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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

SDSS-IV MaNGA: a catalogue of spectroscopically detected strong galaxy–galaxy lens candidates

ABSTRACT We spectroscopically detected candidate emission-lines of 8 likely, 17 probable, and 69 possible strong galaxy–galaxy gravitational lens candidates found within the spectra of $\approx 10\, 000$ galaxy targets contained within the completed Mapping of Nearby Galaxies at Apache Point Observatory survey. This search is based upon the methodology of the Spectroscopic Identification of Lensing Objects project, which extends the spectroscopic detection methods of the BOSS Emission-Line Lensing Survey and the Sloan Lens ACS Survey. We scanned the co-added residuals that we constructed from stacks of foreground subtracted row-stacked-spectra so a sigma-clipping method can be used to reject cosmic rays and other forms of transients that impact only a small fraction of the combined exposures. We also constructed narrow-band images from the signal to noise of the co-added residuals to observe signs of lensed source images. We also use several methods to compute the probable strong lensing regime for each candidate lens to determine which candidate background galaxies may reside sufficiently near the galaxy centre for strong lensing to occur. We present the spectroscopic redshifts within a value-added catalogue (VAC) for data release 17 (DR17) of SDSS-IV. We also present the lens candidates, spectroscopic data, and narrow-band images within a VAC for DR17. High resolution follow-up imaging of these lens candidates are expected to yield a sample of confirmed grade-A lenses with sufficient angular size to probe possible discrepancies between the mass derived from a best-fitting lens model, and the dynamical mass derived from the observed stellar velocities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗
NASA NTRS2020

Fast Neutron Spectroscopy with Organic Scintillation Detectors in a High-Radiation Environment

Organic scintillators with pulse shape discrimination capability are widely used in both research and practical applications of neutron detection. The neutron and gamma-ray identification performance of the detector depends on the classification algorithms, noise filters and pileup rejection criteria in a high-flux bremsstrahlung radiation environment. In this paper, a technique has been developed and implemented for the neutron detection with multiple filter and discrimination steps, which to a high confidence level eliminates counting of gamma-ray pulses. Such a technique is merited when making measurements in a high flux bremsstrahlung and secondary fluorescence environment. The EJ-309 and stilbene detectors coupled to the digital data acquisition system were used for the calibration assessments with standard gamma-ray and neutron sources such as 137Cs, 60Co, 252Cf, and Am-Be. The MCNPX-PoliMi and GEANT4 toolkits were used to simulate the light output and the optical photon transport in the scintillators and create detector response functions for each type of detector. The neutron spectrum unfolding algorithm, GRAVELW, was used to recreate and calibrate with the Am-Be as final step before applying the neutron detection system to extract fusion neutron spectra generated in an intense bremsstrahlung radiation environment. This new technique described offers the user the ability to measure neutron spectra in a high-flux gamma-ray field and tune the parameters to meet required filtering needs.

Neutron Detector, Organic Scintillator, PulseShape↗
DOE OSTI2024

Wavelength modulation laser-induced fluorescence for plasma characterization

Laser-Induced Fluorescence (LIF) spectroscopy is an essential tool for probing ion and atom velocity distribution functions (VDFs) in complex plasmas. VDFs carry information about the kinetic properties of species that is critical for plasma characterization. Accurate interpretation of these functions is challenging due to factors such as multicomponent distributions, broadening effects, and background emissions. Our research investigates the use of Wavelength Modulation (WM) LIF to enhance the sensitivity of VDF measurements. Unlike standard Amplitude Modulation (AM) methods, WM–LIF measures the derivative of the LIF signal. This approach makes variations in VDF shape more pronounced. VDF measurements with WM–LIF were investigated with both numerical modeling and experimental measurements. The developed model enables the generation of both WM and AM signals, facilitating comparative analysis of fitting outcomes. Experiments were conducted in a weakly collisional argon plasma with magnetized electrons and non-magnetized ions. Measurements of the argon ion VDFs employed a narrow-band tunable diode laser, which scanned the 4p 4 D 7/2 –3d 4 F 9/2 transition centered at 664.553 nm in vacuum. A lock-in amplifier detected the second harmonic WM signal, which was generated by modulating the laser wavelength with an externally controlled piezo-driven mirror of the diode laser. Finally, our findings indicate that the WM–LIF signal is more sensitive to fitting parameters, allowing for better identification of VDF parameters such as the number of distribution components, their temperatures, and velocities. In addition, WM–LIF can serve as an independent method to verify AM measurements and is particularly beneficial in environments with substantial light noise or background emissions, such as those involving thermionic cathodes and reflective surfaces.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Uncertainty Quantification of Capacitor Switching Transient Location using Machine Learning

Identification of capacitor switching transient location provides valuable insight into the state of the associated equipment. Machine learning (ML) models, and convolutional neural networks (CNNs) in particular, have demonstrated remarkable performance in signal location. However, ML models are data driven whose predictions are affected by noise in data and may also suffer from large extrapolation errors when applied to new conditions. Uncertainty quantification (UQ) is necessary to ensure model trustworthiness and avoid overconfident predictions in extrapolation. Here, in this work, we propose a novel UQ method, called PI3NN, to quantify prediction uncertainty of ML models and integrate the method with CNNs for transient source location. PI3NN calculates Prediction Intervals by training 3 Neural Networks and uses root-finding methods to determine the interval precisely. Additionally, PI3NN can identify out-of-distribution (OOD) data in a nonstationary condition to avoid overconfident prediction. Results indicate that with PI3NN, transient signals are not only correctly identified, but when said signals are subject to corruptions characteristic of an actual power monitoring system (e.g. non-ideal sensors), the model recognizes when it is uncertain about its predictions, effectively letting the user know when to accept or discard the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2007

An Analysis of the Effects of RFID Tags on Narrowband Navigation and Communication Receivers

The simulated effects of the Radio Frequency Identification (RFID) tag emissions on ILS Localizer and ILS Glide Slope functions match the analytical models developed in support of DO-294B provided that the measured peak power levels are adjusted for 1) peak-to-average power ratio, 2) effective duty cycle, and 3) spectrum analyzer measurement bandwidth. When these adjustments are made, simulated and theoretical results are in extraordinarily good agreement. The relationships hold over a large range of potential interference-to-desired signal power ratios, provided that the adjusted interference power is significantly higher than the sum of the receiver noise floor and the noise-like contributions of all other interference sources. When the duty-factor adjusted power spectral densities are applied in the evaluation process described in Section 6 of DO-294B, most narrowband guidance and communications radios performance parameters are unaffected by moderate levels of RFID interference. Specific conclusions and recommendations are provided.

LaBerge, E. F. Charles↗
DOE OSTI2026

Signal Processing in SBND with Calibrated and Validated Electronics and Field Responses

SBND is a liquid argon time projection chamber in Fermilab’s Short-Baseline Neutrino Program, located 110 m from the neutrino source and operating in a high-rate environment with unprecedented statistics. Charged particles from neutrino interactions ionize the argon, and the resulting electrons drift to the anode wires, inducing current signals recorded as raw waveforms. These waveforms are a convolution of deposited charge with the electronics and TPC field responses, making accurate signal processing essential for recovering the true charge distribution. Signal processing forms the starting point for SBND reconstruction, directly impacting hit finding, charge calibration, clustering, and the reconstruction of tracks and showers, and therefore playing a key role in energy reconstruction and particle identification. In this poster, we present an overview of the SBND signal processing chain, including noise removal, channel-by-channel electronics correction, signal identification, and deconvolution using measured electronics and TPC field responses. We demonstrate that the two kernel functions—electronics and field responses—achieve high precision when compared to data, ensuring that the SBND signal processing chain provides a robust and accurate foundation for event reconstruction and precision physics measurements.

Singh, Prabhjot [Louisiana State U.] (ORCID:000000↗
DOE OSTI2021

The Modeled Performance of the ORNL Matched Filter Detector for Seismic Signatures of Multi-Axle Tractor Trailers

The MINOS program seeks methods to passively monitor the transfer of special materials, which are reproducible and quantitatively defensible. To date, we have demonstrated that short-period seismometers deployed near vehicle tracks can detect and monitor signatures of multi-axle tractor trailers impacting small road obstacles as means to detect and identify some transfer activities. In this report, we model the seismic velocity signal output from a tractor-trailer impacting a small obstacle (a template waveform) to parameterize a matched filter that identifies signals with similar shapes buried in noise, and that indicate repeating events (target waveforms). We then use this model to perform thousands of synthetic experiments, in which we apply our detector to identify noisy waveforms output from a similarly modeled vehicle data set; we process all data in the same manner as we process real data collected from the Oak Ridge National Laboratory (ORNL) seismic network. Our experiments, while limited, reveal that the matched filter shows a high discrimination capability, and at very low SNR values (at visibility thresholds). This means that template waveforms can match target waveforms that are sourced by models that share the same vehicle speed (target vehicles), and have a low probability of mis-identification. In particular, a matched filter designed to detect a five-axle tractor-trailer will reliably identify that target vehicle down to an SNR of 11.25 dB, and within ±0.1 km/hr, while successfully screening target vehicles with three axles.

42 ENGINEERING↗
NASA NTRS1975

Contamination Control in Hybrid Microelectronic Modules. Part 1: Identification of Critical Process and Contaminants

Various hybrid processing steps, handling procedures, and materials are examined in an attempt to identify sources of contamination and to propose methods for the control of these contaminants. It is found that package sealing, assembly, and rework are especially susceptible to contamination. Moisture and loose particles are identified as the worst contaminants. The points at which contaminants are most likely to enter the hybrid package are also identified, and both general and specific methods for their detection and control are developed. In general, the most effective controls for contaminants are: clean working areas, visual inspection at each step of the process, and effective cleaning at critical process steps. Specific methods suggested include the detection of loose particles by a precap visual inspection, by preseal and post-seal electrical testing, and by a particle impact noise test. Moisture is best controlled by sealing all packages in a clean, dry, inert atmosphere after a thorough bake-out of all parts.

Himmel, R. P.↗
NASA NTRS2011

The Application of Acoustic Measurements and Audio Recordings for Diagnosis of In-Flight Hardware Anomalies

In many cases, an initial symptom of hardware malfunction is unusual or unexpected acoustic noise. Many industries such as automotive, heating and air conditioning, and petro-chemical processing use noise and vibration data along with rotating machinery analysis techniques to identify noise sources and correct hardware defects. The NASA/Johnson Space Center Acoustics Office monitors the acoustic environment of the International Space Station (ISS) through periodic sound level measurement surveys. Trending of the sound level measurement survey results can identify in-flight hardware anomalies. The crew of the ISS also serves as a "detection tool" in identifying unusual hardware noises; in these cases the spectral analysis of audio recordings made on orbit can be used to identify hardware defects that are related to rotating components such as fans, pumps, and compressors. In this paper, three examples of the use of sound level measurements and audio recordings for the diagnosis of in-flight hardware anomalies are discussed: identification of blocked inter-module ventilation (IMV) ducts, diagnosis of abnormal ISS Crew Quarters rack exhaust fan noise, and the identification and replacement of a defective flywheel assembly in the Treadmill with Vibration Isolation (TVIS) hardware. In each of these examples, crew time was saved by identifying the off nominal component or condition that existed and in directing in-flight maintenance activities to address and correct each of these problems.

Welsh, David↗
NASA NTRS2007

An Automated Flying-Insect Detection System

An automated flying-insect detection system (AFIDS) was developed as a proof-of-concept instrument for real-time detection and identification of flying insects. This type of system has use in public health and homeland-security decision support, agriculture and military pest management, and/or entomological research. Insects are first lured into the AFIDS integrated sphere by insect attractants. Once inside the sphere, the insect s wing beats cause alterations in light intensity that is detected by a photoelectric sensor. Following detection, the insects are encouraged (with the use of a small fan) to move out of the sphere and into a designated insect trap where they are held for taxonomic identification or serological testing. The acquired electronic wing-beat signatures are preprocessed (Fourier transformed) in real time to display a periodic signal. These signals are sent to the end user where they are graphically. All AFIDS data are preprocessed in the field with the use of a laptop computer equipped with LabVIEW. The AFIDS software can be programmed to run continuously or at specific time intervals when insects are prevalent. A special DC-restored transimpedance amplifier reduces the contributions of low-frequency background light signals, and affords approximately two orders of magnitude greater AC gain than conventional amplifiers. This greatly increases the signal-to-noise ratio and enables the detection of small changes in light intensity. The AFIDS light source consists of high-intensity Al-GaInP light-emitting diodes (LEDs). The AFIDS circuitry minimizes brightness fluctuations in the LEDs and when integrated with an integrating sphere, creates a diffuse uniform light field. The insect wing beats isotropically scatter the diffuse light in the sphere and create wing-beat signatures that are detected by the sensor. This configuration minimizes variations in signal associated with insect flight orientation. Preliminary data indicate that AFIDS has sufficient sensitivity and frequency measuring capability to differentiate between male and female mosquitoes (Figure 1, bottom panel) and fruit flies (data not shown). Similar studies show that AFIDS can be utilized to detect discrete differences between two mosquito species, Aedes aegypti and Aedes albopictus. When fully deployable, a wireless network of AFIDS monitors could be used in combination with other remotely sensed data and visually displayed in a geographic information system (GIS) to provide real-time surveillance (see Figure 2). More accurate and sensitive insect population forecasts and effective rapid response and mitigation of insect issues would then be possible.

Vann, Timi↗
DOE OSTI2025

Beyond traditional diagnostics: Identifying active galactic nuclei using spectral energy distribution fitting in DESI data

Active galactic nuclei (AGN) are typically identified through their distinctive X-ray or radio emissions, mid-infrared (MIR) colors, or emission lines. However, each method captures different subsets of AGN due to signal-to-noise (S/N) limitations, redshift coverage, and extinction effects, underscoring the necessity for a multiwavelength approach for comprehensive AGN samples. This study explores the effectiveness of spectral energy distribution (SED) fitting as a robust method for AGN identification. Using CIGALE optical-MIR SED fits on DESI Early Data Release galaxies, we compare SED-based AGN selection (AGNFRAC ≥ 0.1) with traditional methods including BPT diagrams, WISE colors, X-ray, and radio diagnostics. The SED fitting identifies ∼70% of narrow- and broad-line AGN and 87% of WISE-selected AGN. Incorporating high S/N WISE photometry reduces star-forming galaxy contamination from 62% to 15%. Initially, ∼50% of SED-AGN candidates are undetected by standard methods, but additional diagnostics classify ∼85% of these sources, revealing low-ionization nuclear emission-line regions and retired galaxies potentially representing evolved systems with weak AGN activity. Further spectroscopic and multiwavelength analysis will be essential to determine the true AGN nature of these sources. SED fitting provides complementary AGN identification, unifying multiwavelength AGN selections. This approach enables more complete – albeit somewhat contaminated – AGN samples, which are essential for upcoming large-scale surveys where spectroscopic diagnostics may be limited.

Seyfert↗
NASA NTRS2005

An Automated Flying-Insect-Detection System

An automated flying-insect-detection system (AFIDS) was developed as a proof-of-concept instrument for real-time detection and identification of flying insects. This type of system has use in public health and homeland security decision support, agriculture and military pest management, and/or entomological research. Insects are first lured into the AFIDS integrated sphere by insect attractants. Once inside the sphere, the insect's wing beats cause alterations in light intensity that is detected by a photoelectric sensor. Following detection, the insects are encouraged (with the use of a small fan) to move out of the sphere and into a designated insect trap where they are held for taxonomic identification or serological testing. The acquired electronic wing beat signatures are preprocessed (Fourier transformed) in real-time to display a periodic signal. These signals are sent to the end user where they are graphically displayed. All AFIDS data are pre-processed in the field with the use of a laptop computer equipped with LABVIEW. The AFIDS software can be programmed to run continuously or at specific time intervals when insects are prevalent. A special DC-restored transimpedance amplifier reduces the contributions of low-frequency background light signals, and affords approximately two orders of magnitude greater AC gain than conventional amplifiers. This greatly increases the signal-to-noise ratio and enables the detection of small changes in light intensity. The AFIDS light source consists of high-intensity Al GaInP light-emitting diodes (LEDs). The AFIDS circuitry minimizes brightness fluctuations in the LEDs and when integrated with an integrating sphere, creates a diffuse uniform light field. The insect wing beats isotropically scatter the diffuse light in the sphere and create wing beat signatures that are detected by the sensor. This configuration minimizes variations in signal associated with insect flight orientation.

Vann, Timi↗
DOE OSTI2023

Seismoacoustic Data Fusion for Ground Coupled Airwaves: a FACT Case Study for Calibration and Array Processing

This report covers an inquiry into seismoacoustic array processing using infrasound arrivals combined with resulting Ground Coupled Airwaves (GCA) that are present on collocated seismic sensors. In preparation, data calibration and denoising is completed for a seismoacoustic sensor array that was deployed at the Facility for Acceptance, Calibration, and Testing on Kirtland Airforce Base from August through September of 2021. The events of interest for this study are small, local explosive sources that lead to short duration, impulsive signals on the instruments. The goal is to determine if combining infrasound signals with the corresponding GCAs on collocated seismic sensors can be used to improve the results returned by automated signal detection and characterization (e.g., back azimuth estimates). Preparation for seismic and infrasound data involves removing the instrument response so that sensors have flat power spectra over the frequency range 0.1-10 Hz, where signal from events of interest may be detected. After instrument response removal, deployment conditions specific to this array require a retrospective noise analysis to determine station emplacement characteristics. Once all data is calibrated, a manual search is performed for possible GCA arrivals across the seismoacoustic network. These arrivals are then processed through beamforming and subsequent event identification, resulting in a catalogue of seismoacoustic GCA arrivals with corresponding back azimuth and trace velocity estimations.

47 OTHER INSTRUMENTATION↗
NASA NTRS2022

How Well do Multisatellite Products Capture the Space-Time Dynamics of Precipitation? Part II: Building an Error Model Through Spectral System Identification

Satellite precipitation products, as all quantitative estimates, come with some inherent degree of uncertainty. To associate a quantitative value of the uncertainty to each individual estimate, error modeling is necessary. Most of the error models proposed so far compute the uncertainty as a function of precipitation intensity only, and only at one specific spatio-temporal scale. We propose a spectral error model which accounts for the neighboring space-time dynamics of precipitation into the uncertainty quantification. Systematic distortions of the precipitation signal and random errors are characterized distinctively in every frequency-wavenumber band in the Fourier domain, to accurately characterize error across scales. The systematic distortions are represented as a deterministic space-time linear filtering term. The random errors are represented as a non-stationary additive noise. The spectral error model is applied to the IMERG multi satellite precipitation product and its parameters are estimated empirically through a system identification approach using the GV-MRMS gauge-radar measurements as reference (“truth”) over the eastern United States. The filtering term is found to be essentially low-pass. While traditional error models attribute most of the error variance to random errors, it is found here that the systematic filtering term explains 48% of the error variance at the native resolution of IMERG. This fact confirms that, at high resolution, filtering effects in satellite precipitation products cannot be ignored, and that the error cannot be represented as a purely random additive or multiplicative term. An important consequence is that precipitation estimates derived from totally different sources shall not be expected to automatically have statistically independent errors.

Precipitation↗
DOE OSTI2025

X-Ray and Particle Detection With the Si(Li) Tracker Module of the GAPS Experiment

Here, this work describes the architecture and the experimental results from the characterization of the lithium-drifted silicon (Si(Li)) detector module, which constitutes the building block of the tracker in the general antiparticle spectrometer (GAPS) experiment to search for dark matter. The instrument is designed for the identification of low-energy cosmic anti-nuclei (antiprotons, antideuterons, and antihelium) to be performed during an Antarctic long-duration balloon flight scheduled for late 2025. The GAPS Si(Li) tracker, that is the core of the instrument, is the assembly of 252 modules, each comprised of four Si(Li) detectors and a full custom-integrated circuit designed for detector readout and produced in a commercial 180-nm planar CMOS technology. A general overview of the detector module architecture and its components is provided, together with a description of the test setup and the experimental results obtained from the characterization of the low-noise analog readout channel. In order to verify the effective operation of the entire module, results concerning the detection of X-rays from a 241Am source and cosmic muons are also provided.

Manghisoni, Massimo [Università di Bergamo (Italy)↗
DOE OSTI2025

Tailoring spectral properties for entangled photon generation

The linear intensity scaling of entangled two-photon absorption (ETPA) offers a fundamental mechanism to enable nonlinear optical spectroscopy and microscopy under a substantially lower excitation power than is currently feasible. However, the long data acquisition time and low signal-to-noise ratio in reported ETPA-based spectroscopic and microscopic studies prevent its widespread application. To gain the full potential of this novel quantum light approach, it is essential to optimize entangled photon generation for significantly enhanced ETPA responses. Here, we report a new quantum light source by combining entangled photon generation with free-space femtosecond pump-pulse shaping. Here, through measurements of singles and coincidence counts by varying the patterns applied to a spatial light modulator to control the spectral widths of the pump pulses, we reveal strong dependence of the singles and coincidence count rates as well as their ratios on the spectral widths of pump pulses. An optimal spectral width for the highest ratios between the coincidence photon and the signal or idler photon count rates is also determined. Identification of such optimal spectral widths for entangled photon generation in the presence of postgeneration spectral selection makes this quantum light source a promising choice for ETPA-based spectroscopy and imaging.

Photon pairs & parametric down-conversion↗
DOE OSTI2022

Detailed analysis of excited-state systematics in a lattice QCD calculation of 𝑔 𝐴

Excited state contamination remains one of the most challenging sources of systematic uncertainty to control in lattice QCD calculations of nucleon matrix elements and form factors: early time separations are contaminated by excited states and late times suffer from an exponentially bad signal-to-noise problem. High-statistics calculations at large time separations ≳ 1 fm are commonly used to combat these issues. In this work, focusing on g A , we explore the alternative strategy of utilizing a large number of relatively low-statistics calculations at short to medium time separations (0.2–1 fm), combined with a multistate analysis. On an ensemble with a pion mass of approximately 310 MeV and a lattice spacing of approximately 0.09 fm, we find this provides a more robust and economical method of quantifying and controlling the excited state systematic uncertainty. A quantitative separation of various types of excited states enables the identification of the transition matrix elements as the dominant contamination. The excited state contamination of the Feynman-Hellmann correlation function is found to reduce to the 1% level at approximately 1 fm while, for the more standard three-point functions, this does not occur until after 2 fm. Critical to our findings is the use of a global minimization, rather than fixing the spectrum from the two-point functions and using them as input to the three-point analysis. We find that the ground state parameters determined in such a global analysis are stable against variations in the excited state model, the number of excited states, and the truncation of early-time or late-time numerical data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗