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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Carbon ablator areal density at fusion burn: Observations and trends at the National Ignition Facility

For inertial confinement fusion experiments, the pusher is composed of a high-density deuterium tritium cyrogenic fuel layer and an ablator, often made of carbon. In an ideal, no-mix implosion, increasing the areal density of the pusher transfers more pressure to the hot spot and increases the hot spot confinement time. There has been a lack of knowledge about the final compressed state of the ablator for implosions at the National Ignition Facility. 14 MeV fusion neutrons inelastically scattering on the remaining carbon ablator excites a nuclear metastable state that emits a prompt 4.4 MeV gamma ray. The gamma reaction history diagnostic data, when reduced by a new data analysis technique, can isolate and measure the carbon gamma rays, which are proportional to the areal density of the ablator during fusion burn. The trends over many National Ignition Facility campaigns show that the ablator areal density is weakly sensitive to the maximum shell velocity, the cold fuel radius, the ablator mass remaining, or the laser picket intensity. Controlled parameter scans reveal that, for specific campaigns, ablator compression has a strong dependence on laser coast time, high Z dopants, and the laser drive foot duration. Using a model of the compressed ablator density profile reveals that the greatest variation of the ablator areal density comes from its thickness, with highly compressed, thin layers having high areal density values. The compression and thickness of the ablator are other metrics that designers should understand to differentiate the types of capsule degradation and maximize the inertial confinement fusion performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Delayed Critical Highly Enriched Uranium Metal Cylinders with Thin Graphite Top and Bottom Reflectors

Nine 7, 11, and 15 in. diam highly enriched uranium (HEU, 93.15 wt % 235 U) metal cylinders were assembled on the vertical assembly machine in the Oak Ridge Critical Experiments Facility (ORCEF) and had 1, 2, or 3 in. thick HLM graphite reflectors on the top and bottom. The experiments, which were performed between April 3, 1970, and February 18, 1971, used 23 operational days at ORCEF. Before those experiments were carried out, unreflected and unmoderated, graphite- and polyethylene-reflected, and polyethylene-moderated HEU metal cylinders had been assembled to obtain delayed criticality at ORCEF in the 1960s and reported by the International Criticality Safety Benchmark Evaluation Project (ICSBEP) at the Nuclear Energy Agency (NEA)*. The data from the nine critical experiments are acceptable for use as criticality safety benchmark experiments for the NEA’s ICSBEP once the uncertainty analysis is completed. Based on previous ICSBEP benchmarks with HEU metal at ORCEF, the uncertainties in k eff are expected to be as low as ±0.0004.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies (M2SF-21SN010301072)

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress in modeling and experimental approaches towards the characterization of chemical and physical phenomena that could impact the long-term safety assessment of heatgenerating nuclear waste disposition in deep-seated clay/shale/argillaceous rock. International collaboration activities such as heater tests, continuous field data monitoring, and postmortem analysis of samples recovered from these have elucidated key information regarding changes in the engineered barrier system (EBS) material exposed to years of thermal loads. Chemical and structural analyses of sampled bentonite material from such tests as well as experiments conducted on these are key to the characterization of thermal effects affecting bentonite clay barrier performance and the extent of sacrificial zones in the EBS during the thermal period. Thermal, hydrologic, and chemical data collected from heater tests and laboratory experiments has been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches (e.g., continuum and discrete) to tackle issues related to flow and transport at various scales of the host-rock, its interactions with barrier materials, and EBS design concept.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Integral and Separate Effects Test Facilities To Support Water Cooled Small Modular Reactors: A Review

This study reviews previous experimental facilities and test programs relevant to water-cooled reactor system design and analysis to meet regulatory compliances. This study aims to find the best solution for designing the required experiments, obtaining necessary test data, and verifying the developed computer code/models to support the new reactor design and development while minimizing cost and time while leveraging experiences from previous facilities to minimize. Nuclear reactor licensing requires supportive design, analysis, and experimental results to ensure the safety of the full-scale prototype reactor in regular operation, as well as during postulated accident scenarios. These reactor design analyses are generally performed using system codes and other associated simulation tools that require assessment, verification and validation using an appropriate experimental dataset. Experimental facilities used for reactor system safety analysis and system code assessments are categorized into integral effects test (IET) and separate effects test (SET) facilities. Further, these IET and SET experiments and studies use geometrically scaled systems to reproduce the prototype system behavior at a reasonable cost, albeit with some scaling-related distortions. The design challenge of these model facilities is to identify and minimize scaling distortions while reproducing the most important operational phenomena in steady-state operation and in postulated accident scenarios. Lessons learned from previous experimental facilities, models, and correlations can support the development of new multipurpose, scaled, hybrid, integrated, and modular experimental facilities for advanced light water-cooled small modular reactors (SMRs). Successful operation of these facilities can significantly reduce upfront reactor development and demonstration costs and time to deployment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

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↗
DOE OSTI2023

Evaluation of Digital Twin Modeling and Simulation

A digital twin has intelligent modules that continuously monitor the condition of the individual components and the whole of a system. Digital twins can provide nuclear power plants (NPP) operators an unprecedented level of monitoring, control, supervision, and security by contributing a greater volume of data for more comprehensive data analysis and increased accuracy of insights and predictions for decision making throughout the entire NPP lifecycle. NPP operators and managers have historically relied on limited, second hand or incomplete data. With proper implementation, digital twins can provide a central hub of all intel that allows for a multidisciplinary view of an NPP. This equips operators and managers with the ability to have more information, context, and intel that can be used for greater granularity during planning and decision making. Digital twins can be used in many activities as the technology has many different concepts surrounding it. From the various definitions of a digital twin within the industry, digital twins can be differentiated by levels of integration/automation. The three main models include digital model, digital shadow, and digital twin. Digital twins offer many potential advancements to the nuclear industry that could reduce costs, improve designs, provide safer operation, and improve their overall security.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Enabling Nuclear and Solar Thermal Propulsion with the Computational Laboratory: Faster and Cheaper Materials Characterization

Nuclear and solar thermal propulsion offer enhanced efficiencies for in-space travel which may open up the outer Solar System to both crewed and automated craft. However, these advanced propulsion systems require cutting-edge materials which are often not easily tested in the laboratory. Ab initio thermodynamics and other computational methods offer a way to test materials at high pressures and temperatures more quickly, and with reduced cost. Here, several case studies are presented which highlight the utility of modern simulation techniques. First, an extensive thermodynamic study was performed at the ab initio level to elucidate the role of hot hydrogen flow on the erosion of four refractory carbides to examine their appropriateness for use as channel coatings. A detailed analysis of reaction products informs estimates of erosion which are validated in comparison with heritage NERVA data. Specific material suggestions are made for both nuclear and solar designs. Secondly, we examined the mechanical behavior and chemical stability of various components of an idealized nuclear cermet core design using techniques spanning from the atomic to microscale. Next, the mechanical and chemical behavior of tungsten (a potential matrix material) and the stability of uranium mononitride (a potential ceramic fuel element), are characterized in the presence of hydrogen and at elevated temperatures with ab initio thermodynamics. Finally, the mechanical response and failure of tungsten under tensile strain is simulated at the micron scale with a combined finite element and dislocation dynamics approach. The resultant stress-strain data agrees well with experiments and leads to a workflow which can incorporate ab initio thermodynamic data into micron-scale simulations and thus provide real-world relevant estimates of erosion and stress-strain behavior. The power of this framework and our plans to use it in the future will be discussed.

William C Tucker↗
DOE OSTI2022

Future Trends in Nuclear Physics Computing

In nuclear physics (NP) today the study of quarks, gluons and their strong interactions extends across a broad research program at a varied range of collaborative scales, from a few collaborators up to large experiments at scales comparable to those typical of high energy physics (HEP). Overall, the software and computing efforts vary accordingly, from pragmatic do-it-yourself approaches among a few, to substantial organized software and computing activities within large experiments. With new experiments starting up and on the horizon [1], and rapidly increasing data volumes [2, 3] and processing demands even at small experiments, the NP community has in recent years been thinking about the next generation of data processing and analysis workflows that will maximize the science output. One context for this discussion has been a series of workshops, “Future Trends in Nuclear Physics Computing” [4]. The most recent in this series took place in Fall 2020, organized by the authors together with colleagues. The workshop focused on identifying the unique aspects of software and computing in NP, and discussing how the NP community could strengthen common efforts and chart a path forward for the next decade, sure to be an exciting one with rich ongoing scientific programs at Brookhaven National Laboratory (BNL), Jefferson Lab (JLab), and other NP facilities, and culminating in datataking at the Electron-Ion Collider (EIC) [5,6,7] in the early 2030s. Without claiming to present a collective view from the workshop and discussions since—fortunately this is not expected of us in this opinion editorial—we offer here our reflections on the topic, informed by the workshop and the summary we authored with our colleagues [8], as well as discussions and developments in the eventful time since.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Towards a New nCTEQ global nPDF release

We discuss the foundation for a new global nCTEQ nuclear PDF analysis, combining a number of our previous analyses into one consistent framework with updates to the underlying theoretical treatment as well as the addition of new available data. In particular, the new global release will be the first nCTEQ release containing neutrino DIS scattering data in a consistent manner together with JLab high-x DIS data and new LHC p-Pb data. These additions will improve the data-driven description of nuclear PDFs in new regions, especially the strange quark and the gluon PDF at low-x.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Predicting the neutrinoless double-β-decay matrix element of 136 Xe using a statistical approach

Calculation of the nuclear matrix elements (NMEs) for double-β decay is of paramount importance for guiding experiments and for analyzing and interpreting the experimental data, especially for the search of the neutrinoless double β decay mode (0v⁢ββ). However, there are currently still large differences between the NME values calculated by different methods, hence a quantification of their uncertainties is very much required. Here, in this paper, we propose a statistical analysis of 0⁢v⁢ββ NME for the 136 Xe isotope, based on the interacting shell model, but using three independent effective Hamiltonians, emphasizing the range of the NMEs' most probable values and its correlations with observables that can be obtained from the existing nuclear data. Consequently, we propose a common probability distribution function for the 0⁢vββ NME, which has a range of (1.55–2.65) at 90% confidence level, with a mean value of 1.99 and a standard deviation of 0.37.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Cosmological parameter estimation with a joint-likelihood analysis of the cosmic microwave background and big bang nucleosynthesis

Here, we present a joint-likelihood analysis of big bang nucleosynthesis (BBN) and cosmic microwave background (CMB) data, consistently combining likelihoods and taking into account uncertainties in nuclear reaction rates for the first time. Bayesian inference is performed on the baryon abundance and the effective number of neutrino species, 𝑁 eff , using a CMB Boltzmann solver in combination with LINX , a new flexible and efficient BBN code. We marginalize over Planck nuisance parameters and nuclear rates to find 𝑁 eff =3.0⁢8$^{+0.15}_{−0.14}$, 2.9⁢4$^{+0.16}_{−0.15}$, or 2.96$^{+0.13}_{−0.14}$, for three separate reaction networks. This framework enables robust testing of the lambda cold dark matter paradigm and its variants with CMB and BBN data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Methods for Continuously Resolving Spectral Shifts in Distributed Optical Fiber Sensors Irradiated to Extreme Neutron Fluence

Optical frequency domain reflectometry (OFDR) is a technique for interrogating distributed optical fiber sensors (DOFS) and involves correlating changes in the Rayleigh backscatter fingerprint for a fiber under test (FUT) with a reference measurement. Recently, under the WIRE-21 experiment sponsored by Nuclear Science User Facilities (NSUF) and performed at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL), silica optical fibers were irradiated to a fast neutron fluence of 1x10^21 n/cm^2/s at temperatures from 200--400 C. As in the cases of high-temperature and high-strain conditions, such high levels of neutron bombardment result in a highly dynamic RBS that evades analysis with conventional methods. This work describes the further development and application of graphical signal processing techniques applied to OFDR-based distributed optical fiber sensors specifically deployed in in-pile applications. While the signal processing techniques developed in this work are applied to DOFS in nuclear environments, they provide a general framework for the analysis of OFDR measurements and a tangible method to yield higher quality data, without imposing additional hardware requirements.

Sweeney, Dan↗
DOE OSTI2024

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↗
DOE OSTI2024

Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO 2 F 2 ), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO 2 F 2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. Finally, during this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Quantitative Determination of Total Cesium in Savannah River Site (SRS) Tank Waste by Inductively Coupled Plasma Emission Spectroscropy

Utilization of the significant and unique wavelength dynamic range (165 to 1100 nm) available on the Leeman Prodigy Inductively Coupled Plasma Emission Spectroscopy (ICP-ES) allows for quantification of cesium using the emission line 894.347 nm without the potential of Barium interference in nuclear waste samples. Samples are added to a Sodium Peroxide Fusion and Lithium Carbonate buffer in 2% nitric acid solution to increase sensitivity of the easily ionizable (<6 eV) cesium for quantitation to 5 pbb. Through direct comparison of analytical data results, the method is proven to be complementary to the Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis (LOQ 100 ppt) in support of the Department of Energy’s (DOE) Nuclear Waste Mission.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

STAND Quickstart Guide

STAND is a flexible web application designed to identify and examine potentially feasible sites where advanced nuclear facilities might be welcomed by host communities. STAND allows the user to explore and provide insight on socioeconomic, proximity, and safety data, generate county reports, review regulatory data, and complete a comparative analysis across multiple sites by following several paths, either individually or sequentially based on the user’s needs and where they are in the deployment process. STAND is best used for the contiguous United States. STAND is not a substitute for the in-depth studies required to qualify a site for hosting a nuclear facility, nor is it a substitute for the necessary community engagement to build trust and seek consent. It can, however, be a valuable resource to aid in the siting process.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Modernization efforts for the R -Matrix code SAMMY [Abstract]

The R-Matrix code SAMMY is a widely used nuclear data evaluation code focused on the resolved range, which includes corrections for experimental effects. The code is still mostly written in Fortran 77, and uses a memory management system suitable for the time of its initial writing (1984). A modernization effort is under way to bring the code in-line with modern software development practices. A continuous-integration testing framework was added, automating the large existing set of test cases. It is run on every commit. The memory management was updated to current standard practices suitable for modern software analysis tools. The code can be obtained from https://code.ornl.gov/RNSD/SAMMY. The resonance parameters and covariance information are now stored in C++ objects shared by SAMMY and AMPX, the processing code that generates nuclear data libraries for SCALE. This allows for easier maintenance and access to the resonance parameters inside and outside of SAMMY. This feature is already used by accessing and changing parameters in memory in the Bayesian Monte Carlo Evaluation Framework for Cross Sections Nuclear Data and Integral Benchmark Experiments project, Further plans include the switch to the ENDF reading and writing routines in AMPX, as these routines are more robust, easier to maintain, and support more features. Of note here is support for the new GNDS format. Previously it wasn’t easy to share the full covariance matrix for evaluations containing more than one isotope due to limitations on the ENDF format; this is now supported in GNDS. The data are currently available in a binary SAMMY format and can be exported to GNDS to make them more widely available and sharable. The next step will be to use the same resonance processing code at 0K in AMPX and SAMMY as one of the available Reich-Moore R-Matrix formalism. The first step toward this goal is to isolate the reconstruction into a module that takes resonance parameters as its input and does not depend on SAMMY global parameters. This goal has been achieved and it should now be possible to more easily change the resonance formalism and add enhancements as the Phenomenological R-Matrix parameterization of direct, doorway, and compound nuclear reactions discussed elsewhere on this conference. This concerted modernization and enhancement effort provides multiple advantages to the nuclear data community. It will allow parameter optimization using enhanced formalisms, including experimental effects, that better match complex experimental data. Then those evaluated parameters can immediately be passed off to AMPX to be reconstructed with the exact same cross section model and be put into a data library for subsequent testing using SCALE and the Valid Benchmark suite or other suitable benchmark suites.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗