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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Storage Futures Study: Four Phases Framework and Modeling

This webinar, presented by Paul Denholm and Will Frazier, incorporates material from two publications of the NREL Storage Futures Study: "The Four Phases of Storage Deployment: A Framework for the Expanding Role of Storage in the U.S. Power System" (https://www.nrel.gov/docs/fy21osti/77480.pdf) and "Storage Futures Study: Economic Potential of Diurnal Storage in the U.S. Power Sector" (https://www.nrel.gov/docs/fy21osti/77449.pdf).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

In silico evaluation of plant nitrification suppression effects on agroecosystem nitrogen loss

Abstract Nitrification regulates the potential for nitrogen (N) loss from ecosystems because it converts ammonium to nitrate, which is susceptible to leaching and gaseous emissions. Crops can suppress the microbes that perform nitrification by exuding nitrification‐inhibiting compounds from their roots and taking up available ammonium. However, the effect of nitrification suppression on agroecosystem N losses remains poorly characterized, and a lack of temporal synchrony between nitrification, N losses, and nitrification suppression by plants could limit the effect of nitrification suppression. We used the DayCent‐CABBI model to evaluate the effectiveness of the suppression of nitrification by sorghum to reduce N 2 O emissions and nitrate leaching in an energy sorghum/soybean rotation at the Energy Farm in Urbana‐Champaign, IL. We simulated nitrification suppression at the measured levels (MeasNS) and at the maximum measured level applied to the entire growing season (MaxNS), and we also explored ways to better utilize nitrification suppression by altering the timing of urea–ammonium–nitrate fertilizer applications. Model experiments showed that most nitrification occurred immediately after fertilizer was applied, whereas nitrification suppression began to ramp up more than a month after planting. On an annual basis, MeasNS experiments showed a 1%–2% reduction in annual N 2 O emissions relative to no nitrification suppression (NoNS), and MaxNS experiments showed a 4%–9% reduction in annual N 2 O emissions relative to NoNS. Both nitrification suppression levels showed <1% reduction in nitrate leaching. Altering the timing of fertilizer applications to better synchronize nitrification suppression with high soil ammonium levels had mixed effects on annual N 2 O emissions and nitrate leaching and sometimes resulted in increased N losses. The timing of simulated N 2 O emissions shifted with the timing of fertilization, and N 2 O emissions from denitrification increased when N 2 O emissions from nitrification decreased. Increasing N retention during the non‐growing season may be more effective than growing‐season nitrification suppression for reducing annual N losses in the rainfed Midwest.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

Observation and theory of Pc 5 waves with harmonically related transverse and compressional components

The properties of 23 magnetic pulsation events observed by the AMPTE CCE spacecraft are studied. These events are selected on the basis of the field magnitude which oscillated at the second harmonic of a simultaneously present transverse oscillation. The events have a second harmonic period of 80-600 s (roughly the Pc 5 range), are observed in cluster in the dawn (0300-0800 magnetic local time, MLT) and dusk (1600-2100 MLT) sectors, and are localized near the magnetic equator. Although the azimuthal wave number estimated from an ion finite Larmor radius effect, is generally large (about 50), there is a marked difference between the events observed in the dawn and dusk sectors. In the dawn sector the waves have low frequencies (1-5 mHz), indicate left-hand polarization with respect to the ambient magnetic field, and propagate eastward with respect to the spacecraft. In the dusk sector the waves have high frequencies (5-15 mHz), indicate right-hand polarization, and propagate westward. It is suggested that the waves are all westward propagating in the plasma rest frame and that local-time-dependent Doppler shift is the reason for the local time dependence of the wave properties.

Takahashi, K.↗
NASA NTRS1987

Charge-coupled-device parallel-to-serial converter

A CCD parallel-to-serial converter comprising two successions of charge transfer stages, recurrently side-loaded with respective ones of parallelly supplied charge packets, then serially unloaded by time-interleaved respective shift register operations. The charge packets converted to time-division-multiplexed serial form are supplied to a shared electrometer, and the electrometer response is de-multiplexed. Preferably, shift register operations are carried forward concurrently at the same rate, but with the final charge transfer stages clocked in phases staggered in time.

Tower, John R.↗
NASA NTRS1987

Airborne microwave Doppler measurements of ocean wave directional spectra

A technique is presented for measuring ocean wave directional spectra from aircraft using microwave Doppler radar. The technique involves backscattering coherent microwave radiation from a patch of sea surface which is small compared to dominant ocean wavelengths in the antenna look direction, and large compared to these lengths in the perpendicular (azimuthal) direction. The mean Doppler shift of the return signal measured over short time intervals is proportional to the mean sea surface velocity of the illuminated patch. Variable sea surface velocities induced by wave motion therefore produce time-varying Doppler shifts in the received signal. The large azimuthal dimension of the patch implies that these variations must be produced by surface waves traveling near the horizontal antenna look direction thus allowing determination of the direction of wave travel. Linear wave theory is used to convert the measured velocities into ocean wave spectral densities. Spectra measured simultaneously with this technique and two laser profilometers, and nearly simultaneous with this technique and two laser profilometers, and nearly simultaneous with a surface buoy, are presented. Applications and limitations of this airborne Doppler technique are discussed.

Plant, W. J.↗
NASA NTRS2012

Frequency Correction for MIRO Chirp Transformation Spectroscopy Spectrum

This software processes the flyby spectra of the Chirp Transform Spectrometer (CTS) of the Microwave Instrument for Rosetta Orbiter (MIRO). The tool corrects the effect of Doppler shift and local-oscillator (LO) frequency shift during the flyby mode of MIRO operations. The frequency correction for CTS flyby spectra is performed and is integrated with multiple spectra into a high signal-to-noise averaged spectrum at the rest-frame RF frequency. This innovation also generates the 8 molecular line spectra by dividing continuous 4,096-channel CTS spectra. The 8 line spectra can then be readily used for scientific investigations. A spectral line that is at its rest frequency in the frame of the Earth or an asteroid will be observed with a time-varying Doppler shift as seen by MIRO. The frequency shift is toward the higher RF frequencies on approach, and toward lower RF frequencies on departure. The magnitude of the shift depends on the flyby velocity. The result of time-varying Doppler shift is that of an observed spectral line will be seen to move from channel to channel in the CTS spectrometer. The direction (higher or lower frequency) in the spectrometer depends on the spectral line frequency under consideration. In order to analyze the flyby spectra, two steps are required. First, individual spectra must be corrected for the Doppler shift so that individual spectra can be superimposed at the same rest frequency for integration purposes. Second, a correction needs to be applied to the CTS spectra to account for the LO frequency shifts that are applied to asteroid mode.

Lee, Seungwon↗
NASA NTRS1979

Digital data reformatter/deserializer

A method and apparatus is presented for reformatting and de-serializing a serially-received sequence of data words, each consisting of a fixed number of binary data bits. A block of nm bits is serially fed into a shift register or serially-connected group of shift registers. In lieu of the(nm-1)th shifts, the bits are rearranged within the shift register in parallel fashion, according to a prescribed scheme. Shifting then continues, until the first bit of each data word appears in the last bit position in the shift register, at which time that data word is shifted in parallel into an output buffer stage, from which it is outputted in parallel, after a fixed delay.

Engel, A.↗
DOE OSTI2026

Symmetries and anomalies of Hamiltonian staggered fermions

We review the shift (translation) and time reversal symmetries of Hamiltonian staggered fermions and their connection to continuum symmetries concentrating in particular on the case of massless fermions and (3+1) dimensions. We construct operators using the staggered fields that implement these symmetries on finite lattices. We show that shifts composed of an odd multiple of the elementary shift anticommute with time reversal and are related to continuum axial transformations. We argue that the presence of these nontrivial commutation relations implies the existence of lattice ’t Hooft anomalies. From the shifts we also construct a set of conserved, quantized charges that generate continuous symmetries of the lattice theory. In general these do not commute with the vector charge signaling further ’t Hooft anomalies.

Anomalies↗
NASA NTRSDate not supplied

A Zero-order Hold Approach for Fractional-delay Interpolation in Auralization

During the signal processing chain of an auralization simulating the propagation of a sound from a moving source to a stationary receiver, it is often necessary to interpolate between the samples of the source signal in order to arrive at uniformly-spaced samples at the receiver. In some cases, this interpolation is done in the receiver time frame – where the “input” samples of the source have become irregularly spaced due to time dilation effects. Canonical band-limited interpolation methods (i.e., sinc and sinc-derived approaches) cannot be applied in this case as they rely on having a uniformly-spaced input. The use of geometric interpolation methods that can handle irregularly-spaced input may not be grounded in signal processing principles and may produce unwanted artifacts and noise. This presentation outlines the possibility of embedding an irregularly-spaced zero-order hold signal within a highly over-sampled uniformly-spaced signal, and then processing down to the desired sampling rate through successive decimations. Initial distortion and noise characteristics of the approach are shown for some basic propagation geometries. The possible benefits of using such an approach in an auralization scheme with a time-varying Doppler shift are discussed including: the prevention of aliasing, processing time advantages, and the possibility for asynchronous processing.

Auralization↗
DOE OSTI2024

Distributionally Robust Variational Quantum Algorithms With Shifted Noise

Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is the high sensitivity of quantum noise to environmental changes, and its propensity to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step towards improving the reliability of VQAs influenced by real-time noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bayesian forecasts for dark matter substructure searches with mock pulsar timing data

Dark matter substructure, such as primordial black holes (PBHs) and axion miniclusters, can induce phase shifts in pulsar timing arrays (PTAs) measurements due to gravitational effects. In order to gain a more realistic forecast for the detectability of such models of dark matter with PTAs, we propose a Bayesian inference framework to search for phase shifts generated by PBHs and perform the analysis on mock PTA data. Furthermore, for most PBH masses the constraints on the dark matter abundance agree with previous (frequentist) analyses (without mock data) to $\mathcal{O}$(1) factors. This further motivates a dedicated search for PBHs (and dense small scale structures) in the mass range from 10 -8 M ⊙ to well above 10 2 M ⊙ with the Square Kilometer Array. Moreover, with a more optimistic set of timing parameters, future PTAs are predicted to constrain PBHs down to 10 -11 M ⊙ . Lastly, we discuss the impact of backgrounds, such as Supermassive Black Hole Mergers, on detection prospects, suggesting a future program to separate a dark matter signal from other astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1986

Resynchronization of circadian sleep-wake and temperature cycles in the squirrel monkey following phase shifts of the environmental light-dark cycle

Circadian rhythms in physiological and behavioral functions gradually resynchronize after phase shifts in environmental time cues. In order to characterize the rate of circadian resynchronization in a diurnal primate model, the temperature, locomotor activity, and polygraphically determined sleep-wake states were monitored in squirrel monkeys before and after 8-h phase shifts of an environmental light-dark cycle of 12 h light and 12 h dark (LD 12:12). For the temperature rhythm, resynchronization took 4 d after phase delay shift and 5 d after phase advance shift; for the rest-activity cycle, resynchronization times were 3 d and 6 d, respectively. The activity acrophase shifted more rapidly than the temperature acrophase early in the post-delay shift interval, but this internal desynchronization between rhythms disappeared during the course of resynchronization. Further study of the early resynchronization process requires emphasis on identifying evoked effects and measuring circadian pacemaker function.

Wexler, D. B.↗
NASA NTRS1989

Efficient detection of a CW signal with a linear frequency drift

An efficient method is presented for the detection of a continuous wave (CW) signal with a frequency drift that is linear in time. Signals of this type occur in transmissions between any two locations that are accelerating relative to one another, e.g., transmissions from the Voyager spacecraft. We assume that both the frequency and the drift are unknown. We also assume that the signal is weak compared to the Gaussian noise. The signal is partitioned into subsequences whose discrete Fourier transforms provide a sequence of instantaneous spectra at equal time intervals. These spectra are then accumulated with a shift that is proportional to time. When the shift is equal to the frequency drift, the signal to noise ratio increases and detection occurs. Here, we show how to compute these accumulations for many shifts in an efficient manner using a variety of Fast Fourier Transformations (FFT). Computing time is proportional to L log L where L is the length of the time series.

Swarztrauber, Paul N.↗
DOE OSTI2024

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗
NASA NTRS1984

Input-output characterization of an ultrasonic testing system by digital signal analysis

The input/output characteristics of an ultrasonic testing system used for stress wave factor measurements were studied. The fundamentals of digital signal processing are summarized. The inputs and outputs are digitized and processed in a microcomputer using digital signal processing techniques. The entire ultrasonic test system, including transducers and all electronic components, is modeled as a discrete-time linear shift-invariant system. Then the impulse response and frequency response of the continuous time ultrasonic test system are estimated by interpolating the defining points in the unit sample response and frequency response of the discrete time system. It is found that the ultrasonic test system behaves as a linear phase bandpass filter. Good results were obtained for rectangular pulse inputs of various amplitudes and durations and for tone burst inputs whose center frequencies are within the passband of the test system and for single cycle inputs of various amplitudes. The input/output limits on the linearity of the system are determined.

Karaguelle, H.↗
NASA NTRS1996

Phase-shifting human circadian rhythms: influence of sleep timing, social contact and light exposure

1. Both the timing of behavioural events (activity, sleep and social interactions) and the environmental light-dark cycle have been reported to contribute to entrainment of human circadian rhythms to the 24 h day. Yet, the relative contribution of those putative behavioural synchronizers to that of light exposure remains unclear. 2. To investigate this, we inverted the schedule of rest, sedentary activity and social contact of thirty-two young men either with or without exposure to bright light. 3. On this inverted schedule, the endogenous component of the core temperature rhythm of subjects who were exposed to bright light showed a significant phase shift, demonstrating that they were adapting to the new schedule. In contrast, the core temperature rhythm of subjects who were not exposed to bright light moved on average 0.2 h later per day and after 10 days had not significantly adapted to the new schedule. 4. The direction of phase shift in the groups exposed to bright light was dependent on the time of bright light exposure, while control subjects drifted to a later hour regardless of the timing of their schedule of sleep timing, social contact and meals. 5. These results support the concept that the light-dark cycle is the most important synchronizer of the human circadian system. They suggest that inversion of the sleep-wake, rest-activity and social contact cycles provides relatively minimal drive for resetting the human circadian pacemaker. 6. These data indicate that interventions designed to phase shift human circadian rhythms for adjustment to time zone changes or altered work schedules should focus on properly timed light exposure.

Non-NASA Center↗
DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗