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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Research at Palomar Observatory in planetary astronomy

A wide range of observational studies are carried out to improve our understanding of the bodies of the outer solar system. Using the 200-inch Hale telescope, near-infrared observations are made of Uranus, Neptune, and the Pluto-Charon system. High time resolution occultation observations of the Uranus Ring system are used to study in detail the dynamics of this system. Occultation studies of Neptune are probing this intriguing ring-arc system. Occulation observations of the Pluto-Charon system probe the surface properties of these distant bodies. In addition, the plate material of the PSSII servey is being used to search for new comets and asteroids. Researchers observed one Neptune stellar occultation in July 1987 and completed the analysis of a series of seven separate Neptune occultation observations in conjunction with Nicholson et al., of Cornell. The analysis has shown that minimum of three ring arcs, at radii ranging from 54,000 km - 67,000 km are required to account for the high quality ring events. Current theoretical models can account for these data. Of two observations scheduled of Pluto-Charon mutual occulations scheduled for the 200-inch, the Charon eclipse event was successfully observed (the other was clouded out).

Soifer, B. T.↗
DOE OSTI2022

Real-time Event Detection Using Rank Signatures of Real-world PMU Data

Timely detection of power system events is a crucial task, which can facilitate the implementation of remedial actions to improve reliability, resiliency, and security of the system. Meanwhile, the widespread deployment of phasor measurement units (PMUs) makes it possible to develop data-driven event detection techniques. However, relying purely on data without incorporating domain knowledge for the event detection task in power systems poses substantial security and stability risks due to issues associated with data misinterpretation and model accuracy. In this regard, we propose a real-time event detection method using real-world PMU data by incorporating domain knowledge to adequately capture the event signatures. Specifically, we track the change in rank signatures of PMU data to accurately localize the events. To optimize the detection process, we incorporate an offline Bayesian optimization algorithm to tune the parameters by efficiently searching for the best values. The experiments using the real-world PMU dataset from a U.S. interconnection show that the proposed event detection approach can efficiently detect the events from PMU data streams with high accuracy.

Ghasemkhani, Amir↗
DOE OSTI2022

Ephemeral Learning - Augmenting Triggers with Online-Trained Normalizing Flows

The large data rates at the LHC require an online trigger system to select relevant collisions. Rather than compressing individual events, we propose to compress an entire data set at once. We use a normalizing flow as a deep generative model to learn the probability density of the data online. The events are then represented by the generative neural network and can be inspected offline for anomalies or used for other analysis purposes. We demonstrate our new approach for a toy model and a correlation-enhanced bump hunt.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

First Joint Oscillation Analysis of Super-Kamiokande Atmospheric and T2K Accelerator Neutrino Data

The Super-Kamiokande and T2K Collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of 19.7⁢(16.3) × 10 20 protons on target in (anti)neutrino mode, the analysis finds a 1.9⁢𝜎 exclusion of 𝐶⁢𝑃 conservation (defined as 𝐽 𝐶⁢𝑃 = 0) and a 1.2⁢𝜎 exclusion of the inverted mass ordering.

Neutrino detection↗
NASA NTRS2001

Numerical Simulations of Precipitation Processes, Microphysics, and Microwave Radiative Properties of flood Producing Storms in Mediterranean & Adriatic Basins

A comprehensive understanding of the meteorological and microphysical nature of Mediterranean storms requires a combination of in situ data analysis, radar data analysis, and satellite data analysis, effectively integrated with numerical modeling studies at various scales. An important aspect of understanding microphysical controls of severe storms, is first understanding the meteorological controls under which a storm has evolved, and then using that information to help characterize the dominant microphysical processes. For hazardous Mediterranean storms, highlighted by the October 5-6, 1998 Friuli flood event in northern Italy, a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution. This involves intense convective development, Sratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that effect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. This talk overviews the microphysical elements of a severe Mediterranean storm in such a context, investigated with the aid of TRMM satellite and other remote sensing measurements, but guided by a nonhydrostatic mesoscale model simulation of the Friuli flood event. The data analysis for this paper was conducted by my research groups at the Global Hydrology and Climate Center in Huntsville, AL and Florida State University in Tallahassee, and in collaboration with Dr. Alberto Mugnai's research group at the Institute of Atmospheric Physics in Rome. The numerical modeling was conducted by Professor Oreg Tripoli and Ms. Giulia Panegrossi at the University of Wisconsin in Madison, using Professor Tripoli's nonhydrostatic modeling system (NMS). This is a scalable, fully nested mesoscale model capable of resolving nonhydrostatic circulations from regional scale down to cloud scale and below.

Smith, Eric A.↗
NASA NTRS1999

Comparison of the SPE Model with Proton and Heavy Ion Data

Proton data from the GOES 6 and 7 satellites and heavy ion data from the IMP-8 satellite have been compared to the expected results of Nymmik's new model for solar particle event fluences. This model calculates the energy spectra of Ions for protons through nickel for solar particle events, based upon the observed proton integral fluence above 30 MeV. Based upon 27 observed proton events of solar cycle 22, and three large historical events, with integral fluences above 30 MeV of greater than 106 particles/cm2, a reasonable agreement with model predictions is seen for more than half of the events. However, several events show a marked departure from the model predictions, leading to the conclusion that there may exist more than a single class of event, or that it may be necessary to include additional parameters within the model, such as solar disk position of the source flare, or height of disturbance in the solar corona. Data for heavy Ions, (oxygen and iron), were limited to a total of six solar particle events, of which only two occurred in solar cycle 22. The agreement between data and the model predictions appeared to be quite good, however this agreement was sensitively dependent upon the value taken for the proton fluence above 30 MeV.

Cleghorn, Timothy F.↗
DOE OSTI2024

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2020

Review: Strategies for Using Satellite-Based Products in Modeling PM2.5 and Short-Term Pollution Episodes

Short-term air pollution episodes motivate improved understanding of the association between air pollution and acute morbidity and mortality episodes, and triggers required mitigation plans. A variety of methods have been employed to estimate exposure to air pollution episodes, including GIS-based dispersion models, interpolation between sparse monitoring sites, land-use regression models, optimization models, line- or area-dispersion plume models, and models using information from imaging satellites, often including land-use and meteorological variables. There has been increasing use of satellite-borne aerosol products for assessing short-term air quality events. They provide better spatial coverage, but currently at the price of low temporal coverage and rather crude spatial resolution. This brief review of using satellite data for modeling short-term air quality and pollution events. The review can be pursued as a practical guide for modeling air quality with satellite-based products, as it includes important questions that should be considered in both the study design as well as the model development stages. Progress in this field is detailed and includes published models and their use in environmental and health studies. Both current and future satellite-borne capabilities are covered. It also provides links to access and download relevant datasets and some R code for data processing and modeling.

Meytar Sorek-Hamer↗
NASA NTRS1999

Correlations Between Topex Altimeter and Temperature Profile Data in the Equatorial Pacific

Observations of sea-surface heights from satellite altimeters have been a major contributor to monitoring the evolution of the recent major El Nino event. Assimilating altimeter data directly into numerical models only takes advantage of the surface signature provided by the data. However, that surface signature is usually indicative of processes occurring at depth, especially in the equatorial Pacific. In order for assimilation schemes to make maximum use of surface data, it is helpful to have knowledge of how to best extend that data in the vertical to account for that variability. Toward that end, the vertical correlation structure between satellite-observed sea-surface heights and in situ temperature measurements is examined using TOPEX altimeter and TOGA TAO profile data for the period 1993-1998. This time period includes several states of the tropical Pacific, including a perturbed state from 1993-1994, a quiescent state encompassing 1995-1996, and the major ENSO event of 1997-1998. Analyses for each of these periods, as well as the total period will be presented. In addition to analyses at specific depth levels, analyses for particular density surfaces will also be presented.

Adamec, David↗
NASA NTRS2023

Statistical Approach on Utilizing Ground-Based Experiments to Model Break-Up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗
NASA NTRS1999

Observations of Smoke Aerosol from Biomass Burning in Mexico: Effect of Particle Aging on Radiative Forcing and Remote Sensing

We take advantage of the May 1998 biomass burning event in Southern Mexico to test the global applicability of a smoke aerosol size model developed from data observed in South America. The Mexican event is an unique opportunity to observe well-aged, residual smoke. Observations of smoke aerosol size distribution made from vertical profiles of airborne in situ measurements show an inverse relationship between concentration and particle size that suggests the aging process continues more than a week after the smoke is separated from its fire sources. The ground-based radiometer retrievals show that the column-averaged, aged, Mexican smoke particles are larger (diameter = 0.28 - 0.33 micrometers) than the mean smoke particles in South America (diameter = 0.22 - 0.30 micrometers). However, the difference (delta - 0.06 micrometer) translates into differences in backscattering coefficient of only 4-7% and an increase of direct radiative forcing of only 10%.

Remer, Lorraine A.↗
NASA NTRS2009

Scientific Benefits of Space Science Models Archiving at Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) hosts a set of state-of-the-art space science models ranging from the solar atmosphere to the Earth's upper atmosphere. CCMC provides a web-based Run-on-Request system, by which the interested scientist can request simulations for a broad range of space science problems. To allow the models to be driven by data relevant to particular events CCMC developed a tool that automatically downloads data from data archives and transform them to required formats. CCMC also provides a tailored web-based visualization interface for the model output, as well as the capability to download the simulation output in portable format. CCMC offers a variety of visualization and output analysis tools to aid scientists in interpretation of simulation results. During eight years since the Run-on-request system became available the CCMC archived the results of almost 3000 runs that are covering significant space weather events and time intervals of interest identified by the community. The simulation results archived at CCMC also include a library of general purpose runs with modeled conditions that are used for education and research. Archiving results of simulations performed in support of several Modeling Challenges helps to evaluate the progress in space weather modeling over time. We will highlight the scientific benefits of CCMC space science model archive and discuss plans for further development of advanced methods to interact with simulation results.

Kuznetsova, Maria M.↗
DOE OSTI2023

Quantifying the effect of 3D models on moment tensor results using synthetic data

Moment tensors provide vital information on seismic source properties for seismic events. Moment tensors require seismic wavespeed models to compute Green’s functions, which measure the impulse response between a given source and receiver. Traditionally, researchers have used one-dimensional velocity models to calculate Green’s functions since 1D Green’s functions are computationally cheap to compute. Local 1D velocity models can also accurately model waveforms at short distances (< 500 km). However, 1D velocity models do not account for lateral heterogeneity, which can cause significant misfit in tectonically complex regions such as the Middle East (Covellone and Savage, 2012). Green’s functions calculated using 3D seismic wavespeed models have been shown to perform better in tectonically complex regions (Covellone and Savage, 2012; Kintner and Modrak, 2022), so we are interested in quantifying the effect of considering 3D structure on moment tensor inversion results. The Middle East is an ideal study area for a synthetic moment tensor test for two reasons. Firstly, the Middle East is a tectonically complex region that has been heavily studied. Secondly, the Middle East has significant seismic activity throughout the region, but imperfect station coverage due to limited open data through large swaths of the domain. The tectonic complexity and uneven station coverage will test real-world performance even in a synthetic experiment.

58 GEOSCIENCES↗
DOE OSTI2021

Learning Forecasts of Rare Stratospheric Transitions from Short Simulations

Abstract Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, sudden stratospheric warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event’s progress. Direct numerical simulation can estimate them in principle but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the time scale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in time scales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology.

Finkel, Justin↗
NASA NTRSDate not supplied

Statistical Approach on Utilizing Ground-based Experiments to Model Break-up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office; the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples as with as with the NASA SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗
NASA NTRS2019

OGLE-2014-BLG-0962 and a Comparison of Galactic Model Priors to Microlensing Data

OGLE-2014-BLG-0962 (OB140962) is a stellar binary microlensing event that was well covered by observations from the Spitzer satellite as well as ground-based surveys. Modeling yields a unique physical solution: a mid-M+M-dwarf binary with M(prim) = 0.20 ± 0.01 M(☉) and M(sec) = 0.16 ± 0.01 M(☉), with projected separation of 2.0 ± 0.3 au. The lens is only D(LS) = 0.41 ± 0.06 kpc in front of the source, making OB140962 a bulge lens and the most distant Spitzer binary lens to date. In contrast, because the Einstein radius (θ(E) = 0.143 ± 0.007 mas) is unusually small, a standard Bayesian analysis, conducted in the absence of parallax information, would predict a brown dwarf binary. We compare the results of Bayesian analysis using two commonly used Galactic model priors to the measured values for a set of Spitzer lenses. We find all models tested predict lens properties consistent with the Spitzer data. Furthermore, we illustrate the methodology for probing the Galactic distribution of planets by comparing the cumulative distance distribution of the Spitzer two-body lenses to that of the Spitzer single lenses.

Yutong Shan↗
NASA NTRS2010

Validation of the Integrated Medical Model Using Historical Space Flight Data

The Integrated Medical Model (IMM) utilizes Monte Carlo methodologies to predict the occurrence of medical events, utilization of resources, and clinical outcomes during space flight. Real-world data may be used to demonstrate the accuracy of the model. For this analysis, IMM predictions were compared to data from historical shuttle missions, not yet included as model source input. Initial goodness of fit test-ing on International Space Station data suggests that the IMM may overestimate the number of occurrences for three of the 83 medical conditions in the model. The IMM did not underestimate the occurrence of any medical condition. Initial comparisons with shuttle data demonstrate the importance of understanding crew preference (i.e., preferred analgesic) for accurately predicting the utilization of re-sources. The initial analysis demonstrates the validity of the IMM for its intended use and highlights areas for improvement.

Kerstman, Eric L.↗
NASA NTRS2014

Development of a Bayesian Belief Network Runway Incursion and Excursion Model

In a previous work, a statistical analysis of runway incursion (RI) event data was conducted to ascertain the relevance of this data to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to several of the AvSP top ten TC and identified numerous primary causes and contributing factors of RI events. The statistical analysis served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events, also previously reported. Through literature searches and data analysis, this RI event network has now been extended to also model runway excursion (RE) events. These RI and RE event networks have been further modified and vetted by a Subject Matter Expert (SME) panel. The combined system-level BBN model will allow NASA to generically model the causes of RI and RE events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of runway safety incidents/accidents, and to improve runway safety in general. The development and structure of the BBN for both RI and RE events are documented in this paper.

Green, Lawrence L.↗