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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 OSTI2020

In-Pile Instrumentation (I2) (2018 Report)

Energy demand is growing exponentially, renewing interest in nuclear technology as a reliable, carbon-free energy source. In alignment with the U.S. Department of Energy (DOE), Idaho National Laboratory’s (INL’s) primary mission is to discover, demonstrate and secure innovative nuclear energy solutions. The capability to monitor the conditions inside nuclear reactors core is considered essential to this development process. To enable such capability, the InPile Instrumentation (I2) program was conceived in 2017 as an additional element to DOE Crosscutting Technology Development activities under the Nuclear Energy Enabling Technology (NEET) program. This document reports on the first year of implementation of research activities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Measurements of electron transport in liquid and gas Xenon using a laser-driven photocathode

Measurements of electron drift properties in liquid and gaseous xenon are reported. The electrons are generated by the photoelectric effect in a semitransparent gold photocathode driven in transmission mode with a pulsed ultraviolet laser. The charges drift and diffuse in a small chamber at various electric fields and a fixed drift distance of 2.0 cm. At an electric field of 0.5 kV/cm, the measured drift velocities and corresponding temperature coefficients respectively are 1.97 ± 0.04 mm/µs and (-0.69 ± 0.05)%/K for liquid xenon, and 1.42 ± 0.03 mm/µs and (+0.11 ± 0.01)%/K for gaseous xenon at 1.5 bar. In addition, we measure longitudinal diffusion coefficients of 25.7±4.6 cm2/s and 149±23 cm2/s, for liquid and gas, respectively. The quantum efficiency of the gold photocathode is studied at the photon energy of 4.73 eV in liquid and gaseous xenon, and vacuum. These charge transport properties and the behavior of photocathodes in a xenon environment are important in designing and calibrating future large scale noble liquid detectors.

Njoya, Oumarou↗
DOE OSTI2021

Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

3D imaging↗
DOE OSTI2021

A D$_2$O detector for flux normalization of a pion decay-at-rest neutrino source

We report on the technical design and expected performance of a 592 kg heavy-water-Cherenkov detector to measure the absolute neutrino flux from the pion-decay-at-rest neutrino source at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL). The detector will be located roughly 20 m from the SNS target and will measure the neutrino flux with better than 5% statistical uncertainty in 2 years. This heavy-water detector will serve as the first module of a two-module detector system to ultimately measure the neutrino flux to 2–3% at both the First Target Station and the planned Second Target Station of the SNS. This detector will significantly reduce a dominant systematic uncertainty for neutrino cross-section measurements at the SNS, increasing the sensitivity of searches for new physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Prototype X-ray and Gamma Detection with Cyclotron Radiation Emission Spectroscopy

Cyclotron radiation emission spectroscopy, or CRES, is a novel approach to measuring the energy of an electron. By trapping a free electron in a high magnetic field, it undergoes cyclotron motion and emits radiofrequency (RF) waves. The frequency of this RF radiation is directly related to the energy of the electron. Because many cycles of the RF emission are recorded, the energy resolution of the CRES system is on the order of a single electron volt. To make a CRES system sensitive to photons, a target gas is used to induce a photoelectric effect, producing the electron that is subsequently trapped. By adding the binding energy of the target atom, the energy of the incident photon may be reconstructed. Using a xenon target gas, photoelectric interactions dominate up to approximately 300 keV, covering not only all atomic shell X-rays of the elements, but many low-lying nuclear states as well, including key transuranic elements related to nuclear security. CRES holds the potential of maintaining single-eV resolution up to this 300-keV range, thereby surpassing current state-of-the-art detectors by a factor of 10-100. The instrumental resolution of the system is limited by the uniformity of the applied magnetic field.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A flexible event reconstruction based on machine learning and likelihood principles

Event reconstruction is a central step in many particle physics experiments, turning detector observables into parameter estimates; for example estimating the energy of an interaction given the sensor readout of a detector. A corresponding likelihood function is often intractable, and approximations need to be constructed. Here, in our work, we first show how the full likelihood for a many-sensor detector can be broken apart into smaller terms, and secondly how we can train neural networks to approximate all terms solely based on forward simulation. Our technique results in a fast, flexible, and close-to-optimal surrogate model proportional to the likelihood and can be used in conjunction with standard inference techniques allowing for a consistent treatment of uncertainties. We illustrate our technique for parameter inference in neutrino telescopes based on maximum likelihood and Bayesian posterior sampling. Given its great flexibility, we also showcase our method for geometry optimization enabling to learn optimal detector designs. Lastly, we apply our method to realistic simulation of a ton-scale water-based liquid scintillator detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

BoxScore - A real-time beam-diagnosis program for the CAEN digitizer x730 series

BoxScore is a real-time beam diagnosis and monitoring program for the CAEN x730 series digitizer, developed for the ATLAS in-flight system at Argonne National Laboratory. The CAEN x730 series digitizer, with built-in Digital Pulse Processing for the Pulse-Height-Analysis, digitizes the input signal in real-time and processes it using a trapezoidal filter. BoxScore reads the digitizer’s buffer directly, builds and saves events to local files, plots histograms for particle identification, and outputs the rates of selected isotopes every second. Implementation of BoxScore has shortened the time needed for in-flight beam-tuning and has potential applications for other nuclear physics experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Snowmass 2021 Scintillating Bubble Chambers: Liquid-noble Bubble Chambers for Dark Matter and CE$\nu$NS Detection

The Scintillating Bubble Chamber (SBC) Collaboration is developing liquid-noble bubble chambers for the quasi-background-free detection of low-mass (GeV-scale) dark matter and coherent scattering (CE$\nu$NS) of low-energy (MeV-scale) neutrinos. The first physics-scale demonstrator of this technique, a 10-kg liquid argon bubble chamber dubbed SBC-LAr10, is now being commissioned at Fermilab. This device will calibrate the background discrimination power and sensitivity of superheated argon to nuclear recoils at energies down to 100 eV. A second functionally-identical detector with a focus on radiopure construction is being built for SBC's first dark matter search at SNOLAB. The projected spin-independent sensitivity of this search is approximately $10^{-43}$ cm$^2$ at 1 GeV$/c^2$ dark matter particle mass. The scalability and background discrimination power of the liquid-noble bubble chamber make this technique a compelling candidate for future dark matter searches to the solar neutrino fog at 1 GeV$/c^2$ particle mass (requiring a $\sim$ton-year exposure with non-neutrino backgrounds sub-dominant to the solar CE$\nu$NS signal) and for high-statistics CE$\nu$NS studies at nuclear reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Machine Learning assisted optimization and parameter space exploration dataset of spin ice Hamiltonian

This repository contains both simulated and experimental structure factor data for the data challenge involving the inverse scattering problem. The simulated data were generated during a machine-learning-assisted optimization routine described in ref[1]. The experimental structure factor was measured on a rare-earth oxide, Dy2Ti2O7 using diffuse neutron scattering from time-of-flight techniques on the CORELLI instrument at the Spallation Neutron Source, Oak Ridge National Laboratory. A Metropolis Monte Carlo code implemented to run in a High-performance computing setting was used to calculated simulated structure factors for the spin-ice Hamiltonian at 680 mK, which is the same temperature as for the experimental data. The total size of all the files in this repository is 5.12 GB. A detailed description of the files is given below. ExperimentalData_630mK.dat – A linearized version of 3-dimensional experimental data of size 61×81×21. This data was processed to remove an estimation of non-magnetic background, including nuclear scattering signal and instrumentation background. Parameters.dat – 6700 samples were evaluated over the 4-dimensional parameter space (J_1, J_2, J_3 and J_(3^' )). There is an additional parameter, D in the spin Hamiltonian to mimic the dipolar interaction between magnetic ions. However, this parameter, D was fixed to a value determined by prior work. This file contains five columns for the parameters J_1, J_2, J_3, J_(3^' ) and D respectively. 3D_Simulation_Data.dat – The simulated structure factor, S(Q) data are included in this file. Each raw contains a linearized array of 3D volumes of S(Q) calculated for the parameter set given in the corresponding row of the file Parameters.dat. The size of the volume data was matched to the experimental data. Qx(h,-h,0).dat, Qy(k,k,-2k).dat, Qz(l,l,l).dat – These files contain the h, k, and l values along with the reciprocal vectors [h,-h,0], [k,k,-2k] and [l,l,l] respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Presentation: Sensor Anomaly Detection for Nuclear Reactor Systems Utilizing Linear Regression and K-Means Unsupervised Machine Learning: An overview of methods and results

This presentation is a culmination of work which has occurred over the course of a 10-week internship. Anomaly detection methods must be both robust enough to detect subtle anomalies yet not so sensitive to report false positives, which would result significant loss of revenue. Methods currently being developed for autonomous systems are often pursuing a Digital Twin method, which will look at the entire system and model it as a whole. This presentation, however, focuses less on direct application to an NPP, rather acting as a proof of concept for the methods developed. For the project, we look to develop methods to analyze steady-state data and report anomalies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗