. When a series of time-lapse CSEM surveys are designed to measure the often-small variations in signal seen in CCUS projects, the primary concern must be collecting the highest-quality data and reducing as much noise as possible. This includes optimization during planning and feasibility, careful and consistent quality checks in the field, and transparent and repeatable postprocessing steps. We apply this practice to a baseline (prior to CO 2 injection) CSEM data set collected for a time-lapse survey in Center, North Dakota, as a part of the North Dakota CarbonSAFE project, and describe the rigorous quality control and assessment methods used, including noise removal and data validation with 1D and 3D inversion to tie results to borehole logs. The final result is an accurate and representative CSEM data set and information that stakeholders can use to inform future time-lapse survey costs and designs.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1973

Near real time water resources data for river basin management

The author has identified the following significant results. Twenty Data Collection Platforms (DCP) are being field installed on USGS water resources stations in the Delaware River Basin. DCP's have been successfully installed and are operating well on five stream gaging stations, three observation wells, and one water quality monitor in the basin. DCP's have been installed at nine additional water quality monitors, and work is progressing on interfacing the platforms to the monitors. ERTS-related water resources data from the platforms are being provided in near real time, by the Goddard Space Flight Center to the Pennsylvania district, Water Resources Division, U.S. Geological Survey. On a daily basis, the data are computer processed by the Survey and provided to the Delaware River Basin Commission. Each daily summary contains data that were relayed during 4 or 5 of the 15 orbits made by ERTS-1 during the previous day. Water resources parameters relays by the platforms include dissolved oxygen concentrations, temperature, pH, specific conductance, well level, and stream gage height, which is used to compute stream flow for the daily summary.

Paulson, R. W.↗
DOE OSTI2015

Independent Analysis of Real-Time, Measured Performance Data From Microcogenerative Fuel Cell Systems Installed in Buildings

Pacific Northwest National Laboratory (PNNL) is working with industry to independently monitor up to 15 distinct 5 kW-electric (kWe) combined heat and power (CHP) high temperature (HT) proton exchange membrane (PEM) fuel cell systems (FCSs) installed in light commercial buildings. This research paper discusses an evaluation of the first six months of measured performance data acquired at a 1 s sampling rate from real-time monitoring equipment attached to the FCSs at building sites. Engineering performance parameters are independently evaluated. Based on an analysis of the first few months of measured operating data, FCS performance is consistent with manufacturer-stated performance. Initial data indicate that the FCSs have relatively stable performance and a long-term average production of about 4.57 kWe of power. This value is consistent with, but slightly below, the manufacturer's stated rated electric power output of 5 kWe. The measured system net electric efficiency has averaged 33.7%, based on the higher heating value (HHV) of natural gas fuel. This value, also, is consistent with, but slightly below, the manufacturer's stated rated electric efficiency of 36%. The FCSs provide low-grade hot water to the building at a measured average temperature of about 48.4 degrees C, lower than the manufacturer's stated maximum hot water delivery temperature of 65 degrees C. The uptime of the systems is also evaluated. System availability can be defined as the quotient of total operating time compared to time since commissioning. The average values for system availability vary between 96.1 and 97.3%, depending on the FCS evaluated in the field. Performance at rated value for electrical efficiency (PRVeff) can be defined as the quotient of the system time operating at or above the rated electric efficiency and the time since commissioning. The PRVeff varies between 5.6% and 31.6%, depending on the FCS field unit evaluated. Performance at rated value for electrical power (PRVp) can be defined as the quotient of the system time operating at or above the rated electric power and the time since commissioning. PRVp varies between 6.5% and 16.2%. Performance at rated value for electrical efficiency and power (PRVt) can be defined as the quotient of the system time operating at or above both the rated electric efficiency and the electric power output compared to the time since commissioning. PRVt varies between 0.2% and 1.4%. Optimization to determine the manufacturer rating required to achieve PRVt greater than 80% has been performed based on the collected data. For example, for FCS Unit 130 to achieve a PRVt of 95%, it would have to be down-rated to an electrical power output of 3.2 kWe and an electrical efficiency of 29%. The use of PRV as an assessment metric for FCSs has been developed and reported for the first time in this paper. For FCS Unit 130, a maximum decline in electric power output of approximately 18% was observed over a 500 h period in Jan. 2012.

fuel cell, combined heat and power, CHP, PEM, prot↗
DOE OSTI2023

Measuring higher-order moments of neutron-time-of-flight data for cryogenic inertial confinement fusion implosions on OMEGA

Ion temperatures serve as an important diagnostic for inertial confinement fusion (ICF) implosions. In direct-drive ICF experiments on OMEGA, neutron-time-of-flight (nTOF) data are used to infer the ion temperature of the fusing plasma produced in the implosion experiment. The analysis of the nTOF data requires an assumption about the shape of the underlying source signal. Since the source nTOF signal is a near-replica of the neutron energy spectrum, an ideal Gaussian shape, corresponding to the neutron energy spectrum of a uniform temperature plasma, is routinely employed. However, spatial and temporal variations of the ion temperature in the plasma give rise to higher-order moments, which were first described by Munro [Nucl. Fusion 56, 036001 (2016)]. In this work, we show a simpler alternative analysis to derive moments of the neutron energy spectrum for a plasma with variations in ion temperature. We also present a revised analysis of measured nTOF signals that uses a model with an additional degree of freedom to take into account the effect of ion temperature variations on the shape of the spectrum. Compared to presently used nTOF analysis, the revised analysis yields on average ≈2× more accurate fits to the data and up to 15% higher ion temperatures for cryogenic experiments. As a result, we quantify the ion temperature inflation caused by radially symmetric fluid flows, which are present even in a symmetric implosion, and which serve as a lower bound on the ion temperature inflation in real implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗