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At least 523 records · Page 29

Subsurface Noble Gas Sampling Manual

The intent of this document is to provide information about best available approaches for performing subsurface soil gas sampling during an On Site Inspection or OSI. This information is based on field sampling experiments, computer simulations and data from the NA-22 Noble Gas Signature Experiment Test Bed at the Nevada Nuclear Security Site (NNSS). The approaches should optimize the gas concentration from the subsurface cavity or chimney regime while simultaneously minimizing the potential for atmospheric radioxenon and near-surface Argon-37 contamination. Where possible, we quantitatively assess differences in sampling practices for the same sets of environmental conditions. We recognize that all sampling scenarios cannot be addressed. However, if this document helps to inform the intuition of the reader about addressing the challenges resulting from the inevitable deviations from the scenario assumed here, it will have achieved its goal.

58 GEOSCIENCES↗

Sensitivity and uncertainty analysis applied to the JHR reactivity prediction

The on-going AMMON program in EOLE reactor at CEA Cadarache (France) provides experimental results to qualify the HORUS-3D/N neutronics calculation scheme used for the design and safety studies of the new Material Testing Jules Horowitz Reactor (JHR). This paper presents the determination of technological and nuclear data uncertainties on the core reactivity and the propagation of the latter from the AMMON experiment to JHR. The technological uncertainty propagation was performed with a direct perturbation methodology using the 3D French stochastic code TRIPOLI4 and a statistical methodology using the 2D French deterministic code APOLLO2-MOC which leads to a value of 289 pcm (1{sigma}). The Nuclear Data uncertainty propagation relies on a sensitivity study on the main isotopes and the use of a retroactive marginalization method applied to the JEFF 3.1.1 {sup 27}Al evaluation in order to obtain a realistic multi-group covariance matrix associated with the considered evaluation. This nuclear data uncertainty propagation leads to a K{sub eff} uncertainty of 624 pcm for the JHR core and 684 pcm for the AMMON reference configuration core. Finally, transposition and reduction of the prior uncertainty were made using the Representativity method which demonstrates the similarity of the AMMON experiment with JHR (the representativity factor is 0.95). The final impact of JEFF 3.1.1 nuclear data on the Begin Of Life (BOL) JHR reactivity calculated by the HORUS-3D/N V4.0 is a bias of +216 pcm with an associated posterior uncertainty of 304 pcm (1{sigma}). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DATA QUALITY OBJECTIVES FOR SELECTING WASTE SAMPLES FOR BENCH-SCALE REFORMER TREATABILITY STUDIES

This document describes the data quality objectives to select archived samples located at the 222-S Laboratory for Bench-Scale Reforming testing. The type, quantity, and quality of the data required to select the samples for Fluid Bed Steam Reformer testing are discussed. In order to maximize the efficiency and minimize the time to treat Hanford tank waste in the Waste Treatment and Immobilization Plant, additional treatment processes may be required. One of the potential treatment processes is the fluidized bed steam reformer. A determination of the adequacy of the fluidized bed steam reformer process to treat Hanford tank waste is required. The initial step in determining the adequacy of the fluidized bed steam reformer process is to select archived waste samples from the 222-S Laboratory that will be used in a bench scale tests. Analyses of the selected samples will be required to confirm the samples meet the shipping requirements and for comparison to the bench scale reformer (BSR) test sample selection requirements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

In-Cell Deployment and First Use of Digital Image Correlation for In-Situ Strain Analysis of Irradiated Nuclear Fuel Rods During LOCA Transient

Digital image correlation (DIC) is a noncontact, optical method increasingly used across industries and research environments for acquiring multidimensional strain data. At Oak Ridge National Laboratory’s (ORNL’s) Severe Accident Test Station (SATS), DIC has been extensively applied to study the thermomechanical response of nuclear fuel claddings, yielding fundamental insights into material behavior. However, these efforts have focused exclusively on unirradiated materials and relied on the SATS out-of-cell infrastructure. Efforts over the past two years have been made to extend these capabilities to ORNL’s Irradiated Fuels Examination Laboratory SATS system within the hot-cells to enable testing of irradiated fuel cladding materials. Integrating DIC into the hot-cell SATS infrastructure presents unique challenges, including enabling remote operation of optical equipment and adapting auxiliary hot-cell systems for DIC implementation. This report discusses design, stand-up testing, and application of DIC to an irradiated nuclear fuel cladding segment. A DIC testing rig was successfully built and validated out-of-cell through extensive surrogate tests and calibrations. The rig and specialized DIC furnace were installed in the hot-cell, and a DIC test was successfully conducted. Results from that test correspond to expectations for Zr-based alloys and showed similar uncertainties compared to out-of-cell tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗

Innovative control mechanism for research and test reactors using mandrel-shaped control rods

Research and test reactors have historically played a pivotal role in supporting the initial development of nuclear reactors. They continue to provide essential data for enhancing fuel designs and material knowledge. However, with many such reactors aging and the growing demand for data to bolster advanced reactor development, it is more necessary to research potential design attributes of the next generation of research and test reactors. For test reactors dedicated to fuel and material testing, the design of control mechanisms significantly influences the stabilization of neutron flux levels in irradiation positions while sustaining criticality. This study presents an innovative control mechanism for potential research and test reactor designs. It employs small absorber rods that move in opposite axial directions to maintain axial symmetry of power and neutron flux during burnup cycles. These rods maximize reactivity worth while also offering flexibility to flatten the radial power distribution. An axial translation of the control mechanisms’ absorbers, as compared to the rotational movement of absorbers in control cylinders, also provides a benefit to available excess reactivity and cycle length. Additionally, this work utilizes a simplified core model of the Advanced Test Reactor to assess the performance of this control mechanism. Compared to the current control system based on rotating control cylinders, the new control mechanism has the potential to enhance, or at least maintain, neutronic performance parameters in this reactor design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of Mockups and Instrumentation for Spent Fuel Drying Tests

The purpose of this report is to provide updates on the experimental components, methodology, and instrumentation under development for use in advanced studies of realistic drying operations conducted on surrogate spent nuclear fuel. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system. Water remaining in canisters upon completion of drying procedures can lead to cladding corrosion, embrittlement, and breaching, as well as fuel degradation. Additional information is needed on the drying process efficacy to help evaluate the potential impacts of water retention on extended longterm dry storage. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates additional, well-designed investigations. Smaller-scale tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report describes the implementation of moisture monitoring equipment on a pressurized, submersible system employing a single waterproof, electrically heated spent fuel rod simulator as a demonstration of analytical capabilities during a drying process. A mass spectrometer with specially designed inlets was used to monitor moisture and other gases at 150 kPa to 800 kPa for a test simulating a forced helium dehydration procedure and below 1 torr for tests mimicking a vacuum drying process. The dew point data from the mass spectrometer was found to be in good agreement with a solid-state moisture probe. A distinct advantage of the mass spectrometer system was the capability to directly sample from the hightemperature (>200 °C) head space expected in a prototypic scale experiment where a solid-state moisture probe would suffer considerable loss of accuracy or fail altogether. The operational and analytical experiences gained from this test series are poised to support an expansion to assembly-scale tests at prototypic length. These assemblies are designed to feature prototypic assembly hardware, advanced diagnostics for in situ internal rod pressure monitoring, and failed fuel rod simulators with engineered cladding defects to challenge the drying system with waterlogged fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The impact of interface bonding efficiency on high-burnup spent nuclear fuel dynamic performance

Finite element analysis (FEA) was used to investigate the impact of interfacial bonding efficiency at pellet-pellet and pellet-clad interfaces of high-burnup (HBU) spent nuclear fuel (SNF) on system dynamic performance. Bending moments M were applied to FEA model to evaluate the system responses. From bending curvature, κ, flexural rigidity EI can be estimated as EI = M/κ. The FEA simulation results were benchmarked with experimental results from cyclic integrated reversal bending fatigue test (CIRFT) of HBR fuel rods. The consequence of interface debonding between fuel pellets and cladding is a redistribution of the loads carried by the fuel pellets to the clad, which results in a reduction in composite rod system flexural rigidity. Furthermore, the interface bonding efficiency at the pellet-pellet and pellet-clad interfaces can significantly dictate the SNF system dynamic performance. With the consideration of interface bonding efficiency, the HBU SNF fuel property was estimated with CIRFT test data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dry in-pile fracture test (DRIFT) for separate-effects validation of ceramic fuel fracture models

Fracture is an important component of nuclear fuel behavior, and significant efforts have been invested into developing fuel performance models that are capable of accurately representing fracture. Usable data on the process of fracture propagation in nuclear fuel under realistic service conditions are very limited. To address this need, a series of separate-effects experiments were developed and performed at Idaho National Laboratory's Transient Reactor Test (TREAT) facility. These experiments employ a heat sink to radially remove heat from the fuel in a manner that approximates the effect of coolant in an operating light-water reactor (LWR). The test holder for these experiments is known as the Dry In-pile Fracture Test (DRIFT). A series of experiments employing DRIFT and TREAT were performed to provide data on the extent and nature of fracture in fresh fuel at various points during a ramp to full power. Novel aspects of these experiments include the way they employ a heat sink to replicate steady-state LWR conditions, as well as the use of fiber optic sensors for in-reactor thermal instrumentation. Details on the development of this experiment, experimental conditions, and resulting data (including in situ thermal measurements and post-irradiation imaging of fracture) are provided in this work. LWR-equivalent powers ranging from 10 to 25 kW/m were tested using this apparatus. Cracking was visible at all power levels, with increasing cracking extent as the power level increased, although there was little difference in the cracking between the two highest-power tests, which had LWR-equivalent powers of 20 and 25 kW/m.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sister Rod Destructive Test Results (FY19)

This report documents work performed under the Spent Fuel and Waste Disposition, Spent Fuel and Waste Science and Technology program for the US Department of Energy (DOE) Office of Nuclear Energy (NE). This work was performed to fulfill Level 2 Milestone M2SF-19ORO010201026 within work package SF-19OR01020102 and is an update to the work reported in M2SF-19OR010201028 and M3SF-19OR010201027. The document incorporates comments received with respect to the previous reports and incorporates additional test results. As a part of the US Department of Energy (DOE) Office of Nuclear Energy (NE) High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 gigawatt days per metric ton uranium) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called the “sister rods,” are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin Zircaloy-4 (LT Zirc-4), ZIRLO ® , and M5 ® . The DEs are being conducted to obtain a baseline of the HBU rod’s condition prior to dry storage and are focused on understanding overall SNF rod strength and durability. Both composite fuel and empty cladding will be tested to derive material properties. While the data generated can be used for multiple purposes, a primary goal for obtaining the post-irradiation examination data and the associated measured mechanical properties is to support SNF dry storage licensing and relicensing activities by (1) addressing identified knowledge gaps and (2) enhancing the technical basis for post-storage transportation, handling, and consolidation activities. This report documents the status of the ORNL Phase I DEs of 8 sister rods and outlines the DE tasks performed and the data collected to date, as guided by the sister rod test plans. The DEs are performed using a phased approach, and the Phase 1 DEs being performed at ORNL include: • full-length rod heat treatments (FHT) of 3 selected sister rods to examine the effects of temperatures reached during dry storage preparation, • rod internal pressure and void volume measurements of the 3 FHT rods and 3 corresponding baseline rods, as well as 2 additional rods selected for depressurization/gas transmission tests and fatigue lifetime tests, • fission gas sampling and analysis, • depressurization and gas transmission tests, • rough segmentation of the selected rods for mechanical tests and rod characterization, • fuel sampling and burnup analysis, • metallography, • cladding total hydrogen measurements, • mechanical testing, including fatigue lifetime (CIRFT), four-point bend, axial tension, microhardness, ring compression, and burst tests. Table S-1 provides a summary of the DE status. The mechanical testing will be performed using fueled segments and is expected to complement previous and current mechanical test results using defueled cladding segments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Update on 17 O evaluation and fast neutron evaluation for 181 Ta [Slides]

Reliable fast-neutron evaluation can be entirely encapsulated in the reaction model and related input. Ta181 is a particularly relevant case due to extraordinary coverage of various observables by differential experiments that offer much help and relatively little headache. Differences from the similar ENDF/B-VIII evaluation are as follows: more advanced modeling (CC OMP, MSD, MSC, decay schemes), more careful selection of models and parameters, new experimental data, and isomers. Overall, there is improved agreement with differential data and hints of better performance in integral testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Impact of Changes in ENDF/B-VII.1 and ENDF/B-VIII.0 235U Nuclear Data Indicated by NDSE Studies on LLNL Pulsed Sphere Simulations

A recent journal article by J.A. Gomez et al. measured gamma-ray die-off curves of three subcritical static highly-enriched uranium (HEU) assemblies driven by an external neutron source with a new detector system. This new detector system was developed for being used in dynamically driven subcritical assemblies as part of the Neutron Diagnosed Subcritical Experiments (NDSE) program. Simulations of these die-off curves with various nuclear data and comparison to experimental data indicated that a decrease of the ENDF/B-VII.1 235 U(n,inl) cross section by a factor 0.8 and 0.85 for ENDF/B-VIII.0 would lead to better predictions of experimental data. Here, we test the proposed changes with another type of measurement response, namely neutron-leakage spectra emitted in LLNL pulsed sphere measurements. These spheres were pulsed by 14-MeV neutrons produced via the D+T reaction in their center. The proposed changes in nuclear data have a distinctly smaller impact on predicting pulsed-sphere neutron-leakage spectra than for the die-off curves; they lead to a worsened prediction of the inelastic valley of LLNL pulsed-sphere neutron spectra indicating that the proposed change could constitute a compensating error. Changes in the inelastic angular distributions along with the cross section might be worthwhile to study

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra

A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improving robustness for model discerning synthesis process of uranium oxide with unsupervised domain adaptation

The quantitative characterization of surface structures captured in scanning electron microscopy (SEM) images has proven to be effective for discerning provenance of an unknown nuclear material. Recently, many works have taken advantage of the powerful performance of convolutional neural networks (CNNs) to provide faster and more consistent characterization of surface structures. However, one inherent limitation of CNNs is their degradation in performance when encountering discrepancy between training and test datasets, which limits their use widely. The common discrepancy in an SEM image dataset occurs at low-level image information due to user-bias in selecting acquisition parameters and microscopes from different manufacturers. Therefore, in this study, we present a domain adaptation framework to improve robustness of CNNs against the discrepancy in low-level image information. Furthermore, our proposed approach makes use of only unlabeled test samples to adapt a pretrained model, which is more suitable for nuclear forensics application for which obtaining both training and test datasets simultaneously is a challenge due to data sensitivity. Through extensive experiments, we demonstrate that our proposed approach effectively improves the performance of a model by at least 18% when encountering domain discrepancy, and can be deployed in many CNN architectures.

scanning electron microscopy↗

AGC-5 Graphite Pre-irradiation Data Analysis Report

This report documents all preirradiation examination material property measurement data for the graphite specimens which were to be used within the fifth Advanced Graphite Capsule (AGC-5) irradiation capsule. The AGC-5 capsule was to be the fifth in six planned irradiation capsules comprising the AGC test series that was designed to irradiate graphite specimens in a temperature range of 600 – 1100°C and medium dose levels to 7 dpa. This would provide quantitative data necessary for predicting the irradiation behavior and operating performance of new nuclear graphite grades for use within very high temperature reactor designs (VHTR). However, due to the lack of commercial interest in building a VHTR design within the USA, the graphite irradiation program was redirected by DOE Advanced Reactor Technology (ART) to re-irradiate the existing specimens from AGC-1 through AGC-4 in the remaining AGC capsules to achieve higher dose levels (15 dpa) at a lower irradiation temperature range (600-800°C). These new irradiation capsules have been designated as the High Dose Graphite (HDG) capsules. This new low temperature, high dose irradiation program favors the current high temperature reactor (HTR) design of interest to the US commercial nuclear community. This report summarizes the measurements from material property tests on the designated AGC-5 specimens. Similar to past AGC runs the specimens were categorized as major graphite grades (IG-110, NBG-17, NBG-18, PCEA and 2114), smaller experimental samples (thermal diffusivity sized specimens of major grades). It is anticipated that some AGC-5 specimens may be required for use within the new HDG-1 capsule. Any specimens from this pre-irradiation testing campaign will be identified in the future HDG-1 Pre-Irradiation Data Report. AGC-5 specimen testing was conducted at Idaho National Laboratory (INL) from December 2015 to February 2018.

(AGC)↗

NEA HTTR LOFC Project Test#3 Benchmark Results

In the second half of FY23, the High Temperature Engineering Test Reactor (HTTR) Loss Of Forced Cooling (LOFC)#3 data for the 9 MW test case with Vessel Cooling System (VCS) off were made available through the Nuclear Energy Agency (NEA) LOFC project framework; the neutronic model developed for the initial test (LOFC#1) achieved a satisfactory level of maturity, demonstrating its accuracy in predicting power evolution and core re-criticality, but LOFC#3 should be used primarily to investigate thermal hydraulic phenomena, as the reactor was shut down prematurely due to overheating in the upper reactor components, which prevented re-criticality; this report focuses on advancing the HTTR thermal hydraulic model to accurately simulate the LOFC#3 scenario, including simulating the LOFC#3 benchmark and generating the corresponding benchmark specifications, aiming to ensure consistency across participant models and provide essential data for future participants, including private industry stakeholders seeking to validate their computational tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

FAUST - Benchmark and Validation Framework [Slides]

This presentation discusses Python packages for nuclear data applications and for benchmarking. It also discusses the goals and objectives for FAUST which include providing input and output processing for different calculation codes, allowing for exchanging results between different applications and codes, running benchmarks and processing the results, automating and simplify plot and report generation, and providing a basis for developing applications useful for nuclear data evaluators. The presentation also discusses how the packages can be used both inside and outside LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development of Data Acquisition System for nuclear thermal hydraulic out-of-pile facility using the graphical programming methods

This paper describes the design of data acquisition system (DAQ) that is connected to a PC and development of a feedback control system that maintains the coolant temperature of the process at a desired set point using a digital controller system based on the graphical programming language. The paper will provide details about the data acquisition unit, shows the implementation of the controller, and present test results. (authors)

42 ENGINEERING↗