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At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evolution of the ATLAS event data model for the HL-LHC

The upcoming high-luminosity run of the CERN Large Hadron Collider (HL-LHC) will yield an unprecedented volume of data. In order to process this data, the ATLAS collaboration is evolving its offline software to be able to use heterogeneous resources such as graphical processing units (GPUs) and field-programmable gate arrays (FPGAs). To reduce conversion overheads, the event data model (EDM) should be compatible with the requirements of these resources. While the ATLAS EDM has long allowed representing data as a structure of arrays, further evolution of the EDM can enable more efficient sharing of data between CPU and GPU resources. Some of this work will be summarized here, including extensions to allow controlling how memory for event data is allocated and the implementation of jagged vectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗
DOE OSTI2023

Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction

Understanding dynamics in complex systems is challenging because there are many degrees of freedom, and those that are most important for describing events of interest are often not obvious. The leading eigenfunctions of the transition operator are useful for visualization, and they can provide an efficient basis for computing statistics, such as the likelihood and average time of events (predictions). Here, we develop inexact iterative linear algebra methods for computing these eigenfunctions (spectral estimation) and making predictions from a dataset of short trajectories sampled at finite intervals. We demonstrate the methods on a low-dimensional model that facilitates visualization and a high-dimensional model of a biomolecular system. Implications for the prediction problem in reinforcement learning are discussed.

Chemistry↗
DOE OSTI2024

Case study of a bore wind-ramp event from lidar measurements and HRRR simulations over ARM Southern Great Plains

The rapid change of wind speed and direction on 21 August 2017 is studied using Doppler lidar measurements at five sites of the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility in north-central Oklahoma. The Doppler lidar data were investigated along with meteorological variables such as temperature, humidity, and turbulence available from the large suite of instrumentation deployed at the SGP Central Facility (C1) during the Land-Atmosphere Feedback Experiment in August 2017. Lidar measurements at five sites, separated by 55-70 km, allowed us to document the development and evolution of the wind flow over the SGP area, examine synoptic conditions to understand the mechanism that leads to the ramp event, and estimate the ability of the High-Resolution Rapid Refresh model to reproduce this event. The flow feature in question is an atmospheric bore, a small-scale phenomenon that is challenging to represent in models, that was generated by a thunderstorm outflow northwest of the ARM SGP area. The small-scale nature of bores, its impact on power generation, and the modeling challenges associated with representing bores are discussed in this paper. In conclusion, the results also provide information about model errors between sites of different surface and vegetation types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Single-event burnout in homojunction GaN vertical PiN diodes with hybrid edge termination design

GaN devices play a major role in modern electronics, providing high-power handling, efficient high-frequency operation, and resilience in harsh environments. However, electric field crowding at the edge of the anode often limits its full potential, leading to single-event effects (SEEs) at lower bias voltages under heavy ion radiation. Here, in this work, we report on the performance of homojunction GaN vertical PiN diodes with a hybrid edge termination design under heavy ion irradiation, specifically, oxygen ions, chlorine ions, Cf-252 fission fragments, and alpha particles from an Am-241 source. The unique hybrid edge termination (HET) design provides better electric field management, preventing breakdown from occurring at the edge of the anode at lower voltages. The results of this study reveal that these devices exhibit excellent tolerance to 12-MeV oxygen and 16-MeV chlorine ions, owing to their low linear energy transfer (LET) and range in GaN. However, single-event burnout (SEB) is observed during the Cf-252 exposure at about 50% of the diodes' electrical breakdown voltage due to the presence of higher LET and longer-range ions. Optical and scanning electron microscopy (SEM) reveal that the damage that caused by SEB lies close to the center of these devices rather than the anode edge. Devices with junction termination extension (JTE) instead of HET edge termination also show similar SEB when irradiated with Cf-252 fission fragments. Physical damage due to SEB occurs at the edge of the anode for these devices. These comparative results show the benefits of HET for enhancing the resistance of GaN-based PiN diodes to heavy ion irradiation.

42 ENGINEERING↗
DOE OSTI2020

A method to test the coupling strength of the linear and nonlinear contributions to higher-order flow harmonics via event shape engineering

A Multi-Phase Transport (AMPT) model is used to study the efficacy of shape-engineered events to delineate the degree of coupling between the linear and nonlinear contributions to the higher-order flow harmonics v 4 and v 5 . Here, the study shows that the nonlinear contributions are strongly shape-dependent while the linear contributions are shape-independent, indicating little if any, coupling between the linear and nonlinear flow coefficients. The experimental verification of such patterns could be an invaluable tool for robust extraction of the linear and mode-coupled flow coefficients, especially for beam energies where the charged particle multiplicity and the event statistics precludes the use of current methods to establish the coupling strength.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Search For Electron-Antineutrinos Associated With 2 Gravitational-Wave Events GW150914, GW151012, GW151226, 3 GW170104, GW170608, GW170814, and GW170817 at Daya Bay

Providing a possible connection between neutrino emission and gravitational-wave (GW) bursts is important to our understanding of the physical processes that occur when black holes or neutron stars merge. In the Daya Bay experiment, using the data collected from December 2011 to August 2017, a search has been performed for electron-antineutrino signals coinciding with detected GW events, including GW150914, GW151012, GW151226, GW170104, GW170608, GW170814, and GW170817. We used three time windows of ±10 s, ±500 s, and ±1000 s relative to the occurrence of the GW events, and a neutrino energy range of 1.8 to 100 MeV to search for correlated neutrino candidates. The detected electron-antineutrino candidates are consistent with the expected background rates for all the three time windows. Assuming monochromatic spectra, we found upper limits (90% confidence level) on electron-antineutrino fluence of (1.13 - 2.44)×1011 cm-2 at 5 MeV to 8.0×107cm-2at 100 MeV for the three timewindows. Under the assumption of a Fermi-Dirac spectrum, the upper limits were found to be (5.4 - 7.0)×109 cm-2 for the three time windows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Roles of non-axisymmetric perturbations in free drift vertical displacement events on EAST

Abstract The safe operation of most tokamaks, especially the large ones, relies on the feedback control of vertical displacement events (VDEs). However, most of these feedback control systems are based on axisymmetric VDE models. In this study, we use NIMROD simulations to study the role of non-axisymmetric perturbations in free drift vertical displacement events on EAST. The high- n modes in the non-axisymmetric VDE grow first, which drives the formation of high- n magnetic island chains. Subsequently, the magnetic island chains grow and overlap with each other, leading to the destruction of the magnetic flux surface, which induces a minor disruption and accelerates the start of the following major disruption. The magnetic island and the stochastic magnetic field allow the toroidally non-axisymmetric poloidal plasma current to jet towards the hoop force direction, forming finger-like and filamentary structures. Such a plasma current non-axisymmetry strongly depends on the anisotropy in the thermal transport coefficients.

Physics↗
DOE OSTI2020

A low energy rare event search with the MAJORANA DEMONSTRATOR

The MAJORANA DEMONSTRATOR is sensitive to rare events near its energy threshold, including bosonic dark matter, solar axions, and lightly ionizing particles. In this analysis, a novel training set of low energy small-angle Compton scatter events is used to determine the efficiency of pulse shape analysis cuts, and we present updated bosonic dark matter and solar axion results from an 11.17 kg-y dataset using a 5 keV analysis threshold.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Measurements of Single Event Upset in ATLAS IBL

Effects of Single Event Upsets (SEU) and Single Event Transients (SET) are studied in the FE-I4B chip of the innermost layer of the ATLAS pixel system. SEU/SET affect the FE-I4B Global Registers as well as the settings for the individual pixels, causing, among other things, occupancy losses, drops in the low voltage currents, noisy pixels, and silent pixels. Quantitative data analysis and simulations indicate that SET dominate over SEU on the load line of the memory. Operational issues and mitigation techniques are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Quality assurance test of silicon photomultipliers and electronic boards for STAR event plane detector

The event plane detector (EPD), installed in the Solenoid Tracker at the Relativistic Heavy-Ion Collider located at the Brookhaven National Laboratory is a plastic scintillator-based device that measures the reaction centrality and event plane in the forward region of the relativistic heavy-ion collisions. We used silicon photomultiplier (SiPM) arrays to detect the photons produced in the scintillator via the fiber connection. Signals from the SiPM arrays were amplified by the front-end electronic (FEE) board, and sent to the analog-to-digital converter (ADC) boards for further processing via the receiver (RX) board. The full EPD system consisted of 24 super-sectors (SSs); each SS was equipped with two SiPM boards, two FEE boards and two RX boards, and they corresponded to 744 readout channels. All these boards were mass produced at the University of Science and Technology of China, with a dedicated quality assurance (QA) procedures applied to identify any problems before deployment. This article describes the details of the QA method and the related test system. As a result, the QA test results are presented along with the discussions.

EPD↗
DOE OSTI2021

Performance study of charcoal-based radon reduction systems for ultraclean rare event detectors

The continuous emanation of radon due to trace amounts of uranium and thorium in detector materials introduces radon to the active detection volume of low-background rare event search detectors. 222 Rn produces a particularly problematic background in the physics region of interest by the "naked" beta decay of its 214 Pb daughter nucleus. While charcoal-based adsorption traps are expected to be effective for radon reduction in auxiliary circulation loops that service the warm components of current ton-scale detectors at slow flow rates (0.5-2 SLPM), radon reduction in the entire circulation loop at high flow rates $\mathcal{O}$(100s SLPM) is necessary to reach high sensitivity in future generation experiments. In this article we explore radon dynamics with a charcoal-based radon reduction system in the main circulation loop of time projection chamber detectors. Here, we find that even for perfect radon traps, circulation speeds of 2,000 SLPM are needed to reduce radon concentration in a 10 ton detector by 90%. This is faster by a factor of four than the highest circulation speeds currently achieved in dark matter detectors. We further find that the effectiveness of vacuum swing adsorption systems, which have been employed very successfully at reducing atmospheric radon levels in clean-rooms, is limited by the intrinsic radon activity of the charcoal adsorbent in ultra-low radon environments. Adsorbents with significantly lower intrinsic radon activity than in currently available activated charcoals would be necessary to build effective vacuum swing adsorption systems operated at room temperature for rare event search experiments. If such VSA systems are cooled to about 190 K, this requirement relaxes drastically.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Event driven readout architecture with non-priority arbitration for radiation detectors

A novel event driven readout architecture, EDWARD (Event Driven with Access and 8 Reset Decoder) architecture, for highly granular pixel detectors is presented. It incorporates, inter alia, an asynchronous arbitration tree based on Seitz' arbiters, removing the need for an imposed prioritization scheme. It also provides protection against glitches during readout. The system allows not only reading pixel activities, but also retrieving additional data, both analog and digital, from the pixels. A novel in-channel logic allows the entire readout process to be split into consecutive phases for additional flexibility. All operations are controlled by only one edge of the clock signal, seen as an acknowledge token, so there is no dead time between readouts.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Neutron tagging following atmospheric neutrino events in a water Cherenkov detector

We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218±9 μs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Background studies and normalization of signal events in the Mu2e experiment

The Mu2e experiment is currently being constructed at Fermilab to search for the neutrino-less conversion of negative muons into electrons in the field of an aluminum nucleus. The experiment aims at a sensitivity of four orders of magnitude higher than previous related experiments, which implies highly demanding accuracy requirements both in the design and during the operation. To achieve such a goal, two important tasks should be accomplished. First, it is essential to estimate precisely the particle yields and all the backgrounds that could mimic the monoenergetic conversion electron signal. Second, it is necessary to normalize the signal events accurately. The normalization of the signal events is planned to be done using a detector system made of an HPGe detector and a Lanthanum Bromide detector, which will measure the rate of muons stopped on the aluminum target by looking at the emitted characteristic X-and γ-rays of energies up to 1809 keV. Therefore, it is essential to evaluate the detector system's performance before the start of the actual experiment. In this study, the first task was addressed by an extensive campaign of Monte Carlo simulations to investigate the relevant parameters and their impact on the experiment's sensitivity. The second task was handled by taking advantage of the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) pulsed Bremsstrahlung photon beam at the ELBE facility. The detector system was tested at the ELBE facility under timing and background conditions similar to the ones expected at the Mu2e experiment. The study presents and discusses the simulation results and the detector system testing campaign.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Local, regional, and global adaptations to a compound pandemic-weather stress event

Global food security can be threatened by short-term extreme events that negatively impact food production, food purchasing power, and agricultural economic activity. At the same time, environmental pollutants like greenhouse gases (GHGs) can be reduced due to the same short-term extreme stressors. Stress events include pandemics like COVID-19 and widespread droughts like those experienced in 2015. Here we consider the question: what if COVID-19 had co-occurred with a 2015-like drought year? Using a coupled biophysical-economic modeling framework, we evaluate how this compound stress would alter both agricultural sector GHG emissions and change the number of undernourished people worldwide. We further consider three interdependent adaptation options: local water use for crop production, regional shifts in cropland area, and global trade of agricultural products. We find that GHG emissions decline due to reduced economic activity in the agricultural sector, but this is paired with large increases in undernourished populations in developing nations. Local and regional adaptations that make use of natural resources enable global-scale reductions in impacted populations via increased global trade.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deep learning-based spatiotemporal multi-event reconstruction for delay line detectors

Abstract Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments, such as the ground-breaking Hanbury Brown–Twiss experiment, leading to new physical insights. For low-energy electrons, one possibility is to use a Microchannel plate with subsequent delay lines for the readout of the incident particle hits, a setup called a Delay Line Detector. The spatial and temporal coordinates of more than one particle can be fully reconstructed outside a region called the dead radius. For interesting events, where two electrons are close in space and time, the determination of the individual positions of the electrons requires elaborate peak finding algorithms. While classical methods work well with single particle hits, they fail to identify and reconstruct events caused by multiple nearby particles. To address this challenge, we present a new spatiotemporal machine learning model to identify and reconstruct the position and time of such multi-hit particle signals. This model achieves a much better resolution for nearby particle hits compared to the classical approach, removing some of the artifacts and reducing the dead radius a factor of eight. We show that machine learning models can be effective in improving the spatiotemporal performance of delay line detectors.

Computer Science↗
DOE OSTI2024

Deep learning based event reconstruction for cyclotron radiation emission spectroscopy

The objective of the cyclotron radiation emission spectroscopy (CRES) technology is to build precise particle energy spectra. This is achieved by identifying the start frequencies of charged particle trajectories which, when exposed to an external magnetic field, leave semi-linear profiles (called tracks) in the time–frequency plane. Due to the need for excellent instrumental energy resolution in application, highly efficient and accurate track reconstruction methods are desired. Deep learning convolutional neural networks (CNNs) - particularly suited to deal with information-sparse data and which offer precise foreground localization—may be utilized to extract track properties from measured CRES signals (called events) with relative computational ease. In this work, we develop a novel machine learning based model which operates a CNN and a support vector machine in tandem to perform this reconstruction. A primary application of our method is shown on simulated CRES signals which mimic those of the Project 8 experiment—a novel effort to extract the unknown absolute neutrino mass value from a precise measurement of tritium β - -decay energy spectrum. When compared to a point-clustering based technique used as a baseline, we show a relative gain of 24.1% in event reconstruction efficiency and comparable performance in accuracy of track parameter reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗