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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Proton transparency and neutrino physics: New methods and modeling

Extracting accurate results from neutrino oscillation and cross section experiments requires accurate simulation of the neutrino-nucleus interaction. The rescattering of outgoing hadrons (final state interactions) by the rest of the nucleus is an important component of these interactions. We present a new measurement of proton transparency (defined as the fraction of outgoing protons that emerge without significant rescattering) using electron-nucleus scattering data recorded by the CLAS detector at Jefferson Laboratory on helium, carbon, and iron targets. This analysis uses a new data-driven method to extract the transparency. It defines transparency as the ratio of electron-scattering events with a detected proton to quasi-elastic electron-scattering events where a proton should have been knocked out. Our results are consistent with previous measurements that determined the transparency from the ratio of measured events to theoretically predicted events. We find that the GENIE event generator, which is widely used by oscillation experiments to simulate neutrino-nucleus interactions, needs to better describe both the nuclear ground state and proton rescattering in order to reproduce our measured transparency ratios, especially at lower proton momenta.

direct reactions↗
DOE OSTI2024

Heterogeneous flexibility can contribute to chromatin segregation in the cell nucleus

The highly and slightly condensed forms of chromatin, heterochromatin and euchromatin, respectively, segregate in the cell nucleus. Heterochromatin is more abundant in the nucleus periphery. Here, in this work, we study the mechanism of heterochromatin segregation by modeling interphase chromosomes as diblock ring copolymers confined in a rigid spherical shell using molecular dynamics simulations. In our model, heterochromatin and euchromatin are distinguished by their bending stiffnesses only, while an interaction potential between the spherical shell and chromatin is used to model lamin-associated proteins. Our simulations indicate that in the absence of attractive interactions between the nuclear shell and the chromatin, most heterochromatin segregates towards the nuclear interior due to the depletion of less flexible heterochromatin segments from the nuclear periphery. This inverted chromatin distribution, which is opposite to the conventional case with heterochromatin dominating at the periphery, is in accord with experimental observations in rod cells. This “inversion” is also found to be independent of the heterochromatin concentration and chromosome number. The chromatin distribution at the periphery found in vivo can be recovered by further increasing the bending stiffness of heterochromatin segments or by turning on attractive interactions between the nuclear shell and heterochromatin. Our results indicate that the bending stiffness of chromatin could be a contributor to chromosome organization along with differential effects of HP ⁢1⁢𝛼-driven phase segregation and of loop extruders and interactions with the nuclear envelope and topological constraints.

biomolecular & subcellular processes↗
DOE OSTI2024

Electronic Coherences in Molecules: The Projected Nuclear Quantum Momentum as a Hidden Agent

Electronic coherences are key to understanding and controlling photoinduced molecular transformations. Here, we identify a crucial quantum-mechanical feature of electron-nuclear correlation, the projected nuclear quantum momenta, essential to capture the correct coherence behavior. For simulations, we show that, unlike traditional trajectory-based schemes, exact-factorization-based methods approximate these correlation terms and correctly capture electronic coherences in a range of situations, including their spatial dependence, an important aspect that influences subsequent electron dynamics and that is becoming accessible in more experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Neutrino emission from binary neutron star mergers: characterising light curves and mean energies

Abstract Neutrinos are copiously emitted by neutron star mergers, due to the high temperatures reached by dense matter during the merger and its aftermath. Neutrinos influence the merger dynamics and shape the properties of the ejecta, including the resulting r -process nucleosynthesis and kilonova emission. In this work, we analyse neutrino emission from a large sample of binary neutron star merger simulations in Numerical Relativity, covering a broad range of initial masses, nuclear equation of state and viscosity treatments. We extract neutrino luminosities and mean energies, and compute quantities of interest such as the peak values, peak broadnesses, time averages and decrease time scales. We provide a systematic description of such quantities, including their dependence on the initial parameters of the system. We find that for equal-mass systems the total neutrino luminosity (several $$10^{53}{\hbox {erg}~{\hbox {s}}^{-1}}$$ 10 53 erg s - 1 ) decreases as the reduced tidal deformability increases, as a consequence of the less violent merger dynamics. Similarly, tidal disruption in asymmetric mergers leads to systematically smaller luminosities. Peak luminosities can be twice as large as the average ones. Electron antineutrino luminosities dominate (initially by a factor of 2-3) over electron neutrino ones, while electron neutrinos and heavy flavour neutrinos have similar luminosities. Mean energies are nearly constant in time and independent on the binary parameters. Their values reflect the different decoupling temperature inside the merger remnant. Despite present uncertainties in neutrino modelling, our results provide a broad and physically grounded characterisation of neutrino emission, and they can serve as a reference point to develop more sophisticated neutrino transport schemes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Probabilistic predictions and uncertainty estimation for radiological and nuclear effects modeling

Better characterization of meteorological uncertainty is needed to predict the effects of radiological and nuclear releases in the atmosphere. Multi-physics ensembles of atmospheric simulations can estimate uncertainty of physical processes, but they are often limited for computational reasons. Because weather uncertainty is important for emergency response applications, but the conventional way of running multi-physics ensembles is infeasible, we have developed new machine learning-based methods that quickly estimate and identify key sources of meteorological uncertainty. Machine learning accelerates the analysis of weather uncertainty by iteratively learning about model physics options that affect plume predictions. We have demonstrated the power of machine learning by creating a large multi-physics weather and dispersion ensemble dataset containing 1,200 simulations for two hypothetical radiological release scenarios. By training on less than 10% of the ensemble, we can quickly and accurately predict different outcomes, including the mass of radiological material deposited and spatial distribution and extent of contaminated areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Embedding Sensors in 3D Printed Metal Structures

The Transformational Challenge Reactor (TCR) program is leveraging recent advances in modeling and simulation, materials, and additive manufacturing (AM) technologies to design a modern nuclear reactor. Some of the main TCR technologies include in situ monitoring and the integration of sensors during the manufacturing of quality-significant nuclear reactor components. This report describes the general procedure and process optimization for embedding sensors within generic stainless steel 316 (SS316) components using laser powder bed fusion (LPBF). A more detailed, quality-significant test plan and supporting procedures are available upon request (ORNL/TM-2021/2127). LPBF involves the use of a scanning laser to selectively melt regions of a powder bed, additively building a part layer by layer. This report describes the LPBF processing technique and discusses the effects of LPBF processing parameters on the success of the sensor embedding process. Experiments used machined cavities in the form of channels in an SS316 base for the sensors to lay in while material is additively built over the top, thereby embedding them in an SS316 matrix. A preliminary investigation involved using empty SS316 sheaths as surrogates to explore the effects of various LPBF processing parameters and the dimensional requirements of the machined channels. Microstructural investigations showed that a smaller channel width/depth combination closer to the sensor’s diameter was best for the embedding process. After the desired parameters were selected, Type-K thermocouples were embedded and evaluated post-embedding using nondestructive thermal testing, as well as destructive sectioning and microscopy. Post-build characterization showed that the thermocouples were well-bonded to the SS316 matrix and were fully functional after embedding. During thermal testing to temperatures up to 500 °C, the embedded thermocouples read consistently with one another and deviated only slightly from the readings of a nonembedded thermocouple located within the furnace. This slight discrepancy was most likely due to differences in the thermal time constants for a nonembedded thermocouple vs. a thermocouple embedded in a solid SS316 block. The results presented in this report will serve as the foundation for future work that will focus on embedding sensors in relevant TCR reactor components and eventually testing those components under neutron irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian Calibration of Nuclear Graphite Property Models Accounting for Model Inadequacy and Impacts on Component Performance

Nuclear-grade structural graphite is extensively utilized in the core designs of various advanced nuclear reactors. In the reactor environment, graphite is subjected to prolonged exposure to extreme conditions, including high temperatures, radiation, and potentially molten salt and oxygen. Such exposure can induce several degradation mechanisms in graphite, including nonuniform volumetric strains caused by irradiation and thermal expansion, leading to stresses that may compromise the performance of graphite components. Assessing component integrity requires accurate models of graphite's thermomechanical response. This report documents the Bayesian calibration of thermomechanical properties for nuclear-grade graphite and their application to graphite component modeling and simulation using the Grizzly code. As part of this work, uncertainty-quantified models were developed for the elastic modulus, coefficient of thermal expansion, irradiation-induced dimensional change, and irradiation-induced creep for graphite grades IG-110, NBG-18, NBG-17, PCEA, and 2114. Using a hierarchical Bayesian approach, multiple experimental data sources were combined to develop Gaussian process models for the properties. Using the Kennedy O'Hagan framework, the uncertainties due to inadequacies in the model and the inherent spread in the experimental data were quantified for three different models. These uncertainty-quantified models, with a model-form correction, were subsequently applied to a coupled-physics simulation of representative graphite components, revealing that the uncertainties have a large impact on the components' deformation.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

A Novel Algorithm for CAD to CSG Conversion in McCAD

Modeling and simulation lie at the heart of the design process of any nuclear application. An accurate representation of the radiation environment ensures not only the feasibility of new technologies, but it also aids in operation, maintenance, and even decommissioning. With increasingly complex designs, high-fidelity models have become a necessity for design maturity. McCAD has been under development for many years at Karlsruhe Institute of Technology (KIT) to facilitate the process of generating suitable models for nuclear analyses. In this paper, an overview of the major advances in the new version of the code is presented. A novel conversion algorithm has proven to be robust in significantly reducing the processing time to generate radiation transport models, making it easier to iterate on design details. A first-of-a-kind capability to generate hierarchical void cells is also discussed with preliminary analysis showing performance gains for particle tracking.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2017

Development of a Molecular Tagging Velocimetry Technique for Non-Intrusive Velocity Measurements in Low-Speed Gas Flows

N2O molecular tagging velocimetry (N2O-MTV) is developed for use in very-high-temperature reactor environments. Tests were carried out to determine the optimum excitation wavelength, tracer concentration, and timing parameters for the laser system. Using NO tracers obtained from photo-dissociation of N2O, velocity profiles are successfully obtained in air, nitrogen, and helium for a large range of parameters: temperature from 295 to 781 K, pressure from 1 to 3 bars, with a velocity precision of 0.01 m/s. Furthermore, by using two read pulses at adjustable time delays, the velocity dynamic range can be increased. An unprecedented dynamic range of 5,000 has been obtained to successfully resolve the flow during a helium blowdown from 1000 m/s down to 0.2 m/s. This technique is also applied to the high-temperature test facility (HTTF) at Oregon State University (OSU) during a depressurized condition cooldown (DCC) event. Details of these measurements are presented in a companion paper. This technique shows a strong potential for fundamental understanding of gas flows in nuclear reactors and to provide benchmark experimental data to validate numerical simulations.

Andre, M. A.↗
DOE OSTI2025

Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Modernizing the active neutron collar poison rod correction using simulations to enhance PWR fresh fuel verification

The declared inventory of 235 U in fresh, low enriched uranium, nuclear fuel assemblies is routinely verified by nuclear safeguards inspectorates using the UNCL (Uranium Neutron Collar – Light Water Reactor Fuel) nondestructive assay instrument. The trend in modern fuels is towards higher initial enrichment, which in turn requires a larger number of burnable poison pins with higher Gadolinia concentration to hold down the initial reactivity. UNCL assay error for modern fuel assemblies typically exceeds 10%. The traditional algorithm used to correct the response for burnable poison content needs revision to achieve accuracy comparable to the $\sigma_\text{R}$ of 4.5% expected for poison-free assemblies. Here we review the problem and use a large set of 287 Monte Carlo simulations based on an experimentally benchmarked model corresponding to the 16×16 PWR array used in Brazilian Angra type II and III fuel. Simulated relative responses are used to evaluate the functional form of the poison correction and determine parameters optimal for 16×16 PWR assemblies. This update is conducted using between 4–24 Gadolinia pins ranging 2–11 wt% Gd 2 O 3 with assemblies having mean enrichments ranging 2.5%–5%. Experimental validation of the updated coefficients using seven measurements shows bias is reduced by an order of magnitude and $\sigma_\text{R}$R reduced from 10% to less than 2%. Two updated sets of coefficients are provided, the most accurate of which is directly useable in the existing analysis code (INCC) in use by inspectorate at fuel fabrication facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Unstructured mesh-based multi-physics reactor transient simulation with iMC code

In this study, we present a time-dependent Monte Carlo simulation result about a complex fuel-loaded light water reactor system with thermal-hydraulic feedback using the KAIST iMC code. The intra-pin temperature distribution is calculated based on Monte Carlo-tallied detailed power distribution and the finite element heat transfer method. The temperature effect of fuel, absorber, and coolant are adequately reflected into the dynamic response by the on-the-fly Doppler broadened cross-section correction. For the time-dependent Monte Carlo transport simulation, the predictor-corrector quasi-static Monte Carlo method is used for this study. We tested the coupled analysis framework with a 17-by-17 fuel assembly loaded with the centrally-shielded burnable absorber (CSBA) fuel element. The temperature feedback effect on the material cross-section and the moderator density incurred negative reactivity in response to the external positive reactivity insertion, showing the inherent stability of the reactor system. The pin-wise power and temperature change during the system transient are presented and discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

PUSHing Core-collapse Supernovae to Explosions in Spherical Symmetry. V. Equation of State Dependency of Explosion Properties, Nucleosynthesis Yields, and Compact Remnants

Abstract In this fifth paper of the series, we use the parameterized, spherically symmetric explosion method PUSH to investigate the impact of eight different nuclear equations of state (EOS). We present and discuss the explosion properties and the detailed nucleosynthesis yields, and predict the remnant (neutron star or black hole) for all our simulations. For this, we perform two sets of simulations. First, a complete study of nonrotating stars from 11 to 40 M ⊙ at three different metallicities using the SFHo EOS; and, second, a suite of simulations for four progenitors (16 M ⊙ at three metallicities and 25 M ⊙ at solar metallicity) for eight different nuclear EOS. We compare our predicted explosion energies and yields to observed supernovae and to the metal-poor star HD 84937. We find EOS-dependent differences in the explosion properties and the nucleosynthesis yields. However, when comparing to observations, these differences are not large enough to rule out any EOS considered in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Nuclear Data Assessment for Advanced Reactors

Advanced reactor concepts being developed throughout the industry are significantly different from light-water reactor (LWR) designs with respect to geometry, materials, and operating conditions, and consequently, with respect to their reactor physics behavior. Given the limited operating experience with non-LWRs, the accurate simulation of reactor physics and the quantification of associated uncertainties are important for ensuring that the nuclear design for advanced reactor concepts include appropriate margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of a project sponsored by the US Nuclear Regulatory Commission at Oak Ridge National Laboratory (ORNL), key nuclear data relevant to reactor safety analysis in selected advanced reactor technologies were identified, and their impacts on important key figures of merit were assessed based on (1) a review of available advanced reactor specifications, (2) analysis of previous studies performed at ORNL and other research institutions, and (3) sensitivity and uncertainty analyses performed for six selected benchmarks—three experimental and three computational—to quantify the impacts of the identified key nuclear data on several key metrics. This report summarizes the key nuclear data—nominal data and nuclear data uncertainties— considering the most important nuclear reactions in the fuel and in various materials for the moderator, coolant, and structure of the considered advanced reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Radio-Frequency Resonances and Damping in Metallic Magnetic Calorimeter Sensors

Metallic magnetic calorimeters (MMCs) are particle detectors that combine ultra-high energy resolution with a predictable and smooth response based on the physics of paramagnetism. For best energy resolution, MMCs are read out with dc SQUID preamplifiers. Since the ac Josephson effect also makes dc SQUIDs broadband RF sources in the 1–100 GHz range, the SQUID can potentially excite RF modes of the MMC sensor, with negative consequences. Further, the importance of this possibility is magnified in direct-coupled MMCs, where the MMC sensor is part of the SQUID loop to maximize performance. For these reasons, the RF behavior of MMC sensors must be investigated. In this report, we present the results of exploratory RF simulations of MMC sensor modes and damping, and we assess three approaches to damp the parallel-meander direct-coupled MMC without excessive noise increase.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Large-scale Multiphysics Simulations of Small Modular Reactors Operating in Natural Circulation

Thanks to the advancements in high-performance computing, advanced modeling and simulation have become crucial in driving the development and deployment of next-generation nuclear reactors, such as small modular reactors (SMRs). SMRs offer the promise of cost-effective baseload electricity production and improved safety, while addressing some of the challenges associated with large reactor designs, such as high capital costs and extended construction timelines. As part of the Exascale Computing Project, the large-scale multiphysics simulation of an entire SMR primary system has been achieved by combining computational fluid dynamics and neutronics. In addition to the successful demonstration of full-core SMR simulations, the current study integrated the impact of natural circulation into the system. Natural circulation is the primary mechanism driving coolant circulation in SMRs. The mass flow rate in the core depends on the core power, and a numerical model has been developed to predict it. The pressure drop caused by the helical coil steam generator was also accounted for by developing a pressure drop correlation based on high-fidelity large eddy simulation results, further improving prediction accuracy. In conclusion, the results of the study demonstrate that the implemented natural circulation model is effective in predicting the responses of SMR full-core multiphysics simulations.

ECP↗