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DOE OSTI2021

DESIGN AND PROTOYPING OF A FISSILE-BEARING CHLORIDE SALT IRRADIATION EXPERIMENT

Limited data exists on the properties of irradiated fueled chloride-based salts for use in advanced nuclear reactors. The design and prototyping of a salt irradiation experiment is underway. Mechanical design will integrate the experiment into existing assemblies in TRIGA type cores. Neutronics modeling demonstrated how targeted power densities can be reached and provide insight on radionuclide source term generation within the experiment. Thermal-hydraulic and computational fluid dynamics (CFD) analysis indicated that temperature ranges in the salt can satisfy both safety and programmatic requirements. Initial prototyping tests provided confidence in the ability to extract the salt post-irradiation, and in the heater performance. Future planned prototyping will provide an integral assessment of the proposed design prior to insertion in the reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Results of South-East Flux Trap Dosimetry Measurements for the Advanced Test Reactor Critical Facility in support of Advanced Sensors and Instrumentation Development

Reactor dosimetry measurements are commonly used to validate simulation and modeling in nuclear reactor tests. Numerous standard dosimeter materials exist which are commonly utilized with sensitivities to different energy ranges of neutrons. At the Advanced Test Reactor (ATR), cobalt alloy and pure nickel wires are installed every cycle to monitor thermal- and fast-neutron fluence rates. However, there is growing interest in exploring less commonly used materials which are either more sensitive to different parts of the neutron energy spectrum or which can incorporate multiple activation paths in a single material. Epithermal and fast-neutron energies beyond the typical 1-MeV threshold are of particular interest. Two ATR-C Flux Runs took place during 2024; each flux run included supplemental dosimetry packages in the South-East Flux Trap (SEFT) Filler. The focus of the dosimetry package for flux run 23-4 was to test two novel dosimetry methods that can provide simultaneous thermal and threshold (fast) sensitivity in a single dosimeter wire. A selection of 3% Au in Cu alloyed wires were available that provided sensitivity to fast and thermal neutrons through 5 different reactions. Likewise, Fe offers multiple interaction pathways with sensitivity to both thermal and fast neutrons. The main question to be answered by these irradiations was if sufficient radioactivation would take place in the ATR-C SEFT during a nominal 20-minute irradiation at typical power levels (near 600Wth) to observe the threshold reactions that have smaller activation cross-sections than the thermal reactions without being saturated by interfering interactions and Compton continuum during the High-Purity Germanium (HPGe) measurements. The results from comparing the measurement results to anticipated activity levels provide confidence in our ability to activate both traditional and novel dosimetry materials in ATR-C, however not all the measured values matched with the predicted activities. This leaves further room for investigation both on the experimental and computational approaches for future irradiation experiments.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2019

Neutrino oscillation probabilities through the looking glass

In this paper we review different expansions for neutrino oscillation probabilities in matter in the context of long-baseline neutrino experiments. We examine the accuracy and computational efficiency of different exact and approximate expressions. We find that many of the expressions used in the literature are not precise enough for the next generation of long-baseline experiments, but several of them are while maintaining comparable simplicity. Furthermore the results of this paper can be used as guidance to both phenomenologists and experimentalists when implementing the various oscillation expressions into their analysis tools.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

An integrated computational materials engineering framework to analyze the failure behaviors of carbon fiber reinforced polymer composites for lightweight vehicle applications

A bottom-up multi-scale modeling approach is used to develop an Integrated Computational Materials Engineering (ICME) framework for carbon fiber reinforced polymer (CFRP) composites, which has the potential to reduce development to deployment lead time for structural applications in lightweight vehicles. In this work, we develop and integrate computational models comprising of four size scales to fully describe and characterize three types of CFRP composites. In detail, the properties of the interphase region are determined by an analytical gradient model and molecular dynamics analysis at the nano-scale, which is then incorporated into micro-scale unidirectional (UD) representative volume element (RVE) models to characterize the failure strengths and envelopes of UD CFRP composites. Then, the results are leveraged to propose an elasto-plastic-damage constitutive law for UD composites to study the fiber tows of woven composites as well as the chips of sheet molding compound (SMC) composites. Subsequently, the failure mechanisms and failure strengths of woven and SMC composites are predicted by the meso-scale RVE models. Finally, building upon the models and results from lower scales, we show that a homogenized macro-scale model can capture the mechanical performance of a hat-section-shaped part under four-point bending. Along with the model integration, we will also demonstrate that the computational results are in good agreement with experiments conducted at different scales. The present work illustrates the potential and significance of integrated multi-scale computational modeling tools that can virtually evaluate the performance of CFRP composites and provide design guidance for CFRP composites used in structural applications.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Experimental Guesswork with Quantum Side Information Using Twisted Light

Guesswork is an information–theoretic quantity which can be seen as an alternate security criterion to entropy. Recent work has established the theoretical framework for guesswork in the presence of quantum side information, which we extend both theoretically and experimentally. We consider guesswork when the side information consists of the BB84 states and their higher-dimensional generalizations. With this side information, we compute the guesswork for two different scenarios for each dimension. We then performed a proof-of-principle experiment using Laguerre–Gauss modes to experimentally compute the guesswork for higher-dimensional generalizations of the BB84 states. We find that our experimental results agree closely with our theoretical predictions. This work shows that guesswork can be a viable security criterion in cryptographic tasks and is experimentally accessible in a number of optical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Determination of Critical Experiment Correlations for Experiments Involving Arrays of Low-Enriched Fuel Rods

Quantifying correlations among critical experiments has become a topic of interest over the last 10–15 years. Correlations arise from the shared use of fissile material, nonfissile materials, fixtures, and procedures in multiple experiments or multiple experiment series. A Monte Carlo sampling technique proposed as a viable technical method to evaluate these correlations has been implemented in the SCALE 6.2 Sampler sequence. This paper presents an investigation of the use of this new tool and technique for low-enriched uranium pin array experiments with a thermal neutron energy spectrum. The Nuclear Energy Agency’s Expert Group on Uncertainty Analyses for Criticality Safety Assessments has been examining methods of calculating the correlation coefficients among experiments from the LCT-007 and LCT-039 series. Results for two scenarios are presented to demonstrate the impact of pin pitch uncertainty modeling on the correlation coefficients. The convergence of the correlation coefficients is also investigated. Additional studies examine the impact of the stochastic uncertainty and the use of continuous-energy Monte Carlo for individual realizations on the correlation coefficients. Correlation coefficients are also determined for the LCT-042 experiment series. This experiment series differs from other experiments because unique poison panels and fuel array separation distances may reduce correlation of the individual experiments within the series. The effects of pin pitch uncertainty and stochastic uncertainty are also examined for this series. Comparing the results of the two sets of experiments shows potential conclusions that can be drawn regarding viability of the Monte Carlo sampling technique for determining critical experiment correlations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Women in Science: Fermilab computing analyst Margherita Vittone-Wiersma

With February 11 marking the International Day of Women and Girls in Science, female physicists, engineers and computer scientists from CERN and Fermilab share their experiences of building careers in science. Margherita Vittone-Wiersma came to Fermilab as a physicist in February 1985. Together with a group of researchers from Italy's Institute of Nuclear Physics, she began a new experiment called E687. But she soon learned that she preferred working on data acquisition and the many methods to store and access the huge amount of data coming out of science experiments. What was once mere megabytes of data is now terabytes of information - and experimental physicists need to be able to retrieve stored data and monitor data coming from the detectors in real-time. "It's been an incredible change in scale of the amount of data that is handled by computers and has to be analyzed by the physicists," she says. Margherita migrated from physics to her new role in computing through lots of hands-on learning and classes in different programming languages and software development offered at Fermilab. She officially joined the lab's computing division in 1989. "It's a great experience to work with the physicists," she says. Together physicists and computing experts iterate over tools "to make sure that everything is working the way they expect. It's very rewarding." Credits: Video production - Fermilab Creative Services Music Copyright: Universal Production Music Astral Light Chevalier Idea originally conceived by Tanya Levshina, Fermilab and Maria Dimou, CERN.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Enabling Particulate Materials Processing Science for High-Consequence, Small-Lot Precision Manufacturing

This Laboratory Directed Research and Development project developed and applied closely coupled experimental and computational tools to investigate powder compaction across multiple length scales. The primary motivation for this work is to provide connections between powder feedstock characteristics, processing conditions, and powder pellet properties in the context of powder-based energetic components manufacturing. We have focused our efforts on multicrystalline cellulose, a molecular crystalline surrogate material that is mechanically similar to several energetic materials of interest, but provides several advantages for fundamental investigations. We report extensive experimental characterization ranging in length scale from nanometers to macroscopic, bulk behavior. Experiments included nanoindentation of well-controlled, micron-scale pillar geometries milled into the surface of individual particles, single-particle crushing experiments, in-situ optical and computed tomography imaging of the compaction of multiple particles in different geometries, and bulk powder compaction. In order to capture the large plastic deformation and fracture of particles in computational models, we have advanced two distinct meshfree Lagrangian simulation techniques: 1.) bonded particle methods, which extend existing discrete element method capabilities in the Sandia-developed , open-source LAMMPS code to capture particle deformation and fracture and 2.) extensions of peridynamics for application to mesoscale powder compaction, including a novel material model that includes plasticity and creep. We have demonstrated both methods for simulations of single-particle crushing as well as mesoscale multi-particle compaction, with favorable comparisons to experimental data. We have used small-scale, mechanical characterization data to inform material models, and in-situ imaging of mesoscale particle structures to provide initial conditions for simulations. Both mesostructure porosity characteristics and overall stress-strain behavior were found to be in good agreement between simulations and experiments. We have thus demonstrated a novel multi-scale, closely coupled experimental and computational approach to the study of powder compaction. This enables a wide range of possible investigations into feedstock-process-structure relationships in powder-based materials, with immediate applications in energetic component manufacturing, as well as other particle-based components and processes.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Sorption Modeling and Verification for Off-Gas Treatment

This project was successfully executed to provide valuable adsorption data and improve a comprehensive model developed in previous work by the authors. Data obtained were used in an integrated computer program to predict the behavior of adsorption columns. The model is supported by experimental data and has been shown to predict capture of off gas similar to that evolving during the reprocessing of nuclear waste. The computer program structure contains (a) equilibrium models of off-gases with the adsorbate; (b) mass-transfer models to describe off-gas mass transfer to a particle, diffusion through the pores of the particle, and adsorption on the active sites of the particle; and (c) incorporation of these models into fixed bed adsorption modeling, which includes advection through the bed. These models are being connected with the MOOSE (Multiphysics Object-Oriented Simulation Environment) software developed at the Idaho National Laboratory through DGOSPREY (Discontinuous Galerkin Off-gas SeParation and REcoverY) computer codes developed in this project. Experiments for iodine and water adsorption have been conducted on reduced silver mordenite (Ag0Z) for single layered particles. Adsorption apparatuses have been constructed to execute these experiments over a useful range of conditions for temperatures ranging from ambient to 250°C and water dew points ranging from -69 to 19°C. Experimental results were analyzed to determine mass transfer and diffusion of these gases into the particles and to determine which models best describe the single and binary component mass transfer and diffusion processes. The experimental results were also used to demonstrate the capabilities of the comprehensive models developed to predict single-particle adsorption and transients of the adsorption-desorption processes in fixed beds. Models for adsorption and mass transfer have been developed to mathematically describe adsorption kinetics and transport via diffusion and advection processes. These models were built on a numerical framework for solving conservation law problems in one-dimensional geometries such as spheres, cylinders, and lines. Coupled with the framework are specific models for adsorption in commercial adsorbents, such as zeolites and mordenites. Utilizing this modeling approach, the authors were able to accurately describe and predict adsorption kinetic data obtained from experiments at a variety of different temperatures and gas phase concentrations. A demonstration of how these models, and framework, can be used to simulate adsorption in fixed- bed columns is provided. The CO 2 absorption work involved modeling with supportive experimental information. A dynamic model was developed to simulate CO 2 absorption using high alkaline content water solutions. The model is based upon transient mass and energy balances for chemical species commonly present in CO 2 absorption. A computer code was developed to implement CO 2 absorption with a chemical reaction model. Experiments were conducted in a laboratory scale column to determine the model parameters. The influence of geometric parameters and operating variables on CO 2 absorption was studied over a wide range of conditions. Continuing work could employ the model to control column operation and predict the absorption behavior under various input conditions and other prescribed experimental perturbations. The value of the validated models and numerical frameworks developed in this project is that they can be used to predict the sorption behavior of off-gas evolved during the reprocessing of nuclear waste and thus reduce the cost of the experiments. They can also be used to design sorption processes based on concentration limits and flow-rates determined at the plant level.

42 ENGINEERING↗

DOE OSTI2024

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Evolution of HEP Processing Frameworks

HEP data-processing software must support the disparate physics needs of many experiments. For both collider and neutrino environments, HEP experiments typically use data-processing frameworks to manage the computational complexities of their large-scale data processing needs. Data-processing frameworks are being faced with new challenges this decade. The computing landscape has changed from the past three decades of homogeneous single-core x86 batch jobs running on grid sites. Frameworks must now work on a heterogeneous mixture of different platforms: multi-core machines, different CPU architectures, and computational accelerators; and different computing sites: grid, cloud, and high-performance computing. We describe these challenges in more detail and how frameworks may confront them. Given their historic success, frameworks will continue to be critical software systems that enable HEP experiments to meet their computing needs. Frameworks have weathered computing revolutions in the past; they will do so again with support from the HEP community

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Verifying MCNP Models of the TEX High 240 Plutonium Benchmark

Computational modeling programs are invaluable tools that allow us to understand systems, safely develop new processes, and make reliable predictions about future designs. However, the effectiveness of these codes is limited by the degree to which their parameters match the real world. In the field of nuclear engineering, cross section data is one of these vital parameters. Accurate cross section data on important fissile and fissionable isotopes promotes the design of safer and more efficient fabrication, transportation, storage, and stockpiling of nuclear fuel. Unfortunately, there are knowledge gaps in data on key isotopes. In 2011, a multinational meeting hosted by the US Department of Energy Nuclear Criticality Safety Program ranked the priority of certain cross section data needs. In response, Lawrence Livermore National Lab (LLNL) designed the Thermal and Epithermal eXperiment (TEX) series of benchmark experiments. Benchmark experiments are used to validate current cross section data. They validate data by comparing the results of an actual experiment to the predicted results from a computational model. The data a benchmark applies to depends on the isotope and energy range the experiment’s neutron multiplication factor ( k eff ) is most sensitive to. The development and testing of the TEX High 240 Plutonium Benchmark will help validate 240 Pu cross section data. The configuration and materials of this benchmark are designed to be most sensitive to 240 Pu's intermediate energy range (from 0.625 ev to 100 keV ). MCNP® models of the assembly have been developed by LLNL and the results have been written in the final design report. In order for the discrepancies between benchmark models and experiments to be attributed to cross section inaccuracies, the accuracy of the models needs to be verified. The goal of this project is to verify of the results of LLNL's modeling by creating a new set of MCNP models and comparing the results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Estimating the carbon footprint of computational fluid dynamics

In this study, computational resources have grown exponentially in the past few decades. These machines make possible research and design in fields as diverse as medicine, astronomy, and engineering. Despite ever-increasing computational capabilities, direct simulation of complex systems has remained challenging owing to the degrees of freedom involved. At the cusp of exascale computing, high-resolution simulation of practical problems with minimal model assumptions may soon experience a renaissance. However, growing reliance on modern computers comes at the cost of a growing carbon footprint. To illustrate this, we examine historic computations in fluid dynamics where larger computers have afforded the opportunity to simulate flows at increasingly relevant Reynolds numbers. Under a variety of flow configurations, the carbon footprint of such simulations is found to scale roughly with the fourth power of Reynolds number. This is primarily explained by the computation cost in core-hours, which is also described by similar scaling, though regional differences in renewable energy use also play a role. Using the established correlation, we examine a large database of simulations to develop estimates for the carbon footprint of computational fluid dynamics in a given year. Collectively, the analysis provides an additional benchmark for new computations where, in addition to balancing considerations of model fidelity, carbon footprint should also be considered.

42 ENGINEERING↗

DOE OSTI2024

Simulations, Modeling and Data Analysis of Parity Violating Electron Scattering Experiments

In the Standard Model (SM) of nuclear and particle physics, parity violation is incorporated through the representation of the weak interaction as a chiral gauge interaction. Only the left-handed components of particles and right-handed components of antiparticles participate in weak interactions in the Standard Model. This implies that parity is asymmetric for the weak interaction. Parity violating electron scattering (PVES) experiments are designed to probe the physics parameters related to the SM, with the possibility to discover physics beyond the SM (BSM) by measuring the parity violating asymmetry ¿¿¿ of longitudinally polarized electrons scattered off unpolarized targets with high precision. This dissertation will be focused on two PVES experiments, the next 208Pb Lead Radius Experiment (PREX-II), and the Measurement of a Lepton-Lepton Electroweak Reaction (MOLLER) experiment, as well as in some small sections, the Calcium Radius Experiment (CREX) and P2 experiment which are also PVES experiments). PREX-II and CREX experiments, performed in Hall A at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), measured ¿¿¿ in the elastic scattering of longitudinally polarized electrons from 208Pb and 48Ca targets to provide a precise model independent determination of the neutron skin thickness of 208Pb and 48Ca nuclei, respectively. The MOLLER experiment, proposed to start in 2027 and also to be performed in Hall A at Jefferson Lab, is to measure ¿¿¿ of longitudinally polarized electrons scattered off unpolarized electrons (Møller scattering) to determine the weak charge of electrons ¿¿¿ and the weak mixing angle ¿¿ with high precision. As for the P2 experiment, which will be performed at the upcoming MESA accelerator in Mainz Germany, it is to measure the weak charge of proton ¿¿¿ using ¿¿¿ in the elastic electron-proton scattering of polarized electrons off unpolarized protons. The final results from the PREX-II experiment are presented as ¿¿¿=550±16 (¿¿¿¿)±8 (¿¿¿¿) parts-per-billion (ppb). Combining the PREX-I and PREX-II results, the neutron skin thickness from PREX experiments is determined as ¿¿-¿¿=0.283±0.071 ¿¿ in 208Pb. This thesis lists the software and computational contribution of the author to these PVES experiments, including writing scripts and software to help with the PREX-II/CREX experiments, analyzing data to provide useful information and systematic uncertainty for the PREX-II experiment, modeling and simulations for the MOLLER, and providing an alternative design of an electronic equipment for the P2 experiment.

Chen, Yufan↗

DOE OSTI2024

Simulations, Modeling and Data Analysis of Parity Violating Electron Scattering Experiments

Chen, Yufan↗

DOE OSTI2020

Variable Precision Computing (VPC) (Final Report)

The overall goal of the Variable Precision Computing project is exploring and identifying ways to reduce internodal communication cost in production physics simulation experiments running on a distributed-memory systems by compressing data, either in a lossy or lossless way, thus resulting in a significant computational performance increase. Among the several approaches proposed, the one discussed here has been proposed, designed and implemented by me. It concerns the application of information theory-derived metrics to classical molecular dynamics and computational fluid dynamics simulation experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Graph Neural Network-based Tracking as a Service

Recent studies have shown promising results for track finding in dense environments using Graph Neural Network (GNN)-based algorithms. However, GNN-based track finding is computationally slow on CPUs, necessitating the use of coprocessors to accelerate the inference time. Additionally, the large input graph size demands a large device memory for efficient computation, a requirement not met by all computing facilities used for particle physics experiments, particularly those lacking advanced GPUs. Furthermore, deploying the GNN-based track-finding algorithm in a production environment requires the installation of all dependent software packages, exclusively utilized by this algorithm. These computing challenges must be addressed for the successful implementation of GNN-based track-finding algorithm into production settings. In response, we introduce a ``GNN-based tracking as a service'' approach, incorporating a custom backend within the NVIDIA Triton inference server to facilitate GNN-based tracking. This paper presents the performance of this approach using the Perlmutter supercomputer at NERSC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Exploring code portability solutions for HEP with a particle tracking test code

Traditionally, high energy physics (HEP) experiments have relied on x86 CPUs for the majority of their significant computing needs. As the field looks ahead to the next generation of experiments such as DUNE and the High-Luminosity LHC, the computing demands are expected to increase dramatically. To cope with this increase, it will be necessary to take advantage of all available computing resources, including GPUs from different vendors. A broad landscape of code portability tools—including compiler pragma-based approaches, abstraction libraries, and other tools—allow the same source code to run efficiently on multiple architectures. In this paper, we use a test code taken from a HEP tracking algorithm to compare the performance and experience of implementing different portability solutions. While in several cases portable implementations perform close to the reference code version, we find that the performance varies significantly depending on the details of the implementation. Achieving optimal performance is not easy, even for relatively simple applications such as the test codes considered in this work. Several factors can affect the performance, such as the choice of the memory layout, the memory pinning strategy, and the compiler used. The compilers and tools are being actively developed, so future developments may be critical for their deployment in HEP experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗