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DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Establishing temperature from radiance of dynamically compressed metals

Precise temperature determination is a significant challenge in extreme environments of dynamic compression studies. How can radiance measurements taken in high-pressure shock experiments constrain temperature in a meaningful and physically consistent way? Experiments maintaining sample compression against a transparent window can be tailored to present a uniform measurement area with uncertain spectral emissivity. We compare several methods to analyze radiance collected at multiple wavelengths, applying statistical methods and physical principles to improve temperature inference. With proper radiance collection and analysis, dynamic temperature uncertainties become comparable to thermomechanical ambiguities of the emitting surface.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Preliminary neutronic and thermal analysis of Inertial Fusion Energy systems with a focus on thick liquid wall concepts

This paper provides an assessment of the neutronic behavior of Inertial Fusion Energy systems using the Serpent 2 Monte Carlo code. The study explores different types of reactor concepts, including dry-wall and thick liquid wall systems. In particular, it characterizes the tritium breeding and energy multiplication performance, as well as the effect of long-term irradiation on structural materials. For this purpose, the displacement per atom (DPA) and the gas production rate in structural materials are calculated. A simplified geometry with varying geometrical parameters is used as a representation for the different kinds of devices. Additionally, the case of the HYLIFE-II concept is used to assess modeling inaccuracies arising from certain approximations. A comparison between the simplified geometry and a realistic one is performed, thanks to Serpent’s capability to run transport calculations on unstructured meshes. The study then addresses the impact of these discrepancies on the temperature distribution in the first wall using the GeN-Foam code for conjugate heat transfer analysis. The results highlight the necessity to consider the heterogeneous nature of the liquid wall, as simplified models tend to underestimate radiation damage metrics and heat loads.

Conjugate heat transfer↗

DOE OSTI2020

Progress Toward the First Search for Bound Neutron Oscillation into Antineutron in a Liquid Argon TPC

This note presents current progress for a neutron-antineutron oscillation ($n–\overline{n}$) search in MicroBooNE paving the way for the first search analysis of such process in a Liquid Argon Time Projection Chamber (LArTPC). Convolutional Neural Network (CNN) and Boosted Decision Tree (BDT) algorithms were used to select signal $n–\overline{n}$ events over cosmogenic backgrounds. The CNN-only, BDT-only, and the combined (CNN+BDT) methods were demonstrated on the Monte-Carlo signal and background events. Validation of the CNNonly and the BDT-only methods was carried out on a small dataset of MicroBooNE Run1 off-beam data, setting the starting point toward further improvement of the analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure–Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. Here, we present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Nothing to see here: failed supernovae are faint or rare

ABSTRACT The absence of Type IIP core-collapse supernovae arising from progenitors above 17 solar masses suggests the existence of another evolutionary path by which massive stars end their lives. The direct collapse of a stellar core to a black hole without the production of a bright, explosive transient is expected to produce a long-lived, dim, red transient known as a failed supernova. Despite the detection of a number of candidates for disappearing massive stars in recent years, conclusive observational evidence for failed supernovae remains elusive. A custom-built pipeline designed for the detection of faint transients is used to re-analyse 10 yr of observations of 231 nearby galaxies from the PTF/ZTF surveys. This analysis recovers known supernovae, and yields a number of interesting transients. However, none of these are consistent with a failed supernova. Through Monte Carlo tests the recovery efficiency of our pipeline is quantified. By assuming failed supernovae occur as a Poissonian process with zero detections in the data set, 95 per cent upper limits to the rate of failed supernovae are calculated as a function of failed supernova absolute magnitude. We estimate failed supernovae to be less than 0.61, 0.33, 0.26, or 0.23 of the core-collapse SN rate for absolute magnitudes of −11, −12, −13, and −14, respectively. Finally, we show that if they exist, the Vera C. Rubin Observatory will find 1.7–3.7 failed SNe per year for an absolute bolometric luminosity of ∼6 × 1039 erg s−1 out to distances of 33–43 Mpc, depending on their assumed spectral energy distribution.

Byrne, R. A. (ORCID:0000000177661737)↗

DOE OSTI2025

Optimization of the BDX experiment for Light Dark Matter searches at JLab

The Light Dark Matter (LDM) hypothesis postulates the existence of a new class of sub GeV particles, neutral under Standard Model (SM) interactions. In its simplest form, LDM consists of particles ¿ with masses below 1 GeV/c2, interacting with SM particles via a new force mediated by a light, spin-1 boson A0, commonly referred to as “Dark Photon”. This framework envisions a distinct “Dark Sector” with its own particles and interactions, offering a theoretically well motivated explanation for Dark Matter, consistent with astrophysical observations and a thermal production mechanism. The Beam Dump eXperiment (BDX) is an approved experiment at Jefferson Lab designed to search for Light Dark Matter. BDX will utilize an 11 GeV electron beam impinging on a thick target to produce a forward-boosted secondary beam of Light Dark Matter particles, which will then be detected by a dedicated downstream detector. Approved in 2018, BDX is expected to be commissioned in 2026 and run in 2027-2029. My thesis focuses on the preparatory work to deploy the BDX experiment. The detector design has been optimized to balance practicality with enhanced Light Dark Matter detection capabilities. Extensive characterization of detector components has been performed to ensure a precise understanding of detector response. A custom Monte Carlo framework has been developed to simulate Light Dark Matter signal and explore various theoretical models of interest. Additionally, a comprehensive data analysis framework has been developed to maximize the experiment sensitivity to Light Dark Matter, with optimizations based on expected detector performance. The ultimate goal of this thesis is to optimize BDX as a flagship experiment in Light Dark Matter searches, enabling it to probe different Dark Matter models.

Spreafico, M. [Univ. of Genova (Italy)]↗

DOE OSTI2026

Rapid Gamma Simulations of TRISO Fuel Elements

As energy demand rises, nuclear energy, particularly from reactors that use tristructural isotropic (TRISO) fuels, has gained attention due to the fuel’s enhanced resistance to radiation damage and high temperatures. This report investigates the modeling capabilities of the Gamma Detector Response and Analysis Software (GADRAS) for TRISO fuels, focusing on the gamma signatures of TRISO particles, which have not been extensively explored. Using the Monte Carlo N-Particle (MCNP) code as a benchmark, we developed both homogeneous and heterogeneous models of TRISO pebbles to analyze gamma spectra. Our findings reveal that the homogeneous and heterogeneous models produced different gamma signatures. Additionally, the GADRAS heterogeneous model significantly reduces computation times compared to MCNP, enabling effective modeling of gamma signatures for safeguards applications. This advancement is essential for the International Atomic Energy Agency (IAEA) in detecting anomalies and potential smuggling attempts in TRISO reactor fuel elements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Computational techniques for the analysis of small signals in high-statistics neutrino oscillation experiments

The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as Monte Carlo weighting. In this work we present a staged approach to the generation of expected distributions of observables in order to overcome these challenges. By combining multiple integration and smoothing techniques which address limited statistics from simulation it arrives at reliable analysis results using modest computational resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

High Flux Isotope Reactor Low Enriched Uranium U-10Mo Fuel Design Parameters

Activities to convert the HFIR from HEU to LEU are ongoing as part of the US Department of Energy (DOE) National Nuclear Security Administration (NNSA) nuclear nonproliferation mission. Design activities to study the conversion of HFIR from HEU to LEU fuel explored different fuel design features and shapes with a uranium-molybdenum (U-10Mo) monolithic alloy fuel. This high-density alloy contains 90 wt % uranium and 10 wt % molybdenum and has a uranium density of 15.318gU/cm 3 . The goal of these studies is to generate several candidate HFIR LEU fuel designs of varying fuel fabrication complexity that meet the current HEU performance metrics and safety requirements. Recent advancements in modeling and simulation tools and design methods enabled a thorough analysis of the available design space with U-10Mo fuel. A surrogate model used this analysis as training data to quickly determine the performance of a design given specific design parameters. An optimization module used this surrogate model to quickly search this multidimensional search space given specific desired performance characteristics. This approach was made possible by the large available design space with U-10Mo fuel. Shift, a Monte Carlo tool optimized for high-performance computing (HPC) architectures, was used for faster calculation and better data management for reactor physics simulations. Once most of these design studies were complete, a new suite called the Python HFIR Analysis and Measurement Engine (PHAME) was developed to connect all fuel design analysis steps, making design studies more efficient and reproducible. The post-processing capabilities of these new tools are leveraged for the information provided herein. Leveraging these tools, several candidate fuel designs were selected with varying levels of feature complexity and reactor performance. This report provides design feature details for four selected HFIR LEU U-10Mo fuel designs and their corresponding performance and safety metrics. Nominal best-estimate design parameters and irradiation conditions, including fission rate densities, power densities, heat fluxes, and cumulative fission densities, are provided. Simulations show that the high uranium density of U-10Mo fuel provides a large potential design space that enables various LEU designs to meet HEU core performance metrics and safety requirements with a power increase from 85 MW (HEU) to 95 MW or 100 MW (LEU).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Preliminary analysis of TREAT free-field experiments using openmc

This work analyses activation calculations for dosimetry materials during a steady-state irradiation in the Transient Reactor Test (TREAT) reactor core. Hence, we developed a workflow based on the Monte Carlo code OpenMC alongside a custom depletion solver. The irradiation-induced activity as a function of time is computed, and several sensitivity studies are performed to evaluate uncertainty. This study has shown activity computations are sensitive to flux amplitude, irradiation time, atoms quantity and microscopic cross sections. Stochastic uncertainties have been propagated to evaluate the activity uncertainty for each dosimetry material. Most uncertainties are below our target of 3%, which demonstrates OpenMC as a powerful predictive and analysis tool. The precise results obtained through this newly developed computation scheme will be used in future experiments to characterize quantities of interest when operating the TREAT reactor in new configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Preliminary analysis of TREAT free-field experiments using OpenMC

61 - RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Variations of the physical parameters of the blazar Mrk 421 based on analysis of the spectral energy distributions

Abstract We report on the variations of the physical parameters of the jet observed in the blazar Mrk 421, and discuss the origin of X-ray flares in the jet, based on analysis of several spectral energy distributions (SEDs). The SEDs are modeled using the one-zone synchrotron self-Compton model, its parameters determined using a Markov chain Monte Carlo method. The lack of data at TeV energies means many of the parameters cannot be uniquely determined and are correlated. These are studied in detail. We find that the optimal solution can be uniquely determined only when we apply a constraint to one of four parameters: the magnetic field (B), the Doppler factor, the size of the emitting region, and the normalization factor of the electron energy distribution. We used 31 sets of SEDs from 2009 to 2014 with optical–UV data observed with UVOT/Swift and the Kanata telescope, X-ray data with XRT/Swift, and γ-ray data with the Fermi Large Area Telescope. The result of our SED analysis suggests that, in the X-ray faint state, the emission occurs in a relatively small area (∼1016 cm) with a relatively strong magnetic field (B ∼ 10−1 G). The X-ray bright state shows a tendency opposite to that of the faint state, that is, a large emitting area (∼1018 cm), probably downstream of the jet, and a weak magnetic field (B ∼ 10−3 G). The high X-ray flux was due to an increase in the maximum energy of electrons. On the other hand, the presence of two kinds of emitting areas implies that the one-zone model is unsuitable for reproducing at least part of the observed SEDs.

Yamada, Yurika↗

DOE OSTI2025

Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations

Here, we present a newly implemented ray tracing algorithm in OpenMC for efficiently computing material volume fractions on superimposed meshes in complex geometries. By firing rays along each coordinate direction through the geometry, the approach accumulates track-length data in each mesh element, thereby determining the fractional composition of each material. Scaling studies on three different models—a random tetrahedra configuration, the Frascati Neutron Generator ITER dose rate benchmark, and a stellarator design—show excellent parallel performance, with nearly linear speedup on modern multi-threaded and distributed-memory systems. An analysis of the residual error relative to high-resolution reference solutions demonstrated that under optimal conditions it decreases as 1/R, where R is the number of rays fired, making it straightforward to achieve user-prescribed accuracy. This new functionality enables practical, mesh-based approaches for detailed nuclear analyses in production Monte Carlo workflows without resorting to expensive, fully conformal or unstructured meshing.

Monte Carlo↗

DOE OSTI2021

A method for predicting failure statistics for steady state elevated temperature structural components

This paper presents the initial development of a high temperature life prediction method that accounts for the variability in the material properties of Grade 91 steel. The method accounts for material variability by fitting a variable 3-parameter Weibull distribution to experimental rupture data and accounts for the variability of creep deformation on the steady-state stresses via a Monte Carlo approach. To ensure reasonable computational times, the model represents the material as an extremely viscous Stokes fluid with a non-Newtonian viscosity, therefore solving the stress relaxation problem with a steady, static, instead of transient, analysis. Furthermore, the complete statistical analysis combines this model for creep deformation with a probabilistic model for creep rupture to evaluate the probability of premature failure for a set of sample problems, comparing the predicted failure statistics to the design life predicted by the ASME Boiler and Pressure Vessel Code rules.

42 ENGINEERING↗

DOE OSTI2020

Assessment of CASL VERA for BWR analysis and application to accident tolerant SiC/SiC channel box

Application of the Virtual Environment for Reactor Applications (VERA) to BWR analysis is assessed in this paper by comparing results to those calculated using other widely-used modeling tools, namely the U.S. Nuclear Regulatory Commission’s PARCS/PATHS and the Serpent Monte Carlo particle transport code. Additionally, VERA is used to calculate 3-D temperature and fast neutron flux distributions in silicon carbide (SiC) fiber-reinforced, SiC matrix composite (SiC/SiC) BWR channel boxes, which are being studied as an Accident Tolerant Fuel core structural material concept. We found that the code-to-code comparisons were favorable, and the SiC/SiC channel box evaluation demonstrates the many advanced modeling features VERA provides while also highlighting the non-uniformity in fast neutron flux distributions that can play a role in potential SiC/SiC channel box deformation. Traditional BWR analysis tools do not have the calculation fidelity necessary for coupled assessment of flux and temperature gradients in a SiC/SiC channel box. VERA is a state-of-the-art modeling environment that was developed to increase the safety and economic competitiveness of nuclear power through improved modeling accuracy. While VERA has already been deployed in the nuclear industry for PWR applications, the current study is a vital initial step in the extensive development, validation, and verification that VERA must go through to be useful for BWR applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Lung Cancer in the Mayak Workers Cohort: Risk Estimation and Uncertainty Analysis

The workers at the Mayak nuclear facility near Ozyorsk, Russia are a primary source of information about exposure to radiation at low-dose rates, since they were subject to protracted exposures to external gamma rays and to internal exposures from plutonium inhalation. Here we re-examine lung cancer mortality rates and assess the effects of external gamma and internal plutonium exposures using recently developed Monte Carlo dosimetry systems. Using individual lagged mean annual lung doses computed from the dose realizations, we fit excess relative risk (ERR) models to the lung cancer mortality data for the Mayak Workers Cohort using risk-modeling software. We then used the corrected information matrix (CIM) approach to widen the confidence intervals of ERR by taking into account the uncertainty in doses represented by multiple realizations from the Monte Carlo dosimetry systems. Findings of this work revealed that there were 930 lung cancer deaths during follow-up. Plutonium lung doses (but not gamma doses) were generally higher in the new dosimetry systems than those used in the previous analysis. This led to a reduction in the risk per unit dose compared to prior estimates. The estimated ERR/Gy for external gamma-ray exposure was 0.19 (95% CI: 0.07 to 0.31) for both sexes combined, while the ERR/Gy for internal exposures based on mean plutonium doses were 3.5 (95% CI: 2.3 to 4.6) and 8.9 (95% CI: 3.4 to 14) for males and females at attained age 60. Accounting for uncertainty in dose had little effect on the confidence intervals for the ERR associated with gamma-ray exposure, but had a marked impact on confidence intervals, particularly the upper bounds, for the effect of plutonium exposure [adjusted 95% CIs: 1.5 to 8.9 for males and 2.7 to 28 for females]. In conclusion, lung cancer rates increased significantly with both external gamma-ray and internal plutonium exposures. Accounting for the effects of dose uncertainty markedly increased the width of the confidence intervals for the plutonium dose response but had little impact on the external gamma dose effect estimate. Adjusting risk estimate confidence intervals using CIM provides a solution to the important problem of dose uncertainty. This work demonstrates, for the first time, that it is possible and practical to use our recently developed CIM method to make such adjustments in a large cohort study.

uncertainty, radiation risk estimation, Mayak Prod↗

DOE OSTI2023

Magnetic and singlet phases in the three-dimensional periodic Anderson Model

Heavy-fermion materials are compounds in which localized f orbitals hybridize with delocalized d ones, leading to quasiparticles with large renormalized masses. The presence of strongly correlated f electrons at the Fermi level may also lead to long-range order, such as magnetism, or unconventional superconductivity. From a theoretical point of view, the “standard model” for heavy-fermion compounds is the periodic Anderson model (PAM). Despite being extensively scrutinized, its thermodynamic properties in three-dimensional (3D) lattices have not been carefully addressed by unbiased methodologies. Here we investigate the 3D PAM employing state-of-the-art finite-temperature auxiliary-field quantum Monte Carlo simulations. Furthermore, we present the behavior of the kinetic energy, the entropy, the specific heat, and the double occupancy as functions of the temperature and the hybridization strength. From these quantities, and by the analysis of the spin-spin correlation functions, we investigate the occurrence of magnetic phase transitions at finite temperatures, and we determine the phase diagram of the model, including the behavior of the Néel temperature as a function of the external parameters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗