Search NASA⌕ Search

SEARCH · Search NASA

Results for “Nuclear Data Evaluation Methods”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Explainable Artificial Intelligence Technology for Predictive Maintenance

The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Automated Detection of Alkali-silica Reaction in Concrete using Linear Array Ultrasound Data

Alkali-silica reaction (ASR) is a chemical reaction in either concrete or mortar between hydroxyl ions of the alkalis (sodium and potassium) from hydraulic cement (or other sources), and certain siliceous minerals present in some aggregates. The reaction product, an alkali-silica gel, is hygroscopic having a tendency to absorb water and swell, which under certain circumstances, leads to abnormal expansion and cracking of the concrete. This phenomenon affects the durability and performance of concrete structures severely since it can cause significant loss of mechanical properties. Developing reliable methods and tools that can evaluate the degree of the ASR damage in existing structures, so that informed decisions can be made toward mitigating ASR progression and damage, is important to the long term operation of nuclear power plants especially if licenses are extended beyond 60 years. This paper examines an automated method of determining the extent of ASR damage in fabricated concrete specimens.

Santos-Villalobos, Hector J↗
DOE OSTI2016

SURROGATE MODEL DEVELOPMENT AND VALIDATION FOR RELIABILITY ANALYSIS OF REACTOR PRESSURE VESSELS

In nuclear light water reactors (LWRs), the reactor coolant, core and shroud are contained within a massive, thick walled steel vessel known as a reactor pressure vessel (RPV). Given the tremendous size of these structures, RPVs typically contain a large population of pre-existing flaws introduced in the manufacturing process. After many years of operation, irradiation-induced embrittlement makes these vessels increasingly susceptible to fracture initiation at the locations of the pre-existing flaws. Because of the uncertainty in the loading conditions, flaw characteristics and material properties, probabilistic methods are widely accepted and used in assessing RPV integrity. The Fracture Analysis of Vessels – Oak Ridge (FAVOR) computer program developed by researchers at Oak Ridge National Laboratory is widely used for this purpose. This program can be used in order to perform deterministic and probabilistic risk-informed analyses of the structural integrity of an RPV subjected to a range of thermal-hydraulic events. FAVOR uses a one-dimensional representation of the global response of the RPV, which is appropriate for the beltline region, which experiences the most embrittlement, and employs an influence coefficient technique to rapidly compute stress intensity factors for axis-aligned surface-breaking flaws. The Grizzly code is currently under development at Idaho National Laboratory (INL) to be used as a general multiphysics simulation tool to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled RPVs. Grizzly can be used to model the thermo-mechanical response of an RPV under transient conditions observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local 3D models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtain stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. To use Grizzly for probabilistic analysis, it is necessary to have a way to rapidly evaluate stress intensity factors. To accomplish this goal, a reduced order model (ROM) has been developed to efficiently represent the behavior of a detailed 3D Grizzly model used to calculate fracture parameters. This approach uses the stress intensity factor influence coefficient method that has been used with great success in FAVOR. Instead of interpolating between tabulated solutions, as FAVOR does, the ROM approach uses a response surface methodology to compute fracture solutions based on a sampled set of results used to train the ROM. The main advantages of this approach are that the process of generating the training data can be fully automated, and the procedure can be readily used to consider more general flaw configurations. This paper demonstrates the procedure used to generate a ROM to rapidly compute stress intensity factors for axis-aligned flaws. The results from this procedure are in good agreement with those produced using the traditional influence coefficient interpolation procedure, which gives confidence in this method. This paves the way for applying this procedure for more general flaw configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Sulfur Pellets Responses to a Bare and Steel Reflected Pulse of the Oak Ridge National Laboratory Health Physics Research Reactor

The experiments analyzed in this report were conducted at the Health Physics Research Reactor (HPRR), also known as the $\textit{Fast Burst Reactor}$. The reactor was designed and built at Oak Ridge National Laboratory (ORNL) in 1961. The HPRR was an unmoderated, unshielded fast reactor that used highly enriched uranium and molybdenum alloy as fuel. The reactor was initially sent to the Nevada Test Site in 1962, where it was used to evaluate radiation doses received as a result of the Hiroshima and Nagasaki bombings during World War II. A few years later, the reactor was sent back to ORNL to be part of the Dosimetry Application Research (DOSAR) facility shown in Figure 1, which included a reactor building shown on the left (west) of the picture and a control and laboratory building in the upper right corner (northeast). The critical assembly was used for numerous technical studies, including systems calibration, dosimetry, radiobiology of plants and animals, testing of radiation alarms, as well as teaching and training in radiation dosimetry and nuclear engineering. Between 1963 and 1987, the HPRR was operated for thousands of hours, achieving criticality close to 10,000 times and motivating many publications. The HPRR was decommissioned in 1987. The goal of this effort was to use historical data from operation of the HPRR to create a criticality accident alarm system (CAAS) benchmark to be included in the $\textit{International Handbook of Evaluated Criticality Safety Benchmark Experiments}$ (ICSBEP Handbook). A thorough inspection was performed of all available documentation and information available. The most promising experiments that were selected for evaluation were those described in the 1987 ORNL report entitled $\textit{Health Physics Research Reactor Reference Dosimetry}$, ORNL-6240. The report includes reference dosimetry results of the shielded and unshielded configurations of the HPRR after burst operations. Because of changes to the reactor positioning and storage systems that were made in 1985, the previous dosimetry reports became obsolete, and the newly designed experiments were needed to create the HPRR’s adjusted dosimetry data. The various results reported in ORNL-6240 include reference doses and dose equivalents from different conventions at different distances and elevations as determined using the detected neutron fluence and conversion factors. The HPRR neutron fluence was obtained through different methods, including sulfur pellet analysis and threshold detector unit data. Information about the HPRR spectrum was also obtained through Bonner sphere measurements. This benchmark is focused on a part of the measured sulfur fluences reported in Appendix H of ORNL-6240. Standard commercial sulfur pellets were placed at different distances from the HPRR centerline during burst operation and were activated due to the 32 S(n,p) 32 P reaction. The resulting 32 P activity was then measured and the information about the corresponding sulfur fluence and/or neutron dose could be extracted. Many of those measurements have 7 been performed with the HPRR in its bare configuration or with different shields (combinations of Lucite, concrete, steel). All the necessary, precise information about material and/or dimensions of the different shields was not found, so it was decided to focus only on the unshielded and steel-shielded configurations to minimize the benchmark uncertainty. A total of 31 cases (24 unshielded and 7 shielded cases at different positions) of sulfur fluence were selected before evaluation to develop the benchmark.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Extended Burnup Credit for BWR Spent Nuclear Fuel in Storage and Transportation Systems

[Full Text] Oak Ridge National Laboratory and the United States Nuclear Regulatory Commission have initiated a multiyear project to investigate the application of burnup credit (BUC) for boiling-water reactor (BWR) fuel in storage and transportation casks. This project includes two phases. The first phase investigates the applicability of peak reactivity methods currently used for spent fuel pools to spent fuel storage and transportation casks and the validation of reactivity (k eff ) calculations and depleted fuel compositions. The second phase focuses on extending BUC beyond peak reactivity. This paper documents work performed to date, investigating some aspects of extended BUC, and it also describes the plan to complete the evaluations. The technical basis for application of peak reactivity methods to BWR fuel in storage and transportation systems is presented in a companion paper. Two reactor operating parameters are being evaluated to establish an adequate basis for extended BWR BUC, including investigation of the axial void profile effect and the effect of control blade utilization during operation. A detailed analysis of core simulator data for one cycle of an operating BWR plant was performed to determine the range of void profiles and the variability of the profile experienced during irradiation. While a single cycle does not provide complete data, the data obtained are sufficient to use to determine the primary effects and identify conservative modeling approaches. Using data resulting from a single cycle, the axial void profile is studied by first determining the temporal fidelity necessary in depletion modeling, and then using multiple void profiles to examine the effect of the void profile on cask reactivity. The results of these studies are being used to develop recommendations for conservatively modeling the void profile effects for BWR depletion calculations. The second operational parameter studied is control blade exposure. Control blades are inserted in various locations and at varying degrees during BWR operation based on the reload design. The presence of control blades during depletion hardens the neutron spectrum locally due to both moderator displacement and introduction of a thermal neutron absorber. The reactivity impact of control blade presence is investigated herein, as well as the effect of multiple (continuous and intermittent) exposure periods. The coupled effects of control blade presence on power density, void profile, or burnup profile have not been considered to date but will be addressed in future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Commissioning of Robotic Inspection and Automated Analysis System for Assay of Gas Diffusion Piping - 19500

Robotic, in-pipe, nondestructive assay (NDA) is a revolutionary and important means for measuring, analyzing, and reporting radioactive holdup deposits in enrichment piping. This innovation promises vast advantages for efficiency, safety, and cost savings. Payoff, however, lies in utilization much more than innovation. Crossing that threshold from a technical capability to an everyday tool occurs only after rigorous commissioning, adoption, and infusion. This must meet the highest standard, and there can be no compromise. Certification of a new NDA technology must meet the highest standards for quality, safety, and efficacy. Prior to this work, there was no precedent of procedure and method for certification of a robotic methodology for this purpose. The best of robotics had not certified NDA. The best of NDA had not certified robotics. Hence, a great deal of discovery, resourcefulness, and collaboration contributed to this success. This paper chronicles the first-of-kind chartering, co-development, testing, documentation, and site integration that certified this trailblazing in-pipe, robotic NDA. Commissioning had to demonstrate and certify end-to-end NDA automation from robot traversal to computer analysis to report generation of contaminated process piping at the Portsmouth, Ohio gaseous diffusion facility. This was a rigorous campaign of tests, evaluations, and documentation. Highlights included multiple tests in four elevated pipes exercised the gamut of NDA and robotic capabilities. Each of the four test pipes presented a unique loading of U-235. The tests demonstrated operations in both 30- inch and 42-inch diameter pipes with varying lengths and terminated by a variety of valves and fittings. Tests in a fifth pipe at floor level demonstrated deployment and applicability for pipes at this ground height and robot recognition of another fitting type. All operations, calibration, deployment, auto-reporting, and analysis were handled by Portsmouth site personnel. These tests concluded a series of component-level acceptance tests which certified all constituent technologies and operational features. Test metrics included comparison of reported to ground truth results and assessment of data quality from quality assurance and replicate measurement comparison. Beyond the radiometry associated with any NDA method, this unique commissioning path exercised and evaluated all the robotic features that are intrinsic to automation. These include odometry, geometric modeling, autonomy, remote launch and recovery, and end-to-end data flow. Each of these required verification and certification. These evaluations were first-of-kind for the decommissioning community, requiring innovation and resourcefulness in their own right. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

SU-E-T-117: Analysis of the ArcCHECK Dosimetry Gamma Failure Using the 3DVH System

Purpose: To evaluate gamma analysis failure for the VMAT patient specific QA using ArcCHECK cylindrical phantom. The 3DVH system(Sun Nuclear, FL) was used to analyze the dose difference statistic between measured dose and treatment planning system calculated dose. Methods: Four case of gamma analysis failure were selected retrospectively. Our institution gamma analysis indexes were absolute dose, 3%/3mm and 90%pass rate in the ArcCHECK dosimetry. The collapsed cone convolution superposition (CCCS) dose calculation algorithm for VMAT was used. Dose delivery was performed with Elekta Agility. The A1SL(standard imaging, WI) and cavity plug were used for point dose measurement. Delivery QA plans and images were used for 3DVH Reference data instead of patient plan and image. The measured data of ‘.txt’ file was used for comparison at diodes to acquire a global dose level. The,.acml’ file was used for AC-PDP and to calculated point dose. Results: The global dose of 3DVH was calculated as 1.10 Gy, 1.13, 1.01 and 0.2 Gy respectively. The global dose of 0.2 Gy case was induced by distance discrepancy. The TPS calculated point dose of was 2.33 Gy to 2.77 Gy and 3DVH calculated dose was 2.33 Gy to 2.68 Gy. The maximum dose differences were −2.83% and −3.1% for TPS vs. measured dose and TPS vs. 3DVH calculated respectively in the same case. The difference between measured and 3DVH was 0.1% in that case. The 3DVH gamma pass rate was 98% to 99.7%. Conclusion: We found the TPS calculation error by 3DVH calculation using ArcCHECK measured dose. It seemed that our CCCS algorithm RTP system over estimated at the central region and underestimated scattering at the peripheral diode detector point. The relative gamma analysis and point dose measurement would be recommended for VMAT DQA in the gamma failure case of ArcCHECK dosimetry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Analysis of Alternatives for Dismantling of the Equipment in Building 117/1 at Ignalina NPP - 13278

Ignalina NPP was operating two RBMK-1500 reactors which are under decommissioning now. In this paper dismantling alternatives of the equipment in Building 117/1 are analyzed. After situation analysis and collection of the primary information related to components' physical and radiological characteristics, location and other data, two different alternatives for dismantling of the equipment are formulated - the first (A1), when major components (vessels and pipes of Emergency Core Cooling System - ECCS) are segmented/halved in situ using flame cutting (oxy-acetylene) and the second one (A2), when these components are segmented/halved at the workshop using CAMC (Contact Arc Metal Cutting) technique. To select the preferable alternative MCDA method - AHP (Analytic Hierarchy Process) is applied. Hierarchical list of decision criteria, necessary for assessment of alternatives performance, are formulated. Quantitative decision criteria values for these alternatives are calculated using software DECRAD, which was developed by Lithuanian Energy Institute Nuclear engineering laboratory. While qualitative decision criteria are evaluated using expert judgment. Analysis results show that alternative A1 is better than alternative A2. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Lidar Mapping and Surveillance of Nuclear Infrastructure

Wear is unavoidable, whether it occurs in a nuclear facility or abridge on the highway its detection is crucial to preventing the failure of a system. While tools capable of detecting localized damage exist, industry lacks methods to evaluate the health of larger infrastructure. Routine inspection of nuclear facilities must be undertaken to ensure the safety of personnel and proper containment of nuclear materials. Most systems in a nuclear facility are designated as radioactive and confined spaces. To constantly monitor such systems in person would be hazardous but with a remote inspection tool it can be done in a safer and easier way. Lidar: Operates by emitting a laser pulse and looking for the reflected light. Allows user to gain 3D information of the environment. Project Objective: To develop an inspection tool for evaluating the health of large scale infrastructure using Lidar and machine learning. Autonomous Platform + Lidar + Data Fusion + Big Data. Use SLAM to build a 2D map of the environment. Point cloud created by transforming the points between reference frames. Point cloud to Surface: Inherent representation of surface geometry; Difficult to process with conventional techniques. Point cloud to Image: Easily processed by conventional machine learning algorithms. The quantity of data generated will necessitate a big data framework to manage the data for processing. Additional Sensors: Detecting the temperature (a) chemical makeup (b) and radiation emission (c) of a surface could assist in detecting problems. Human inspection can detect irregularities in both physical objects and their point-cloud representations. This is a good indication that mapping nuclear sites using Lidar will provide qualitative insight into the health of the facility. If deep learning can be used to automatically identify problem areas then the completed tool could become an invaluable asset.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

A Burnup Credit Approach for Margin Estimation of Loaded Boiling Water Reactor Canisters in UNF-ST&DARDS

This paper discusses the modeling approach applied in the Used Nuclear Fuel Storage, Transportation, & Disposal Analysis Resource and Data System (UNF-ST&DARDS) to take credit for the reduced reactivity associated with the burnup of boiling water reactor (BWR) fuel for canister-specific as loaded criticality analysis. Burnup credit is routinely used for the analysis of pressurized water reactor (PWR) spent nuclear fuel (SNF) storage (wet), transportation, and disposal. The fresh fuel assumption has historically been applied to BWR SNF criticality analyses for dry storage and transportation, and the peak reactivity method of burnup credit has been applied to pool storage. The fresh fuel assumption ignores the credit for gadolinium burnable absorbers in BWR fuel, as well as the burnup of the fuel, and is therefore conservative. This work employs the framework traditionally used for PWR burnup credit analyses and applies available data and recently published regulatory guidance to justify a new approach to model the as-loaded burnup and enrichment of SNF assemblies in currently loaded dry casks. The following features of this criticality analysis approach are presented in this paper: (1) selection of axial burnup profiles for BWR fuel from publicly available sources using methods derived from recently published research, (2) justification of the selected axial burnup profiles as relevant to all types of BWR fuel, (3) justification for modeling the fuel assemblies with a uniform axial and radial enrichment, and (4) justification for modeling the axial void profile and control blade insertion during depletion. This analysis approach was used to evaluate 153 already-loaded BWR casks at 8 sites as a function of time in UNF ST&DARDS. Finally, the results of the as-loaded criticality safety margin assessments are presented. The results show the k eff calculated for storage and transportation cases range from 0.71 to 0.83, and the eigenvalues calculated for the disposal cases range from 0.85 to 1.03, though the highest cases are dominated by very limiting hypothetical damaged fuel assumptions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Studying fuel failure behaviour with a micromechanical approach

Under Loss Of Coolant Accident (LOCA) conditions in light water reactors, the temperature evolution within the fuel pellets combined with a reduction of the cladding confinement can lead to fuel fragmentation. This work focuses on the pellet rim, where bubbles density increases owing to a higher irradiation level. This area, called 'High Burn-up Structure' (HBS), has a specific behaviour due to a microstructure reorganization composed of small grains about 100 nm compared to 10 μm for initial UO{sub 2} fuel. The aim of this study is to define a macroscopic fragmentation model based on a micro mechanical approach to have a better understanding of the fuel mechanical behaviour at lower scale: size and volume fraction of fragments. This paper introduces a stepwise micromechanical method: firstly, we detail how to model the HBS microstructure including pressurized porosities, based on experimental or numerical data and define a Representative Volume Element (RVE). Then we use 3D full field computations in order to determine crack snapshot. Elastic computations are performed to find the bubbles pressure level which is required to reach the cracks initiation threshold. Then nonlinear computations, using a failure local behavior law, are conducted to identify the failure snapshot. The results of these nonlinear computations will be used as an input data of the homogenization ('macroscopic') model. First computations with Full-Fields FEM method give promising results at local scale. Nevertheless, material parameters need to be refined as their experimental values are not perfectly defined yet, leaving an uncertainty in the model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Reassessing the Origins and Contemporary Relevance of ck Acceptability Parameters: Evolving Perspectives on Similarity

“Sensitivity and Uncertainty Analyses Applied to Criticality Safety Validation,” introduces sensitivity and uncertainty methods to address challenges in defining and extending areas of applicability for criticality safety validation. These areas are traditionally defined by the bounds or limits on key parameters, but establishing valid ranges and managing complex parameter variations remain challenging. NUREG/CR-6655 introduces ck and other integral indices, as well as concepts such as the completeness of benchmark coverage, to better quantify system similarities. The work proposed herein seeks to evaluate these foundational concepts to ensure that the bounds remain effective in guiding the assessment of similarity and applicability in modern applications. The concept of completeness, along with other parameters envisioned within the framework, serves as an example of the foundational ideas that have been established, though their effectiveness in practice may not be fully understood. Advancements in scripting tools, coupled with the speed and efficiency of modern computing and statistical models, now allow for faster and more thorough assessments than previously possible. These advancements also enable the identification of trends within the data, which could provide additional insight into system behavior and further broaden the scope of previously performed benchmarks. By leveraging these capabilities, we will revisit and expand the scope of these foundational methods to determine whether the necessary elements for robust similarity evaluation are already embedded, partially realized, or remain untapped.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Robust regression on noisy data for fusion scaling laws

We introduce the method of geodesic least squares (GLS) regression for estimating fusion scaling laws. Based on straightforward principles, the method is easily implemented, yet it clearly outperforms established regression techniques, particularly in cases of significant uncertainty on both the response and predictor variables. We apply GLS for estimating the scaling of the L-H power threshold, resulting in estimates for ITER that are somewhat higher than predicted earlier.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Effects of Chlorine Capture and a Proposed Density Law on the Reactivity of Plutonium Solution Systems

During fissionable material processing, all normal and credible abnormal conditions must remain safely subcritical. Nuclear Criticality Safety (NCS) uses a number of methods to determine subcriticality, one of which is the use of neutron transport codes such as MCNP6. In order to create models for use with MCNP6, both the geometry and materials in fissionable material processes must be known, or assumptions must be made and quantified for the impact to bias. One of the systems with a significant amount of bias due to material modeling assumptions is in the area of aqueous plutonium processing. These solutions are typically plutonium nitrate solutions or plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution and there is no current predictive capability approved for use at Los Alamos National Laboratory (LANL) for modeling them. This research is currently underway to fill the gap and develop an algorithm for use with MCNP6 to model the density of plutonium chloride solutions. The method is to be validated with experimental data for density, and also validated with critical experiments using MCNP6. Note that the Chlorine Worth Study (CWS) was performed in December 2021 to help bridge the gap in chlorine data for critical experiments, and is currently awaiting International Criticality Safety Benchmark Evaluation Project (ICSBEP) review. This study was performed by LANL at the National Criticality Experiments Research Center (NCERC) at the Nevada National Security Site (NNSS). Additional information regarding this experiment may currently be found in LA-UR- 22-29180. Additionally, the Chemistry-Actinide Analytical Chemistry (C-AAC) at LANL has performed a number of solution density measurements for PuCl 3 -HC 1 -H 2 O, allowing for such data be used to create a semi-empirical density via the Pitzer method. The published dataset for the measurements is documented in LA-UR-22-25454. This method has already been tested successfully for aqueous plutonium nitrate solutions in SCALE. Current solution density measurements exist of plutonium concentrations of 0-~142g/L, all at 2M HC1, at temperatures 20-40°C. Additional data was taken for HC1-corrected density values, which essentially mimics the data for a pure PuCl x -water solution. The calculations in this report aim to support the current research by demonstrating the difference in system reactivity for the current modeling method when compared to the new proposed modeling with a density law implementation, which is being written as a Python tool to be used with MCNP6.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

A burnup credit approach for margin estimation of loaded boiling water reactor canisters in UNF-ST-DARDS

This paper discusses the modeling approach applied in the Used Nuclear Fuel Storage, Transportation, and Disposal Analysis Resource and Data System (UNF-ST-DARDS) to take credit for the reduced reactivity associated with the burnup of boiling water reactor (BWR) fuel for canister-specific as-loaded criticality analysis. Burnup credit is routinely used for the analysis of pressurized water reactor (PWR) spent nuclear fuel (SNF) storage (wet), transportation, and disposal. The fresh fuel assumption has historically been applied to BWR SNF criticality analyses for dry storage and transportation, and the peak reactivity method of burnup credit has been applied to pool storage. The fresh fuel assumption ignores the credit for gadolinium burnable absorbers in BWR fuel, as well as the burnup of the fuel, and is therefore conservative. This work employs the framework traditionally used for PWR burnup credit analyses and applies available data and recently published regulatory guidance to justify a new approach to model the as-loaded burnup and enrichment of SNF assemblies in currently loaded dry casks. The following features of this criticality analysis approach are presented in this paper: (1- selection of axial burnup profiles for BWR fuel from publicly available sources using methods derived from recently published research, (2- justification of the selected axial burnup profiles as relevant to all types of BWR fuel, (3- justification for modeling the fuel assemblies with a uniform axial and radial enrichment, and (4- justification for modeling the axial void profile and control blade insertion during depletion. This analysis approach was used to evaluate 153 already-loaded BWR casks at 8 sites as a function of time in UNF-ST-DARDS. Finally, the results of the as-loaded criticality safety margin assessments are presented. The results show the k{sub eff} calculated for storage and transportation cases range from 0.71 to 0.83, and the eigenvalues calculated for the disposal cases range from 0.85 to 1.03, though the highest cases are dominated by very limiting hypothetical damaged fuel assumptions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Physics-Infused AI/ML Based Digital-Twin Framework for Flow-Induced-Vibration Damage Prediction in a Nuclear Reactor Heat Exchanger

This report summarizes some of the ongoing work related to the development of an expert-elicitation-digital-twin framework for real time damage state prediction in heat exchanger components of a nuclear reactor. The framework is targeted towards predicting damage associated with coupled low cycle fatigue (associated with regular heat-up, cool-down and power operation transients) and high cycle fatigue (associated with flow induced vibration transients). The overall framework will be based on a NoSQL based database, physics-infused-geometry-dependent virtual-sensor data, different AI/ML techniques-based data-driven-predictive-model applications (Apps) and real-time plant sensor measurements available through few existing sensors. Towards this overall goal, this report updates some of the ongoing work, such as on implementation of a NoSQL Database (such as MongoDB), FE based heat transfer analysis of a heat exchanger (e.g. of a PWR steam generator) for generating geometry-dependent virtual sensor data and evaluation of various AI/ML models such as based on multivariate linear regression, ensembled decision-tree based Random-Forest and Gradient-Boosting regression and high-dimensional-kernel-function-transformation based Support-Vector-Machine regression models. The AI/ML models were evaluated for predicting multi-time-series thermal states at thousands of 3D point-clouds

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Tritium Specific Adsorption Simulation Utilizing the OSPREY Model

During the processing of used nuclear fuel, volatile radionuclides will be discharged to the atmosphere if no recovery processes are in place to limit their release. The volatile radionuclides of concern are 3 H, 14 C, 85 Kr, and 129 I. Methods are being developed, via adsorption and absorption unit operations, to capture these radionuclides. It is necessary to model these unit operations to aid in the evaluation of technologies and in the future development of an advanced used nuclear fuel processing plant. A collaboration between Fuel Cycle Research and Development Offgas Sigma Team member INL and a NEUP grant including ORNL, Syracuse University, and Georgia Institute of Technology has been formed to develop off gas models and support off gas research. This report is discusses the development of a tritium specific adsorption model. Using the OSPREY model and integrating it with a fundamental level isotherm model developed under and experimental data provided by the NEUP grant, the tritium specific adsorption model was developed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Use of Percutaneous Aspiration Thrombectomy vs. Anticoagulation Therapy to Treat Acute Iliofemoral Venous Thrombosis: 1-year Follow-up Results of a Randomised, Clinical Trial

PurposeThe purpose of this study was to compare the efficacy of percutaneous aspiration thrombectomy (PAT) followed by standard anticoagulant therapy, with anticoagulation therapy alone, for the treatment of acute proximal lower extremity deep vein thrombosis.MethodsIn this randomised, prospective study, 42 patients with acute proximal iliofemoral deep vein thrombosis documented via Doppler ultrasound examination, were separated into an interventional treatment group (16 males, 5 females, average age 51 years) and a medical treatment group (13 males, 8 females, average age 59 years). In the interventional group, PAT with large-lumen 9-F diameter catheterisation was applied, after initiation of standard anticoagulant therapy. Balloon angioplasty (n 19) and stent implementation (n: 14) were used to treat patients with residual stenosis (>50 %) after PAT. Prophylactic IVC filters were placed in two patients. The thrombus clearance status of the venous system was evaluated by venography. In both the medical and interventional groups, venous patency rates and clinical symptom scores were evaluated at months 1, 3, and 12 after treatment.ResultsDeep venous systems became totally cleared of thrombi in 12 patients treated with PAT. The venous patency rates in month 12 were 57.1 and 4.76 % in the interventional and medical treatment groups, respectively. A statistically significant improvement was observed in clinical symptom scores of the interventional group (PAT) with or without stenting (4.23 ± 0.51 before treatment; 0.81 ± 0.92 at month 12) compared with the medical treatment group (4.00 ± 0.63 before treatment; 2.43 ± 0.67 at month 12). During follow-up, four patients in the medical treatment and one in the interventional group developed pulmonary embolisms.ConclusionsFor treatment of acute deep vein thrombosis, PAT with or without stenting is superior to anticoagulant therapy alone in terms of both ensuring venous patency and improving clinical symptoms. PAT is a safe, inexpensive, and easily performed method of endovascular treatment with a low rate of major complications. Our present findings and literature data suggest that PAT can be used as first-line treatment in proximal deep vein thrombosis patients, especially when thrombolytic treatment is contraindicated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗