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At least 919 records · Page 51

Materials and Fuels Complex Operations Management Improvement Strategy for FY2022

The Materials and Fuels Complex (MFC) has experienced substantial growth in terms of staff, research, and production in recent years. MFC operational performance has effectively kept pace with this growth. However, to capture the continuous improvement actions needed to improve effectiveness and increase the efficiency of our management systems, a broad operations management strategy is necessary. The MFC Operations Management Improvement (OMI) Strategy is complementary to the MFC Five-Year Mission and Investment Strategies and the MFC Management Plan. The OMI strategy is structured to address the management systems outlined in the Nuclear Facility Management Standard Operations Model. Selected management systems are evaluated independently in chapters that describe the prior 5 years of performance improvement, a description of improvement actions for the MFC staff that directly perform within or contribute to the management system, process improvements, and any needed equipment improvements. Chapter selection is based on a management system’s need for improvement. In some cases, management systems may be combined in a single chapter. Additional chapters are added to address subject areas not formally described in the standard operations model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Materials and Fuels Complex Operations Management Improvement Strategy for Fiscal Year 2023

The Materials and Fuels Complex (MFC) has experienced substantial growth in terms of staff, research, and production in recent years. MFC operational performance has effectively kept pace with this growth. However, to capture the continuous improvement actions needed to improve effectiveness and increase the efficiency of our management systems, a broad operations management strategy is necessary. The MFC Operations Management Improvement (OMI) Strategy is complementary to the MFC Five-Year Mission and Investment Strategies and the MFC Management Plan. The OMI strategy is structured to address the management systems outlined in the Nuclear Facility Management Standard Operations Model. Selected management systems are evaluated independently in chapters that describe the prior 5 years of performance improvement, a description of improvement actions for the MFC staff that directly perform within or contribute to the management system, process improvements, and any needed equipment improvements. Chapter selection is based on a management system’s need for improvement. In some cases, management systems may be combined in a single chapter. Additional chapters are added to address subject areas not formally described in the standard operations model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

AI-ENABLED MONITORING OPTIONS TOWARDS SECURE MICROREACTOR DEPLOYMENT AND OPERATIONS

Global nuclear energy deployment scenarios suggest favorable economics for smaller, more versatile, and self-contained reactor technologies. Recognizing their key features as integrated, autonomous and either semi-remotely operated or fully remotely operated systems, microreactors are expected to be deployed in large numbers servicing off/micro-grids, many in geographically remote locations. Integrated nature of these systems as well as ease of their transportation as complete units, simplified installation and relocation/decommissioning challenge traditional continuity-of-knowledge practices used for conventional light water reactors where refueling is done onsite at designated times only replacing portions of their cores and only after their full commissioning for operations including completion of their containment building with security and safeguards measures in place. This effort is exploring AI (artificial intelligence)-enabled monitoring options that would be design agnostic and would assure secure unit deployment and operations. The principle is to maintain situational awareness via real-time evaluations of simultaneous and remotely transmitted monitoring data capturing key safeguards attributes including such characteristics as temperature, radiation, vibrational signals (inter alia), and others. The key principle is to provide reliable and resilient security options while maintaining simplified and economical deployment. The paper will review feasible options for AI-enabled solutions for such evaluations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Initial development of viscoplastic constitutive model of Alloy 800H in support of the use of inelastic analysis methods for ASME Section III, Division 5, Class A applications

This report describes the development of a preliminary inelastic constitutive model for the thermomechanical behavior of Alloy 800H. The objective is to develop a model suitable for incorporating into Nonmandatory Appendix Z to Section III, Division 5 of the ASME Boiler & Pressure Vessel Code, which provides guidance and reference constitutive models for the ASME design by inelastic analysis rules for Class A components. The report describes the process of collecting experimental data, developing a mathematical form for the model, and training the model against the test data. The initial version of the model captures most of the relevant material deformation mechanisms, including dynamic strain aging effects. However, further development of the model form will be required to develop a final model suitable for ASME use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Generation of the Thermal Scattering Law of Uranium Dioxide with Ab Initio Lattice Dynamics to Capture Crystal Binding Effects on Neutron Interactions

Scattering of thermal neutrons and Doppler broadening of epithermal neutron resonances in uranium and its compounds may be sensitive to crystal binding. The thermal scattering law (TSL) for uranium dioxide, which captures crystal binding effects, has been reevaluated for ENDF/B-VIII.0. Phonon spectra were generated using ab initio lattice dynamics for the paramagnetic phase and validated against experiment. Improved agreement with the Debye-Waller coefficient as a function of temperature is found relative to the spectrum used for the ENDF/B-VII.1 evaluation. The TSL was generated using the phonon expansion method within the NJOY nuclear data processing package and was found to be in reasonable agreement with inelastic neutron scattering measurements. The present evaluation predicts a reduction in the inelastic scattering cross section relative to ENDF/B-VII.1 and a total scattering cross section consistent with neutron transmission experiments

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Tale of Two Simulators—A Comparative Human-in-the-Loop Nuclear Power Plant Operations Study on Thermal Power Dispatch for Hydrogen Production

A study was designed for a reconfigurable, full-scale, full-scope nuclear power plant control room simulator to compare two different thermal power dispatch systems, on separate simulator platforms, demonstrating a TPD concept of operation. A TPD system can provide a desirable alternative revenue source for utilities but requires addressing new and unique operational issues. The selection of representative scenarios and the scenario-based experimental design are presented as key elements to capture evidence for validating the developed TPD concept of operations overcome these operational issues.

Ulrich, Thomas A.↗

Dynamic Human-in-the-Loop Simulated Nuclear Power Plant Thermal Dispatch System Demonstration and Evaluation Study

An Idaho National Laboratory research team performed a human-in-the-loop study with two formerly licensed retired operators to evaluate thermal power dispatch operations supported by the modified GSE Systems GPWR plant simulator. Virtual representations of the analog control panels were presented on touch-screen bays configured to mimic the control room layout in the newly renovated Human Systems Simulation Laboratory. The operators performed 15 scenarios covering normal evolutions to transition the plant from full turbine operation to joint turbine and thermal power dispatch operations in addition to transient response scenarios induced with simulated faults to evaluate the impact of thermal power dispatch system on operator and plant responses. A prototype human-system interface (HSI) was developed and displayed in tandem with the virtual analog panels to support the operators executing the procedurally drive evolutions and transient responses. An interdisciplinary team of operations experts, nuclear engineers, and human factors experts observed the operators performing the scenarios to evaluate the operations. Only a preliminary analysis of the results has been performed. The full analysis will be shared in a milestone report scheduled for release at the end of September; however, some high-level conclusions were readily available. Two high level findings for the system design were captured in the study. The manual control supported by the HSI to transition from standard operations to thermal power dispatch operation imposed a considerable amount of workload on the operators due to tedious manual valve manipulations and system monitoring required to verify their intended effect. An additional operator would be required in the control room to support the daily evolution. Automatic control for the transition was deemed a requirement for plant adoption without imposing additional staffing costs. The second finding was the necessity for an automatic thermal power dispatch system trip isolation function linked to a turbine and reactor trip signal. The operators completed scenarios with automatic isolation functionality and manually required actuation of the thermal power dispatch system. The operator response was sufficiently slower in the manual trip condition, such that operators were unable to manually actuate key post trip safety functions an indicate a degraded control capability that should be avoided. With an automatic trip signal little to no impact of the thermal power dispatch system was identified on the primary plant response and therefore the system could be readily and safely adopted. Together these two findings represent the need to support the adoption of thermal power dispatch capability into existing operations by leveraging automation to augment any additional operator tasking required to control and monitor an additional system beyond existing operations.

99 GENERAL AND MISCELLANEOUS↗

Thermal scattering law for structure-dependent-Doppler broadening in FLASSH

Traditional Doppler broadening methods assume that target nuclei velocities follow a Maxwell-Boltzmann distribution which inherently assumes that the atoms are a free gas or that their velocities are independent of each other. This approximation is reasonable at high target temperatures and high neutron energies. However, nuclei are not independent: the lattice temperature and chemical binding will define the atomic motion. The thermal scattering law (i.e., TSL or S(α,β)) is a material property which describes the chemical binding and temperature response in terms of available momentum and energy states. In the thermal energy range, this TSL will define the thermal scattering cross sections. In the resonance region, the TSL offers a first-principles description of the probability distribution function for the velocity of the target nuclei. Using the TSL in Doppler broadening captures the structure of the material consistently from the thermal range into the resonance cross sections. In this work, both traditional free-gas and precise TSL Doppler broadening methods for resonance cross section evaluation have been implemented within the Full Law Analysis Scattering System Hub (FLASSH). This framework provides a generalized formulation for evaluating low-lying resonance data and streamlines nuclear data processing methods. TSL data generated using ab initio lattice dynamics (AILD) can be used to broaden cross section libraries in ENDF format for high-fidelity input into reactor physics calculations. These capabilities are demonstrated for the lowest absorption resonances of {sup 238}U in UO{sub 2}, UC and UN. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Coupled Neutronics - Thermal-Hydraulics - Thermomechanics modeling of Molten Chloride Reactor

Molten Salt Reactors (MSRs) are innovative Generation-IV nuclear reactors known for their enhanced safety features, fuel economy, and fuel cycle advancements. However, designing and studying these reactors present unique safety and modeling challenges. The Department of Energy (DOE)'s Nuclear Energy Advanced Modeling and Simulation program addresses these challenges through the development of flexible multi-fidelity, multiphysics simulation tools. This study exemplifies NEAMS tools' capabilities by modeling a chloride-based micro-MSR: Griffin for neutronics simulations, Pronghorn for thermal-hydraulics simulations, and BISON for thermomechanics simulations. These tools are integrated into a comprehensive 3D multiphysics model, successfully capturing steady-state and transient reactor operations. A loss of flow accident is examined as an illustrative example of transient behavior. Additionally, this paper contributes to demonstrating the theoretical feasibility of micro-MSR concepts, which have received less attention compared to other designs. The subsequent sections provide a brief description of the MSR concept studied, an overview of the computational tools used, and present results for both steady-state operation and a loss of flow accident.

42 - ENGINEERING↗

Autonomous Navigation and Control of UGVs' in Nuclear Power Plants - 20381

The purpose of the husky A200 ground robot is to autonomously navigate through the places where it is very hazardous for human beings to reach and operate, like nuclear power plants, chemical industries. The aim is to navigate the ground robot autonomously with an Arm mounted on the robot along with the different sensors as camera, and Lidar. The autonomous motion of the robot is controlled by the controller which uses path planner for trajectory generation of the robot. The mission planner uses the current position of the husky A200, given the way points of the initial and the destination it would extract a best possible route based on the current events provided using GMapping. The global reference frame is used for planning the way points. Creating the appropriate path and the actions required to follow the path are given by the motion planner. The motion planner depends on the active sensor data such as obstacles, lanes, based on the sensor data feasible path is generated. Feasibility of the path is determined by the dynamics of the husky and a series of points generated with certain velocity and acceleration profile. The controller adjusts the lateral, longitudinal and yaw motion of the husky to command the behaviors. The kinematic model is developed for kinematic motion of the husky and the dynamic model is developed for transient and steady state characteristics. The images and other type of data captured by the camera are processed through the computational framework used to build machine learning models. TensorFlow will be used for deep learning and to identify and classify different objects around the husky. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Bayesian model mixing with multireference energy density functional

Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technology. To this day, however, all the theoretical models that can scale at the level of the chart of isotopes remain semiphenomenological. Because they are fitted locally, their predictive power can vary significantly; different versions of the same theory provide different predictions. Bayesian model mixing takes advantage of such imperfect models to build a local mixture of a set of models to make improved predictions. Earlier attempts to use Bayesian model mixing for mass table calculations relied on models treated at single-reference energy density functional level, which fail to capture some of the correlations caused by configuration mixing or the restoration of broken symmetries. In this study we have applied Bayesian model mixing techniques within a multireference energy density functional (MR-EDF) framework. We considered predictions of two-particle separation energies from particle number projection or angular momentum projection with four different energy density functionals—a total of eight different MR-EDF models. We used a hierarchical Bayesian stacking framework with a Dirichlet prior distribution over weights together with an inverse log-ratio transform to enable positive correlations between different models. We found that Bayesian model mixing provides significantly improved predictions compared to the participating models. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Laboratory Instrument Software Controlled Spread Spectrum Time Domain Reflectometry for Electrical Cable Testing

This research discusses development of a software-controlled laboratory instrument based spread spectrum time domain reflectometry system (SSTDR). This constitutes one task within PNNL’s Light Water Sustainability Program (LWRS) whose mission includes advancing nondestructive examination (NDE) techniques for off-line and on-line in-situ cable condition monitoring. In 2022, PNNL evaluated SSTDR for detection and characterization of a number of cable anomalies (Glass et al. 2022). The review included comparison of SSTDR to Frequency Domain Reflectometry (FDR) techniques which have enjoyed encouraging feedback and are starting to be used in nuclear power plants for periodic cable condition monitoring of cable systems as part of the plant’s overall cable aging management program. The FDR test introduces a broad-band chirp onto the cable at the cable end then listens for any reflection from a change of impedance along the cable caused by a damaged conductor or insulation, splices, contact with moisture, or other cable anomalies. The signal is captured in the frequency domain then transformed back to the time domain using an inverse Fourier transform (IFT). Based on the velocity of propagation, the impedance response signal is plotted against distance along the cable. Peak locations along the X-axis indicate the distance along the cable where a portion of the signal has been reflected back to the instrument as a result of a cable anomaly. The FDR test is considered the gold standard of reflectometry however it does require the cable to be de-energized to perform the test. The LIVEWIRE commercial SSTDR produces a similar plot to the FDR however all processing is in the time domain. A pseudo-random noise code (PN code) is input onto the cable conductor and the instrument listens for any reflected response from cable anomalies. The SSTDR processes the signal as an autocorrelation comparing the input PN code to any reflected signal detected. The autocorrelation analysis for thermal aging, water and water ingress detection, ground fault and phase-to-phase fault detection at various locations along the cable and with the cable attached and detached from a motor load, and on both energized and un-energized conditions were performed. These results were contrasted to Frequency Domain Reflectometry (FDR) measurements of the un-energized cable. Results were encouraging but indicated more work was warranted – particularly with the SSTDR, it seemed that the insulation damage would likely be better evaluated with multiple bandwidth cable tests particularly including larger bandwidths than were possible with the current commercial instrument. The commercial instrument’s bandwidth was set at 6, 12, 24, and 48MHz but note that SSTDR and FDR definitions of bandwidth trend similarly but are not the same. The FDR response could be more broadly adjusted, and the bandwidth of 100 to 500 MHz produced the best responses. FDR responses to anomalies were clearer than SSTDR responses and indications were that a broader bandwidth SSTDR may lead to improved SSTDR detection capability. This project used a laboratory instrument based SSTDR (primarily using an Arbitrary Waveform Generator (AWG) and a digital oscilloscope plus Python in-house software) that allowed software adjustment of the SSTDR bandwidth, window functions applied to the exciting Pseudo-random Noise (PN) code plus and other aspects of the SSTDR signal processing. Hereafter, this will be referred to as the PNNL SSTDR. Evaluating specific performance of the PNNL SSTDR is left to a separate report. This report documents hardware and software development to produce the SSTDR cable test system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗

Design and characterization of hierarchical aluminosilicate composite materials for Cs entrapment: Adsorption efficiency tied to microstructure

The growing quantity of nuclear waste and the serious threats to the environment challenge researchers to innovate and target new waste form technologies. In the past decades, considerable efforts have been devoted to developing highly selective sorbents followed by safe disposal with the assurance of chemical stability and robust retention performance. Zeolite-containing geopolymers are regarded as a possible 2-in-1 material able to both capture and sequester elements such as Cs in bed fixed column application perspective. Here, these composites show promise for combining extraction properties of zeolite powder due to its crystalline structure (high capacity and selective adsorption), with the tunable microstructure and the shaping feasibility of the geopolymer binder. For the development of materials devoted to Cs immobilization, porous zeolite/geopolymer composites were prepared by dispersing NaY zeolite particles in a geopolymer binder. The influence of the structural properties of such composites on their ability to entrap a large amount of Cs by an ionic exchange process was notably studied. Composites' compositions, porosities, morphologies and crystallinity were analyzed by scanning electron microscopy coupled with energy dispersive x-ray spectroscopy (SEM-EDX), x-ray diffraction analysis (XRD) and nitrogen adsorption/desorption studies. Experimental Cs sorption in batch mode was used to follow the ionic exchange phenomenon in these materials. Along with 5 wt% amount of zeolite in geopolymer improves the Cs adsorption performance offering multiple new adsorption sites. Additionally, the geopolymer mesopores are beneficial facilitating the access of Cs and its role as a binder is advantageous to tailor granular hierarchical structure for safer industrial application.

36 MATERIALS SCIENCE↗

A matrix completion algorithm for efficient calculation of quantum and variational effects in chemical reactions

This work examines the viability of matrix completion methods as cost-effective alternatives to full nuclear Hessians for calculating quantum and variational effects in chemical reactions. The harmonic variety-based matrix completion (HVMC) algorithm, developed in a previous study (https://doi.org/10.1063/5.0018326), exploits the low-rank character of the polynomial expansion of potential energy to recover, using a small sample, vibrational frequencies (square roots of nuclear Hessian eigenvalues) constituting the reaction path. Furthermore, these frequencies are essential for calculating rate coefficients using variational transition state theory with multidimensional tunneling (VTST-MT). HVMC performance is examined for four SN2 reactions and five hydrogen transfer reactions, with each H-transfer reaction consisting of at least one vibrational mode strongly coupled to the reaction coordinate. HVMC is robust and captures zero-point energies, vibrational free energies, zero-curvature tunneling, and adiabatic ground state and free energy barriers as well as their positions on the reaction coordinate. For medium to large reactions involving H-transfer, with the exception of the most complex Ir catalysis system, less than 35% of total eigenvalue information is necessary for accurate recovery of key VTST-MT observables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ab initio translationally invariant nucleon-nucleus optical potentials

We combine the ab initio symmetry-adapted no-core shell model (SA-NCSM) with the single-particle Green's function approach to construct optical potentials rooted in first principles. Specifically, we show that total cross sections and phase shifts for neutron elastic scattering from a 4 He target with projectile energies between 0.5 and 10 MeV closely reproduce the experiment. In addition, we discuss an important new development that resolves a long-standing issue with spurious center-of-mass motion in the Green's function formalism for many-body approaches. Furthermore, the new development opens a path for first-principle predictions of cross sections for elastic scattering of single-nucleon projectiles, nucleon capture, and deuteron breakup reactions, feasible for a broad range of open-shell spherical and deformed nuclei in the SA-NCSM approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗