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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mid-Atlantic Turbulence Intensity Data in Observational Space

The dataset archives observed and model-simulated turbulence intensity and meteorological profiles and timeseries at the Air-Sea Interaction Tower (ASIT) of Woods Hole Oceanographic Institution’s Martha’s Vineyard Coastal Observatory (MVCO). The observational data were measured by lidar and buoy deployed at ASIT. The simulated profiles and timeseries data are interpolated in time and/or space according to observations. Simulations were carried out for the mid-Atlantic region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles at the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing.

17 WIND ENERGY↗
DOE OSTI2022

Observational process data analytics using causal inference

Voluminous process data are available with the paradigm shift toward smart manufacturing. However, most historical data are observational, containing noncausal correlations due to confounders and mediators. Estimating causal effects from observational data remains a bottleneck in leveraging them for active applications such as optimization and control. Further, this work aims to introduce a causal modeling framework for analyzing observational process data and extracting quantitative causal information. We demonstrate a real-world application in steel manufacturing where causal inference is used to analyze observational production data and improve the steelmaking process. Additionally, we propose a novel formulation for identifying critical process parameters from observational data, where causal inference is combined with variance-based methods to estimate corresponding risks of interventions to the manufacturing system. The proposed methods are compared with statistical ones to illustrate that causally interpreting statistical correlation leads to problematic results, while the provided workflow generates satisfactory strategies for process improvement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Multiple-wavelength Variability and Quasi-periodic Oscillation of PMN J0948+0022

We present a comprehensive analysis of multiple-wavelength observational data of the first GeV-selected narrow-line Seyfert 1 galaxy PMN J0948+0022. We derive its light curves in the γ -ray and X-ray bands from the data observed with Fermi /LAT and Swift /XRT, and generate the optical and radio light curves by collecting the data from the literature. These light curves show significant flux variations. With the LAT data we show that this source is analogous to typical flat spectrum radio quasars in the L {sub γ} –Γ {sub γ} plane, where L {sub γ} and Γ {sub γ} are the luminosity and spectral index in the LAT energy band. The γ -ray flux is correlated with the V-band flux with a lag of ∼44 days, and a moderate quasi-periodic oscillation (QPO) with a periodicity of ∼490 days observed in the LAT light curve. A similar QPO signature is also found in the V-band light curve. The γ -ray flux is not correlated with the radio flux in 15 GHz, and no similar QPO signature is found at a confidence level of 95%. Possible mechanisms of the QPO are discussed. We propose that gravitational-wave observations in the future may clarify the current plausible models for the QPO.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

DID THE INFANT R136 AND NGC 3603 CLUSTERS UNDERGO RESIDUAL GAS EXPULSION?

Based on kinematic data observed for very young, massive clusters that appear to be in dynamical equilibrium, it has recently been argued that such young systems are examples of where the early residual gas expulsion did not happen or had no dynamical effect. The intriguing scenario of a star cluster forming through a single starburst has thereby been challenged. Choosing the case of the R136 cluster of the Large Magellanic Cloud, the most cited one in this context, we perform direct N-body computations that mimic the early evolution of this cluster including the gas-removal phase (on a thermal timescale). Our calculations show that under plausible initial conditions which are consistent with observational data, a large fraction (>60%) of a gas-expelled, expanding R136-like cluster is bound to regain dynamical equilibrium by its current age. Therefore, the recent measurements of velocity dispersion in the inner regions of R136, which indicate that the cluster is in dynamical equilibrium, are consistent with an earlier substantial gas expulsion of R136 followed by a rapid re-virialization (in Almost-Equal-To 1 Myr). Additionally, we find that the less massive Galactic NGC 3603 Young Cluster (NYC), with a substantially longer re-virialization time, is likely to be found to have deviated from dynamical equilibrium at its present age ( Almost-Equal-To 1 Myr). The recently obtained stellar proper motions in the central part of the NYC indeed suggest this and are consistent with the computed models. This work significantly extends previous models of the Orion Nebula Cluster which already demonstrated that the re-virialization time of young post-gas-expulsion clusters decreases with increasing pre-expulsion density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Antiproton signatures from astrophysical and dark matter sources at the galactic center

The center of our Galaxy is a complex region characterized by extreme phenomena. The presence of the supermassive Sagittarius A* black hole, a high dark matter density and an even higher baryonic density are able to produce very energetic processes. Indeed, high energetic gamma-rays have been observed by different telescopes, although their origin is not clear. In this work, we estimate the possible antiproton flux component associated with this signal. The expected secondary astrophysical antiproton background already saturates the observed data. It implies that any other important astrophysical source leads to an inconsistent excess. We estimate the sensitivity of PAMELA to this new primary antiproton source, which depends on the diffusion model and its spectral features. In particular, we consider antiproton spectra described by a power-law, a monochromatic signal and a Standard Model particle-antiparticle channel production. This latter spectrum is typical in the production from annihilating or decaying dark matter. We pay particular attention to the case of a heavy dark matter candidate, which could be associated with the High Energy Stereoscopic System (HESS) data observed from the J1745-290 source.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Spread Spectrum Time Domain Reflectometry and Steepest Descent Inversion to Measure Complex Impedance

In this paper, we present a method for estimating complex impedances using reflectometry and a modified steepest descent inversion algorithm. We simulate spread spectrum time domain reflectometry (SSTDR), which can measure complex impedances on energized systems for an experimental setup with resistive and capacitive loads. A parametric function, which includes both a misfit function and stabilizer function, is created. The misfit function is a least squares estimate of how close the model data matches observed data. The stabilizer function prevents the steepest descent algorithm from becoming unstable and diverging. Steepest descent iteratively identifies the model parameters that minimize the parametric function. We validate the algorithm by correctly identifying the model parameters (capacitance and resistance) associated with simulated SSTDR data, with added 3 dB white Gaussian noise. With the stabilizer function, the steepest descent algorithm estimates of the model parameters are bounded within a specified range. Furthermore, the errors for capacitance (220pF to 820pF) and resistance (50 Ω to 270 Ω) are < 10%, corresponding to a complex impedance magnitude |R +1/jωC| of 53 Ω to 510 Ω.

14 SOLAR ENERGY↗
DOE OSTI2023

Evaluation of a preliminary regional Earth model through comparison of synthetic and observed waveform data

In this report, we document the process related to developing a regional geologic model of a 605 x 1334 km area centered around Utah and encompassing surrounding states. This model is developed to test the effect that composition of a model has on the generation of synthetic data with the intent of using this information to improve upon full waveform moment tensor inversions. We compare observed data from three seismic events and five stations to the synthetic data generated by a preliminary model derived from a geologic framework model (GFM) developed by the USGS. The synthetic data and observed data comparisons indicate that our preliminary model performs well at smaller offset distances in the northern and central sections of the model. However, the southern stations consistently display synthetic data P- and S-wave arrival times that do not match the observed data arrival times, indicating that the velocity structure of the southern part of the model especially is inaccurate.

58 GEOSCIENCES↗
DOE OSTI2016

Development of an ideal observer that incorporates nuisance parameters and processes list-mode data

Observer models were developed to process data in list-mode format in order to perform binary discrimination tasks for use in an arms-control-treaty context. Data used in this study was generated using GEANT4 Monte Carlo simulations for photons using custom models of plutonium inspection objects and a radiation imaging system. We evaluated observer model performance and then presented using the area under the receiver operating characteristic curve. Lastly, we studied the ideal observer under both signal-known-exactly conditions and in the presence of unknowns such as object orientation and absolute count-rate variability; when these additional sources of randomness were present, their incorporation into the observer yielded superior performance.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Correlation and 3D-tracking of objects by pointing sensors

A method and system for tracking at least one object using a plurality of pointing sensors and a tracking system are disclosed herein. In a general embodiment, the tracking system is configured to receive a series of observation data relative to the at least one object over a time base for each of the plurality of pointing sensors. The observation data may include sensor position data, pointing vector data and observation error data. The tracking system may further determine a triangulation point using a magnitude of a shortest line connecting a line of sight value from each of the series of observation data from each of the plurality of sensors to the at least one object, and perform correlation processing on the observation data and triangulation point to determine if at least two of the plurality of sensors are tracking the same object. Observation data may also be branched, associated and pruned using new incoming observation data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Utilizing Environmental Tracers to Reduce Groundwater Flow and Transport Model Parameter Uncertainties

Abstract Non‐uniqueness in groundwater model calibration is a primary source of uncertainty in groundwater flow and transport predictions. In this study, we investigate the ability of environmental tracer information to constrain groundwater model parameters. We utilize a pilot point calibration procedure conditioned to subsets of observed data including: liquid pressures, tritium ( 3 H), chlorofluorocarbon‐12 (CFC‐12), and sulfur hexafluoride (SF 6 ) concentrations; and groundwater apparent ages inferred from these environmental tracers, to quantify uncertainties in the heterogeneous permeability fields and infiltration rates of a steady‐state 2‐D synthetic aquifer and a transient 3‐D model of a field site located near Riverton, Wyoming (USA). To identify the relative data worth of each observation data type, the post‐calibration uncertainties of the optimal parameters for a given observation subset are compared to that from the full observation data set. Our results suggest that the calibration‐constrained permeability field uncertainties are largest when liquid pressures are used as the sole calibration data set. We find significant reduction in permeability uncertainty and increased predictive accuracy when the environmental tracer concentrations, rather than apparent groundwater ages, are used as calibration targets in the synthetic model. Calibration of the Riverton field site model using environmental tracer concentrations directly produces infiltration rate estimates with the lowest uncertainties, however; permeability field uncertainties remain similar between the environmental tracer concentration and apparent groundwater age calibration scenarios. This work provides insight on the data worth of environmental tracer information to calibrate groundwater models and highlights potential benefits of directly assimilating environmental tracer concentrations into model parameter estimation procedures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability (‘p-theory’), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically-based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of data uncertainty on cold season threshold-based climate indices

Climate indices are used to reduce the complex climate system and its changes to simple measures. The data basis – whether observational data or climate model data – to which the climate indices are applied, is usually subject to uncertainties. For threshold-based climate indices, the data uncertainty influences the threshold value, and, hence, the uncertainty can influence the values for the climate index. What the actual impacts of these uncertainties are on threshold-based climate indices is examined in this paper. The focus is not only on the climate model uncertainty, but also on the observational data uncertainty. The general sensitivity of each of the chosen climate indices to arbitrary changes in the threshold is studied. This shows a higher sensitivity of indices assessing extremes (ice days, heavy precipitation days) to changes in the threshold than indices that integrate a quantity over a given time interval (coldsum, consecutive days). For assessing an ensemble of climate model data with respect to their ability to reproduce the index values for current climate, the reference data uncertainty is applied to the chosen threshold-based climate indices by changing their threshold value by its corresponding uncertainty. It is shown that the climate model uncertainty can be within the range of the reference data uncertainty. When using threshold-based climate indices to assess changes in future climate periods, uncertainties should always be taken into account and ideally corrected in an appropriate way. This is especially important for indices that assess extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Precise Timing Based on Pulsar Observation for Grid Synchronization

While Global Positioning System signals are widely used as the synchronized timing Sources for wide-area measurement systems for power grid monitoring and control, they are vulnerable to failures and malicious attacks. To address this Problem, an alternative kind of timing sources, the millisecond pulsars, were proposed to serve the power grid as they are more precise and physically indestructible. Millisecond pulsars are a kind of neutron stars that emit radio pulse signals that have extremely stable periods of milliseconds. However, the observed pulse Signals from pulsars cannot be directly used for timing because of their low signal-to-noise ratio and the dispersion effects of interstellar medium. In this paper, the precise timing method based on pulsar observation data is proposed to interpret the pulsar observation data and therefrom to generate precise timing signal for the power grid synchronization. In our proposed method,. incoherent de-dispersion is used on the observation data to mitigate the effect of interstellar medium. dispersion. Then spectrum analysis and segment folding are used to precisely estimate the local pulsar period. Finally the standard pulse per second signal is generated from. the estimated pulsar period and its precision. is analyzed. Experiments with the observation data of the pulsar based timing signal can be more accurate compared to GPS timing signals.

Luo, Xiqian↗