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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Comparisons Between Unsteady Aerodynamic Events in a Gas Turbine Generator and an Identical Compressor Rig

Extensive testing done on a T55-L-712 turboshaft engine compressor in a compressor test rig is being followed by engine tests in progress as part of the Army Non-Recoverable Stall Program. Goals include a greater understanding of the gas turbine engine start cycle and compressor/engine operation in the regions 'beyond' the normal compressor stall line (rotating stall/surge). Rig steady state instrumentation consisted of 497 steady state pressure sensors and 153 temperature sensors. Engine instrumentation was placed in similar radial/axial locations and consists of 122 steady state pressure sensors and 65 temperature sensors. High response rig instrumentation consisted of 34 wall static pressure transducers. Rig and engine high response pressure transducers were located in the same axial/radial/circumferential locations in front of the first three stages. Additional engine high response instrumentation was placed in mach probes in front of the engine and on the compressor hub. This instrumentation allows for the generation of detailed stage characteristics, overall compressor mapping, and detailed analysis of dynamic compressor events.

Owen, A. Karl↗
DOE OSTI2020

Frequency Disturbance Event Detection Based on Synchrophasors and Deep Learning

Power system frequency disturbances are caused by various generation and transmission events including generator trips, load disconnections, line trips, etc. Accurate detections of the events are crucial to bulk power system situation awareness and event investigation. This paper utilizes the recent advances of deep learning to build a convolutional neural network model to detect events in an accurate yet straightforward manner. Herein, the rate of change of frequency and the relative angle shift are converted to images as the inputs of the proposed model. Finally, this paper uses two convolutional neural networks and classifier fusion to achieve the detection result. Compared with the conventional event detection algorithm and the frequency only deep learning model, the proposed model improves the detection accuracy by over 48%. As a promising tool for bulk power system situation awareness, the proposed model requires a short decision time, which is suitable for practical scenarios.

42 ENGINEERING↗
DOE OSTI2020

Calibrating Synchronous-Generator-Interfaced DG Models in Microgrids Using Multiple Event Data

Microgrids, consisting of distributed generators (DGs), loads, and energy storage systems, play an important role in future smart grids. In order to evaluate how microgrids operate and their dynamic response, it is necessary to develop accurate dynamic models of DGs in microgrids. This paper proposes a systematic method to calibrate synchronous-generator-interfaced DG models. Challenges associated with model validation in microgrids are analyzed. Underlying parameters are categorized into two groups, i.e., the steady-state parameters and time constants, which are estimated in two successive stages using multiple event data. This methodology ensures that the validated model with the estimated parameters are applicable for all events. A modified unscented Kalman filter (UKF) is proposed to deal with the cases in which measurement of power angle is unavailable. The effectiveness of the proposed method is validated using field test data of a 2.6 MVA diesel generator in a real microgrid.

Wang, Zhiwen↗
DOE OSTI2024

Scalable Risk Assessment of Rare Events in Power Systems With Uncertain Wind Generation and Loads

Risk assessment of rare events has become increasingly important in power system planning and operation with the increasing integration of renewable energy and the presence of system uncertainties. However, quantifying the risk posed by rare events via the traditional method, i.e., Monte Carlo sampling (MCS), incurs substantial computational expense stemming from the vast ensemble of power flow simulations. To accelerate the assessment, this paper proposes a Deep Neural Network (DNN)-kernelized vector-valued Gaussian Process (VVGP) approach with excellent computational efficiency while maintaining high accuracy. Consequently, serving as a surrogate model for the power flow solver, the DNN-kernelized VVGP enables significantly faster but accurate risk assessment compared to the power flow solver. The developed surrogate model evaluates low-order N - k events that contain more than 90% instances by adeptly capturing the topological features while the high-order N - k events are assessed via a power flow solver, thereby striking a balance between computational efficiency and uncertainty quantification accuracy. Moreover, the model incorporates a Support Vector Machine (SVM) classifier to resample concerning low-probability tail events to counteract the biases potentially introduced during the DNN-kernelized VVGP evaluations. Simulations conducted on the modified IEEE 24-bus, 118-bus, and European 1354-bus systems demonstrate that the proposed method maintains the accuracy benchmark set by MCS while significantly reducing computational demands in large-scale power systems as compared to other state-of-the-art methods.

17 WIND ENERGY↗
DOE OSTI2022

Interpretation of HFTS 2 Microseismic Data Using Bedding-Plane-Slip Mechanism

Summary The objective of this study is to understand how microseismic events are generated during hydraulic fracturing, as well as the role of geomechanical conditions (i.e., stress and mechanical stratigraphy) in this process. In the industry, microseismic event clouds have been generally used as an “outer boundary” of the “stimulated reservoir volume” (SRV). However, by comparing with other surveillance data (low-frequency distributed acoustic sensing, or LF-DAS, strain) in the Hydraulic Fracturing Test Site (HFTS) 2 experiment, we show that this assumption is fundamentally flawed. The HFTS 2 data have three unique observations that have not been commonly observed in other datasets: (1) Due to the influence of offset pad depletion, microseismic data show that hydraulic fractures from the child well can propagate over 3,000 ft into the depleted low-stress zone. (2) By comparing microseismic and horizontal fiber LF-DAS strain data, we observe that the microseismic event cloud does not necessarily reflect the created hydraulic fracture volume. Particularly, the extent of microseismic event clouds near heel stages is much shorter than what is shown with LF-DAS strain data. (3) Microseismic event magnitudes are larger in the depleted regions. Through geomechanical analysis, we demonstrate that the “bedding-plane-slip” model is likely the mechanism for microseismic generation during hydraulic fracturing. This model successfully explains the above field observations from the HFTS 2 experiment. We also provide a quantitative relationship connecting the microseismic event magnitude with fracture width increment and layer mechanical property contrast.

Engineering↗
NASA NTRS2016

The TESS Science Processing Operations Center

The Transiting Exoplanet Survey Satellite (TESS) will conduct a search for Earth’s closest cousins starting in late 2017. TESS will discover approx.1,000 small planets and measure the masses of at least 50 of these small worlds. The Science Processing Operations Center (SPOC) is being developed based on the Kepler science pipeline and will generate calibrated pixels and light curves on the NAS Pleiades supercomputer. The SPOC will search for periodic transit events and generate validation products for the transit-like features in the light curves. All TESS SPOC data products will be archived to the Mikulski Archive for Space Telescopes.

TESS↗
DOE OSTI2023

Search for Resonant WZ Production in the Fully Leptonic Final State at 13 TeV With the CMS Detector

A search for an electrically charged, narrow-width diboson (WZ) resonance in the fully leptonic final state using 137:65 fb?1 of data collected by the CMS experiment during the 2016-2018 run period, at the LHC and a center of mass energy of p s = 13 TeV is presented. The search focuses on a channel where the resonance decays to a pair of standard model vector bosons: W and Z. The Z boson subsequently decays to a pair of leptons, either electrons (e) or muons (?). While the W boson decays to a lepton and a neutrino (?). As ? escapes undetected, the neutrino is reconstructed from the missing transverse momentum (Pmisst ) of the event. The analysis is based on a bump-hunt search strategy with background estimation based on stochastically generated simulation events. No significant excess of events is observed above the expected background from the Standard Model and limits are set on the production cross-section of the diboson resonance as a function of the resonance mass at 95% confidence level. Results are interpreted in the context of the Heavy Vector Triplet (HVT) framework.

Hernandez, Andres Vargas↗
DOE OSTI2024

Sampling Rare Events in Aqueous Systems Using Molecular Simulations

Birth of a new distinct phase is a phenomenon encountered in a myriad of processes, and has wide ranging consequences in material processing, biological self-assembly, separations and several other processes. Several phase transitions are nucleation driven. The nucleation events occur over nanosecond timescales and involve hundreds to thousands of molecules. These length and timescales are difficult to access in experiments, thereby making experimental studies of nucleation challenging. On the other hand, molecular simulations sample the nanosecond and nanometer scales making them ideal to study nucleation. However, nucleation is a rare event, meaning that the waiting time to observe one nucleation event is significant. This makes simulation studies of rare events challenging. The project focused on a multi-pronged approach to address such challenges to develop the next generation rare event sampling methods for molecular simulations. The key outcomes of our work include developing more effective methods for sampling rare events, utilizing machine learning to better elucidate nucleation mechanisms, development of software for easy implementation of the methodologies, and applications of the methods to realistic systems to push the method applicability beyond model systems. Overall, this work has enabled pushing the frontiers of molecular simulations to study rare events with a focus on nucleation in aqueous solutions.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Automatic generation of efficient orderings of events for scheduling applications

In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.

Morris, Robert A.↗
DOE OSTI2025

Data-driven picosecond X-ray imaging for quantitative plasma-induced shock characterization

Imaging dynamic events, especially shockwave behavior, is key to advancing high-energy-density (HED) research. Recent advances in fourth- and fifth-generation X-ray light sources allow for high-resolution imaging of fast phenomena, but limited beam time necessitates maximizing data acquisition. We present a benchtop-scale pulsed plasma device submerged in liquid heptane, capable of generating dynamic events at rates exceeding 10 Hz, supporting the field’s data-driven goals by producing large, high-quality imaging datasets. Using X-ray phase contrast imaging (XPCI) at the Advanced Photon Source, we imaged weak shockwaves (Mach ~ 1.2) in heptane interacting with plasma-induced cavitation bubbles, causing deviation from Rankine-Hugoniot behavior; to our knowledge, this represents the first direct imaging of such interaction. Our quantitative analysis offers insight into weak shock phenomena and energy-focusing applications in pulsed plasmas. These results highlight the potential for large datasets to advance dynamic HED research at current light source facilities, and have implications for fields such as inertial confinement fusion, plasma-enhanced chemical processing, and biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reverse Time Migration of Explosion-generated Infrasound and Ground-Coupled Airwaves

Accurately locating sources of seismic and infrasonic energy is integral to global monitoring of earthquakes and explosions. Infrasound arrivals times can be used to calculate the origins of events that generate acoustic energy. Picking times of emergent infrasound arrivals, however, can be difficult and prone to uncertainty. Reverse time migration (RTM) is a waveform based location method that does not rely on picked arrival times. Here we use RTM to locate a known chemical explosion that generated acoustic and acoustic-to-seismic signals on 26 and 108 receivers, respectively. All location predictions are less than 24 km from the known location with time errors of less than three minutes. We find strong overall agreement between our results and those of existing RTM and arrival time based methods. Our initial results suggest that RTM is a promising method of event location using acoustic arrivals recorded on both infrasound and seismic instrumentation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Modeling particulate generation during high energy explosive events

Laser produced plasmas are used to simulate high energy events and are useful for a variety of applications e.g. in industrial sectors, such as semi-conductor manufacturing, as well as medical, environmental, and energy sectors. Particulate generation in laser produced plasmas is related to key features of the plasma: temperature and pressure evolution during plume expansion, plasma chemistry etc. Several uncertainties persist in relating initial high energy events (~microseconds) to particulate formation that happens as the plasma cools and evolves (~milliseconds).

42 ENGINEERING↗
NASA NTRS2016

The TESS Science Processing Operations Center

The Transiting Exoplanet Survey Satellite (TESS) will conduct a search for Earth's closest cousins starting in early 2018 and is expected to discover approximately 1,000 small planets with R(sub p) less than 4 (solar radius) and measure the masses of at least 50 of these small worlds. The Science Processing Operations Center (SPOC) is being developed at NASA Ames Research Center based on the Kepler science pipeline and will generate calibrated pixels and light curves on the NASA Advanced Supercomputing Division's Pleiades supercomputer. The SPOC will also search for periodic transit events and generate validation products for the transit-like features in the light curves. All TESS SPOC data products will be archived to the Mikulski Archive for Space Telescopes (MAST).

Jenkins, Jon M.↗
DOE OSTI2020

Feature Engineering and Process Mining to Enable Hazard Detection in Health Information Technology

Motivation for this work originates from a recognized need for developing data-driven approaches through analysis of complex electronic health records. Specifically, we aim to enhance the reliability of health information technology (HIT) systems by detection of plausible HIT hazards in clinical order transactions. In the absence of well-defined event logs in corporate data warehouses, our proposed approach identifies relevant timestamped data fields that could indicate transactions in the clinical order life cycle generating raw event sequences. Subsequently, we adopt state transitions of the OASIS Human Task standard to map the raw event sequences and simplify the complex process that clinical radiology orders go through. We describe how the current approach provides the potential to investigate areas of improvement and potential hazards in HIT systems. The discussion concludes with a use case and opportunities for future applications.

Ozmen, Ozgur↗
NASA NTRS2007

The Cusp: Open Questions

The northern and southern cusps play an important role in the overall solar wind-magnetosphere- ionosphere interaction. Optical, radar, and ground magnetometer observations of transient events in the dayside auroral oval provide strong evidence for bursty reconnection on the dayside magnetopause occurring along extended reconnection lines during periods of southward and/or ecliptic IMF orientation. During periods of northward IMF orientation, the same ground-based observations provide evidence for reconnection on the magnetopause poleward of the cusps. Cluster observations in the cusp have confirmed the transition in reconnection locations from the dayside to the high-latitude magnetopause as a function of IMF orientation, while in situ observations of the dayside magnetopause indicate that bursty reconnection frequently generates transient events marked by symmetric bipolar magnetic field signatures normal to the nominal magnetopause and magnetic field strength enhancements. In this talk we review recent and invoke new results from analytical, two-dimensional hybrid, and three-dimensional MHD codes to describe the motion and fate of the newly-reconnected magnetic field lines within FTEs, with a view to predicting (I) the locations where events form, (2) the mechanism(s) by which they are generated, (3) their signatures on the dayside and flank magnetopause, (4) their antisunward motion, (5) their interaction with the cusps, and (6) their signatures in the dayside auroral oval, including their occurrence patterns as a function of season. We compare these predictions with observations, in particular the results of a statistical study of Interball-1 FTEs and new multipoint THEMIS observations of FTEs.

Sibeck, D. G.↗
NASA NTRS2004

Derivation of Failure Rates and Probability of Failures for the International Space Station Probabilistic Risk Assessment Study

National Aeronautics and Space Administration s (NASA) International Space Station (ISS) Program uses Probabilistic Risk Assessment (PRA) as part of its Continuous Risk Management Process. It is used as a decision and management support tool to not only quantify risk for specific conditions, but more importantly comparing different operational and management options to determine the lowest risk option and provide rationale for management decisions. This paper presents the derivation of the probability distributions used to quantify the failure rates and the probability of failures of the basic events employed in the PRA model of the ISS. The paper will show how a Bayesian approach was used with different sources of data including the actual ISS on orbit failures to enhance the confidence in results of the PRA. As time progresses and more meaningful data is gathered from on orbit failures, an increasingly accurate failure rate probability distribution for the basic events of the ISS PRA model can be obtained. The ISS PRA has been developed by mapping the ISS critical systems such as propulsion, thermal control, or power generation into event sequences diagrams and fault trees. The lowest level of indenture of the fault trees was the orbital replacement units (ORU). The ORU level was chosen consistently with the level of statistically meaningful data that could be obtained from the aerospace industry and from the experts in the field. For example, data was gathered for the solenoid valves present in the propulsion system of the ISS. However valves themselves are composed of parts and the individual failure of these parts was not accounted for in the PRA model. In other words the failure of a spring within a valve was considered a failure of the valve itself.

Vitali, Roberto↗
DOE OSTI2026

Time-integrated Southern-sky Neutrino Source Searches with 10 yr of IceCube Starting-track Events at Energies Down to 1 TeV

In the IceCube Neutrino Observatory, a signal of astrophysical neutrinos is obscured by backgrounds from atmospheric neutrinos and muons produced in cosmic-ray interactions. IceCube event selections used to isolate the astrophysical neutrino signal often focus on the morphology of the light patterns recorded by the detector. The analyses presented here use the new IceCube Enhanced Starting Track Event Selection (ESTES), which identifies events likely generated by muon–neutrino interactions within the detector geometry, focusing on neutrino energies of 1–500 TeV with a median angular resolution of 1.4°. Selecting for starting-track events filters out not only the atmospheric-muon background but also the atmospheric-neutrino background in the southern sky. This improves IceCube’s muon–neutrino sensitivity to southern-sky neutrino sources, especially for Galactic sources that are not expected to produce a substantial flux of neutrinos above 100 TeV. In this work, the ESTES sample was applied for the first time to search for astrophysical sources of neutrinos, including a search for diffuse neutrino emission from the Galactic plane. No significant excesses were identified from any of the analyses; however, constraining limits are set on the hadronic emission from TeV gamma-ray Galactic plane objects and models of the diffuse Galactic plane neutrino flux.

Abbasi, R. [Loyola University, Chicago, IL (United↗
DOE OSTI2021

Quantum dot lightning detection and warning system and method

A quantum dot (QD) lightning detection and warning (LDW) system and method. This LDW system and method find broader applicability to spark and other transient optical event detection as well. The QDs are operable for receiving ultraviolet (UV), infrared (IR), visible, x-ray, and/or gamma ray radiation emanating from lightning or the like and generating visible radiation that may be detected and utilized to generate topological event information, such that property, human life, and the like may be safeguarded.

Bahritdinov, Farhod↗