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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Impulse Noise Sampling at 9965 - Armag

One detonation test was monitored for impulse noise at Thunder Range on November 6, 2020. The TNT equivalency for this shot was 100 lbs. Ground zero for this test was located at an open area of Range 7. The Armag, where MOW were remotely located, was just south of the east end of the TR shock tube The purpose of this sampling event was to characterize the noise attenuation provided by the Armag which will be used as the primary firing location in a future test series. To determine attenuation provided by the Armag, one sound level monitor was placed inside and a second monitor was placed outside the hardened structure at the same distance from ground zero. The Armag was located 1300 feet from ground zero. Essential personnel performing these tests were remotely located inside the Armag and wore hearing protection with a minimum NRR of 23. Members of the Workforce (MOW) who are exposed to noise levels above 140 dBC, regardless of hearing protection worn, are required to be enrolled into the SNL Hearing Conservation Program which includes audiometric testing, online training (HCP100) and wearing hearing protection.

42 ENGINEERING↗
DOE OSTI2022

Impulse Noise Sampling at 9965 - 300-pound energetic experimant

On October 1, 2022, sound level measurements were taken at various locations throughout Kirtland Air Force Base (KAFB) and Southeastern Albuquerque. The purpose was to support sound propagation modeling predictions and sound regulations for public exposure during the detonation of an approximately 300-pound energetic experiment. Ground Zero was located on Range 7 of Sandia Thunder Range (06647). A total of 8 measurement locations were identified (e.g., 5 on KAFB and 3 in the Southeastern Albuquerque neighborhoods).

42 ENGINEERING↗
DOE OSTI2025

Masked Symbol Modeling for Demodulation of Oversampled Baseband Communication Signals in Impulsive Noise-Dominated Channels

Recent breakthroughs in natural language processing show that attention mech- anism in Transformer networks, trained via masked-token prediction, enables models to capture the semantic context of the tokens and internalize the grammar of language. While the application of Transformers to communication systems is a burgeoning field, the notion of context within physical waveforms remains under-explored. This paper addresses that gap by re-examining inter-symbol con- tribution (ISC) caused by pulse-shaping overlap. Rather than treating ISC as a nuisance, we view it as a deterministic source of contextual information embedded in oversampled complex baseband signals. We propose Masked Symbol Model- ing (MSM), a framework for the physical (PHY) layer inspired by Bidirectional Encoder Representations from Transformers methodology. In MSM, a subset of symbol-aligned samples is randomly masked, and a Transformer predicts the missing symbol identifiers using the surrounding “in-between” samples. Through this objective, the model learns the latent syntax of complex baseband waveforms. We illustrate MSM’s potential by applying it to the task of demodulating sig- nals corrupted by impulsive noise, where the model infers corrupted segments by leveraging the learned context. Our results suggest a path toward receivers that interpret, rather than merely detect communication signals, opening new avenues for context-aware PHY layer design.

Bedir, Oguz↗
DOE OSTI2026

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics. In this work, we present a computationally efficient unsupervised method for multimodal event detection based on Rolling Root Mean Square based Event Detection (RRMSED). The method is developed using in-house, field deployed sensors collecting data at a utility substation. The sensing system comprises voltage and current sensors, triaxial accelerometers, and magnetometers, collectively capturing electrical, vibrational, and magnetic waveform measurements at high temporal resolution. RRMSED operates by extracting rolling RMS energy features and their first-order temporal differences from consecutive waveform segments for each channel and then applying channel-specific statistical thresholds learned from historical data. A persistence-based exceedance logic is employed to robustly identify transient events while suppressing impulsive noise, and to provide precise temporal localization with high resolution. The framework is designed for continuous server-side operation and can be deployed in real time without requiring complex models. Experiments on simulated waveform data with known ground truth demonstrate low false positive (FP) and false negative (FN) rates. Application to real substation data shows RRMSED to identify events that are not captured by conventional monitoring indicators including fast transient detection algorithm currently deployed in the system. These results indicate that rolling RMS based features provide an effective and practical basis for real-time multimodal event detection in smart-grid substations.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2022

Triboelectric backgrounds to radio-based polar ultra-high energy neutrino (UHEN) experiments

Here, in the hopes of observing the highest-energy neutrinos (E EeV) populating the Universe, both past (RICE, AURA, ANITA) and current (RNO-G, ARIANNA, ARA and TAROGE-M) polar-sited experiments exploit the impulsive radio emission produced by neutrino interactions. In such experiments, rare single event candidates must be unambiguously identified above backgrounds. Background rejection strategies to date primarily target thermal noise fluctuations and also impulsive radio-frequency signals of anthropogenic origin. In this paper, we consider the possibility that ‘fake’ neutrino signals may also be generated naturally via the ‘triboelectric effect.’ This broadly describes any process in which force applied at a boundary layer results in displacement of surface charge, leading to the production of an electrostatic potential difference V. Wind blowing over granular surfaces such as snow can induce such a potential difference, with subsequent coronal discharge. Discharges over timescales as short as nanoseconds can then lead to radio-frequency emissions at characteristic MHz–GHz frequencies. Using data from various past (RICE, AURA, SATRA, ANITA) and current (RNO-G, ARIANNA and ARA) neutrino experiments, we find evidence for such backgrounds, which are generally characterized by: (a) a threshold wind velocity which likely depends on the experimental trigger criteria and layout; for the experiments considered herein, this value is typically $\mathscr{O}$(10 m/s), (b) frequency spectra generally shifted to the low-end of the frequency regime to which current radio experiments are typically sensitive (100–200 MHz), (c) for the strongest background signals, an apparent preference for discharges from above-surface structures, although the presence of more isotropic, lower amplitude triboelectric discharges cannot be excluded.

Background rejection↗
DOE OSTI2021

Novel 2D velocity estimation method for large transient events in plasmas

Dynamics of fast transient events are challenging to be analyzed with high time resolution. Such events can occur in fusion plasmas such as the filaments during edge-localized modes (ELMs). Here, we present a robust method—the spatial displacement estimation—for estimating the displacements of structures with fast dynamics from high spatial and time resolution imaging diagnostics [e.g., gas-puff imaging (GPI)] with sampling time temporal resolution. First, a background suppression method is shown, which suppresses the slowly time-evolving and spatially non-uniform background in the signal. In the second step, a two-dimensional polynomial trend subtraction method is presented to tackle the remaining polynomial order trend in the signal. After performing these pre-processing steps, the spatial displacement of the propagating structure is estimated from the two-dimensional spatial cross-correlation coefficient function calculated between consecutive frames. The method is tested for its robustness and accuracy by simulated Gaussian events and spatially displaced random noise. An example application of the method is presented on propagating ELM filaments measured by the GPI system on the National Spherical Torus Experiment spherical tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Using time reversal with long duration broadband noise signals to achieve high amplitude and a desired spectrum at a target location

Time Reversal (TR) is a signal processing technique that can be used to focus acoustic waves to a specific location in space, with most applications aiming to create an impulsive focus. Here, this study instead aims to focus long-duration noise signals using TR. This paper seeks to generate higher amplitude noise at a desired location over an existing method of broadcasting equalized noise. Additionally, this paper explores various characteristics associated with focusing long duration noise using TR. The dependence of the focal amplitude on the duration of the focused signal is explored as well as the implications of using multiple sources when focusing noise. The focal amplitude decreases with longer duration and then levels off when the duration exceeds a few seconds. Coherent addition of focused noise is observed if all loudspeakers have coherent noise signals convolved with their reversed impulse responses. Lastly, focusing noise with a desired spectrum is explored.

42 ENGINEERING↗
DOE OSTI2022

On the determination of shocked surface velocities

Laser Doppler velocimetry is commonly fielded in shock physics experiments to diagnose the times of arrival, magnitudes, and durations of shock impulses as they arrive at shock loaded surfaces. However, in the presence of ejecta, the resulting frequency noise often obscures the surface and subsequent impulses at later times. In this context, we evaluate a dominant wave analysis technique applied to velocimetry data from explosively shocked Sn subjected to a second shockwave, on which ejecta are emitted subsequent to both the first and subsequent shockwave impulses. The analysis reveals surface velocities, the times of arrival of subsequent impulses, and their durations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Notes on Synthetic Aperture Radar Image Quality

Synthetic Aperture Radar (SAR) creates an image of a target scene by coherently processing radar echo returns collected along a flightpath. The quality of the SAR image is inextricably linked to the utility of the image for exploitation supporting the task at hand. Aspects of quality include the fidelity with which it can render the scene being imaged, to include the system’s Impulse Response (IPR) and underlying noise levels/characteristics. Other factors also impact utility.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

First demonstration of a fiber optic bolometer on a tokamak plasma (invited)

A fiber optic bolometer (FOB) was demonstrated observing a fusion plasma for the first time at the DIII-D tokamak. A FOB uses a fiber optics-based interferometric technique that is designed to have a high sensitivity to temperature changes [75 mK/(W/m2) responsivity in high vacuum with 0.38 mK noise level] with a negligible susceptibility to electromagnetic interference (EMI) that can be problematic for resistive bolometers in a tokamak environment. A single-channel test apparatus was installed on DIII-D consisting of a measurement FOB and shielded reference FOB. The single-channel FOB showed a negligible increase in the noise level during typical plasma operations (0.39 mK) compared to the benchtop results (0.38 mK), confirming an insignificant EMI impact to the FOB. Comparisons to DIII-D resistive bolometers showed good agreement with the single-channel FOB, indicating that the FOB is comparable to a resistive bolometer when the impulse calibration is applied. The noise-equivalent power density of the calibrated FOB during a plasma operation was 0.55 W/m2 with an average sampling time of 20 ms. The major potential effect of ionizing radiation on the FOB would be the radiation-induced attenuation, which can be efficiently compensated for by adjusting the probing light power.

Lee, S. (ORCID:0000000170289004)↗
DOE OSTI2026

Delivery Ring Spill Characterization and Impulse Study

High-intensity particle physics experiments require uniform beam extraction to prevent instantaneous rate spikes from overwhelming detector systems. By analyzing accelerator parameters and extracted beam dynamics, we directly inform spill regulation systems that make real-time adjustments to minimize non-uniformity. This Department of Energy Visiting Faculty Program project transitioned from characterizing Main Injector half-integer slow extraction for SpinQuest to Delivery Ring third-integer slow extraction for Mu2e. Working alongside the Fast Adaptive Neural Control (FANC) group, we developed an automated pipeline that aligns asynchronous instrument channels, embeds quality metrics, and isolates clean spill populations. Analyzing baseline spills alongside a dedicated quadrupole impulse study allowed us to quantify noise structures while mapping time-varying beam response and transit-delay dynamics. These empirical measurements directly ground digital twin models, supporting FANC’s deployment of real-time, FPGA-based neural network controllers in the Mu2e Spill Regulation System.

Dolen, James William [Purdue U., West Lafayette] (↗
DOE OSTI2022

A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation

Extraction and enhancement of weak impulse signature is the key of rolling bearing fault prognostics in which case the features are often weak and covered by noise. Tunable Q-factor wavelet transform (TQWT), as an emerging wavelet construction theory developed in a frequency domain explicitly, has the advantages of matching with the specific oscillation behavior of signal components. In this article, an adaptive sparse representation (ASR) method is proposed, which integrates the sparse code shrinkage (SCS) and parameter optimization into TQWT. However, direct application of ASR is difficult to extract fault signatures at the early stage or low-speed operation due to weak fault symptoms and background noise. A novel fault diagnosis strategy based on continuous wavelet transform (CWT) and ASR is investigated. CWT owns significant advantages on multiscale subdivision and weak signal detection. The results of simulated and experimental vibration signal analyses verify the effectiveness of the proposed method in accurately extracting weak impulse features from the noise environment.

Yuan, Xing↗
DOE OSTI2022

The level-1 trigger for the SuperCDMS experiment at SNOLAB

The SuperCDMS SNOLAB dark matter search experiment aims to be sensitive to energy depositions down to Script O(1 eV). This imposes requirements on the resolution, signal efficiency, and noise rejection of the trigger system. To accomplish this, the SuperCDMS level-1 trigger system is implemented in an FPGA on a custom PCB. A time-domain optimal filter algorithm realized as a finite impulse response filter provides a baseline resolution of 0.38 times the standard deviation of the noise, σn, and a 99.9% trigger efficiency for signal amplitudes of 1.1 σ n in typical noise conditions. Embedded in a modular architecture, flexible trigger logic enables reliable triggering and vetoing in a dead-time-free manner for a variety of purposes and run conditions. The trigger architecture and performance are detailed in this article.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Combining quantum noise reduction resources: A practical approach

Optomechanical sensors are capable of transducing external perturbations to resolvable optical signals. A particular regime of interest is that of high-bandwidth force detection, where an impulse is delivered to the system over a short period of time. Exceedingly sensitive impulse detection has been proposed to observe very weak signals like those due to long-range interactions with dark matter that require much higher sensitivities than current sensors can provide. Quantum resources to go beyond the traditional standard quantum limit of these sensors include squeezing of the light used to transduce the signal, backaction evasion by measuring the optimal quadrature, and quantum nondemolition (QND) measurements that reduce backaction directly. These methods have been developed in the context of gravitational wave detection for target frequencies in the audio band range. Here, we provide the theoretical limits to quantum noise reduction for higher and broader frequency targets, such as those from dark matter signals, while combining quantum-enhanced readout techniques based on squeezed light and QND measurements with optomechanical sensors. Here, we demonstrate that backaction evasion through QND techniques dramatically reduces the technical challenges presented when using squeezed light for broadband force detection, paving the way for combining multiple quantum noise reduction techniques for enhanced sensitivity in the context of impulse metrology.

Optomechanics↗
DOE OSTI2025

Detection of a Space Capsule Entering Earth’s Atmosphere with Distributed Acoustic Sensing (DAS)

On 24 September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer sample return capsule (SRC) entered Earth’s atmosphere after successfully collecting samples from an asteroid. The known trajectory and timing of this return provided a rare opportunity to strategically instrument sites to record geophysical signals produced by the capsule because it travelled at hypersonic speeds through the atmosphere. For this work, we deployed two distributed acoustic sensing (DAS) interrogators to sample over 12 km of surface-draped fiber-optic cables, as well as six collocated seismometer-infrasound sensor pairs, spread across two sites near Eureka, Nevada. This campaign-style rapid deployment is the first reported recording of an SRC re-entry with any distributed fiber-optic sensing technology. The DAS interrogators recorded an impulsive arrival with an extended coda which had features that were similar to recordings from both the seismometers and infrasound sensors. While the signal-to-noise ratio of the DAS data was lower than the seismic-infrasound data, the extremely dense spacing of fiber-optic sensors allowed for more phases to be clearly distinguished and the visualization of the continuous transformation of the wavefront as it impacted the ground. Unexpectedly, the DAS recordings contain less low-frequency content than is present in both the seismic and infrasound data. The deployment conditions strongly affected the recorded DAS data; in particular, we observed that fiber selection and placement exert strong controls on data quality.

58 GEOSCIENCES↗
DOE OSTI2022

Monitoring the propagation of mechanical discontinuity using data-driven causal discovery and supervised learning

Mechanical wave transmission through a material is influenced by the mechanical discontinuity in the material. The propagation of embedded discontinuities can be monitored by analyzing the wave-transmission measurements recorded by a multipoint sensor system placed on the surface of the material. The proposed workflow monitors the propagation of mechanical discontinuity through three stages, namely initial, intermediate, and final stages, by using supervised learning followed by data-driven causal discovery. To the end, the workflow processes the multipoint waveform measurements resulting from a single impulse source, while considering the effects of wave attenuation, dispersion and multiple wave-propagation modes due to the discontinuity and material boundaries. Among various feature reduction techniques ranging from decomposition methods to manifold approximation methods, the features derived based on statistical parameterizations of the measured waveforms lead to reliable monitoring that is robust to changes in precision, resolution, and signal-to-noise ratio of the multipoint sensor measurements. The numbers of zero-crossing, negative-turning, and positive turning in the waveforms are the strongest causal signatures of the propagation of mechanical discontinuity. Higher order moments of the waveforms, such as variance, skewness and kurtosis, are also strong causal signatures of the propagation. Finally, the newly discovered causal signatures confirm that the statistical correlations and conventional feature rankings are not always statistically significant indicators of causality.

42 ENGINEERING↗
DOE OSTI2023

Lightning Interferometry with the Long Wavelength Array

The Long Wavelength Array is a radio telescope array located at the Sevilleta National Wildlife Refuge in La Joya, New Mexico, well suited and situated for the observation of lightning. The array consists of 256 high-sensitivity dual polarization antennas arranged in a 100 m diameter. This paper demonstrates some of the capabilities that the array brings to the study of lightning. Once 32 or more antennas are used to image lightning radio sources, virtually every integration period longer than the impulse response of the array includes at least one identifiable lightning emitter, independent of the integration period used. The use of many antennas also allows multiple simultaneous lightning radio sources to be imaged at sub-microsecond timescales; for the flash examined, 51% of the images contained more than one lightning source. Finally, by using many antennas to image lightning sources, the array is capable of locating sources fainter than the galactic background radio noise level, yielding possibly the most sensitive radio maps of lightning to date. This incredible sensitivity enables, for the first time, the emissions originating from the positive leader tips of natural in-cloud lightning to be detected and located. The tip emission is distinctly different from needle emission and is most likely due to positive breakdown.

Stock, Michael (ORCID:0000000193336790)↗