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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Post-Mortem Characterization of Cerium Speciation in Molten Calcium Chloride

Abstract Advancing radiochemistry and nuclear materials science requires understanding actinide interactions with molten salts, which are used in next-generation nuclear reactors and for processing of actinides to recover useful fissile material. Understanding chemical interactions of actinides with molten salts has been limited by challenges in developing spectroscopic and X-ray techniques that are compatible with the high temperatures necessary to study molten salts. In this work, interactions of CeO2 (serving as a nonradioactive surrogate for uranium and plutonium) with CaCl2 are characterized following heating. Scanning electron microscopy indicates CeO2 morphological changes from small (<1 μm) particles to 3–5 μm sheets. Powder X-ray diffraction and infrared and Raman spectroscopies show the formation of CeOCl at higher (850–1050 °C) temperatures. In the absence of a chemical reducing agent, it was found that a high-temperature, low-oxygen environment is the key to the formation of oxychloride and that oxychloride formation is inhibited by annealing the CeO2 starting material. Lastly, thermal analysis revealed lowering of the melting point of CaCl2 after heating with CeO2. In all, this work identifies applicable spectroscopic techniques to target studies of heavy elements in molten salt environments and highlights the relationship between chemical speciation and melting behavior, a key thermophysical property.

Kelly, Sheridon N. [Lawrence Livermore National La↗
DOE OSTI2021

Efficiency analysis of helium-cooled MAS DNP: case studies of surface-modified nanoparticles and homogeneous small-molecule solutions

Despite the growing number of successful applications of dynamic nuclear polarization (DNP)-enhanced magic-angle spinning (MAS) NMR in structural biology and materials science, the nuclear polarizations achieved by current MAS DNP instrumentation are still considerably lower than the theoretical maximum. Here, the method could be significantly strengthened if experiments were performed at temperatures much lower than those currently widely used (~100 K). Recently, the prospects of helium (He)-cooled MAS DNP have been increased with the instrumental developments in MAS technology that uses cold helium gas for sample cooling. Despite the additional gains in sensitivity that have been observed with He-cooled MAS DNP, the performance of the technique has not been evaluated in the case of surfaces and interfaces that benefit the most from DNP. Herein, we studied the efficiency of DNP at temperatures between ~30 K and ~100 K for organically functionalized silica material and a homogeneous solution of small organic molecules at a magnetic field B 0 = 16.4 T. We recorded the changes in signal enhancement, paramagnet-induced quenching and depolarization effects, DNP build-up rate, and Boltzmann polarization. For these samples, the increases in MAS-induced depolarization and DNP build-up times at around 30 K were not as severe as anticipated. In the case of the surface species, we determined that MAS DNP at 30 K provided ~10 times higher sensitivity than MAS DNP at 90 K, which corresponds to the acceleration of experiments by multiplicative factors of up to 100.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics

The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. CERN's Large Hadron Collider (LHC) represents a huge step forward in this quest. The discovery of the Higgs boson, the observation of exceedingly rare decays of $B$ mesons, and stringent constraints on many viable theories of physics beyond the Standard Model (SM) demonstrate the great scientific value of the LHC physics program. The next phase of this global scientific project will be the High-Luminosity LHC (HL-LHC) which will collect data starting circa 2029 and continue through the 2030s. The primary science goal is to search for physics beyond the SM and, should it be discovered, to study its implications. In the HL-LHC era, the ATLAS and CMS experiments will record around 100 times as many collisions as were used to discover the Higgs boson (and at twice the energy). Both NSF and DOE are making large detector upgrade investments so the HL-LHC can operate in this high-rate environment. Similar investment in software R&D for acquiring, managing, processing and analyzing HL-LHC data is critical to maximize the return-on-investment in the upgraded accelerator and detectors. This report presents a strategic plan for a possible second 5-year funded phase (2023 through 2028) for the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) which will close remaining software and computing gaps to deliver HL-LHC science.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Partnership for Radiation Studies (PaRS): A Consortium for Advancing Radiation Science among Underrepresented STEM Students

The Partnership for Radiation Studies (PaRS) consortium was recently awarded by U.S. Department of Energy’s National Nuclear Security Administration (NNSA). The five-year grant aims to increase the number of underrepresented students in STEM disciplines, with simultaneous advancement of nuclear radiation science. The goal is to hire more underrepresented minorities at national laboratories. The consortium’s progress will be tracked/reported annually. This paper and subsequent presentation cover details of the consortium, highlighting the key activities of participating national laboratories in assisting the minority-serving institutions.

Minority Serving Institutions Partnership Program,↗
DOE OSTI2024

Autonomous anomaly detection of proliferation in the AGN-201 nuclear reactor digital twin

The expansion of global nuclear power necessitates advanced methods for analyzing proliferation indicators. This study introduces a novel application of the Isolation Forest Machine Learning (IFML) algorithm within a digital twin (DT) of the AGN-201 nuclear reactor to autonomously detect anomalies. Leveraging real-time operational data from the AGN-201 DT, the IFML algorithm identifies outliers without prior data labeling and operates as a lightweight, complementary approach to traditional physics-based anomaly detection methods for nuclear safeguards. In a simulated Red vs. Blue team exercise, the IFML algorithm successfully detected six significant unseen anomalies related to reactivity changes, achieving an accuracy of 99% for identifying operational deviationxs. These anomalies, caused by deliberate perturbations, were detected alongside known physics-based models, underscoring the potential of IFML to enhance real-time monitoring without displacing traditional methods. Further, this study highlights the applicability of IFML in nuclear environments by providing an additional, redundant layer of anomaly detection to improve safeguards and operational safety in complex systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A PIPS + SrI 2 (Eu) detector for atmospheric radioxenon monitoring

The PIPS–SrI 2 (Eu) is a prototype atmospheric radioxenon detection system designed at Oregon State University in support of international efforts towards monitoring clandestine nuclear weapon testing activities. This detector aims to address some shortcomings found in currently deployed beta–gamma atmospheric radioxenon detection systems, such as lackluster energy resolution and memory effect, by employing modern detection materials and readout. The system uses a PIPSBox, a silicon-based gas cell, for electron detection, and a pair of ultrabright, D-shaped SrI 2 (Eu) scintillators coupled to silicon photomultipliers for photon detection. A custom eight-channel digital pulse processor equipped with a field programmable gate-array (FPGA) identifies electron–photon coincidences between the volumes in near real-time. Gas samples of the four radioxenon isotopes of interest were independently measured with the PIPS–SrI 2 (Eu) detection system to determine energy resolution and efficiency. Application of FPGA-based coincidence discrimination in near real-time reduced the ambient background count rate by 95.85 ± 0.04%. Using parameters from the Xenon International gas processing unit and assuming a blank sample and zero memory effect the minimum detectable concentrations (MDCs) for the isotopes were calculated to be 0.12 ± 0.03, 0.27 ± 0.05, 0.15 ± 0.02, and 1.00 ± 0.08 mBq/m 3 air for 131m Xe, 133 Xe, 133m Xe, and 135 Xe, respectively. These MDC estimates compare well with other radioxenon detection systems employed in the International Monitoring System (IMS) and indicate that the PIPS–SrI 2 (Eu) is in compliance with the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO) sensitivity requirement of ≤ 1 mBq/m 3 for 133 Xe.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Classification of events from α -induced reactions in the MUSIC detector via statistical and ML methods

The Multi-Sampling Ionization Chamber (MUSIC) detector is typically used to measure nuclear reaction cross sections relevant for nuclear astrophysics, fusion studies, and other applications. From the MUSIC data produced in one experiment scientists carefully extract an order of 10 3 events of interest from about 10 9 total events, where each event can be represented by an 18-dimensional vector. However, the standard data classification process is based on expert driven, manually intensive data analysis techniques that require several months to identify patterns and classify the relevant events from the collected data. Here, to address this issue, we present a method for the classification of events originating from specific α-induced reactions by combining statistical and machine learning methods that require significantly less input from the domain scientist, relative to the standard technique. Here, we applied the new method to two experimental data sets and compared our results with those obtained using traditional methods. With few exceptions, the number of events classified by our method agrees within ±20% with the results obtained using traditional methods. With the present method, which is the first of its kind for the MUSIC data, we have established the foundation for the automated extraction of physical events of interest from experiments using the MUSIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Progress in end-to-end optimization of fundamental physics experimental apparata with differentiable programming

In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the specification of a software pipeline including all factors impacting performance — from the data-generating processes to their reconstruction and the inference on the parameters of interest — along with the careful specification of a utility function well aligned with the end goals of the experiment. Building on previous studies originated within the MODE Collaboration, we focus specifically on applications involving instruments for particle physics experimentation, as well as industrial and medical applications that share the detection of radiation as their data-generating mechanism. This report illustrates the most recent advancements in the area, and outlines, for each of the discussed applications as well as for automatic differentiation itself, ongoing and future work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Identifications and classifications of human locomotion using Rayleigh-enhanced distributed fiber acoustic sensors with deep neural networks

Abstract This paper reports on the use of machine learning to delineate data harnessed by fiber-optic distributed acoustic sensors (DAS) using fiber with enhanced Rayleigh backscattering to recognize vibration events induced by human locomotion. The DAS used in this work is based on homodyne phase-sensitive optical time-domain reflectometry (φ-OTDR). The signal-to-noise ratio (SNR) of the DAS was enhanced using femtosecond laser-induced artificial Rayleigh scattering centers in single-mode fiber cores. Both supervised and unsupervised machine-learning algorithms were explored to identify people and specific events that produce acoustic signals. Using convolutional deep neural networks, the supervised machine learning scheme achieved over 76.25% accuracy in recognizing human identities. Conversely, the unsupervised machine learning scheme achieved over 77.65% accuracy in recognizing events and human identities through acoustic signals. Through integrated efforts on both sensor device innovation and machine learning data analytics, this paper shows that the DAS technique can be an effective security technology to detect and to identify highly similar acoustic events with high spatial resolution and high accuracies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Preliminary searches for spin-dependent interactions using sidebands of nuclear spin-precession signals

Various theories beyond the Standard Model predict new particles with masses in the sub-eV range with very weak couplings to ordinary matter. A new P-odd and T-odd interaction between polarized and unpolarized nucleons proportional to s⃗⋅r̂ is one such possibility, where r⃗=rr̂ is the spatial vector connecting the nucleons, and s⃗ is the spin of the polarized nucleon. Such an interaction involving a scalar coupling gsN at one vertex and a pseudoscalar coupling gpn at the polarized nucleon vertex can be induced by the exchange of spin-0 pseudoscalar bosons. We describe a new technique to search for interactions of this form and present the first measurements of this type. We show that future improvements to this technique can improve the laboratory upper bound on the product gsNgpn by two orders of magnitude for interaction ranges at the 100 micron scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Analyzing the effect of pressure on the properties of point defects in $\gamma\mathrm{U–Mo}$ through atomistic simulations

Uranium–molybdenum (U–Mo) alloys in monolithic fuel foil are the primary candidate for the conversion of high-performance research reactors in the USA. Monolithic fuel is utilized in a plate-type design with a zirconium diffusion barrier and aluminum cladding. These fuel types are unique in that they contain no plenum for the release of fission gases, which, in conjunction with the aluminum cladding, can lead to large stress states within the fuel. The nature of how fundamental processes of radiation damage, including the evolution of point defects, under such stresses occur is unknown. In this work, we present molecular dynamics simulations of the formation energy of point defects under applied stress. We report this work will allow for the implementation of stress-dependent microstructural evolution models of nuclear fuels, including those for both fission gas bubble growth and creep, which are critical to ensure the stable and predictable behavior of research reactor fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Nuclear Physics Exascale Requirements Review: An Office of Science Review sponsored jointly by Advanced Scientific Computing Research and Nuclear Physics, June 15 - 17, 2016, Gaithersburg, Maryland

Imagine being able to predict — with unprecedented accuracy and precision — the structure of the proton and neutron, and the forces between them, directly from the dynamics of quarks and gluons, and then using this information in calculations of the structure and reactions of atomic nuclei and of the properties of dense neutron stars (NSs). Also imagine discovering new and exotic states of matter, and new laws of nature, by being able to collect more experimental data than we dream possible today, analyzing it in real time to feed back into an experiment, and curating the data with full tracking capabilities and with fully distributed data mining capabilities. Making this vision a reality would improve basic scientific understanding, enabling us to precisely calculate, for example, the spectrum of gravity waves emitted during NS coalescence, and would have important societal applications in nuclear energy research, stockpile stewardship, and other areas. This review presents the components and characteristics of the exascale computing ecosystems necessary to realize this vision.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Completion of Irradiation of Sensors in ATRC Milestone

This set of PowerPoint slides demonstrates how milestone "M2CT-21IN0702023: Perform test of neutron flux sensors in the Advanced Test Reactor Critical Facility". It supports an entry in PICS claiming achievement of the milestone. These slides provide a good summary of the purpose and impact of the milestone for our DOE Headquarters colleagues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Performance Analysis and Radiation Damage Estimation of the Stopping Target Monitor Detectors in Mu2e

The Mu2e experiment aims to search for the charged lepton flavour violating (CLFV) process of a coherent, neutrinoless, conversion of a muon into an electron within the proximity of an aluminium nucleus. Mu2e seeks to measure the ratio (R μe ) of the rate of this conversion process, relative to that of ordinary muon capture. Mu2e will achieve world-leading sensitivity, improving the current limit of Rμe < 7 ×10 -13 (90% C.L.),set by the SINDRUM-II experiment, by an order of 104. This corresponds to a single-event sensitivity of Rμe < 2.87 × 10 -17 (90% C.L.). Many beyond Standard Model (BSM) theories require CLFV to occur at a rate accessible by Mu2e. Any observation of CLFV at Mu2e would have profound implications on particle physics. The Stopping Target Monitor (STM) will be comprised of both a HPGe and a LaBr3 detector which will monitor the signals of photons produced in stopped-muon processes to a required accuracy of 10%. To achieve the desired sensitivity, it is imperative that the detectors perform at their optimal level. The STM detectors are placed within a harsh radiation environment in the form of a high energy ‘flash’ of gamma radiation as well as a flux of fast neutrons. Estimations of radiation damage to HPGe in literature is limited. This thesis reports an approach which utilizes the Kinetic-Energy Released in Matter (KERMA) parameter that considers the energy dependence of the incident flux and the cross-section information for the incident particle. Resampling schemes have been adopted to give a realistic rate over the experiment run time. The results have then been normalized to the radiation damage caused by a 252 Cf source. The estimated time before annealing of the detector is necessary is found to be 75 and 78 months in the case of neutron damage and τ ~ 24 years, 11 months in the case of electron/positron induced damage. This shows significant improvement on the previous estimations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

DRiFT - Release 1.1.1: Organic Scintillators

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that postprocesses output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. Although DRiFT development has included scintillator, gas, and semiconductor features, the focus of this release is on organic scintillator and associated capabilities. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

IER-479/547: Low-Temperature TEX Surrogate Testing and Reflector Design [Slides]

This lecture includes a look into progress in surrogate testing. This includes a new chiller that has been fabricated and testing that has resumed. Additional tests are being conducted, including: using formed aluminum gaskets, extended testing with natural uranium, testing with pseudo-spindle, testing with no vacuum. This lecture includes a look into the Reflector Design. Results for detailed model are consistent with results presented in CED-2. Calculations provide flexibility in the physical design of the reflectors (e.g. reflector segment widths and heights). Provided initial CAD models of reflector components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Markov Process to Evaluate the Value Proposition of a Risk-Informed Predictive Maintenance Strategy

To achieve high-capacity factors, the nuclear fleet has relied on labor-intensive and time-consuming operation and preventive maintenance programs for plant systems. Manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies, along with time-based replacement of assets irrespective of condition, have resulted in a costly, labor-centric business model. Fortunately, there are technologies that can eliminate unnecessary preventive maintenance activities by deploying risk-informed predictive maintenance, enabling the transition to a technology-centric business model. The technology-centric business model will enable plants to optimize and automate maintenance activities, leading to cost reductions since labor is a rising cost and technology is a declining cost. The implementation of scalable technologies and methodologies across plant systems and across the nuclear fleet is critical for successful deployment of a risk-informed predictive maintenance strategy at commercial nuclear power plants. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report describes the technical basis using the Markov Process to evaluate the value proposition for the risk-informed predictive maintenance strategy for the circulating water system. The plant process data from the Salem nuclear plant’s circulating water system is utilized to develop a Markov chain risk models and formulation to estimate the loss and gain in revenue based on plant availability. The outcomes presented in this report provides the technical basis for extensive quantitative evaluation of a scalable risk-informed predictive maintenance strategy as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Incorporating the latest Neutron NDA analysis techniques into INCC6

International Neutron Coincidence Counting (INCC6) is the IAEA’s neutron NDA software. With FY25 SGTech support we implemented self-diagnostic features into INCC6. For FY26 we propose to implement advanced analysis methods that have been splintered into custom software for one-off instruments. Incorporating these capabilities in INCC6 will make them available for any new or existing application on the ubiquitous INCC6 platform, increasing safeguards efficiency and effectiveness.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗