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At least 1,297 records · Page 72

Evaluation of a positron-emission-tomography-based SiPM readout for compact segmented neutron imagers

Gamma-ray emission from special nuclear material (SNM) is relatively easy to shield from detection using modest amounts of high-Z material. In contrast, fast-neutrons are much more penetrating and can escape relatively thick high-Z shielding without losing significant energy. Furthermore, fast neutrons provide a clear and unambiguous signature of the presence of SNM with few competing natural background sources. The challenge of detecting fast neutrons is twofold. First, the neutron flux from SNM are only a fraction of the corresponding gamma-ray flux. Second, fast neutrons can be difficult to differentiate from gamma rays. The ability to discriminate gamma rays from neutrons, combined with a neutron imaging capability, can in some situations enable the localization of SNM neutron sources distinct from background. With the developments of pulse-shape-sensitive plastic scintillators that offer excellent gamma-ray/neutron discrimination, and arrays of silicon photomultipliers combined with highly scalable and fast positron-emission-tomography (PET) multi-channel readout systems, field-deployable neutron imagers suitable for SNM detection might now be within reach. In this paper, we present a characterization of the performance of a recently available commercial PET-scanner readout, including its sensitivity to pulse-shape differences between fast neutrons and gamma rays, energy and timing resolution. Here, we find that, while the pulse-shape discrimination is achievable with stilbene, further improvement of the readout is required to achieve it with the PSD-capable available plastic scintillators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Electrospraying deposition and characterization of potassium chloride targets for nuclear science measurements

Natural and isotopically enriched KCl targets were prepared using specially formulated KCl solutions, deposited by electrospraying on thin (1.5 μm) gold backings, followed by a short annealing in a preheated (350-450 °C) furnace. Various techniques, such as X-ray fluorescence (XRF), scanning electron microscopy (SEM) imaging, and energy-dispersive X-ray spectroscopy (EDS), were used to characterize the produced targets. A white neutron beam at the Los Alamos Neutron Science Center (LANSCE) facility was also used to verify the estimated atomic percentages of the enriched 40 KCl targets. KCl was deposited relatively uniformly as large particles rather than films on the gold surface. As a result, this method can be broadly extended to make stable targets that are difficult to produce with other methods and more exotic radioactive targets required for research in fundamental sciences and applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

pyEGAF: An open-source Python library for the Evaluated Gamma-ray Activation File

The Evaluated Gamma-ray Activation File (EGAF) is one of the most comprehensive resources for thermal neutron-capture data. This database contains data from prompt gamma activation analysis measurements carried out in a consistent manner using the same experimental configuration at the Budapest Research Reactor for 245 isotopes. Although these valuable datasets have been freely available for many years, one of the drawbacks is the outdated and cryptic Evaluated Nuclear Structure Data File (ENSDF) format that is currently adopted for dissemination, making it difficult for users unfamiliar with the format to access and utilize the data contained therein. Furthermore, the ENSDF format does not readily lend itself to modern computational technologies and a parser is required to interpret the complicated mixed-record format. To help overcome these challenges, we have developed a translator to convert the ENSDF-formatted datasets into an open standard JavaScript Object Notation (JSON) format enabling accessibility to applications using different programming languages running in different environments. To compliment this effort, we have also developed an open-source software package implemented in Python, pyEGAF, that is designed to interact with the JSON data structures for general purpose access, manipulation, and analysis of the neutron-capture $\gamma$-ray data in EGAF. The new format, together with the pyEGAF library, greatly enhances access to the wider applications community where EGAF data may be useful or is required.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Neutron resonance transmission analysis prototype system for thorium fuel cycle safeguards

Emerging thorium-based reactor designs and fuel cycles present challenges to traditional non-destructive assay techniques used in international safeguards. Specifically, assaying the masses of 233 U and 235 U when they are present together in samples with high gamma ray backgrounds is difficult because of similar passive neutron signatures and relatively weak gamma-ray emissions of 233 U. The Pacific Northwest National Laboratory (PNNL) and the Massachusetts Institute of Technology (MIT) are developing a compact neutron resonance transmission analysis (NRTA) system as one potential solution to these challenges. The NRTA technique provides isotopic information for a sample via neutron time-of-flight (TOF) measurements that exploit a sample’s epithermal neutron resonance cross-sections. A recently developed portable NRTA system uses a commercially available, pulsed deuterium-tritium neutron generator with a ~2 m flight path and a GS20 lithium glass scintillator detector. Finally, this paper describes the prototype NRTA system design, a refined radiation transport model of the system, preliminary measurements with thorium and uranium sources, and demonstration of a quantitative isotopic estimation algorithm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Unsupervised anomaly detection in MeV ultrafast electron diffraction

MeV ultrafast electron diffraction (MUED) is a pump-probe technique used to study the dynamic structural evolution of materials. An ultrashort laser pulse triggers structural changes, which are then probed by an ultrashort relativistic electron beam. To overcome low signal-to-noise ratios, diffraction patterns are averaged over thousands of shots. However, shot-to-shot instabilities in the electron beam can distort individual patterns, introducing uncertainty. Improving MUED accuracy requires detecting and removing these anomalous patterns from large datasets. In this work, we developed a fully unsupervised methodology for the detection of anomalous diffraction patterns. Using a convolutional autoencoder, we calculate the reconstruction mean squared error of the diffraction patterns. Based on the statistical analysis of this error, we provide the user an estimation of the probability that the pattern is normal, which also allows a posterior visual inspection of the images that are difficult to classify. This method has been trained with only 100 diffraction patterns and tested on 1521 patterns, resulting in a false positive rate between 0.2% and 0.4%, with a training time of 10 s per image and a test time of about 1 s per image. Here, the proposed methodology can also be applied to other diffraction techniques in which large datasets are collected that include faulty images due to instrumental instabilities.

43 PARTICLE ACCELERATORS↗

Producing 236 U reference standards for Accelerator Mass Spectrometry at the University of Notre Dame

36 U is a rare isotope of uranium, naturally occurring in ores with an abundance of 236 U/ 238 U$<$ 1 x 10 -9 . The ability to detect it and make isotopic ratio measurements has applications ranging from nuclear forensics and nonproliferation to energy production and environmental protection. Currently, Accelerator Mass Spectrometry (AMS) is the only technique sensitive enough to accurately measure 236 U/ 238 U isotopic ratios as they exist in naturally occurring ores in the range of 236 U/ 238 U = 10 -12 $-$ 10 -9 . Some AMS facilities have demonstrated their capabilities to make these measurements. Historically, the lack of commercially available reference standards covering the range of naturally occurring 236 U/ 238 U abundances has necessitated the use of absolute measurements, notoriously difficult to do using AMS, resulting in increased uncertainties in measurements and a reliance on knowledge of systematic effects. To mitigate these issues, various AMS facilities have sought to develop their own reference standards. Using a reference standard prepared for other forms of mass spectrometry, a series of AMS suitable standards was created through dilution with low-background natural uranium. The techniques used to produce and characterize these materials as well as analysis of them using AMS will be discussed.

236U↗

Towards standardized nuclear reactors: Seismic isolation and the cost impact of the earthquake load case

We report nuclear energy has a key role to play in global decarbonization. Impediments to the widespread deployment of reactors are their projected high capital cost and levelized cost of energy, and time required to analyze, design, license, construct, and commission them. The earthquake load case is a key cost driver for a new build nuclear plant, because near-surface soils and seismic hazard are different at each site, requiring site-specific analysis, design, engineering, qualification, licensing, and regulatory review, essentially making every design First-of-a-Kind (FoaK). To enable deployment at the scale needed for deep decarbonization, the cost and time impact of the seismic load case must be significantly mitigated, and plants must be standardized. Seismic base isolation has been proven to considerably reduce the earthquake response of structures and equipment but has yet to be applied to a nuclear power plant in the United States, in part because the financial impacts, positive or negative, are not known. Because there are no recent non-proprietary data to characterize the influence of the seismic load case on capital cost, it is difficult to confidently quantify the financial benefits of seismic isolation. Scheme-level designs of two fundamentally different advanced reactor buildings were developed to assemble cost data on the influence of the seismic load case. Both buildings were equipped with three bespoke pieces of safety-related equipment and analyzed for incremented levels of earthquake shaking to quantify the seismic penalty on equipment, in terms of vessel weights and horizontal accelerations. Using analysis results, a questionnaire was developed and transmitted to nuclear utilities, reactor developers, engineers, and equipment suppliers to collect cost data on engineering and fabrication costs for these unique pieces of safety-class equipment. Synthesis of the cost data showed that the seismic load case significantly affects the capital cost (sum of engineering and fabrication cost) of safety-class equipment, with engineering costs being comparable to fabrication costs. Standardization of safety-class equipment is made possible by seismic isolation, that is, equipment designed for minimal seismic robustness can resist earthquake shaking at a site of much higher seismic hazard. The average reduction in the capital cost of the safety-related equipment, enabled by seismic isolation, is a factor of two for FoaK equipment and a factor of five for standardized equipment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Development and application of two-step uncertainty propagation and sensitivity analysis methodology for fast reactor safety analysis

Uncertainty quantification (UQ) in nuclear reactors for transients is directly linked with safety assessment through the cross-sections uncertainties, provided as a covariance matrix, which are propagated through the reactor system to output of interest pertaining to reactor safety, such as peak temperatures in fuel/clad/coolant. Using a two-step approach, uncertainties are first quantified and propagated from basic input variables (such as reaction cross-sections) to intermediate quantities (such as reactivity feedback coefficients) through lattice level calculations. Uncertainties of intermediate quantities (from the first step) are then propagated through the system transient calculations, in the second step, to obtain uncertainties on reactor safety output parameters of interest. The scope of this work consists of Uncertainty Quantification & Propagation of nuclear data uncertainties that are highly correlated through unprotected transient overpower and unprotected loss of flow to assess their impact on core safety parameters. This two-step approach in the presence of covariance renders the sensitivity analysis very challenging. In fact, usually the sensitivity analysis is restricted to each step, which limits its application since the sensitivities between the system output quantities and the basic input variables are difficult to obtain. Here, in this work, we address this issue by proposing a simple, general methodology to combine the sensitivity indices obtained in each step by assuming the model behavior being linear. For the first step Generalized Perturbation theory based indices are used while in the second step the recently studied Johnson indices. The uncertainty quantification and sensitivity methodologies discussed here are demonstrated on a generic LFR design which is based on the 500 MWth demonstration Lead-cooled fast reactor (DLFR) using oxide fuel, developed by Westinghouse Electric Company (WEC).

42 - ENGINEERING↗

Government sector activities to reduce thermal-spectrum molten salt breeder reactor investment risk

Thermal-Spectrum Molten Salt Breeder Reactors (TS-MSBRs) have long been recognized as having high potential for clean, safe, large-scale, cost-effective energy production for the foreseeable future. U.S. government support for TS-MSBR development was stopped half a century ago in the belief that they were too technically difficult. Technology progression over the past several decades as well as the pressing need for clean power on-demand provides incentives to reconsider the development program cancellation. Limited, early-stage, government sector activities have the potential to sufficiently reduce investor risk to trigger the private sector investment necessary to commercialize the reactor class. In conclusion, these activities are summarized in this article.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Neutron elastic and inelastic scattering differential cross sections on carbon

Elastic and inelastic neutron scattering angular distributions were measured on natural carbon samples to confirm existing experimental data and evaluations in the fast neutron region and to guide improvements in resonance parameters, where needed. Sixty-four (n,n') differential cross section measurements were performed at 45 incident neutron energies between 0.5 and 8.0 MeV. Experimental angle-integrated elastic scattering cross sections are consistent with ENDF/B-VIII.0 values with the exception of the region from 3.2 to 4.0 MeV where our results are ~3% higher. In the 3.4 to 3.6 MeV region our differential cross sections are slightly lower at forward angles and somewhat higher at backward angles than the ENDF/B-VIII.0 calculations; however, our results are consistent with measured data from other research groups. The first- through fourth-order elastic scattering Legendre coefficients from fits to these experimental data are consistent with ENDF/B-VIII.0 values across this range of incident neutron energies. Inelastic scattering cross sections were measured at 12 incident neutron energies between 5.6 and 7.8 MeV. Angle-integrated cross sections agree well with the 1978 Perey and ENDF/B-VIII.0 values; however, the angular-distribution shapes deviate somewhat from the ENDF/B-VIII.0 calculations. These data will allow refinement of the resonance parameter description in this difficult energy region.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

What's new? An ab initio investigation of the 3 He-4He radiative capture into 7 Be

The 3 He$(α, γ)$ 7 Be radiative capture reaction plays an important role in the creation of elements in stars and in the production of solar neutrinos. It is difficult to experimentally measure this fusion cross section at energies relevant to solar processes because of Coulomb repulsion. Therefore, theory is needed to perform extrapolations from higher energies (where experimental fusion measurements are feasible) to the astrophysical regime. Here, we present the first microscopic calculations of 3 He$(α, γ)$ 7 Be with explicit inclusion of three-nucleon forces. With the incorporation of experimental bound-state and scattering information, our calculation of the astrophysical S factor agrees quantitatively with experimental data.

Physics - Nuclear physics and radiation physics↗

Power performance and loads characterization of laboratory-scale cross-flow rotors fabricated using additive manufacturing

Tidal energy conversion is a relatively new application for additive manufacturing (AM), where the focus has been on fabricating axial-flow turbine blades. AM techniques add material precisely where it is needed, creating more complex shapes with less waste. Cross-flow rotor geometry presents an opportunity for AM to improve rotor performance by fabricating features that cannot be created economically via conventional manufacturing. The challenges associated with using AM in cross-flow design include water resistance and degradation over time while retaining a level of quality equivalent to conventionally machined parts. In this work, AM materials were tested by environmentally conditioning samples in a seawater tank for 5 months, followed by performance and phase-resolved load testing of laboratory-scale rotors in a hydraulic flume. We found that while metals like titanium and Inconel have excellent performance in marine environments, achieving the desired geometry and performance is difficult. Thermoplastics degraded in seawater but were easier to form into desired geometries and could exceed the performance of an aluminum control rotor. Warping and surface finish were significant detractors from AM rotor performance. These results suggest that the primary benefits of using AM for cross-flow rotors is to quickly fabricate and test unconventional rotor geometries.

16 TIDAL AND WAVE POWER↗

Optimization with the OpenACC-to-FPGA framework on the Arria 10 and Stratix 10 FPGAs

The reconfigurable computing paradigm with field programmable gate arrays (FPGAs) has received renewed interest in the high-performance computing field due to FPGAs’ unique combination of performance and energy efficiency. However, difficulties in programming and optimizing FPGAs have prevented them from being widely accepted as general-purpose computing devices. In accelerator-based heterogeneous computing, portability across diverse heterogeneous devices is also an important issue, but the unique architectural features in FPGAs make this difficult to achieve. To address these issues, a directive-based, high-level FPGA programming and optimization framework was previously developed. In this work, developed optimizations were combined holistically using the directive-based approach to show that each individual benchmark requires a unique set of optimizations to maximize performance. We perform this exploration on Intel Arria 10 and Stratix 10 FPGAs. We also explored the relationships between performance, resource usages, and compilation times, and investigated implications for performance portability. Finally, we present an initial evaluation of a real-world proxy application, LULESH.

97 MATHEMATICS AND COMPUTING↗

Lowering entry barriers to developing custom simulators of distributed applications and platforms with SimGrid

Researchers in parallel and distributed computing (PDC) often resort to simulation because experiments conducted using a simulator can be for arbitrary experimental scenarios, are less resource-, labor-, and time-consuming than their real-world counterparts, and are perfectly repeatable and observable. Many frameworks have been developed to ease the development of PDC simulators, and these frameworks provide different levels of accuracy, scalability, versatility, extensibility, and usability. Further, the SimGrid framework has been used by many PDC researchers to produce a wide range of simulators for over two decades. Its popularity is due to a large emphasis placed on accuracy, scalability, and versatility, and is in spite of shortcomings in terms of extensibility and usability. Although SimGrid provides sensible simulation models for the common case, it was difficult for users to extend these models to meet domain-specific needs. Furthermore, SimGrid only provided relatively low-level simulation abstractions, making the implementation of a simulator of a complex system a labor-intensive undertaking. In this work we describe developments in the last decade that have contributed to vastly improving extensibility and usability, thus lowering or removing entry barriers for users to develop custom SimGrid simulators.

97 MATHEMATICS AND COMPUTING↗

Confidence-weighted integration of human and machine judgments for superior decision-making

Large language models (LLMs) can surpass humans in certain forecasting tasks. What role does this leave for humans in the overall decision process? One possibility is that humans, despite performing worse than LLMs, can still add value when teamed with them. A human and machine team can surpass each individual teammate when team members’ confidence is well calibrated and team members diverge in which tasks they find difficult (i.e., calibration and diversity are needed). We simplified and extended a Bayesian approach to combining judgments using a logistic regression framework that integrates confidence-weighted judgments for any number of team members. Using this straightforward method, we demonstrated its effectiveness in both image classification and neuroscience forecasting tasks. Combining human judgments with one or more machines consistently improved overall team performance. Our hope is that this simple and effective strategy for integrating the judgments of humans and machines will lead to productive collaborations.

97 MATHEMATICS AND COMPUTING↗

Genome-scale modelling of the primary-specialized metabolism interface

Environmental challenges and development require plants to reallocate resources between primary and specialized metabolites to survive. Genome-scale metabolic models, which map carbon flux through metabolic pathways, are a valuable tool in the study of tradeoffs that arise at this interface. Due to annotation gaps, models that characterize all the enzymatic steps in individual specialized pathways and their linkages to each other and to central carbon metabolism are difficult to construct. Recent studies have successfully curated subsystems of specialized metabolism and characterized the interfaces where flux is diverted to the precursors of glucosinolates, terpenes, and anthocyanins. Although advances in metabolite profiling can help to constrain models at this interface, quantitative analysis remains challenging because of the different timescales on which specialized metabolites from constitutive and reactive pathways accumulate.

59 BASIC BIOLOGICAL SCIENCES↗

Secondary porosity prediction in complex carbonate reefs using 3D CT scan image analysis and machine learning

Development and preservation of carbonate porosity and permeability are critical to characterizing reservoirs. However, secondary porosity, such as vugs and fractures, are difficult to identify and require collection of expensive wireline tools or core sampling. Wireline logs and cores have traditionally been used to identify the presence of secondary porosity but fail to quantify the contribution to total reservoir porosity. Additionally, advanced wireline logs and core are not readily available for most wells. Dual energy CT scans were collected on whole core from the A-1 Carbonate and Brown Niagaran formations drawn from six wells in northern Michigan. 3D analysis techniques were applied to identify and isolate secondary porosity features. A series of machine learning and data analytics techniques were applied to the dataset to predict secondary porosity features on basic wireline logs. The predictive model successfully predicted secondary porosity with high confidence.

02 PETROLEUM↗

Deep inverse photonic design: A tutorial

Deep learning (DL) has been used to design deep neural networks (DNNs) which have recently been applied to solving inverse problems in artificial electromagnetic materials (AEMs). Although inverse problems are often ill-posed, and therefore are difficult to solve, deep inverse models (DIMs) have achieved impressive results often surpassing capabilities possible with other approaches. We overview the process of deep inverse learning applied to AEM problems, including the building of data sets, design of a forward model, and comparison of inverse approaches including limitations. We conclude by detailing some important outstanding issues of deep inverse design of AEMs, and present an outlook of this exciting field.

42 ENGINEERING↗