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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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Hydrogen turbopump cycles for obtaining high engine inlet pressures in advanced nuclear rockets, and data on gaseous nuclear reactors and heavy gas containment
We present an HST I-band Planetary Camera image of the nuclear region of NGC 4314, an anemic barred galaxy with recent star formation confined to a nuclear ring. These data resolve the nuclear ring into multiple sites of new star formation and resolve associated dust lanes into discrete clouds. Deconvolution results in at least 0.13 arcsec resolution, as demonstrated by the de Vaucouleurs r exp 1/4 law. Contrasted with similar studies of M87 and NGC 7457, we find no photometric evidence for an extreme concentration of stars in the center of NGC 4314. We identify an oval distortion of length 8 arcsec in the nuclear region, using ellipse-fitting routines and the unsharp masked frame. This nuclear bar has newer stars near its ends. We catalog 14 star clusters associated with H II regions in the nuclear ring. As an additional demonstration of the resolution achieved, the integral size distribution of these clusters is described by an exponential relationship which prevails down to 0.14 arcsec.
Yttrium hydride (YH x ) is of interest as a high-temperature moderator material in advanced nuclear reactor systems because of its superior ability to retain hydrogen at elevated temperatures. Thermal neutron scattering laws (TSL) for hydrogen bound in yttrium hydride (H-YH 2 ) and yttrium bound in yttrium hydride (Y-YH 2 ) were previously evaluated by Naval Nuclear Laboratory using the ab initio approach and released in ENDF/B-VIII.0. In that work, density functional theory, incorporating the generalized gradient approximation (GGA) for the exchange-correlation energy, was used to simulate the face-centered cubic structure of YH 2 and calculate the interatomic Hellmann-Feynman forces for a 2×2×2 supercell containing 96 atoms. Lattice dynamics calculations using PHONON were used to determine the phonon density of states. The calculated phonon density of states for H and Y in YH 2 were then used to prepare H-YH 2 and Y-YH 2 TSL evaluations, in the incoherent approximation, using the LEAPR module of NJOY. In addition, elastic scattering was assumed to be incoherent for both H and Y. While the incoherent elastic scattering approximation is appropriate for H-YH 2 , it introduces an undesirable approximation for Y-YH 2 . In this work, we re-evaluate the TSL for Y-YH 2 using FLASSH (Full Law Analysis Scattering System Hub). Y-YH 2 is evaluated using the FLASSH generalized coherent elastic scattering capability in order to capture the Bragg peaks associated with the YH 2 crystal structure which were neglected in the prior NJOY-based evaluation due to limitations in LEAPR. An experimental approach to validate the Y-YH 2 TSL using neutron transmission measurements is discussed.
With the recent successful attempts against the digital control systems of critical infrastructures, there is a need to develop new defense strategies that recognize two important realities, 1) state- sponsored attackers can rely on a number of techniques including espionage, social engineering, and brute force techniques, etc. to gain access to the raw data used to control system behavior, 2) attackers can falsify operational data in manners that do not trigger conventional outlier/anomaly detection techniques in order to go undetected, which is referred to as false data injection attacks. Therefore, there is a strong need to explore another class of defense measures, referred to as physical process defense, serving as a new line of defense in the event existing defenses relying on information protection measures are breached. This physical process defenses utilize the physics and engineering models of the system to build unique signatures for genuine system behavior. If successful, the signatures would be able to detect attacks that falsify the operational data and render them harmless before they can inflict physical damage on the system. This report is focused on exploring the feasibility of physical process defenses for nuclear reactors, and their associated functional requirements to maximize their resiliency against state-sponsored, or equivalent, attackers.
Recently, Chatterjee et al [1] used a hadronic transport model to estimate the resolution with which various experimental quantities select the impact parameter of relativistic heavy ion collisions at collision energies relevant to the Beam Energy Scan (BES) program at the Relativistic Heavy Ion Collider (RHIC). Measures based on particle multiplicity at forward rapidity were found to be significantly worse than those based on midrapidity multiplicity. Using the same model, we show that a slightly more sophisticated measure greatly improves the resolution based on forward rapidity particles; this improvement persists even when the model is filtered through a realistic simulation of a recent upgrade detector to the STAR experiment. Furthermore, these results highlight the importance of optimizing centrality measures based on particles detected at forward rapidity, especially for experimental studies that search for a critical point in the QCD phase diagram. Such measurements usually focus on proton multiplicity fluctuations at midrapidity, hence selecting events based on multiplicity at midrapidity raises the possibility of nontrivial autocorrelations.
This presentation begins by providing an overview of the research and discusses recent efforts in validating thermal neutron scattering cross sections, including differential cross section measurements at ORNL for evaluation and validation, total cross section measurements at RPI, pulsed-neutron die-away experiments at LLNL, and integral criticality experiments by LLNL. The presentation also proposes a methodology not only for validating thermal scattering files that utilizes all available experimental data, but also for evaluating new libraries as demonstrated on polystyrene. In conclusion, polystyrene evaluation was conducted using multiple experiments, including differential and integral. The proposed methodology has been shown to improve neutron transport and files have been submitted to NNDC for inclusion in ENDF/B-VIII.1 release. MCT-012 & PCM-002 has been relatively insensitive to changes in $\mathcal{S}(α,β)$. The research found that differences in differential results don’t always propagate to differences in integral results, hence why evaluation of differential data important. Future work on the project is also discussed.
This presentation discusses the motivations behind the project, which include facilitating compact formulation for TSL data, extending AI knowledge, and providing advanced reactor simulation framework. It also discusses how the project accounts for beryllium and graphite complexity, including atomistic, dynamical, and neural. Additionally, new material-informed neural thermal scattering (NeTS) Modules are examined. The implications, conclusions, and plan future work for the project are also discussed.
With the reduction of experimental activities in several countries accompanied by closing of many experimental facilities, the need to preserve the valuable information on the performed radiation shielding benchmarks became increasingly crucial. Since the early 1990's the Organization for Economic Cooperation and Development's Nuclear Energy Agency Data Bank (OECD/NEADB) and the Radiation Safety Information Computational Center (RSICC) are working together on the Shielding Integral Benchmark Archive and Database (SINBAD) project to preserve and make available the information on the past shielding benchmark experiments. The OECD NEA Working Party on Scientific Issues of Reactor Systems (WPRS) Expert Group on Radiation Transport and Shielding (EGRTS) was started in 2011 with the mandate among others, to monitor, steer and support the continued development of the SINBAD database. The database comprises now 102 shielding benchmarks, divided into three categories, covering both low and inter-mediate energy particles applications: fission reactor shielding (48 benchmarks), fusion blanket neutronics (31), and accelerator shielding (23) benchmarks. They are fundamental to ensure that modelling tools meet the requirements of nuclear industry and licensing needs. Validation of nuclear cross-section data, nuclear codes and models as well as nuclear design components are few examples of the use of the database. (authors)
This presentation discusses the Bayesian Monte Carlo evaluation framework of differential and integral data, specifically in relation to two methods that are based on Bayes theorem, which assumes that all PDFs are normal (Gaussian) and that they use a linear approximation for IBEs. The presentation states that basic components of the MC evaluation framework include the computation of random MC ensemble from ENDF File 32, the simulation of IBEs and R-matrix cross section compared to experimental data, and the computation of weighted averages. It also states that the application to U-233 indicates deviation from the conventional linear approximation. In conclusion, evaluation framework will require MCMC method e.g., Metropolis-Hastings (M.-H.).
Experimental data on the isotopic concentrations in irradiated nuclear fuel represent one of the primary methods for validating computational methods and nuclear data used for reactor and spent fuel depletion simulations that support nuclear fuel cycle safety and safeguards programs. Measurement data have previously not been available to users in a centralized or searchable format, and the majority of accessible information has been, for the most part, limited to light-water-reactor designs. This paper describes a recent initiative to compile spent fuel benchmark data for additional reactor designs used throughout the world that can be used to validate computer model simulations that support nuclear energy and nuclear safeguards missions. Experimental benchmark data have been expanded to include VVER-440, VVER-1000, RBMK, graphite moderated MAGNOX, gas cooled AGR, and several heavy-water moderated CANDU reactor designs. Additional experimental data for pressurized light water and boiling water reactor fuels has also been compiled for modern assembly designs and more extensive isotopic measurements. These data are being compiled and uploaded to a recently revised structured and searchable database, SFCOMPO, to provide the nuclear analysis community with a centrally-accessible resource of spent fuel compositions that can be used to benchmark computer codes, models, and nuclear data. The current version of SFCOMPO contains data for eight reactor designs, 20 fuel assembly designs, more than 550 spent fuel samples, and measured isotopic data for about 80 nuclides.
Multisensor networks deployed at nuclear facilities can be leveraged to collect data used as inputs to machine learning models predicting nuclear safeguard relevant information. This work demonstrates an application of this idea by regressing nuclear reactor power levels, a key indicator for nuclear safeguard verification, at the McClellan Nuclear Research Center using data collected by five Merlyn multisensor platforms with LASSO and LSTM models. This work also demonstrates the use of Leave One Node Out to measure the importance of each multisensor for this regression problem providing insight into model explainability and allowing inferential hypotheses about the nuclear facility to be made. This work can be used as a starting point for future development of methods for regression on reactor power levels at nuclear facilities using multisensor network data.
Purpose: To investigate potential causes for differences in TG-43 brachytherapy dosimetry parameters in the existent literature for the model IAI-125A{sup 125}I seed and to propose new standard dosimetry parameters. Methods: The MCNP5 code was used for Monte Carlo (MC) simulations. Sensitivity of dose distributions, and subsequently TG-43 dosimetry parameters, was explored to reproduce historical methods upon which American Association of Physicists in Medicine (AAPM) consensus data are based. Twelve simulation conditions varying{sup 125}I coating thickness, coating mass density, photon interaction cross-section library, and photon emission spectrum were examined. Results: Varying{sup 125}I coating thickness, coating mass density, photon cross-section library, and photon emission spectrum for the model IAI-125A seed changed the dose-rate constant by up to 0.9%, about 1%, about 3%, and 3%, respectively, in comparison to the proposed standard value of 0.922 cGy h{sup −1} U{sup −1}. The dose-rate constant values by Solberg et al. [“Dosimetric parameters of three new solid core {sup 125}I brachytherapy sources,” J. Appl. Clin. Med. Phys. 3, 119–134 (2002)], Meigooni et al. [“Experimental and theoretical determination of dosimetric characteristics of IsoAid ADVANTAGE™ {sup 125}I brachytherapy source,” Med. Phys. 29, 2152–2158 (2002)], and Taylor and Rogers [“An EGSnrc Monte Carlo-calculated database of TG-43 parameters,” Med. Phys. 35, 4228–4241 (2008)] for the model IAI-125A seed and Kennedy et al. [“Experimental and Monte Carlo determination of the TG-43 dosimetric parameters for the model 9011 THINSeed™ brachytherapy source,” Med. Phys. 37, 1681–1688 (2010)] for the model 6711 seed were +4.3% (0.962 cGy h{sup −1} U{sup −1}), +6.2% (0.98 cGy h{sup −1} U{sup −1}), +0.3% (0.925 cGy h{sup −1} U{sup −1}), and −0.2% (0.921 cGy h{sup −1} U{sup −1}), respectively, in comparison to the proposed standard value. Differences in the radial dose functions between the current study and both Solberg et al. and Meigooni et al. were <10% for r ≤ 5 cm, and increased for r > 5 cm with a maximum difference of 29% at r = 9 cm. In comparison to Taylor and Rogers, these differences were lower (maximum of 2% at r = 9 cm). For the similarly designed model 6711 {sup 125}I seed, differences did not exceed 0.5% for 0.5 ≤ r ≤ 10 cm. Radial dose function values varied by 1% as coating thickness and coating density were changed. Varying the cross-section library and source spectrum altered the radial dose function by 25% and 12%, respectively, but these differences occurred at r = 10 cm where the dose rates were very low. The 2D anisotropy function results were most similar to those of Solberg et al. and most different to those of Meigooni et al. The observed order of simulation condition variables from most to least important for influencing the 2D anisotropy function was spectrum, coating thickness, coating density, and cross-section library. Conclusions: Several MC radiation transport codes are available for calculation of the TG-43 dosimetry parameters for brachytherapy seeds. The physics models in these codes and their related cross-section libraries have been updated and improved since publication of the 2007 AAPM TG-43U1S1 report. Results using modern data indicated statistically significant differences in these dosimetry parameters in comparison to data recommended in the TG-43U1S1 report. Therefore, it seems that professional societies such as the AAPM should consider reevaluating the consensus data for this and others seeds and establishing a process of regular evaluations in which consensus data are based upon methods that remain state-of-the-art.
The reactor physics related integral experiments are significant to criticality safety analysis and the design of the next generation nuclear system. Measurements of parameters such as prompt neutron decay constant α, prompt neutron generation time Λ, effective delayed neutron fraction β{sub eff}, neutron importance distribution, etc., can provide data for the verification of calculation methods, computer codes and cross-section data in criticality safety analysis and test the design of new reactors. Among these parameters, neutron importance distribution has its unique value. Beside verification and validation of nuclear data, computer codes, and simulation methods, the experimental results of neutron importance distribution are also useful to the correcting of the spatial effects in Rossi-α measurement, which is based on point-reactor neutron kinetics. The relative neutron importance distribution experiments were performed on the {sup 235}U fast critical reactor of China Academy of Engineering Physics (CAEP). The key experimental objective was to obtain the importance distribution data for nuclear data validation and criticality safety analysis. We demonstrate in this paper the experiment and the data analysis. {sup 252}Cf neutron importance spatial distributions in the diametral hole of a depleted uranium reflected {sup 235}U fast critical reactor were measured. The evaluated uncertainties of the experiment data were varying with the source location but within 1.5% ranges in all. The experiment results can provide useful data for applications like nuclear data validation and the determination of rectification factor R of Rossi-a measurements. However, the experimental uncertainties are not satisfying and can be further reduced by using a {sup 252}Cf source with much higher intensity, recording more precisely the absolute position of the neutron source, and carrying out the experiment in more shallow subcritical states in which the system multiplication is larger. (authors)
Initial results from a topological analysis of CC “0 pion” muon neutrino events in LAr collected by the ArgoNeuT experiment on the NuMI LE beam at Fermilab (in the few GeV energy region) are presented and compared with predictions from MC simulations. A new analysis method, based on the reconstruction of exclusive topologies, fully exploiting the LArTPC technique capabilities, is used to analyze the events and study nuclear effects in neutrino interactions on Argon nuclei. Multiple protons accompanying the leading muon and the presence of vertex activity are clearly visible (and measured) in the events. Ratios among rates of different exclusive topologies provide indications of the size of nuclear effects in neutrino-nucleus interactions in LAr.
Here, in this article, we present the High-Performance Output (HiPO) data format developed at Jefferson Laboratory for storing and analyzing data from Nuclear Physics experiments. The format was designed to efficiently store large amounts of experimental data, utilizing modern fast compression algorithms. The purpose of this development was to provide organized data in the output, facilitating access to relevant information within the large data files. The HiPO data format has features that are suited for storing raw detector data, reconstruction data, and the final physics analysis data efficiently, eliminating the need to do data conversions through the lifecycle of experimental data. The HiPO data format is implemented in C++ and JAVA, and provides bindings to FORTRAN, Python, and Julia, providing users with the choice of data analysis frameworks to use. In this paper, we will present the general design and functionalities of the HiPO library and compare the performance of the library with more established data formats used in data analysis in High Energy and Nuclear Physics (such as ROOT and Parquete). In columnar data analysis, HiPO surpasses established data formats in performance and can be effectively applied to data analysis in other scientific fields.
Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.
The goal of the project was to develop a procedure to generate covariance matrix for S( α,β ) data that incorporated both computational simulations and experimental data. Experimental data and computer simulation fit is achieved using the Unified Monte Carlo (UMC) method. The framework is material & simulation method independent, and this is demonstrated using light water. A methodology was developed for generalized generation of covariances for thermal scattering files. The framework was subsequently tested on light water by generating covariance of pDOS with encouraging results. Preliminary results suggest temperature effects of polyethylene may warrant further investigation.
Experimental data from reaction and decay studies on nuclei with A=216 have been reviewed. Elements included in this review span from mercury (Z=80) to uranium (Z=92). Based on the published data, level and decay schemes are presented for the evaluated nuclides. In conclusion, this work updates and supersedes the previous A=216 evaluation (2007Wu02).