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At least 91 records · Page 5

Joint neutron measurements on the flat-top HEU critical assembly machine - 14388

Flat-Top is a critical assembly with a spherical core (either ∼17 kg of HEU or ∼6 kg of δ-phase Pu) surrounded by a spherical 1000 kg natural uranium reflector. In 2013, joint LANL and CEA measurements were conducted to measure Flat-Top configurations with the HEU core using He-3 detector systems. Similar experiments were previously documented in which the Caliban and Godiva critical assemblies were measured. The core and reflector of Flat-Top have a glory hole in which nuclear material or non-nuclear material may be placed. Five configurations were measured and included subcritical configurations at various reactivity states as well as a configuration at delayed critical. The various reactivity states were achieved by varying the placement of the safety blocks and control rods (composed of natural uranium). A description of the assembly and the specific configurations measured will be presented. The subcritical and delayed critical measurements were analyzed using the Hage-Cifarelli formalism of the Feynman Variance-to-Mean method. This analysis can be used to calculate the multiplication of each configuration, from which the multiplication factor and reactivity are determined. These results are compared to the reactivity states based upon control rod worth curves and MCNP simulations. For this work, a new MCNP model was made to accurately represent the measured configurations. The ICSBEP handbook contains a benchmark of Flat-Top but all models are very simple and do not have the required fidelity to accurately represent the measured configurations. This work also examines the number of neutrons emitted per fission for this assembly (which has a significant contribution of induced fissions in U-238 due to the large natural uranium reflector). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

HFIR Core Modeling and Analysis for the PROSPECT Reactor Antineutrino Experiment

Nuclear reactors have been employed as a copious source of antineutrinos for over six decades. Research initially directed at the study of antineutrino physics has led to applications of these highly penetrating particles to reactor safeguards because the antineutrino flux and spectrum can be related to the state of the reactor core, including burnup evolution. One of the main challenges of antineutrino-based safeguards is operation of the detectors near surface (within the reactor containment or in the close proximity). Lack of overburden results in increased contribution to the detector noise from cosmic radiation. Similarly to safeguards, experiments to definitively confirm or exclude the existence of sterile neutrino oscillations require detector technologies capable of operating at short baselines (tens of meters) at the surface. The Precision Reactor Oscillation and Spectrum Experiment (PROSPECT) at the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is an experiment with a main objective to make a precision measurement of the flux and energy spectrum of antineutrinos emitted from nuclear reactors in order to search for the oscillation signature of sterile neutrinos. Fissions of highly-enriched uranium of HFIR will serve as a source of antineutrinos. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗

Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements, and deficiencies in the developed models. The three types of underlying uncertainties have not yet been properly quantified in open literature. Here, this paper presents the Bayesian uncertainty quantification (UQ) using massively parallelizable Markov chain Monte Carlo samplers. The uncertainties due to model parameters, model inadequacy, and experimental measurement noise are quantified, with the σ term used to represent the sum of the model inadequacy and measurement noise uncertainties. It is worth noting that this is the first time the σ term is inferred for nuclear fuel experiments, as compared to using prescribed values for uncertainty quantification in previous work. The parallelizable Markov chain Monte Carlo samplers efficiently infer the model parameters and the σ term, giving insight into physical parameters like diffusion coefficients and the combined model discrepancy and measurement noise. A subsequent forward uncertainty quantification (UQ) is also performed based on the calibration results to generate more accurate predictions of the Ag release. The model inadequacy plus experimental noise is the most dominant source of uncertainty compared to the parametric uncertainty. All the UQ analyses presented in this work are based on the second series of the irradiation experiments in the Advanced Gas Reactor program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

In situ compression artifact removal in scientific data using deep transfer learning and experience replay

The massive amount of data produced during simulation on high-performance computers has grown exponentially over the past decade, exacerbating the need for streaming compression and decompression methods for efficient storage and transfer of this data---key to realizing the full potential of large-scale computational science. Lossy compression approaches such as JPEG when applied to scientific simulation data realized as a stream of images can achieve good compression rates but at the cost of introducing compression artifacts and loss of information. This paper develops a unified framework for in situ compression artifact removal in which the fully convolutional neural network architectures are combined with scalable training, transfer learning, and experience replay to achieve superior accuracy and efficiency while significantly decreasing the storage footprint as compared with the traditional optimization-based approaches. We demonstrate the proposed approach and compare it with compressed sensing postprocessing and other baseline deep learning models using climate simulations and nuclear reactor simulations, both of which are driven by hyperbolic partial differential equations. Our approach when applied to remove the compression artifacts on the JPEG-compressed nuclear reactor simulation data (using a transfer-trained model that was pretrained on the climate simulation data and updated incrementally as the nuclear reactor simulation progressed), achieved a significant improvement---mean peak signal-to-noise ratio of 42.438 as compared with 27.725 obtained with the compressed sensing approach.

97 MATHEMATICS AND COMPUTING↗

Passive acoustic leak detection for sodium cooled fast reactors using hidden Markov models

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970's and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Simulation of magnetic hysteresis loops and magnetic Barkhausen noise of α-iron containing nonmagnetic particles

Here, the magnetic hysteresis loops and Barkhausen noise of a single α-iron with nonmagnetic particles are simulated to investigate into the magnetic hardening due to Cu-rich precipitates in irradiated reactor pressure vessel (RPV) steels. Phase field method basing Landau-Lifshitz-Gilbert (LLG) equation is used for this simulation. The results show that the presence of the nonmagnetic particle could result in magnetic hardening by making the nucleation of reversed domains difficult. The coercive field is found to increase, while the intensity of Barkhausen noise voltage is decreased when the nonmagnetic particle is introduced. Simulations demonstrate the impact of nucleation field of reversed domains on the magnetization reversal behavior and the magnetic properties.

36 MATERIALS SCIENCE↗

Effects of aging time and temperature of Fe-1wt.%Cu on magnetic Barkhausen noise and FORC

Magnetic Barkhausen noise (MBN), hysteresis measurements, first order reversal curves (FORC), Vickers microhardness, and Transmission Electron Microscopy (TEM) analyses were performed on Fe-1wt.%Cu (Fe-Cu) samples isothermally aged at 700°C for 0.5 – 25 hours to obtain samples with different sized Cu precipitates and dislocation structures. Fe-Cu is used to simulate the thermal and irradiation-induced defects in copper-containing nuclear reactor materials such as cooling system pipes and pressure vessel materials. The sample series showed an initial increase followed by a decrease in hardness and coercivity with aging time, which is explained by Cu precipitates formation and growth as observed by TEM measurements. Further, the MBN envelope showed a continuous decrease in its magnitude and the appearance of a second peak with aging. Also, FORC diagrams showed multiple peaks whose intensity and location changed for different aging time. The changes in FORC diagrams are attributed to combined changes of the magnetic behavior due to Cu precipitate characteristics and dislocation structure. A second series of samples aged at 850°C, which is above the solid solution temperature of Fe-Cu, was studied to isolate the effects of dislocations. These samples showed a continuous decrease in MBN amplitude with aging time although the coercivity and hardness did not change significantly. The decrease of MBN amplitude and the appearance of the second MBN envelope peak are attributed to the changes in dislocation density and structure. This study shows that the effect of dislocations on MBN and FORC of Fe-Cu materials can vary significantly and should be considered in interpreting magnetic signatures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Analysis of the Temporal Response of Coupled Asymmetrical Zero-Power Subcritical Bare Metal Reactor Systems

The behavior of symmetrical coupled-core systems has been extensively studied, yet there is a dearth of research on asymmetrical systems due to the increased complexity of the analysis of such systems. In this research, the multipoint kinetics method is applied to asymmetrical zeropower, subcritical, bare metal reactor systems. Existing research on asymmetrical reactor systems assumes symmetry in the neutronic coupling; however, it will be shown that this cannot always be assumed. Deep subcriticality adds another layer of complexity and requires modification of the multipoint kinetics equations to account for the effect of the external neutron source. A modified set of multipoint kinetics equations is derived with this in mind. Subsequently, the Rossi-alpha equations are derived for a two-region asymmetrical reactor system. The predictive capabilities of the radiation transport code MCNP6 for neutron noise experiments are shown in a comparison to the results of a series of Rossi-alpha measurements performed by J. Mihalczo utilizing a coupled set of symmetrical bare highly-enriched uranium (HEU) cylinders. The ptrac option within MCNP6 can generate time-tagged counts in a cell (list-mode data). The list-mode data can then be processed similarly to measured data to obtain values for system parameters such as the dual prompt neutron decay constants observable in a coupled system. The results from the ptrac simulations agree well with the historical measured values. A series of case studies are conducted to study the effects of geometrical asymmetry in the coupling between two bare metal HEU cylinders. While the coupling behavior of symmetrical systems has been reported on extensively, that of asymmetrical systems remains sparse. In particular, it appears that there has been no previous research in obtaining the coupling time constants for asymmetrically-coupled systems. The difficulty in observing such systems is due in part to the inability to determine the individual coupling coefficients from measurement: unlike the symmetrical cases, only the product of the values can be obtained. A method is proposed utilizing MCNP6 tally ratios to separate the coupling coefficients for such systems. This work provides insight into the behavior of asymmetrically-coupled systems as the separation distance between the two cores is changed and also as the asymmetry is increased. As the asymmetry increases, both the slower and the faster observable prompt neutron decay constants increase in magnitude. The coupling time constants are determined from the measured decay constants. As the separation distance increases, both coupling coefficients decrease as expected. Based on these findings, an effective computational method utilizing MCNP6 and the Rossialpha technique can be applied to the prediction of asymmetrical coupled system measurements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Status of NTD Ge bolometer material and devices

The first IR Detector Technology Workshop took place at NASA Ames Research Center on July 12 and 13, 1983. The conclusions presented at that meeting are still valid. More was learned about the physics of hopping conduction at very low temperatures which will be important for bolometer design and operation at ever decreasing temperatures. Resistivity measurements were extended down to 50 mK. At such low temperatures, precise knowledge of the neutron capture cross sections sigma (sub n) of the various Ge isotopes is critical if one is to make an accurate prediction of the dopant concentrations and compensation, and therefore resistivity, that will result from a given irradiation. An empirical approach for obtaining the desired resistivity material is described and the process of conducting a set of experiments which will improve the knowledge of the effective sigma (sub n) values for a given location in a particular reactor is discussed. A wider range of NTD Ge samples is now available. Noise measurements on bolometers with ion implanted contacts show the no 1/f noise component appears down to 1 Hz and probably lower.

Haller, E. E.↗

Enhanced NIF neutron activation diagnostics

The NIF neutron activation diagnostic suite relies on removable activation samples, leading to operational inefficiencies and a fundamental lower limit on the half-life of the activated product that can be observed. A neutron diagnostic system measuring activation of permanently installed samples could remove these limitations and significantly enhance overall neutron diagnostic capabilities. The physics and engineering aspects of two proposed systems are considered: one measuring the {sup 89}Zr/{sup 89m}Zr isomer ratio in the existing Zr activation medium and the other using potassium zirconate as the activation medium. Both proposed systems could improve the signal-to-noise ratio of the current system by at least a factor of 5 and would allow independent measurement of fusion core velocity and fuel areal density.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of Thermal Tomography Imaging System for In-Service Nondestructive Evaluation of Additively Manufactured Components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. We investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin. MIT research reactor (MITR) has been identified as a representative environment to perform investigation of feasibility of in-service NDE during shutdown. Preliminary study of radiation level in the MITR viewport, with geometric parameters potentially compatible with compact TT system, has been conducted.

36 MATERIALS SCIENCE↗

Neutron noise calculations in a hexagonal geometry and comparison with analytical solutions

This paper presents the development of a neutronic and kinetic solver for hexagonal geometries. The tool is developed based on the diffusion theory with multi-energy groups and multi-groups of delayed neutron precursors allowing the solutions of forward and adjoint problems of static and dynamic states, and is applicable to both thermal and fast systems with hexagonal geometries. In the dynamic problems, the small stationary fluctuations of macroscopic cross sections are considered as noise sources, and then the induced first order noise is calculated fully in the frequency domain. Numerical algorithms for solving the static and noise equations are implemented with a spatial discretization based on finite differences and a power iterative solution. A coarse mesh finite difference method has been adopted for speeding up the convergence. Since no other numerical tool could calculate frequency-dependent noise in hexagonal geometry, validation calculations have been performed and benchmarked to analytical solutions based on a 2-D homogeneous system with two-energy groups and one-group of delayed neutron precursor, in which point-like perturbations of thermal absorption cross section at central and non-central positions are considered as noise sources. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Measurement of neutron and gamma-ray noise in large subcritical condition for criticality safety - 14485

Various experimental methods have been proposed for subcriticality measurement and neutron noise analysis method is one of important experimental techniques for this purpose. The variance to mean value method, called Feynman-alpha method, is one of well-known noise analysis methods. In this method, variation of neutron count rate distribution from the Poisson distribution caused by fission chain reactions, which is called Y-value, is measured, however, it is difficult to measure the Y-value in large subcritical state such as nuclear fuel facility, because number of emitted neutrons by fission chain reaction is small, which causes large statistical error. We developed new experimental technique based on Feynman-alpha method combined with pulsed neutron source, called Delayed Neutron Noise Analysis (DNNA) method, to monitor the change of subcriticality. In this new method, neutron and gamma-ray counts measured only appeared in the delayed neutron region after injection of pulsed neutron are analyzed, and the prompt neutron region is completely ignored. The advantage of DNNA compared with conventional method is that spatial dependency of detector positions on measured results can be greatly decreased, which result in increase of accuracy of measured subcriticality. The validity of the DNNA method was experimentally investigated in the Kyoto University Critical Assembly (KUCA) at Kyoto University Research Reactor Institute. In the experiments, pulsed neutrons by D-T reactions are injected into the core and we used {sup 3}He detectors to measure neutron noise signals and BGO scintillation detectors to measure gamma-ray noise signals, and all data in the delayed neutron region were analyzed based on Feynman-alpha method. From the experimental results, it was found that the Y-values are clearly larger than zero in the case of existence of fuel assemblies and this method can be applied to detection of hidden special nuclear materials for example in a cargo container. (authors)

42 ENGINEERING↗

High Multiplication Neutron Noise Measurements Using the 7uPCX Assembly

The Seven Percent Critical Experiment, or 7uPCX, is a system that mimics the physics of light water nuclear reactor systems by using uranium dioxide fuel pins at an enrichment of approximately 7%. 7uPCX is often used for benchmarking and nuclear data purposes. As part of a collaboration between Lawrence Livermore National Laboratory, Los Alamos National Laboratory, Sandia National Laboratories, and the Institut de Radioprotection et de Sûreté Nucléaire, measurements were performed in support of a high-multiplication, subcritical benchmark candidate for a thermal system. The measurements were completed by making subcritical configurations using the fuel loading pattern of a well-documented configuration of the Seven Percent Critical Experiment at Sandia National Laboratories, which exists as a benchmark in the International Criticality Safety Benchmark Evaluation Project handbook. These measurements, which aimed to capture multiplications ranging from approximately 10 to 1,000, also serve as an intercomparison between both the fielded detector systems and analysis methodologies with the goal of better characterizing the detectors and their ability to capture the state of the criticality these types of systems. Los Alamos National Laboratory’s measurements for this collaboration were made with five linked helium-3 based neutron multiplicity detectors placed on the periphery of the reactor tank beyond the infinite reflector thickness of water, and four organic scintillators placed in dry-wells in-reactor near the edge of the upper fuel grid plate. This work captures the Los Alamos National Laboratory measurements, the Rossi-α and Feynman-Y results, provides an intercomparison between the results of the 3 He neutron detectors and the organic scintillators, compares to simulation where possible, and expands on future work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A novel technique applying spectral estimation to Johnson noise thermometry - 317

Johnson noise thermometry is one of many important measurement techniques used to monitor the safety levels and stability in a nuclear reactor. However, this measurement is very dependent on the minimal electromagnetic environment. Properly removing unwanted electromagnetic interference (EMI) is critical for accurate drift free temperature measurements. The two techniques developed by Oak Ridge National Laboratory to remove transient and periodic EMI are briefly discussed in this paper. Spectral estimation is a key component in the signal processing algorithm used for EMI removal and temperature calculation. The cross-power spectral density is a key component in the Johnson noise temperature computation. Applying either technique requires the simple addition of electronics and signal processing to existing resistive thermometers. With minimal installation changes, the system discussed here can be installed on existing nuclear power plants. The Johnson noise system developed is tested at three locations: Oak Ridge National Laboratory, Sandia National Laboratory, and Tennessee Valley Authority (TVA) Kingston Steam Plant. Each of these locations enabled improvement on the EMI removal algorithm. The conclusions made from the results at each of these locations is discussed, as well as, possible future work. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of Neutron Detection Third Order Time Correlation

Neutron noise experiments on fissile materials are used to get information such as reactivity, fissile mass, neutron sources, prompt neutron lifetime. One of the more popular methods is based on correlated moments of the neutron counts distribution. The second correlated moment method originally proposed by Feynman was extended to the third order. In this paper we present the application of the third order correlation moments method to SILENE reactor measurements. The third order correlation moments method has been applied to analyse time list mode - subcritical measurements on SILENE reactor in order to evaluate the system subcriticality, The multiplication coefficient is obtained with large statistical uncertainties, but remains consistent with MCNP calculations. To reduce the experimental uncertainties longer measurement time and higher detector efficiency should be necessary. The systematic errors coming from the fission neutron data (moments of the fission neutron distributions) and point model formulas should also be investigated. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗