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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Instrumental uncertainties in radiative corrections for the MUSE experiment

The MUSE experiment at the Paul Scherrer Institute is measuring elastic lepton-proton scattering cross sections in a four-momentum transfer range from Q 2 of approximately 0.002–0.08 GeV 2 using positively and negatively charged electrons and muons. The extraction of the Born cross sections from the experimental data requires radiative corrections. Estimates of the instrumental uncertainties in those corrections have been made using the ESEPP event generator. The results depend in particular on the minimum lepton momentum that contributes to the experimental cross section and the fraction of events with hard initial-state radiation that is detected in the MUSE calorimeter and is excluded from the data. Furthermore, these results show that the angular-dependent instrumental uncertainties in radiative corrections to the electron cross section are less than 0.4% and are negligible for the muon cross section.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Hard color-singlet exchange in dijet events in proton-proton collisions at $\sqrt{s} = 13$ TeV

We present a measurement of events with two jets separated by a pseudorapidity gap (jet-gap-jet). The signature is expected from hard color-singlet exchange. The jets are reconstructed with the CMS detector. The highest p_\text{T} p T jets have p_\text{T}^\text{jet1,2} > 40 p T jet1,2 > 40 GeV, with 1.4 < |\eta^\text{jet1,2}| < 4.7 1.4 < | η jet1,2 | < 4.7 and \eta^\text{jet1} \eta^\text{jet2} < 0 η jet1 η jet2 < 0 . We measure the fraction of color-singlet exchange dijet events, f_\text{CSE} f CSE , and compare it to previous measurements and to predictions. We also study jet-gap-jet events where the colliding protons remain intact and are detected with the Roman pots of TOTEM. A larger fraction f_\text{CSE} f CSE is found in the latter subsample.

Baldenegro Barrera, Cristian↗
DOE OSTI2023

A New Approach to Monitoring Solvent Extraction Processes for the Nuclear Industry

As part of an initiative to steward research, development, and innovation into the nuclear fuel cycle, Idaho National Laboratory is building the Beartooth testbed. Beartooth will include a cascade of centrifugal contactors, glove box lines, solidification, and dissolution equipment to aid in the progression of novel separation techniques and provide hands-on opportunities to early-career separation scientists. Beartooth will incorporate novel monitoring techniques using sensors and machine learning algorithms to inform a process operator of separation conditions. This research is examining monitoring technologies not typically used in nuclear separation processes such as acoustic microphones, accelerometers, infrared cameras, red-green-blue color sensors, among others. These sensors are being examined for their functionality within a separation process and their ability to detect applicable signals. Machine learning methods are being developed to determine their utility in detecting faults and alerting operators of expected and unexpected events. These methods have the potential to impact Safeguards by Design efforts and real-time decision making. This overview will detail preliminary results from acoustic, vibration, and color sensors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Application of Principal Component Analysis to Electrochemical Reprocessing PM and NMAC

In this report, data from an electrorefiner (ER) for nuclear fuel reprocessing is evaluated for process monitoring (PM) conclusions. This data comes from tests performed at the Idaho National Laboratory in 2022. Multivariate approaches utilizing methods of Principal Component Analysis (PCA) is applied. This is based off established work in process monitoring for fault detection in industrial facilities. This report will discuss the background, methods, and results of the application and some of the conclusions and applications that can be drawn from them. PCA is applied to two different electrorefiner (ER) operations that occurred at Idaho National Laboratory between August and October 2022. The first operation occurred with little incident while the second had several noted faults in the equipment in operational logs. The data from the first run was used to train the data for “normal” operations and applied to both sets of data to determine when operations were in an “off-normal” condition and identify where the fault occurs through PCA. PCA was able to identify off-normal events and identify the cause for off-normal operations. These identified off-normal events matched with the events and their causes in the operational logs. However, small amounts of variance in the data led to false detection of “off-normal” events. Thus, careful selection of training data and a-posteriori conclusions based off operator assessments will both be required for application of PCA to PM applications. This work demonstrated that multivariate approaches and latent variables are applicable to pyroprocessing PM applications and can be further expanded in future work as quality variables such as salt concentration from sensors and sampling become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
DOE OSTI2021

LL18-Signal Analysis-NDD2Ad (Final Report)

Under favorable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially-distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection, and scaling with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning, and possible application to studies of repeating events in induced, volcanic, and glacial seismicity. Our results place limits on the widely-held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
DOE OSTI2026

A compact, low-power epithermal neutron counter for lunar water detection

The detection and characterization of lunar water are critical for enabling sustainable human and robotic exploration of the Moon. Orbital neutron spectrometers, such as instruments on Lunar Prospector and the Lunar Reconnaissance Orbiter, have revealed hydrogen-rich regions near the poles but are limited by coarse spatial resolution and low counting efficiency. We present a compact, lightweight, and low-power epithermal neutron detector based on boron-coated silicon imagers, designed to probe subsurface hydrogen at decimeter scales from mobile platforms such as lunar rovers. This instrument leverages the high neutron capture cross-section of 10 B to convert epithermal neutrons into detectable α and 7 Li ions in a fully-depleted silicon imager, providing a unique event topology to identify neutrons while suppressing backgrounds. Monte Carlo simulations demonstrate that a 3 μm boron layer achieves optimal neutron detection efficiency, further enhanced with polyethylene moderation to improve sensitivity to the 0.4 eV–500 keV epithermal energy range. For a 10 cm 2 active area, the detector achieves sensitivity to H 2 O weight fractions as low as 0.01 wt% in a 15 minute measurement. This scalable, portable, low-mass design is well-suited for integration into upcoming Artemis and commercial lunar rovers, providing a transformative capability for in-situ resource prospecting and ground-truth validation of orbital measurements.

Detector modelling and simulations I (interaction ↗
DOE OSTI2025

Three-dimensional core-collapse supernova models with phenomenological treatment of neutrino flavor conversions

Abstract We perform three-dimensional supernova simulations with a phenomenological treatment of neutrino flavor conversions. We show that the explosion energy can increase to as high as $\sim 10^{51}$ erg depending on the critical density for the onset of flavor conversions, due to a significant enhancement of the mean energy of electron antineutrinos. Our results confirm previous studies showing such energetic explosions, but for the first time in three-dimensional configurations. In addition, we predict neutrino and gravitational wave (GW) signals from a nearby supernova explosion aided by flavor conversions. We find that the neutrino event number decreases because of the reduced flux of heavy-lepton neutrinos. In order to detect GWs, next-generation GW telescopes such as Cosmic Explorer and the Einstein Telescope are needed even if the supernova event is located at the Galactic Center. These findings show that the neutrino flavor conversions can significantly change supernova dynamics and highlight the importance of further studies on the quantum kinetic equations to determine the conditions of the conversions and their asymptotic states.

Mori, Kanji↗
DOE OSTI2022

The scintillation light detection system of ICARUS-T600: Hardware implementation and early results

The ICARUS-T600 Liquid Argon (LAr) Time Projection Chamber (TPC) is taking data with the Fermilab Booster Neutrino Beam-line (BNB) in the Short Baseline Neutrino (SBN) program to search for a possible LSND-like sterile neutrino signal. A light detection system, based on 360 Hamamatsu R5912-MOD Photo-Multiplier Tubes (PMTs) deployed behind the TPC wire chambers, has been realized to detect vacuum ultraviolet (VUV) photons produced by ionizing particles in LAr. This system is fundamental for the detector operation, providing an efficient trigger and contributing to the 3D reconstruction of events. Moreover, since the TPC is exposed to a huge flux of cosmic rays due to its shallow depths operations, the light detection system allows for the time reconstruction of events, contributing to the identification and to the selection of neutrino interactions within the beam spill gates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Regional and Temporal Variability of Atmospheric River Seasonality: Influences of Detection Algorithms and Moisture Transport Dynamics

Abstract Understanding the regional and temporal variability of atmospheric river (AR) seasonality is crucial for preparedness and mitigation of extreme events. While ARs were thought to peak in winter, recent research shows they exhibit region‐specific seasonality and are heavily influenced by the chosen detection algorithm. This study examines the link between the year‐to‐year consistency of peak‐AR activity to the presence of a dominant seasonal pattern, considering both location and algorithm choice. Regions are categorized by their temporal characteristics: consistent patterns (e.g., East Asia), patterns with occasional outliers (e.g., British Columbia coast), and regions lacking a clear dominant peak season (e.g., South Atlantic, parts of Australia). Hence, not all regions display a consistent seasonal cycle of AR activity. This study quantifies the extent to which a region experiences a dominant peak season of AR activity (or lacks one) and offers insights to enhance decision‐making in water management, natural hazard preparedness, and forecasting. Furthermore, given our finding that detection algorithms influence the peak season of AR activity, we also examine two diagnostic variables representative of moisture transport to corroborate our results. Integrated vapor transport, which captures meridional and zonal moisture transport, and Moist Wave Activity, representing moisture intrusions from lower to higher latitudes, are examined. Our analysis indicates that inconsistencies in the seasonal cycle of AR activity are not solely due to discrepancies in detection algorithms but also arise from changes in moisture transport. Plain Language Summary Atmospheric rivers (ARs) are critical weather phenomena that can cause extreme events like heavy rainfall and flooding. Understanding when and where ARs are most likely to occur throughout the year is essential for preparing and responding to these events. Traditionally, ARs were thought to peak in winter, but recent studies show this varies by region. Our study helps address the challenge decision‐makers face in anticipating and preparing for AR events by providing insights into the consistency of peak seasonal patterns across different areas. Some regions, like East Asia, and the British Columbia coast, show a consistent peak season, while others, like the South Atlantic and parts of Australia, have significant year‐to‐year variations, making it hard to identify a dominant season. To better understand these changes over time, the study also examines how moisture moves in the atmosphere, using Integrated Vapor Transport (which looks at moisture movement in various directions) and Moist Wave Activity (which tracks moisture shifts from lower to higher latitudes). The findings suggest that inconsistencies in AR patterns are due not only to detection methods but also due to changes in moisture transport. Key Points The peak season of atmospheric river activity can change depending on the year in some areas Interannual variations in the peak season can make identifying a dominant season challenging for some regions Frequent shifts in peak season across years reflect inconsistencies tied to detection algorithms and to underlying dynamics

Kamnani, Diya↗
DOE OSTI2024

Data vs. MC Comparison of Light Signal from Cosmic Rays in the ICARUS Detectors

Currently, the ICARUS-T600 liquid argon TPC is collecting data exposed to Booster Neutrino and Numi off-axis beams within the SBN program at Fermilab. A light detection system, based on PMTs deployed behind the TPC wire chambers, is in place to detect vacuum ultraviolet photons produced by ionizing particles in LAr. This system is fundamental for the detector operation, providing an efficient trigger and contributing to the 3D reconstruction of events. Moreover, since the TPC is exposed to a huge flux of cosmic rays due to its operations at shallow depths, the light detection system allows for the time reconstruction of events, contributing to the identification and to the selection of neutrino interactions within the beam spill gates. This contribution will primarily focus on the comparative study (data vs. MC) of light signal of cosmic muons to validate the light emulation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Time calibration and synchronization of the scintillation light detection system in ICARUS-T600

The ICARUS-T600 Liquid Argon (LAr) Time Projection Chamber (TPC) is presently used as a far detector of the Short Baseline Neutrino (SBN) program at Fermilab (USA) to search for a possible LSND-like sterile neutrino signal at $\Delta m^2 \approx 1 eV^2$ with the Booster Neutrino Beam (BNB). A light detection system, based on 360 large area Photo-Multiplier Tubes (PMTs), has been realized for ICARUS-T600 to detect VUV photons produced after the passage of ionizing particles in LAr. This system is fundamental for the TPC operation, providing an efficient trigger and contributing to the 3D reconstruction of events. Moreover, since the detector is exposed to a huge flux of cosmic rays due to its shallow depths operations, the light detection system allows for the time reconstruction of events, contributing to the identification and to the selection of neutrino interactions within the BNB spill gate. The correct time reconstruction of events requires the precise knowledge of the delay of each PMT channel and a good synchronization of recording electronics, this last based on fast sampling digitizers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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

Multichannel Deconvolution of Vibrational Shock Signals: An Inverse Filtering Approach

When transporting critical systems of national security interest, out-of-the ordinary, impulsive events that can potentially be undetected and affect overall system performance are of great concern. Impulsive events that can occur are essentially pulse-like, transient signals of short duration that evolve from various phenomena. Here the event can be created by either the dropping of a test object, the system, subjecting it to a compact high-energy blow or being struck unintentionally during transit resulting in potential damage. The intensity and location of the strike can cause an inoperability condition that is unacceptable in a national security environment. Therefore, it is essential to detect, classify and localize damage of any test object subjected to an impulsive-event. This effort was targeted to evaluate the vibrational response of test objects that are subjected to “transport” shocks and roadway vibrations during shipping and handling. Any potential damage that could be inflicted during transportation must not only be detected, but also be evaluated to determine the operational readiness of a test object before and after transport. This event is a critical task that must be addressed as part of the Lawrence Livermore National Laboratory (LLNL) national security mission. The estimation of excitation signals from noisy data is termed the deconvolution problem in the signal processing literature. The deconvolution problem is based on recovering the input excitation signal from a system characterized by its impulse response sequence. Using this model of the system, an “inverse” representation or filter is developed to remove the system from the measured data and recover the input. Deconvolution techniques have existed for a long-time; however, transient deconvolution presents a few uncommon problems, since the signal has a finite-length time duration resulting in a limited amount of data containing information about the excitation process. The transient is wideband in the frequency domain relative to any measurement sensor implying that the smaller bandwidth sensor system “filters” the excitation eliminating some of its essential information for recovery. This fact, coupled with the filtering effect of the test object itself makes this excitation recovery (deconvolution) problem a challenge for signal processing.

42 ENGINEERING↗
DOE OSTI2022

Machine Learning–Based Detection of Weather Fronts and Associated Extreme Precipitation in Historical and Future Climates

Extreme precipitation events, including those associated with weather fronts, have wide-ranging impacts across the world. Here we use a deep learning algorithm to identify weather fronts in high resolution Community Earth System Model (CESM) simulations over the contiguous United States (CONUS), and evaluate the results using observational and reanalysis products. We further compare results between CESM simulations using present-day and future climate forcing, to study how these features might change with climate change. We find that detected front frequencies in CESM have seasonally varying spatial patterns and responses to climate change and are found to be associated with modeled changes in large scale circulation such as the jet stream. We also associate the detected fronts with precipitation and find that total and extreme frontal precipitation mostly decreases with climate change, with some seasonal and regional differences. Here, decreases in Northern Hemisphere summer frontal precipitation are largely driven by changes in the frequency of different front types, especially cold and stationary fronts. On the other hand, Northern Hemisphere winter exhibits some regional increases in frontal precipitation that are largely driven by changes in frontal precipitation intensity. While CONUS mean and extreme precipitation generally increase during all seasons in these climate change simulations, the likelihood of frontal extreme precipitation decreases, demonstrating that extreme precipitation has seasonally varying sources and mechanisms that will continue to evolve with climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Performance of photosensors in a high-rate environment for gas Cherenkov detectors

We report the solenoidal large intensity device (SoLID) at Jefferson Lab will push the boundaries of luminosity for a large-acceptance detector, which necessitates the use of a light-gas threshold Cherenkov counter for online event selection. Due to the high luminosity, the single-photon background rate in this counter can exceed 160 kHz/cm 2 at the photosensors. Therefore, it is essential to validate the high-rate limits of the planned photosensors and readout electronics in order to mitigate the risk of failure. We report on the design and an early set of studies carried out using a small Cherenkov counter in a high-rate environment up to 60 kHz/cm 2 , in Hall C at Jefferson Lab. Commercially available multi-anode photomultipliers (MaPMT) and low-cost large-area picosecond photodetectors (LAPPD) were tested using the JLab FADC250 modules for readout. The test beam results show that the MaPMT array and the internal stripline LAPPD can detect and identify single-electron and pair-production events in high-rate environments. Due to its higher quantum efficiency, the MaPMT array provided a better separation between the single-electron and the pair-production events compared to the internal stripline LAPPD. A GEANT4 simulation confirms the beam test performance of our counter device.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

A Joint Search for the Electromagnetic Counterpart to the Gravitational-Wave Binary Black-Hole Merger Candidate S250328ae with the Dark Energy Camera and the Prime Focus Spectrograph

The first detection of an optical counterpart to a gravitational wave signal revealed that collaborative efforts between instruments with different specializations provide a unique opportunity to acquire impactful multi-messenger data. We present results of such a joint search with the Dark Energy Camera (DECam) and Prime Focus Spectrograph (PFS) for the optical counterpart of the LIGO-Virgo-KAGRA event S250328ae, a binary black hole merger candidate of high significance detected at a distance of 511$\pm$82 Mpc and localized within an area of 3 (15) square degrees at 50% (90%) confidence. We observed the 90% confidence area with DECam and identified 36 high-confidence transient candidates after image processing, candidate selection, and candidate vetting. We observed with PFS to obtain optical spectra of DECam candidates, Swift-XRT candidates, and potential host galaxies of S250328ae. In total, 3897 targets were observed by seven pointings covering ~50% of the 90% confidence area. After template fitting and visual inspection, we identified 12 SNe, 159 QSOs, 2975 galaxies, and 131 stars. With the joint observations of DECam and PFS, we found variability in 12 SNe, 139 QSOs, 37 galaxies, and 2 stars. We do not identify any confident optical counterparts, though the association is not ruled out for three variable candidates that are not observed by PFS and 6 QSO candidates without clear variability if the optical counterpart of S250328ae is faint. Despite the lack of confident optical counterparts, this paper serves as a framework for future collaborations between wide-field imagers and multi-object spectrographs to maximize multi-messenger analyses.

Zhang, Haibin [Natl. Astron. Observ. of Japan] (OR↗
DOE OSTI2021

SNEWS 2.0: a next-generation supernova early warning system for multi-messenger astronomy

The next core-collapse supernova in the Milky Way or its satellites will represent a once-in-a-generation opportunity to obtain detailed information about the explosion of a star and provide significant scientific insight for a variety of fields because of the extreme conditions found within. Supernovae in our galaxy are not only rare on a human timescale but also happen at unscheduled times, so it is crucial to be ready and use all available instruments to capture all possible information from the event. The first indication of a potential stellar explosion will be the arrival of a bright burst of neutrinos. Its observation by multiple detectors worldwide can provide an early warning for the subsequent electromagnetic fireworks, as well as signal to other detectors with significant backgrounds so they can store their recent data. The supernova early warning system (SNEWS) has been operating as a simple coincidence between neutrino experiments in automated mode since 2005. In the current era of multi-messenger astronomy there are new opportunities for SNEWS to optimize sensitivity to science from the next galactic supernova beyond the simple early alert. This document is the product of a workshop in June 2019 towards design of SNEWS 2.0, an upgraded SNEWS with enhanced capabilities exploiting the unique advantages of prompt neutrino detection to maximize the science gained from such a valuable event.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗