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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Bayesian Evaluation Including Covariance Matrices of Neutron-induced Reaction Cross Sections of {sup 181}Ta

A new evaluation of neutron-induced reactions on {sup 181}Ta using a consistent procedure based on Bayesian statistics is presented. Starting point of the evaluation is the description of nuclear reactions via nuclear models implemented in TALYS 1.4. A retrieval of experimental data was performed and covariance matrices of the experiments were generated from an extensive study of the corresponding literature. All reaction channels required for a transport file up to 200 MeV have been considered and the covariance matrices of cross section uncertainties for the most important channels are determined. The evaluation has been performed in one step including all available experimental data. A comparison of the evaluated cross sections and spectra with experimental data and available evaluations is performed. In general the evaluated cross section reflect our best knowledge and give a fair description of the observables. However, there are few deviations from expectation which clearly indicate the impact of the prior and the need to account for model defects. Using the results of the evaluation a complete ENDF-file similarly to those of the TENDL library is generated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Majorana parameters of the interacting boson model of nuclear structure and their implication for 0 ν β β decay

Here, the well-known spherical-deformed-transitional nucleus and potential 0$\textit{νββ}$ emitter 150 Nd and its daughter 150 Sm were investigated in nuclear resonance fluorescence experiments using quasimonoenergetic, linearly polarized γ-ray beams. For both nuclei transitions from the 1 + scissors mode to the $0^+_2$ and $2^+_2$ states were observed for the first time and their respective $\textit{M}$ 1 transition strengths were determined. Through a systematic investigation, a sensitivity of these transition strengths to the three Majorana parameters of the interacting boson model-2 (IBM-2) was established. In combination with the novel experimental data, this poses strong constraints to the Majorana parameters in improved IBM-2 representations of both nuclei. A subsequent recalculation of the nuclear matrix elements (NMEs) for the 150 Nd → 150 Sm 0$\textit{νββ}$ decay in the IBM-2 with these improved representations results in $M^{(0νββ)}_{\text{IBM-2}}[0^+_1]$ = 3.35 for the NME for 0$\textit{νββ}$ decay into the ground state of 150 Sm and $M^{(0νββ)}_{\text{IBM-2}}[0^+_2]$ = 1.30 for 0$\textit{νββ}$ decay to its $0^+_2$ state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Expanded analysis of machine learning models for nuclear transient identification using TPOT

Industries around the world are becoming more and more data driven. The nuclear field is no exception with several different applications being proposed. One popular area of research is the use of machine learning in transient detection. This paper seeks to build upon a previous study which made use of the AutoML package TPOT to train traditional machine learning models to classify transient events occurring with a reactor. Synthetic data was once again collected using a GPWR reactor simulator. Data on 12 different events was collected using 15 different initial conditions. Here, a dataset consisting of over 100,000 data points was compiled and used to train 7 different machine learning models using a pre-defined TPOT dictionary with 12 different preprocessing techniques. Three of the trained models were able to produce validation results in the 90s with the expanded dataset. Once the models were trained, it was possible to look into where during the simulation, misclassifications occurred. Using these three models, analysis was done to determine if TPOT could be used to train models that were effective if important features were missing. The results from this were positive with the newly trained models scoring close to the original models. Finally, to conclude this study, the three high performing models were retrained using different random states to see if there was any major variation when different states were used.

42 ENGINEERING↗
DOE OSTI2020

Self-accelerated corrosion of nuclear waste forms at material interfaces

The US plan for high-level nuclear waste includes the immobilization of long-lived radionuclides in glass or ceramic waste forms in stainless-steel canisters for disposal in deep geological repositories. Here we report that, under simulated repository conditions, corrosion could be significantly accelerated at the interfaces of different barrier materials, which has not been considered in the current safety and performance assessment models. Severe localized corrosion was found at the interfaces between stainless steel and a model nuclear waste glass and between stainless steel and a ceramic waste form. The accelerated corrosion can be attributed to changes of solution chemistry and local acidity/alkalinity within a confined space, which significantly alter the corrosion of both the waste-form materials and the metallic canisters. The corrosion that is accelerated by the interface interaction between dissimilar materials could profoundly impact the service life of the nuclear waste packages, which, therefore, should be carefully considered when evaluating the performance of waste forms and their packages. Moreover, compatible barriers should be selected to further optimize the performance of the geological repository system.

Guo, Xiaolei↗
DOE OSTI2022

Benchmarking intra-nuclear cascade models for neutrino scattering with relativistic optical potentials

The description of final-state interactions (FSI) in the large phase space probed in neutrino experiments poses a great challenge. In neutrino experiments, which operate under semi-inclusive conditions, cascade models are commonly used for this task, while under exclusive conditions FSI can be treated with relativistic optical potentials (ROP). We formulate conditions under which the ROP approach and cascade model can be directly compared. We feed the NEUT cascade with events from a relativistic distorted-wave impulse approximation calculation that uses the real part of an optical potential. Cuts on the missing energy of the resulting events are applied to define a set of events that can be directly compared to RDWIA calculations with the full optical potential. The NEUT cascade and ROP agree for proton kinetic energies $T_p > 150$ MeV for carbon, oxygen and calcium nuclei when a realistic nuclear density is used to introduce events in the cascade. For $T_p < 100$ MeV the ROP and NEUT cross sections differ in shape and differences in magnitude are larger than 50 %. Single transverse variables allow to distinguish different approaches to FSI, but due to a large non-QE contribution the comparison to T2K data does not give an unambiguous view of FSI. We discuss electron scattering and argue that with a cut in missing energy FSI can be studied with minimal confounding factors in e.g. $e4\nu$. The agreement of the ROP and NEUT for T2K conditions lends confidence to these models as a tool in oscillation analyses for sufficiently large nucleon kinetic energies. These results urge for caution when a cascade model is applied for small nucleon energies. The assessment of model assumptions relevant to this region are strongly encouraged. This paper provides novel constraints on cascade models from proton-nucleus scattering that can be easily applied to other neutrino event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2006

Multiphysics Thrust Chamber Modeling for Nuclear Thermal Propulsion

The objective of this effort is to develop an efficient and accurate thermo-fluid computational methodology to predict environments for a solid-core, nuclear thermal engine thrust chamber. The computational methodology is based on an unstructured-grid, pressure-based computational fluid dynamics formulation. A two-pronged approach is employed in this effort: A detailed thermo-fluid analysis on a multi-channel flow element for mid-section corrosion investigation; and a global modeling of the thrust chamber to understand the effect of heat transfer on thrust performance. Preliminary results on both aspects are presented.

Wang, Ten-See↗
DOE OSTI2023

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?

Machine learning (ML) has been leveraged to tackle a diverse range of tasks in almost all branches of nuclear engineering. Many of the successes in ML applications can be attributed to the recent performance breakthroughs in deep learning, the growing availability of computational power, data, and easy-to-use ML libraries. However, these empirical successes have often outpaced our formal understanding of the ML algorithms. An important but under-rated area is uncertainty quantification (UQ) of ML. ML-based models are subject to approximation uncertainty when they are used to make predictions, due to sources including but not limited to, data noise, data coverage, extrapolation, imperfect model architecture and the stochastic training process. The goal of this paper is to clearly explain and illustrate the importance of UQ of ML. We will elucidate the differences in the basic concepts of UQ of physics-based models and data-driven ML models. Various sources of uncertainties in physical modeling and data-driven modeling will be discussed, demonstrated, and compared. We will also present and demonstrate a few techniques to quantify the ML prediction uncertainties, including Monte Carlo dropout, deep ensemble, Bayesian neural networks, Gaussian Processes and conformal prediction. Lastly, we will discuss the need for building a verification, validation and UQ framework to establish ML credibility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Bayesian calibration of a hybrid nuclear collision model using $\textit{p}$₋Pb and Pb-Pb data at energies available at the CERN Large Hadron Collider

Here, we posit a unified hydrodynamic and microscopic description of the quark-gluon plasma (QGP) produced in ultrarelativistic p₋Pb and Pb-Pb collisions at $\sqrt{s}_\text{NN}$ = 5.02 TeV and evaluate our assertion using Bayesian inference. Specifically, we model the dynamics of both collision systems using initial conditions with parametric nucleon substructure, a preequilibrium free streaming stage, event-by-event viscous hydrodynamics, and a microscopic hadronic afterburner. Free parameters of the model, which describe the initial state and QGP medium are then simultaneously calibrated to fit charged-particle yields, mean $p_T$, and flow cumulants. We argue that the global agreement of the calibrated model with the experimental data strongly supports the existence of hydrodynamic flow in small collision systems at ultrarelativistic energies, and that the flow produced develops at length scales smaller than a single proton. Posterior estimates for the model's input parameters are obtained, and new insights into the temperature dependence of the QGP transport coefficients and event-by-event structure of the proton are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Construction of a Cyber Attack Model for Nuclear Power Plants

The consideration of how one compromised digital equipment can impact neighboring equipment is critical to understanding the progression of cyber attacks. The degree of influence that one component may have on another depends on a variety of factors, including the sharing of resources such as network bandwidth or processing power, the level of trust between components, and the inclusion of segmentation devices such as firewalls. The interactions among components via mechanisms that are unique to the digital world are not usually considered in traditional PRA. This means potential sequences of events that may occur during an attack may be missed if one were to only look at conventional accident sequences. This paper presents a method where, starting from the initial attack vector, the progression of a cyber attack can be modeled. The propagation of the attack is modeled by considering certain attributes of the digital components in the system. These attributes determine the potential vulnerability of a component to a class of attack and the capability gained by the attackers once they are in control of the equipment. The use of attributes allows similar components (components with the same set of attributes) to be modeled in the same way, thereby reducing the computing resources required for analysis of large systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Construction of a cyber attack model for nuclear power plants - 115

The consideration of how a compromised digital component can impact neighboring components is critical to understanding the progression of cyber attacks. The degree of influence that one component may have on another depends on a variety of factors, including the sharing of resources such as network bandwidth or processing power, the level of trust between components, and the inclusion of segmentation devices such as firewalls. The interactions among components via mechanisms that are unique to the digital world are not usually considered in traditional probabilistic risk assessment (PRA). This means potential sequences of events that may occur during an attack may be missed if one were to only look at conventional accident sequences. This paper presents a method where, starting from the initial attack vector, the progression of a cyber attack can be modeled. The propagation of the attack is modeled by considering certain attributes of the digital components in the system. These attributes determine the potential vulnerability of a component to different classes of attack and the capability gained by the attackers once they are in control of the equipment. The use of attributes allows similar components (components with the same set of attributes) to be modeled in the same way, thereby reducing the computing resources required for analyzing large systems. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Rancor-HUNTER: Using a Simulator Engine for Realistic Human Performance Modeling of Nuclear Power Operations

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a software system to simulate human performance in support of human reliability analysis (HRA) in nuclear power plants. This paper summarizes recent work to integrate HUNTER with a plant simulator, namely the Rancor Microworld Simulator. Rancor is an offshoot of earlier work at Idaho National Laboratory (INL) to support plant modernization. The graphical software tools used to mimic digital human-system interface upgrades at INL’s Human Systems Simulation Laboratory were linked to the Rancor Microworld Simulator, an INL-developed simplified plant model. HUNTER becomes a “virtual operator” coupled to the Rancor simulator, thereby allowing a tight coupling between a digital human twin and a digital twin of the plant. Rancor-HUNTER may be run through Monte Carlo iterations across a dynamic range of performance shaping factors, thereby producing distributions of human performance in terms of procedure paths, errors instantiations, and task durations. This paper overviews the various unique features of Rancor-HUNTER and presents an example run of Rancor-HUNTER for a startup scenario.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

A Review of Finite Element Method Models for Nuclear Graphite Applications

Graphite components serve as structural support and as a neutron moderator in multiple nuclear power stations and is also a prospective material in Generation IV reactor concepts. The environment (e.g. high temperature and intense radiation) within a graphite core changes the geometry, microstructure and material properties of the graphite components, that could limit the lifetime (i.e. safe operation) of a reactor. Some of the assessments made for graphite reactor core components include Finite Element Method (FEM) simulations. These simulations are used to estimate the stress state and strain state and probability of failure of irradiated graphite components. FEM also forms part of the validation of measurements or as a complementary technique to experimental procedures in graphite research. A comprehensive overview of FEM methodologies is provided in this review, including: FEM software, basics steps to set up a FEM model, and analytical solutions used to validate simulations for this field of study. In conclusion, the objective of this paper is to inform researchers in the different available FEM techniques and tools used in the research of nuclear graphite.

42 ENGINEERING↗
DOE OSTI2016

Neutrino-induced reactions and neutrino scattering with nuclei in low and high neutrino energy

We reviewed present status regarding theoretical approaches for neutrino-induced reactions and neutrino scattering. With a short introduction of relevant data, our recent calculations by distorted-wave Born approximation (DWBA) for quasielastic region are presented for MiniBooNE data. We also discussed that one step-process estimated by the DWBA is comparable to the two-step process, which has been usually used in the neutrino-nucleosynthesis. For much higher energy neutrino data, such as NOMAD data, elementary process approach was shown to be useful instead of using complicated nuclear models. But, in the low energy region, detailed nuclear structure model, such as QRPA and shell model, turn out to be inescapable to explain the reaction data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Special Nuclear Geometric Modeling

This report is a summary of our summer interns project that focused on investigating the usefulness of the Gamma Detector Response and Analysis Software (GADRAS) into the Material Control & Accountability (MC&A) Measurements Team. The project's findings highlight the advantages of using GADRAS and demonstrate its value in improving the MC&A Measurements Team's analytical capabilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

High-accuracy Geant4 simulation and semi-analytical modeling of nuclear resonance fluorescence

Nuclear resonance fluorescence (NRF) is a photonuclear interaction that enables highly isotope-specific measurements in both pure and applied physics scenarios. High-accuracy design and analysis of NRF measurements in complex geometries is aided by Monte Carlo simulations of photon physics and transport, motivating Jordan and Warren (2007) to develop the G4NRF codebase for NRF simulation in Geant4. In this work, we enhance the physics accuracy of the G4NRF code and perform improved benchmarking simulations. The NRF cross section calculation in G4NRF, previously a Gaussian approximation, has been replaced with a full numerical integration for improved accuracy in thick-target scenarios. A high-accuracy semi-analytical model of expected NRF count rates in a typical NRF measurement is then constructed and compared against G4NRF simulations for both simple homogeneous and more complex heterogeneous geometries. Furthermore, agreement between rates predicted by the semi-analytical model and G4NRF simulation is found at a level of ~1% in simple test cases and ~3% in more realistic scenarios, improving upon the ~20% level of the initial benchmarking study and establishing a highly-accurate NRF framework for Geant4.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Nuclear-Physics Model of the Knee in the EAS Spectrum

Spectra of the most energetic hadrons in cores of extensive air showers (EAS) were obtained for the first time in the HADRON hybrid experiment in Tien Shan mountains. The spectra in question exhibit a scaling violation, which requires invoking nontrivial effects in order to explain this circumstance. In the present article, unusual data on pp-interaction cross sections from recent experiments at the Large Hadron Collider are analyzed with this aim in view. A comparison with data at lower energies shows that the elastic cross section for pp interaction grows faster than the respective inelastic cross section. It would be natural to expect that a similar or a stronger effect is present in nucleus–nucleus interactions in cosmic rays. A possible change in the properties of nuclear cascades in the Earth’s atmosphere provides the possibility of discussing a new interpretation of the knee in the EAS spectrum and some exotic phenomena observed in cosmic-ray experiments. This interpretation is proposed for the first time. Particular attention is given to unique data from the HADRON hybrid experiment.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Development of an object-oriented ORIGEN for advanced nuclear fuel modeling applications

The ORIGEN package serves as the core depletion and decay calculation module within the SCALE code system. A recent major re-factor to the ORIGEN code architecture as part of an overall modernization of the SCALE code system has both greatly enhanced its maintainability as well as afforded several new capabilities useful for incorporating depletion analysis into other code frameworks. This paper will present an overview of the improved ORIGEN code architecture (including the methods and data structures introduced) as well as current and potential future applications utilizing the new ORIGEN framework. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗