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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

THE STRUCTURE FUNCTION OF THE FREE NEUTRON AT HIGH X-BJORKEN

Understanding the internal structure of nucleons is one of the primary goal of nuclear physicists. As protons and neutrons are only the bound state solution of the QCD lagrangian (at least inside atomic nuclei), studying protons and neutrons helps uncover nuclear struc ture. Due to its easy availability, many studies on protons have been done on a wide range of kinematics. However, free neutron targets are not readily achievable. So, any information on neutrons has to be extracted from neutron-rich nuclei, and some nuclear models have to be used to subtract the contributions from other nucleons to extract the information on neutrons. So, the Barely Off-shell Nucleon Structure (BONuS12) experiment at Jefferson Lab was conducted to overcome these challenges by using spectator tagging. The experiment effectively created a quasi-free neutron target by scattering electrons off a deuterium target and detecting low-momentum, backward-moving protons using a custom-built Radial Time Projection Chamber (RTPC). Selecting the low momentum and backward-moving spectators would enable us to minimize the model-dependent effects due to final state interactions and target fragmentation. The RTPC was a 40 cm-long cylindrical detector that works on the principle of gaseous ionization. It had three layers of Gas Electron Multipliers (GEMs) for charge amplification and a surrounding readout pad. The scattered electrons were measured using the CLAS12 detector, and data were collected using a 10.4 GeV electron beam dur ing Spring and Summer 2020. Using spectator tagging, we extracted the structure function ratio Fn 2 of the quasi-free neutron in the deep inelastic scattering at high x, upto x ~ 0.8. The result was extracted in the region with the invariant mass W > 1.8 GeV/c2, and Q2 in the range 1.3 to 11 GeV2. This dissertation presents the methodology, event selection criteria and refinements, estimation and subtraction of backgrounds, and complete analysis of extraction of Fn 2/Fp 2 in a model-independent way. Also, systematic uncertainties in our final analysis will be discussed in detail.

Pokhrel, Madhusudhan [Old Dominion Univ., Norfolk,↗
DOE OSTI2024

Data-driven reevaluation of f t values in superallowed β decays

We present a comprehensive reevaluation of the ft values in superallowed nuclear β decays crucial for the precise determination of V ud and low-energy tests of the electroweak standard model. It consists of the first, fully data-driven analysis of the nuclear β decay form factor, that utilizes isospin relations to connect the nuclear charged weak distribution to the measurable charge distributions. This prescription supersedes previous shell-model estimations, and allows for a rigorous quantification of theory uncertainties in f which is absent in the existing literature. Furthermore, our new evaluation shows an overall downward shift of the central values of f at the level of 0.01%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Machine-Learning Enabled Evaluation of Probability of Piping Degradation In Secondary Systems of Nuclear Power Plants

The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Proceedings of RIKEN BNL Research Center Workshop: Predictions for sPHENIX [Slides]

To complete the RHIC mission, sPHENIX was specifically designed to measure jet and heavy-flavor observables with a level of precision not previously achievable at RHIC. This will enhance our understanding of the quark-gluon plasma (QGP) properties and their temperature dependence beyond what is possible with existing and planned data from the LHC and other RHIC experiments. A major goal of the sPHENIX program is to address the question of the approach to thermalization of the quark-gluon plasma and its transport properties using hard probes such as jets and heavy flavor. The current three-year run plan includes Au+Au, p+Au and p+p collisions at 200 GeV. The Au+Au dataset provides a large QGP system to study the QGP properties. The p+Au dataset will allow for additional studies of the intriguing behavior observed in flow measurements from other RHIC experiments as well as transport properties of cold QCD matter and proton/nuclear structure. The p+p collisions provide a necessary reference for Au+Au and p+Au collisions and also allow for additional studies of proton structure. Anticipated measurements include but are not limited to, jet substructure observables, photon and heavy flavor tagged jets as well as comparisons of the production of the different upsilon states in all three collision systems. To maximize the rich physics sPHENIX is capable of accessing, this workshop will enhance the discussions between the experimentalists making the measurements and the theorists whose models will be tested and constrained by the new data. Since sPHENIX will start taking data in early 2023, this workshop is timely for theorists wishing to make final predictions of anticipated observables before data collection commences. In addition, it will provide an opportunity for theorists and experimentalists to propose and discuss new observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Improvements to the Modeling of the TREAT Reactor and Experiments

This paper summarizes the latest improvements and lessons learned from the modeling and simulation of the transient test reactor at Idaho National Laboratory using the MAM- MOTH reactor physics application. MAMMOTH is a MOOSE-based, Finite Element Method application that specializes in the analysis of the spatial dynamics behavior of nuclear reactors. Since early 2018 several transient tests have been conducted at TREAT, thus providing the opportunity to apply and benchmark modern modeling and simulation tools. MAMMOTH was used to provide predictions of the power coupling factor between the core and the experiment for various experiments. Even though the power coupling factor predictions agree very well with the experimental data, within the bounds of the experimental uncertainty, one shortcoming was the underprediction of the total energy deposited in the core and in the experiment. Determination of the sources for this discrepancy are ongoing, but several key problems have been identified and resolved, thus providing valuable insights for future research. This paper discusses several of these lessons learned. First, the heat capacity data for the TREAT fuel has some significant problems due to limitations of the measurement techniques used circa 1960s. The sensitivity of the peak power and the total energy deposition to various representations of the heat capacity is approximately 5%. Second, the effects of the biological shield and thermal column on the modeling of the core are non-negligible, since they affect the mean generation time and the effective reflection of neutrons back into the core, which is suspected to be important during the core heat up. Matching the reactor period resolves the fact that the reduced spatial domain used in the MAMMOTH model underpredicts the mean generation time. The neutron reflection from these regions is marginally improved with the use of an albedo boundary condition. Third, modeling of the control rod movement with a multi-scheme method is introduced and its current limitations are exposed. Fourth, we explore the effects of using a homogenized model with Superhomogenization equivalence and how that differs from fully heterogeneous simulations. Finally, the energy condensation effects for this graphite core are significant. Solutions with 10 and 26 energy groups show the benefits of using a finer coarse group structure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Enhancement of α -particle formation near Sn 100

The superfluid tunneling model is applied to the calculation of ground-state-to-ground-state α decay in the even-even neutron-deficient Te-Ba nuclei. Here, we show that there is a larger α-particle formation probability in nuclei of this region above 100 Sn when compared to analogous nuclei above 208 Pb. This is consistent with the expected systematic variation of the pair gap Δ as a function of mass number. Finally, the recent experimental data on the α decay of the N=Z nuclei 104 Te and 108 Xe are shown to leave open the possibility of enhanced α-particle formation involving nucleon correlations beyond the standard treatment of like-nucleon pairing, which is the mechanism suggested as underlying "superallowed" α decay.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Shell model analysis of the B ( E 2,2 + → 0 + ) values in the A = 70, T = 1 triplet 70 Kr, 70 Br, and 70 Se

The B(E2, 2 + → 0 + ) transition strengths of the T=1 isobaric triplet 70 Kr, 70 Br, 70 Se, recently measured at the RIKEN Radioactive Isotope Beam Factory (RIBF), are discussed in terms of state-of-the-art large scale shell model calculations using the JUN45 and JUN45 + LNPS plus Coulomb interactions. In this Letter we argue that, depending on the effective charges used, the calculations are either in line with the experimental data within statistical uncertainties, or the anomaly happens in 70 Br, rather than 70 Kr. In the latter case, we suggest that it can be due to the presence of a hitherto undetected 1 + T = 0 state below the yrast 2 + T = 1 state. Furthermore, our results do not support a shape change of 70 Kr with respect to the other members of the isobaric multiplet.

59 ≤ A ≤ 89↗
DOE OSTI2023

Measurement of the cross section of the Q=4.4398 MeV 12 C (n, n'γ) reaction from threshold to 16.5 MeV using γ and correlated n–γ detection

The Q=4.4398 MeV 12 C (n, n'γ) cross section was measured using a white incident neutron source through the detection of γ rays only and n–γ coincidences using a segmented liquid scintillator detector array. While the n–γ technique utilized here is more generally applicable to a wide variety of neutron scattering measurements, the γ-only technique was successfully applied to this reaction to exploit the precise time resolution and high efficiency of this detection system to yield results with unprecedented statistical precision and total uncertainties < 2 % from reaction threshold up to 16 MeV incident neutron energy, clearly resolving many features in this reaction that were previously not well known. The γ-only and n–γ results are consistent with each other for the majority of the incident energy range covered in this paper, thereby lending validation to the n–γ technique for future measurements, though significant disagreements are observed between both results and with the ENDF/B-VIII.0 nuclear data evaluation. These differences are particularly noticeable in the recently evaluated energy range below 6.5 MeV, and also near 14 MeV where a “sawtooth”-like feature is observed similar to that in other 12 C+n reaction channels. Finally, both γ-only and n–γ results are presented here with thorough covariance derivations.

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

Analysis of X-ray images and spectra (aXis2000): A toolkit for the analysis of X-ray spectromicroscopy data

Spectromicroscopy refers to analytical methods that combine imaging and spectroscopy to provide detailed, spatially resolved analytical information about a sample, such as the type and quantitative spatial distributions of chemical components, geometric or magnetic alignment information, crystal structure, etc. The analysis of X-ray images and spectra (aXis2000) software described in this work provides a set of routines within a single, integrated, graphical-oriented package to read, display, manipulate and analyze spectromicroscopy data, with particular focus on soft X-ray spectromicroscopy methods such as scanning transmission X-ray microscopy (STXM), X-ray photoemission electron microscopy (XPEEM), scanning photoelectron X-ray microscopy (SPEM) and transmission X-ray microscopy (TXM). Here, this free software is described and compared to other software that can provide similar or complementary capabilities. Examples of spectromicroscopic analyses using advanced features of aXis2000 are provided.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Simulation of the Fast Reactor Fuel Assembly Duct-Bowing Reactivity Effect Using Monte Carlo Neutron Transport and Finite Element Analysis

This paper discusses a new method of simulating the fuel assembly duct-bowing reactivity coefficient for EBR-II run 138B. Quantification of the fuel assembly duct-bowing reactivity effect in liquid metal–cooled fast reactors has been a persistent problem since they were first designed and operated. Simulation of the duct-bowing reactivity effect is difficult because the level of detail required to simulate the effect has exceeded most modeling capabilities. The new method outlined in this paper utilizes the finite element analysis code ANSYS to analyze the thermal and structural components. Here, the displacement of the fuel assembly duct due to thermal expansion and mechanical interaction was calculated by ANSYS using recorded EBR-II run 138B temperature and power boundary value data. The displacement values were incorporated into to a Monte Carlo model of EBR-II run 138B and keff was calculated. Multiple Monte Carlo calculations were performed with duct displacement values corresponding to different reactor temperatures. Using the calculated keff values associated with the different duct displacement results allowed calculation of the duct-bowing reactivity coefficient. The duct-bowing reactivity coefficient was calculated to be –14.5 × 10 –4 $/°C/ ± 4.4%.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Artificial Reasoning System for Symptom-Based Conditional Failure Probability Estimation Using Bayesian Network

Advances in nuclear power technologies require enhanced capabilities for operator advice and autonomous control. One of the first tasks in the development of such capabilities is the formulation of symptom-based conditional failure probabilities for structures, systems, and components (SSCs) of interest, for which the primary goal is to aid plant personnel in deducing the probabilistic performance status of the monitored SSCs and in detecting impending faults/failure. The task of conditional failure probability estimation is a bidirectional inference problem and shall be logically tackled by the Bayesian network (BN) approach. As a knowledge-based artificial intelligence tool and a probabilistic graphical model, BN offers the capability of reasoning under uncertainty and graphical representation emulating the physical behavior of the target SSC. This paper provides a systematic overview of the BN technique and the software tools for handling implementation of BN models, along with the associated knowledge representation and reasoning paradigm. Both operational data and expert judgement can be readily incorporated into the knowledge base of a BN model. The challenges with data availability are highlighted, and the general approach to target SSC identification is presented. Our focus is upon failure-prone and risk-important balance of plant assets, especially cases having strong operator involvement. An exemplary case study on the failure of a motor-driven centrifugal pump is also conducted to demonstrate the usefulness and technical feasibility of the proposed artificial reasoning system using an expert system shell.

Zhao, Xingang↗
DOE OSTI2025

Bayesian Calibration of Nuclear Graphite Property Models Accounting for Model Inadequacy and Impacts on Component Performance

Nuclear-grade structural graphite is extensively utilized in the core designs of various advanced nuclear reactors. In the reactor environment, graphite is subjected to prolonged exposure to extreme conditions, including high temperatures, radiation, and potentially molten salt and oxygen. Such exposure can induce several degradation mechanisms in graphite, including nonuniform volumetric strains caused by irradiation and thermal expansion, leading to stresses that may compromise the performance of graphite components. Assessing component integrity requires accurate models of graphite's thermomechanical response. This report documents the Bayesian calibration of thermomechanical properties for nuclear-grade graphite and their application to graphite component modeling and simulation using the Grizzly code. As part of this work, uncertainty-quantified models were developed for the elastic modulus, coefficient of thermal expansion, irradiation-induced dimensional change, and irradiation-induced creep for graphite grades IG-110, NBG-18, NBG-17, PCEA, and 2114. Using a hierarchical Bayesian approach, multiple experimental data sources were combined to develop Gaussian process models for the properties. Using the Kennedy O'Hagan framework, the uncertainties due to inadequacies in the model and the inherent spread in the experimental data were quantified for three different models. These uncertainty-quantified models, with a model-form correction, were subsequently applied to a coupled-physics simulation of representative graphite components, revealing that the uncertainties have a large impact on the components' deformation.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Homomorphic Encryption for Machine Learning and Artificial Intelligence Applications

Third-party and expert analysis is a cost-effective solution for solving specialized problems or processing large datasets related to reactor structural health monitoring and nondestructive evaluation. However, when handling proprietary information, third-party and expert analysts pose a privacy risk. To address this challenge, Homomorphic Encryption (HE) permits arithmetic operations on encrypted data without exposing the underlying data. Implementations of Machine Learning (ML) and Artificial Intelligence (AI) algorithms using HE greatly enhances the capabilities of third-party analysts while maintaining a low security risk. This paper details current success in applying Principal Component Analysis (PCA) and Fully Connected Neural Networks (NN) using the Microsoft SEAL implementation of the popular CKKS Fully Homomorphic Encryption (FHE) algorithm. The MNIST Handwritten Dataset is analyzed as a proof-of-concept demonstration of the implementations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Fast and accurate calculation of EXAFS Debye-Waller factors in U⁢O2 using the dynamical matrix method

Theoretical modeling of bonding dynamics in metal oxides is required for predicting their thermal conductivity, catalytic activity, and mechanical properties. A primary challenge is the scarcity of experimental methods for validating theoretical predictions of these atomic-scale dynamics. This work presents a workflow that uses experimental extended x-ray absorption fine structure (EXAFS) data collected at high temperatures to validate an interatomic force field for uranium dioxide (UO2), an important model material. The validated force field is then used to drive computationally intensive molecular dynamics (MD) simulations and as input for the much faster dynamical matrix Debye-Waller (DMDW) method. The predicted values of the Debye-Waller factors from the DMDW calculations are in good agreement with those obtained from the MD simulations, with residual pair-specific differences attributable to quantum zero-point motion at low temperatures and lattice anharmonicity at high temperatures. We further show that theoretical EXAFS spectra constructed directly from DMDW-derived Debye-Waller factors reproduce the experimental data (at relatively low temperatures) with accuracy comparable to full MD-EXAFS, providing an additional validation of the choice of the potential. This study establishes a validated, rapid computational pathway for modeling bond dynamics, naturally incorporating quantum nuclear\\\\r\\\\nstatistics absent in classical simulations, which are essential for the mechanistic understanding of complex oxide materials.

58 GEOSCIENCES↗
DOE OSTI2024

2023 SRNL Aging and Lifetimes Report: Tritium Aging of Welded and Additively Manufactured Austenitic Stainless Steels

This report documents work performed in fiscal year 2023 at Savannah River National Laboratory (SRNL) collaborating with Sandia National Laboratories in support of the Aging and Lifetimes program. This work supports Gas Transfer Systems (GTS) design by measuring the mechanical behavior of structural materials used in GTS. Data on properties in relevant conditions are crucial for GTS lifetime assessments and predictions. To simulate relevant conditions, SRNL, in concert with the Savannah River Site, thermally pre-charges test specimens with tritium and stores them at -80°C to allow the tritium decay product, helium-3, to build up while limiting tritium diffusion. According to test plans based on how much helium-3 has accumulated, specimens are removed from storage and tested. Results from mechanical testing provide an empirical basis for GTS design as well as insight to how these structural materials degrade in a tritium environment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Hybrid physics-based and machine learning tools for materials assessment

In this work, we develop novel physics-based and machine learning computational techniques to predict fundamental properties of metallic systems that affect radiation damage behavior in reactor structural materials. Oftentimes, atomistic predictions of engineering alloys simplify chemical compositions to a single element to reduce computational cost and complexity, introducing large sources of uncertainty and potentially missing important behavior. In addition, engineering alloys such as SS 316 are particularly challenging to simulate with first principles methods because of the additional degrees of freedom introduced by magnetic natures of the constituent elements, and very little data of this type exists within the literature. These novel methods aim to improve the qualitative prediction of radiation damage in engineering alloys by more accurately simulating their compositions, both by accelerating the computations and by developing novel analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

AGR-5/6/7 Experiment Monitoring and Simulation Progress

Advanced Gas Reactor (AGR)--5/6/7 is the last of a series of AGR experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The test train contains five separate capsules that are independently controlled and monitored. Each capsule contains multiple 12.51 mm long compacts filled with low-enriched uranium carbide/oxide (UCO) TRISO fuel particles. The objectives of the AGR-5/6/7 experiment are to: 1. Irradiate reference-design fuel particles to support fuel qualification. 2. Establish operating margins for the fuel beyond normal operating conditions. 3. Provide irradiated fuel performance data and irradiated fuel samples for post-irradiation examination (PIE) and safety testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

AGR-5/6/7 Experiment Monitoring and Simulation Progress

Advanced Gas Reactor (AGR)--5/6/7 is the last of a series of AGR experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The test train contains five separate capsules that are independently controlled and monitored. Each capsule contains multiple 12.51 mm long compacts filled with low-enriched uranium carbide/oxide (UCO) TRISO fuel particles. The objectives of the AGR-5/6/7 experiment are to: 1. Irradiate reference-design fuel particles to support fuel qualification. 2. Establish operating margins for the fuel beyond normal operating conditions. 3. Provide irradiated fuel performance data and irradiated fuel samples for post-irradiation examination (PIE) and safety testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗