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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analog optical signal transmission for HEP experiments

A critical element in all high-energy physics experiments is the signal transmission from the active elements to the data acquisition system. It is especially challenging in large volume detectors based on noble liquids that are extensively being used for dark matter and neutrino detection.The topic of this contribution is the optical signal transmission of the signals acquired with silicon photomultipliers, which is able to satisfy many stringent experimental requirements. It is RF-noise immune and operates in cryogenic liquids and in high-electric fields.This transmission system is based on commercially available electronics components and customized Fabry-Perot laser diodes.I will talk about encountered challenges, breakthrough, and advances from the original concept of this system up to final validation tests, demonstrating progressive developments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Exploration of signal processing methods for superconducting magnet and quench data

Quenching is the phenomenon of a superconducting magnetic material carrying current transitioning into a regular conducting material. This may cause severe and irreparable damage to the superconductor due to Joule heating. The Magnet Department at Fermi National Accelerator Laboratory (FNAL) has acquired experimental data through quench antenna arrays that are recorded when the quench is detected. These data are in terms of voltage signals that are sampled at 100kHz for several minutes. There are multiple channels and each channel provides a data set of more than 20 million observations, while there is one channel, called the trigger channel which shows the time when quench is detected. Despite some advancements that were made including machine learning, data complexity still shadows the progress. In this work, we studied a multi-resolution analysis of the quench antenna data through the Haar wavelet transform. In particular, we applied the maximally overlapped discrete w avelet transform (MODWT) of a suitable level L to the given data and then projected it onto the wavelet basis. This decomposes a given signal (Original data) $x ϵ \mathbb{R}^N$ into $L + 1$ subspaces of $\mathbb{R}^N$. One of the subspaces called the approximation, captures the trend of the signal, and the others, called the details, capture the fluctuations at different frequency bands. This decomposition provides a clear trend of the data at a suitable level and also various activities (spikes) are seen in the details of the decomposition at every level. These spikes might reveal some information about the quench under investigation but in any case, give information about magnet behavior. Also, this decomposition is seen to be very useful in removing noise present in the data due to the source or mechanism of the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗
DOE OSTI2022

Large Area Detection of Microstructural Defects with Multi-Mode Ultrasonic Signals

Cyclic loading or other stresses can lead to development of cracks and crack growth in mechanical structures, leading to eventual failure. While ultrasound imaging can be used for non-destructive testing of such structures, conventional ultrasound techniques are often limited by crack size, density, and areal coverage. An effective characterization of real-world, large-area structures is required at an early damage stage to prevent catastrophic failure and predict remaining life. In this study, a new nonlinear ultrasonic testing (NUT) method is proposed for large-area monitoring of practical structures with arbitrary complexity by using multiple-mode guided-wave ultrasonic signals. The proposed guided-wave NUT technique requires single-element transducers, simple electronics, and a mixed time-frequency domain signal processing. As a proof-of-concept demonstration, numerical simulations and experiments are performed on an A36 carbon steel beam assembly with previously formed microstructural defects that cause nonlinearities in ultrasonic response. The quadratic dependence of the nonlinear wave excitation on the input ultrasonic signal amplitude is shown by numerical simulations, and such a nonlinear ultrasonic response is experimentally observed in the zone with a high density of microstructural defects.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Seismic Observations of the OSIRIS-REx Sample Return Capsule Reentry: Deployment, Signal Characteristics, and Wavefield Phenomenology

Controlled spacecraft reentries from interplanetary trajectories provide rare, well-characterized hypersonic sources for advancing seismoacoustic observation techniques. Here we present seismic observations of the OSIRIS-REx sample return capsule (SRC) reentry on 24 September 2023, recorded by 16 three-component nodal seismometers deployed near Eureka, Nevada, at ground distances of 7–20 km from the capsule trajectory. Air-to-ground coupled signals are detected at all stations, exhibiting impulsive onsets consistent with ballistic shock arrivals from the descending Mach cone. We characterize the seismic wavefield through signal amplitude, period, waveform cross-correlation, and array processing. Signal periods decrease systematically with increasing distance from the trajectory within the airport array, indicating that higher-frequency content becomes more prominent at greater offsets, opposite to expectations from geometric spreading and atmospheric absorption. Seismic array processing identifies frequency-dependent back-azimuth variations whose origin remains unresolved; possible contributing factors include source geometry, scattering by fine-scale layered structure in the stratosphere, and near-surface effects. These observations document a spatially complex seismic wavefield from a well-characterized hypersonic line source and provide constraints for future modeling of atmospheric propagation and air-to-ground coupling.

OSIRIS-REx↗
DOE OSTI2024

Decoding FGF/FGFR Signaling: Insights into Biological Functions and Disease Relevance

Fibroblast Growth Factors (FGFs) and their cognate receptors, FGFRs, play pivotal roles in a plethora of biological processes, including cell proliferation, differentiation, tissue repair, and metabolic homeostasis. This review provides a comprehensive overview of FGF-FGFR signaling pathways while highlighting their complex regulatory mechanisms and interconnections with other signaling networks. Further, we briefly discuss the FGFs involvement in developmental, metabolic, and housekeeping functions. By complementing current knowledge and emerging research, this review aims to enhance the understanding of FGF-FGFR-mediated signaling and its implications for health and disease, which will be crucial for therapeutic development against FGF-related pathological conditions.

Edirisinghe, Oshadi↗
DOE OSTI2020

Metabolic Signaling Cascades Prompted by Glutaminolysis in Cancer

Aberrant glutamatergic signaling has been implicated in altered metabolic activity and the demand to synthesize biomass in several types of cancer including melanoma. In the last decade, there has been a significant contribution to our understanding of metabolic pathways. An increasing number of studies are now emphasizing the importance of glutamate functioning as a signaling molecule and a building block for cancer progression. To that end, our group has previously illustrated the role of glutamatergic signaling mediated by metabotropic glutamate receptor 1 (GRM1) in neoplastic transformation of melanocytes in vitro and spontaneous development of metastatic melanoma in vivo. Glutamate, the natural ligand of GRM1, is one of the most abundant amino acids in humans and the predominant excitatory neurotransmitter in the central nervous system. Elevated levels of glutaminolytic mitochondrial tricarboxylic acid (TCA) cycle intermediates, especially glutamate, have been reported in numerous cancer cells. Herein, we highlight and critically review metabolic bottlenecks that are prevalent during tumor evolution along with therapeutic implications of limiting glutamate bioavailability in tumors.

Shah, Raj (ORCID:0000000204400189)↗
DOE OSTI2021

IL-10 Signaling Elicited by Nivolumab-Induced Activation of the $\mathrm{MAP}$ Kinase Pathway Does Not Fully Contribute to Nivolumab-Modulated Heterogeneous T Cell Responses

Immune checkpoint inhibitor (ICI) therapy has revolutionized anti-cancer treatment for many late-stage cancer patients. However, ICI therapy has thus far demonstrated limited efficacy for most patients, and it remains unclear why this is so. Interleukin 10 (IL-10) is a cytokine that has been recognized as a central player in cancer biology with its ability to inhibit anti-tumor T cell responses. Recent studies suggest that IL-10 might also exert some intrinsic anti-tumor T cell responses, and clinical studies using recombinant IL-10 alone or in combination with ICI are underway. This paradoxical effect of IL-10 and its underlying mechanisms impacting ICI-modulated T cell responses remain poorly understood. In this study, using an in vitro mixed lymphocyte reaction assay, we found that treatment with ICIs such as the anti-programmed cell death receptor-1 (PD-1) mAb nivolumab elicits a strong expression of IL-10. While neutralization of IL-10 signaling with an anti-IL-10 specific mAb significantly decreases the production of IFN-γ by T cells in a cohort of donor cells, the opposite effect was observed in other donor cells. Similarly, neutralization of IL-10 signaling significantly decreases the expression of T cell activation markers Ki67 and CD25, as well as the production of Granzyme B in a cohort of donor cells, whereas the opposite effect was observed in others. Furthermore, we found that nivolumab and IL-10 differentially modulate the signal transducer and activator of transcription 3 (STAT3) and AKT serine–threonine kinase pathways. Finally, we found that nivolumab activates the mitogen-activated protein kinase (MAPK) pathway, which in turn is responsible for the observed induction of IL-10 production by nivolumab. These findings provide new insights into the mechanisms underlying anti-PD-1-modulated T cell responses by IL-10, which could lead to the discovery of novel combination treatments that target IL-10 and immune checkpoint molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Novel Approach for Real-Time Quality Monitoring in Machining of Aerospace Alloy through Acoustic Emission Signal Transformation for DNN

Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Transcriptomic and Proteomic Insights into Host Immune Responses in Pediatric Severe Malarial Anemia: Dysregulation in HSP60-70-TLR2/4 Signaling and Altered Glutamine Metabolism

Severe malarial anemia (SMA, Hb < 6.0 g/dL) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission zones. This study explored the entire expressed human transcriptome in whole blood from 66 Kenyan children with non-SMA (Hb ≥ 6.0 g/dL, n = 41) and SMA (n = 25), focusing on host immune response networks. RNA-seq analysis revealed 6862 differentially expressed genes, with equally distributed up-and down-regulated genes, indicating a complex host immune response. Deconvolution analyses uncovered leukocytic immune profiles indicative of a diminished antigenic response, reduced immune priming, and polarization toward cellular repair in SMA. Weighted gene co-expression network analysis revealed that immune-regulated processes are central molecular distinctions between non-SMA and SMA. A top dysregulated immune response signaling network in SMA was the HSP60-HSP70-TLR2/4 signaling pathway, indicating altered pathogen recognition, innate immune activation, stress responses, and antigen recognition. Validation with high-throughput gene expression from a separate cohort of Kenyan children (n = 50) with varying severities of malarial anemia (n = 38 non-SMA and n = 12 SMA) confirmed the RNA-seq findings. Proteomic analyses in 35 children with matched transcript and protein abundance (n = 19 non-SMA and n = 16 SMA) confirmed dysregulation in the HSP60-HSP70-TLR2/4 signaling pathway. Additionally, glutamine transporter and glutamine synthetase genes were differentially expressed, indicating altered glutamine metabolism in SMA. This comprehensive analysis underscores complex immune dysregulation and novel pathogenic features in SMA.

Microbiology↗
DOE OSTI2022

Skyfall: Signal Fusion from a Smartphone Falling from the Stratosphere

A smartphone plummeted from a stratospheric height of 36 km, providing a near-real-time record of its rapid descent and ground impact. An app recorded and streamed useful internal multi-sensor data at high sample rates. Signal fusion with external and internal sensor systems permitted a more detailed reconstruction of the Skyfall chronology, including its descent speed, rotation rate, and impact deceleration. Our results reinforce the potential of smartphones as an agile and versatile geophysical data collection system for environmental and disaster monitoring IoT applications. We discuss mobile environmental sensing capabilities and present a flexible data model to record and stream signals of interest. The Skyfall case study can be used as a guide to smartphone signal processing methods that are transportable to other hardware platforms and operating systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Bolide Infrasound Signal Morphology and Yield Estimates: A Case Study of Two Events Detected by a Dense Acoustic Sensor Network

Two bolides (2016 June 2 and 2019 April 4) were detected at multiple regional infrasound stations, with many of the locations receiving multiple detections. Analysis of the received signals was used to estimate the yield, location, and trajectory, as well as the type of shock that produced the received signal. The results from the infrasound analysis were compared with ground-truth information that was collected through other sensing modalities. This multimodal framework offers an expanded perspective on the processes governing bolide shock generation and propagation. The majority of signal features showed reasonable agreement between the infrasound-based interpretation and the other observational modalities, though the yield estimate from the 2019 bolide was significantly lower using the infrasound detections. There was also evidence suggesting that one of the detections was from a cylindrical shock that was initially propagating upward, which is unusual though not impossible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Constraining Properties of the Next Nearby Core-collapse Supernova with Multimessenger Signals

With the advent of modern neutrino and gravitational wave (GW) detectors, the promise of multimessenger detections of the next galactic core-collapse supernova (CCSN) has become very real. Such detections will give insight into the CCSN mechanism and the structure of the progenitor star, and may resolve longstanding questions in fundamental physics. In order to properly interpret these detections, a thorough understanding of the landscape of possible CCSN events, and their multimessenger signals, is needed. We present detailed predictions of neutrino and GW signals from 1D simulations of stellar core collapse, spanning the landscape of core-collapse progenitors from 9 to 120 M ⊙ . In order to achieve explosions in 1D, we use the Supernova Turbulence In Reduced-dimensionality model, which includes the effects of turbulence and convection in 1D supernova simulations to mimic the 3D explosion mechanism. We study the GW emission from the 1D simulations using an astroseismology analysis of the protoneutron star. We find that the neutrino and GW signals are strongly correlated with the structure of the progenitor star and remnant compact object. Using these correlations, future detections of the first few seconds of neutrino and GW emission from a galactic CCSN may be able to provide constraints on stellar evolution independent of preexplosion imaging and the mass of the compact object remnant prior to fallback accretion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Method for enhancing a computer to estimate an uncertainty of an onset of a signal of interest in time-series noisy data

A computer-implemented method of enhancing a computer to estimate an uncertainty of an onset of a signal of interest in time-series noisy data. A first mathematical model of first time series data that contains only noise is calculated. A second mathematical model of second time series data that contains the noise and an onset of a signal of interest in the second time series data is calculated. A difference is evaluated between a first combination, being the first mathematical model and the second mathematical model, and a second combination, being the first time series data and the second time series data, wherein evaluating is performed using a generalized entropy metric. A specific time when an onset of the signal of interest occurs is estimated from the difference. An “a posteriori” distribution is derived for an uncertainty of the specific time at which the onset occurs.

Stracuzzi, David John↗
DOE OSTI2021

Electronic demodulation of optically phase demodulated signals

Device, methods and systems for the electronic demodulation of optically phase demodulated signals are described. An example optical local oscillator generator configured to generate a radio frequency (RF) tone at a desired RF frequency includes a first input configured to receive a broadband optical pulse train, a second input coupled to a delay line interferometer to receive a first control voltage for controlling a delay value of the interferometer and to produce an output optical pulse train, a dispersive element, coupled to the delay line interferometer, to map the output optical pulse train to a time-domain modulated optical pulse train, an optical-to-electrical converter, coupled to the dispersive element, to convert the time-domain modulated optical pulse train to an analog electrical signal, and an RF filter, coupled to the optical-to-electrical converter, to filter the analog electrical signal to generate the RF tone at the desired RF frequency.

Perlmutter, David Simon↗
DOE OSTI2021

3D printable feedstock inks for signal control or computation

A 3D printable feedstock ink is disclosed for use in a 3D printing process where the ink is flowed through a printing nozzle. The ink may be made up of a non-conductive flowable material and a plurality of chiplets contained in the non-conductive flowable material in random orientations. The chiplets may form a plurality of percolating chiplet networks within the non-conductive flowable material as ones of the chiplets contact one another. Each one of the chiplets has a predetermined circuit characteristic which is responsive to a predetermined electrical signal, and which becomes electrically conductive when the predetermined electrical signal is applied to the ink, to thus form at least one conductive signal path through the ink.

Murialdo, Maxwell↗
DOE OSTI2021

Fractional delay filter for a digital signal processing system

A processing element for implementation in a digital signal processing system is provided. The processing element is configured to receive a first data stream comprising a plurality of digital values where each value represents a sample of an analog signal. The processing element is further configured to receive a second data stream comprising a series of digital values where each value represents a sample of the analog signal. The processing element is configured to filter the first data stream via a first Farrow-structured fractional delay (FD) filter and output a filtered first data stream; filter the second data stream via a second Farrow-structured FD filter and output a filtered second data stream; and temporarily store values from the second data stream and output the stored values to the first Farrow-structured FD filter so that the stored values can be used to filter the first data stream.

Stanley, Dennis L.↗
DOE OSTI2022

Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Vehicular Controller Area Networks (CANs) are susceptible to cyber attacks of different levels of sophistication. Fabrication attacks are the easiest to administer—an adversary simply sends (extra) frames on a CAN—but also the easiest to detect because they disrupt frame frequency. To overcome time-based detection methods, adversaries must administer masquerade attacks by sending frames in lieu of (and therefore at the expected time of) benign frames but with malicious payloads. Research efforts have proven that CAN attacks, and masquerade attacks in particular, can affect vehicle functionality. Examples include causing unintended acceleration, deactivation of vehicle’s brakes, as well as steering the vehicle. We hypothesize that masquerade attacks modify the nuanced correlations of CAN signal time series and how they cluster together. Therefore, changes in cluster assignments should indicate anomalous behavior. We confirm this hypothesis by leveraging our previously developed capability for reverse engineering CAN signals (i.e., CAN-D [Controller Area Network Decoder]) and focus on advancing the state of the art for detecting masquerade attacks by analyzing time series extracted from raw CAN frames. Specifically, we demonstrate that masquerade attacks can be detected by computing time series clustering similarity using hierarchical clustering on the vehicle’s CAN signals (time series) and comparing the clustering similarity across CAN captures with and without attacks. We test our approach in a previously collected CAN dataset with masquerade attacks (i.e., the ROAD dataset) and develop a forensic tool as a proof of concept to demonstrate the potential of the proposed approach for detecting CAN masquerade attacks.

Moriano Salazar, Pablo↗