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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Synoptic Typing of Multiduration, Heavy Precipitation Records in the Northeastern United States: 1895–2017

Much of the previous research on total and heavy precipitation trends across the northeastern United States (herein, the Northeast) used daily precipitation totals over relatively short periods of record, which do not capture the full range of climate variability and change. Less well understood are the characteristics of long-term changes and synoptic patterns in longer-duration heavy precipitation events across the Northeast. A multiduration (1, 2, 3, 7, 14, and 30 days), multi-return-interval (2, 5, 10, and 50 years) precipitation dataset was used to diagnose changes in various types of precipitation events across the Northeast from 1895 to 2017. Increasing trends were found in all duration and return-interval event combinations with the rarest, longest duration events increasing at faster rates than more-frequent, shorter-duration ones. Daily 850-hPa geopotential height patterns associated with precipitation events were extracted from rotated principal component analysis and k -means clustering analysis, which allowed for the main synoptic types present as well as their structure and evolution to be analyzed. The daily synoptic patterns thus identified were found to be similar across all durations and return intervals and included coastal low (Northeasters, tropical cyclones, and predecessor rain events), deep trough, East Coast trough, zonal, and high pressure patterns.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Binary helium dwarf supernovae

The possibility of helium dwarf evolution to sufficiently high densities for violent helium ignition in low-massed binary systems is investigated. During accretional evolution the occurrence of thermonuclear runaway is found to be probable when the dwarf's mass approaches 1 solar mass, and steady-state discontinuous wave propagation considerations indicate that the dwarf is totally incinerated (i.e., its total mass burns to nuclear equilibrium) by a detonation wave. A numerical stellar dynamic investigation, including the full effects of nuclear statistical equilibrium and electron capture indicates total disruption for all reasonable dwarf central densities. For consistency with the cosmic element abundances, the conclusion of total disruption requires a low frequency for helium supernova events, implying that helium ignition in mass-exchanging binaries must occur at the lower densities of the relatively mild helium flash.

Mazurek, T. J.↗
DOE OSTI2022

Parasitic Bacteria and Their Effect on Carbon Capture by Biofuel-Relevant Microalgae

The 2022 IPCC Sixth Assessment Report tells a worrying tale of global warming that temperatures will exceed beyond a 1.5 °C increase in the near future. Higher global temperatures result in more frequent and extreme weather events, irreversible ecosystem changes, and will contribute to detrimental impacts on human health. Anthropogenic greenhouse gas emissions— including those from burning fossil fuels for energy use—are the primary drivers of climate change. Organizations like the U.S Department of Energy’s (DOE) Office of Fossil Energy and Carbon Management (FECM) are working to decrease the environmental impacts of fossil fuels as society works towards net-zero emissions. To complete this goal, society must reduce its dependence on fossil fuels and move towards cleaner energy sources such as biofuels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Use of Machine Learning on PMU Data for Transmission System Fault Analysis

Synchrophasor technology has been used for monitoring, control, and protection of bulk power system for over 10 years. Deployment of phasor measurement units (PMUs) in the USA power system has surpassed 3000 units installed in the transmission substations as stand-alone intelligent electronic devices (IEDs) or as a software add-on to other devices such as digital protective relays (DPRs) or digital fault recorders (DFRs). By now, thousands of terabytes of PMU data may have been captured and stored by various transmission system operators (TSOs) and independent system operators (ISOs). This creates an opportunity to deploy advanced machine learning (ML) techniques to detect and classify faults recorded by PMUs automatically to be used by the system operators for rapid, critical decision-making when manual analysis of the past or unfolding events is not feasible. In this paper we offer a brief background on how the automated fault analysis may be done using DPR and/or DFR data, and compare some of the legacy approaches to the new ML approaches in the context of the system-wide PMU recordings. We then offer insights from developing practical ML solutions that have been applied on field recordings captured by close to 450 PMUs from all three US interconnections (Western, Eastern and ERCOT) over two years (2016-2017). We identify and illustrate ML challenges we addressed: inaccurate data, data with scarce and temporally imprecise fault labels, data recorded by PMUs sparsely located at substations resulting in the fault records taken afar from the ends of the faulted lines, data containing only positive sequence values, and data taken at different voltage levels. We then illustrate the ML model results for fault analysis under different application scenarios. The novelty of this study is not only in the design, implementation, and performance analysis of the ML algorithms, but also in the use of advanced fault modelling and simulation approaches to improve the training results when developing supervised ML models for fault detection and classification. Extensive simulations of faults were conducted on a 14-bus power system to create a training dataset with over 1400 accurately labelled faults. This dataset was applied to enhance the accuracy of fault detection and classification of machine learning-based models trained with small number of labelled faults in large datasets recorded in the grid interconnections ranging from 5,000 to 70,000 buses.

Synchrophasors, Machine Learning, Fault Analysis, ↗
DOE OSTI2025

Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

Mesoscale model predictions of wind, turbulence, and wind energy capacity factors are evaluated in the Altamont Pass Wind Resource Area of California (APWRA), where the diurnal regional sea breeze and associated terrain-driven speedup flows drive wind energy production during the summer months. Results from the Weather Research and Forecasting model version 4.4 using a novel three-dimensional planetary boundary layer (3D PBL) scheme, which treats both vertical and horizontal turbulent mixing, are compared to those using a well-established one-dimensional (1D) scheme that treats only vertical turbulent mixing. Each configuration is evaluated over a nearly 3-month-long period during the Hill Flow Study, and due to the recurring nature of the observed speedup flows, diurnal composite averaging is used to capture robust trends in model performance. Both model configurations showed similar overall skill. The general timing and direction of the speedup flows is captured, but their magnitude is overestimated within a typical wind turbine rotor layer. Both also fail to capture a persistent observed near-surface jet-like flow, likely due to the limited grid resolution that is typical of mesoscale models. However, the 3D PBL configuration shows several minor improvements over the 1D PBL configuration, including improved wind speed and turbulence kinetic energy profiles during the accelerating phase of the speedup events, as well as reduced positive wind speed bias at surface stations across the APWRA region. Using a mesoscale wind farm parameterization, modeled capacity factors are also compared to monthly data reported to the US Energy Information Administration (EIA) during the study period. Although the monthly trend in the data is captured, both model configurations overestimate capacity factors by roughly 7 %–11 %. Through model evaluation, this study provides confidence in the 3D PBL scheme for wind energy applications in complex terrain and provides guidance for future testing.

17 WIND ENERGY↗
DOE OSTI2025

Computational Modeling of Water Infiltration From Ditches Into Roadway Embankments

Ditches are built along roadways to convey the stormwater runoff. They collect the runoff from the pavement and adjacent drainage areas. Water can move freely in a ditch away from the road surface, thus making it safer for the vehicular traffic. South Carolina DOT expressed interest in studying infiltration of water from ditches into roadway embankments. As part of the current design criteria, it is recommended that the road subgrades be 1.0 foot above the design event water surface elevation in the ditch. The distance between the water surface and bottom of the subbase is referred to as “freeboard”. The purpose of this requirement is to lower the risk of pavement damage by moving the flow away from the pavement, containing the captured flow, and conveying flow received from adjacent properties to outfalls. With changes in roadway design standards, larger shoulders and flatter cross-slopes have moved ditches further away from the pavement and the subbase. These changes could allow for a lower freeboard standard without reducing safety margins due to the increased lateral distance from the subbase to the ditch. The objective of this study is to evaluate whether the current SCDOT criterion requiring the roadway subgrade to be 1 ft above the design-event ditch water surface can be relaxed under selected geometric and soil conditions, particularly where larger shoulder widths and flatter side slopes increase horizontal separation between ditch water and pavement structure.

42 ENGINEERING↗
DOE OSTI2022

A laser powder bed fusion system for operando synchrotron x-ray imaging and correlative diagnostic experiments at the Stanford Synchrotron Radiation Lightsource

Laser powder bed fusion (LPBF) is a highly dynamic multi-physics process used for the additive manufacturing (AM) of metal components. Improving process understanding and validating predictive computational models require high-fidelity diagnostics capable of capturing data in challenging environments. Synchrotron x-ray techniques play a vital role in the validation process as they are the only in situ diagnostic capable of imaging sub-surface melt pool dynamics and microstructure evolution during LPBF-AM. In this article, a laboratory scale system designed to mimic LPBF process conditions while operating at a synchrotron facility is described. The system is implemented with process accurate atmospheric conditions, including an air knife for active vapor plume removal. Significantly, the chamber also incorporates a diagnostic sensor suite that monitors emitted optical, acoustic, and electronic signals during laser processing with coincident x-ray imaging. The addition of the sensor suite enables validation of these industrially compatible single point sensors by detecting pore formation and spatter events and directly correlating the events with changes in the detected signal. Experiments in the Ti–6Al–4V alloy performed at the Stanford Synchrotron Radiation Lightsource using the system are detailed with sufficient sampling rates to probe melt pool dynamics. X-ray imaging captures melt pool dynamics at frame rates of 20 kHz with a 2 µm pixel resolution, and the coincident diagnostic sensor data are recorded at 470 kHz. Furthermore, this work shows that the current system enables the in situ detection of defects during the LPBF process and permits direct correlation of diagnostic signatures at the exact time of defect formation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Digital Twin for an Inverter-Based Resource Power Plant: Real-time data streaming unlocks situation awareness

Here, this study presents the development and successful implementation of a digital twin specifically designed for a grid-connected IBR power plant. By integrating a reduced-order model of the IBR system and dynamically updating the grid impedance with real-time data, the digital twin effectively captures and replicates the behavior of the physical system. Its accuracy and reliability are validated through critical test scenarios, including a three-phase fault and a line-tripping event. The results confirm that the digital twin closely emulates its physical counterpart, demonstrating its strong potential for real-time analysis, system monitoring, and predictive decision making in modern power systems.

Digital twins↗
DOE OSTI2020

Determination of jet calibration and energy resolution in proton–proton collisions at $\sqrt{s} = 8~\hbox {TeV}$ using the ATLAS detector

The jet energy scale, jet energy resolution, and their systematic uncertainties are measured for jets reconstructed with the ATLAS detector in 2012 using proton–proton data produced at a centre-of-mass energy of 8 TeV with an integrated luminosity of 20fb -1 . Jets are reconstructed from clusters of energy depositions in the ATLAS calorimeters using the anti-k t algorithm. A jet calibration scheme is applied in multiple steps, each addressing specific effects including mitigation of contributions from additional proton–proton collisions, loss of energy in dead material, calorimeter non-compensation, angular biases and other global jet effects. The final calibration step uses several in situ techniques and corrects for residual effects not captured by the initial calibration. Furthermore, these analyses measure both the jet energy scale and resolution by exploiting the transverse momentum balance in γ + jet, Z + jet, dijet, and multijet events. A statistical combination of these measurements is performed. In the central detector region, the derived calibration has a precision better than 1% for jets with transverse momentum 150 GeV < p T < 1500 GeV, and the relative energy resolution is (8.4 ± 0.6)% for p T =100 GeV and (23 ± 2)% for p T =20 GeV. The calibration scheme for jets with radius parameter R = 1.0, for which jets receive a dedicated calibration of the jet mass, is also discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Tunnel Event 2020 (G-tunnel event modeling) [Slides]

HOSS (Hybrid Optimization Software Suite) is a fracture mechanics code that properly conserves mass, energy and momentum. HOSS-FSIS was utilized to conduct exploratory calculations (2D plane strain/3D) for the G-tunnel event 2020 where a pseudo NPE 1.1kt HE equivalent source is used. The purpose of this analysis is to determine if the HOSS fluid-solid coupling solver can capture relevant down-tunnel phenomenology.

42 ENGINEERING↗
NASA NTRS1982

A ball trunnion capture latch

The Ball Trunnion Capture Latch described was developed and designed to restrain a spacecraft deployable appendage in three translational directions. The latch is capable of supporting an appendage during STS ascent and landing events and is capable of releasing and restowing an appendage distorted in three translational directions by thermal growth. The requirements, design, analyses, and tests conducted on a development unit of the latch are discussed.

Adams, D. V.↗
NASA NTRS2002

Science Goal Driven Observing and Spacecraft Autonomy

Spacecraft autonomy will be an integral part of mission operations in the coming decade. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will meet the science goals of a program, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the onboard software can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download a subset of observations at a reduced resolution, the spacecraft's overall efficiency will be dramatically increased. The science goal monitoring (SGM) system is a proof-of-concept effort to address the above challenge. The SGM will have an interface to help capture higher level science goals from the scientists and translate them into a flexible observing strategy that SGM can execute and monitor. We are developing an interactive distributed system that will use on-board processing and storage combined with event-driven interfaces with ground-based processing and operations, to enable fast re-prioritization of observing schedules, and to minimize time spent on non-optimized observations.

Koratkar, Amuradha↗
NASA NTRS1993

Causal modeling and event-driven simulation for monitoring of continuous systems

We describe extensions to the traditional techniques for anomaly detection, as well as new anomaly detection techniques based on alternate models of what distinguishes normal from abnormal behavior. Some of these techniques are designed to capture anomalies at individual sensors; some detect anomalies across collections of sensors. To assist in reasoning about complex global behaviors, we construct and simulate a causal model of the physical system being monitored. These techniques have been tested on data from the ECLSS of Space Station Freedom (SSF) and are being applied in advanced monitoring prototypes for the SSF External Active Thermal Control System of SSF and the Environmental Emergency and Consumables Management subsystem of the Space Shuttle.

Doyle, Richard↗
NASA NTRS2017

Strategies for SEE Hardness Assurance From Buy-It-And-Fly-It to Bullet Proof

This part of the course first outlines the conventional Single Event Effect (SEE), radiation hardness assurance (RHA) approach, which emphasizes mission success. Next, Dr. Ladbury will discuss the challenges posed by new satellite platforms (e.g., cubesats, nanosats, etc.), where cost and schedule receive emphasis equal to if not greater than mission success. These additional pressures, along with growing demands to reduce size, weight and power, coupled with increased performance, drive many projects toward expanding their use of commercial-off-the-shelf (COTS) technologies. While this may reduce direct parts cost and procurement lead times, it undermines many cost-reduction strategies used for conventional SEE RHA and can make radiation testing and analysis one of the most significant risksor worse, a risk neglected altogether. That section will end with some approaches for restoring balance in the troika of mission success, cost, and schedule. This is captured in SEE RHA as risk management: identify the threat, evaluate the threat, and mitigate the threat.

commercial-off-the-shelf (COTS)↗
NASA NTRS2017

Strategies for SEE Hardness Assurance - From Buy-It-And-Fly-It to Bullet Proof

This part of the course first outlines the conventional Single Event Effect (SEE), radiation hardness assurance (RHA) approach, which emphasizes mission success. Next, Dr. Ladbury will discuss the challenges posed by new satellite platforms (e.g., cubesats, nanosats, etc.), where cost and schedule receive emphasis equal to if not greater than mission success. These additional pressures, along with growing demands to reduce size, weight and power, coupled with increased performance, drive many projects toward expanding their use of commercial-off-the-shelf (COTS) technologies. While this may reduce direct parts cost and procurement lead times, it undermines many cost-reduction strategies used for conventional SEE RHA and can make radiation testing and analysis one of the most significant risks or worse, a risk neglected altogether. That section will end with some approaches for restoring balance in the troika of mission success, cost, and schedule. This is captured in SEE RHA as risk management: identify the threat, evaluate the threat, and mitigate the threat.

commercial-off-the-shelf (COTS)↗
DOE OSTI2020

Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas

Estimation of daily suspended sediment concentration (SSC) is required for water resources and environment management. In this paper, a copula-based stochastic method was proposed for daily SSC simulation. Here, the multivariate copula function, constructed based on a bivariate copula and two bivariate conditional probability distributions, was used to model the temporal and cross dependence structures in daily SSCs. Then, the daily SSCs were generated by sampling from the multivariate conditional distribution. As a result, synthetic long-term SSCs data beyond the limited observation period can be provided for water resources managers, which plays a critical role in accurately estimating frequency and magnitude of extreme SSCs events. The proposed method was under rigorous examination by applying to a case study at Pingshan station in the Jinsha River Basin, China. Results showed that the generated daily SSC sequences not only had a high degree of accuracy in preserving the statistical characteristics of the daily SSC observations, but also captured both the temporal correlation and the cross-correlation between the daily streamflow and daily SSC. Specifically, the average daily relative error values corresponding to mean, standard deviation, skewness, lag-1 temporal correlation, and cross correlation were 0.87%, 4.24%, 7.52%, 0.51% and 2.02%, respectively. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resources management such as frequency analysis and risk assessment of extreme SSC events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

The Properties of Large Amplitude Whistler Mode Waves in the Magnetosphere: Propagation and Relationship with Geomagnetic Activity

Wepresent resultsof a studyof the characteristicsof very large amplitude whistler mode waves inside the terrestrial magnetosphere at radial distances of less than 15 RE using waveform capture data from the Wind spacecraft. We observed 247 whistler mode waves with at least one electric field component (105/247 had !80 mV/m peak!to!peak amplitudes) and 66 whistler mode waves with at least one search coil magnetic field component (38/66 had !0.8 nT peak!to!peak amplitudes). Wave vectors determined from events with three magnetic field components indicate that 30/46 propagate within 20 of the ambient magnetic field, though some are more oblique (up to "50 ). No relationship was observed between wave normal angle and GSM latitude. 162/247 of the large amplitude whistler mode waves were observed during magnetically active periods (AE > 200 nT). 217 out of 247 total whistler mode waves examined were observed inside the radiation belts. We present a waveform capture with the largest whistler wave magnetic field amplitude (^8 nT peak!to!peak) ever reported in the radiation belts. The estimated Poynting flux magnitude associated with this wave is ^300 mW/m2, roughly four orders of magnitude above estimates from previous satellite measurements. Such large Poynting flux values are consistent with rapid energization of electrons.

Wilson, L. B., III↗
NASA NTRS2002

Science Goal Driven Observing and Spacecraft Autonomy

Spacecraft autonomy will be an integral part of mission operations in the coming decade. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will meet the science goals of a program, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the onboard software can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download a subset of observations at a reduced resolution, the spacecraft's overall efficiency will be dramatically increased. The science goal monitoring (SGM) system is a proof- of-concept effort to address the above challenge. The SGM will have an interface to help capture higher-level science goals from the scientists and translate them into a flexible observing strategy that SGM can execute and monitor. We are developing an interactive distributed system that will use on-board processing and storage combined with event-driven interfaces with ground-based processing and operations, to enable fast re-prioritization of observing schedules, and to minimize time spent on non-optimized observations. This paper will focus on our strategy for developing SGM and the technical challenges that we have encountered. We will discuss the SGM architecture as it applies to the proposed MIDEX-class mission Kronos. However, the architecture and interfaces will also be designed for easy adaptability to other observing platforms, including ground-based systems and to work with different scheduling and pipeline processing systems.

Jones, Jeremy↗