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At least 757 records · Page 42
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DOE OSTI2023

Automated integration gate selection for Gaussian mixture model pulse shape discrimination

Pulse shapes differ between neutron and gamma particles when measured with detector devices employing pulse shape discriminating (PSD) scintillators. Digitized waveforms can be used in detection systems to perform pulse shape discrimination for this application. Prior Gaussian Mixture Model (GMM) methods require access to the pulse full-waveform. Reducing the waveform to a smaller set of combined samples reduces computational cost while affecting PSD performance. In this work, we develop a method for selecting the best performing combination of integration gates, or contiguous summed segments of the digitized pulse for PSD. The method uses a discrimination score based on the GMM PSD approach. Furthermore, the final selection is performed using Bayesian Optimization. PSD detection results are compared with varying numbers of selected gates on time-of-flight (TOF) data. This method can be used to fully automate the selection of gates in an unsupervised (without ground truth labels) setting.

42 ENGINEERING↗
DOE OSTI2021

Technoeconomic assessment of hydrogen cogeneration via high temperature steam electrolysis with a light-water reactor

Increased electricity production from renewable energy resources, coupled with low natural gas (NG) prices, has caused existing light-water reactors (LWRs) to experience diminishing returns from the electricity market. This reduction in revenue is forcing LWRs to consider alternative revenue streams, such as introduction hydrogen production or desalination, to remain profitable. This paper performs a technoeconomic assessment (TEA) regarding the viability of retrofitting existing pressurized-water reactors (PWRs) to produce green hydrogen (H 2 ) via high-temperature steam electrolysis (HTSE). Such an integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long term and eliminate CO 2 emissions from the hydrogen production process. Here, to accommodate such an integration, a detailed single market levelized cost of hydrogen (LCOH) and multimarket analyses were conducted of HTSE process operation, requirements, costing, and flexibility. Alongside this costing analysis, market analyses were conducted on the electric and hydrogen markets in the PJM interconnect. Utilizing a novel stochastic, dispatch optimization approach results suggest that a positive gain is achievable, and by operating in multiple markets, the nuclear facility can avoid the sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted is a differential cash flow analysis and, as such, does not present profit levels. LCOH analysis results demonstrate the potential exists to produce hydrogen at a cost as low as $1.20/kg. This price is lower than traditional steam methane reforming (SMR) allowing nuclear based hydrogen production to disrupt the existing hydrogen production market.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Risk Management and Risk Aversion, from Benefit to Impediment

Risk management is a critical tool for improving the probability of project success by identifying, assessing, prioritizing, and attempting to control threats to project realization. For industries that require high operational reliability due to the potential consequences of off-normal events, such as the nuclear, aerospace, and chemical sectors, a major focus of risk management is the preservation of process safety. Due to the nature of the processes or systems under consideration, the associated process safety analyses (such as risk and safety assessments) and safety features can require significant resources. These costs are typically tolerated either due to the need to satisfy regulatory requirements or based on the assumption that they generally decrease the occurrence of unwanted events and therefore improve the probability of project success. However, as the level of acceptable or tolerable risk from unwanted events decreases, the required resources necessary for ensuring and demonstrating satisfaction of these criteria can grow and in turn can become one of the dominant impediments to project success. This paper outlines a high-level theoretical framework for the consideration of dominant project risks, which includes potential project failure from both the occurrence of high consequence off-normal events and the inability to achieve project completion due to the resource needs and innovation losses associated with extreme risk aversion. Utilizing such an integrated approach permits an attempt to optimize the probability of successful project realization while also providing valuable insight into the proper level of acceptable risk. The work is presented as a first step, in hopes of spurring additional discussion and analysis regarding appropriate levels of risk tolerance and the balance of project benefits.

Grabaskas, David↗
DOE OSTI2022

Rossi-alpha Analysis of Thermal/Epithermal eXperiments Optimized for Polyethylene Thermal Neutron Scattering

Accurate nuclear data is the foundation for predictive simulations and design of new experimental in the nuclear community. The criticality safety community has particular interest in benchmarking assemblies with thermal neutron data. To address such needs the Nuclear Criticality Safety Program (NCSP) funded the Thermal/Epithermal eXperiments (TEX) campaigns that were to be completed between Lawrence Livermore National Laboratory (LLNL) and Los Alamos National Laboratory (LANL). Specifically, analysis of plutonium with a thermal neutron spectrum expands on previous work to help validate thermal scattering law data, which can have larger impacts in thermal applications. The first of these experiments were successfully conducted in 2018, but this paper will focus on the 2021 measurement focused on investigating the the thermal scattering law (TSL) for polyethylene. These experiments were successfully conducted at the National Criticality Experiments Research Center (NCERC) using the Planet vertical lift critical assembly machine. Polethylene plates were layered with trays of Zero Power Physics Reactor (ZPPR) 24 plates in a 12" by 12" square. The ZPPR plates were 2" by 3" by 0.125" bearing weapons grade plutonium. The polyethylene moderator was either 2" or 1.6875" thick. This work builds on the Rossi-alpha calculations done by McKenzie et al. for the same detector-assembly system and will only focus on the Rossi-alpha neutron noise method. This work will aim to further validate the results of the experiment through a novel neutron noise python package. Following similar methodology to the previous analysis, analysis of TEX evaluated the prompt neutron decay constant at delayed critical, $α_{DC}$ using Rossi-alpha for different polyethylene moderator thicknesses. These results will help improve understanding of TSL in critical experiments. Alpha (α), is the prompt neutron decay constant of the measured system and allows for the evaluation of a systems propensity to sustain fission chains via prompt neutrons. The single value description of the assemblies allow for comparison between experiments regardless of composition, geometry, and reflectors/moderators. Rossi-alpha measurements were performed on the polyethylene moderated TEX experiments to estimate $α_{DC}$.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Development of High-Temperature Bonding Techniques to Enable High-Temperature Static or Dynamic Strain Measurements

Current light-water nuclear reactors rely on a variety of different sensors and sensor applications to meet their structural health monitoring needs throughout the entirety of the reactor primary, secondary, and containment systems. Optical fiber–based sensor technologies could provide solutions to reduce the sensor system footprint while enhancing the measurement fidelity and spatial resolution by leveraging distributed monitoring techniques. Moreover, advanced reactors may require optical fiber–based sensors for structural health monitoring because their operating temperatures will exceed the limits of conventional transducers used to acquire dynamic strain or acoustic data in nuclear power plants. Therefore, this report describes experiments targeting the development of high-temperature bonding techniques that would allow for potentially long lengths of fibers to be bonded to metallic reactor components in advanced reactor systems. The high temperatures experienced within target application, next-generation nuclear reactors, necessitate a high-temperature resistant bond to limit the amount of tension on the fiber at the target application temperature. The primary bonding method investigated in this work is brazing; hot-rolling has also been investigated to a lesser extent. Both techniques are well-suited to bonding optical fibers to large reactor components such as primary coolant piping, pressure vessels, or heat exchangers. Optical frequency domain reflectometry was used to monitor the strain in metal-coated optical fibers before, during, and after the high-temperature bonding process. On select optical fibers that were successfully bonded, additional thermal cycling was performed to assess the extent to which the fiber remained bonded based on the expected thermal expansion of the test specimen material. The results of the various experiments yielded the following general conclusions: (1) brazing is a viable technique for bonding and allows significant compressive strain to be applied to the fiber at room temperature; (2) hot-rolling is a viable technique as well, which has been more optimized than the brazing technique for bonding, but less residual compressive strain has been observed with this technique; and (3) both techniques will need further development and optimization to demonstrate bonding of a long length of fiber that can provably operate at relevant temperatures for an advanced nuclear reactor application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

FY 2022 Idaho National Laboratory Site Sustainability Plan

The mission of the Department of Energy (DOE) is to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions. This FY 2022 Idaho National Laboratory Site Sustainability Plan (SSP) was developed to enable and sustain Idaho National Laboratory’s (INL’s) mission to discover, demonstrate, and secure innovative nuclear solutions, clean energy options, and critical infrastructure. DOE Order 436.1, “Departmental Sustainability,” provides requirements and assigns responsibilities for managing sustainability within DOE to ensure that DOE missions are carried out in a sustainable manner, to institute wholesale cultural change to factor sustainability into all DOE decisions, and to ensure DOE achieves sustainability goals. DOE Order 436.1 also requires DOE sites to commit appropriate personnel resources, establish a financing plan that prioritizes the use of life-cycle cost effective private-sector financing, optimize the application of appropriations and budgeted funds, and establish specific performance measures and deliverables designed to achieve the listed requirements. The SSP was developed according to the narrative requirements from the “FY 2022 DOE Site Sustainability Plan Guidance” document issued in September 2021. The SSP contains strategies and activities that will lead to continual energy, water, and waste reductions that move the INL site toward meeting DOE sustainability goals and requirements. The SSP summarizes energy and available fuel use reporting requirements and references criteria for instituting sustainable design. SSP requirements are integrated into each INL site contractor’s Integrated Safety Management System and Environmental Management System (EMS). Finally, the Sustainability Program directives, based on this SSP, are integrated into INL/LTD-21-62463, Annual Laboratory Plan 2021, and operations and acquisition systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

FY 2023 Idaho National Laboratory Site Sustainability Plan

The mission of the Department of Energy (DOE) is to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions. This FY 2022 Idaho National Laboratory Site Sustainability Plan (SSP) was developed to enable and sustain Idaho National Laboratory’s (INL’s) mission to discover, demonstrate, and secure innovative nuclear solutions, clean energy options, and critical infrastructure. DOE Order 436.1, “Departmental Sustainability,” provides requirements and assigns responsibilities for managing sustainability within DOE to ensure that DOE missions are carried out in a sustainable manner, to institute wholesale cultural change to factor sustainability into all DOE decisions, and to ensure DOE achieves sustainability goals. DOE Order 436.1 also requires DOE sites to commit appropriate personnel resources, establish a financing plan that prioritizes the use of life-cycle cost effective private-sector financing, optimize the application of appropriations and budgeted funds, and establish specific performance measures and deliverables designed to achieve the listed requirements. The SSP was developed according to the narrative requirements from the “FY 2022 DOE Site Sustainability Plan Guidance” document issued in September 2021. The SSP contains strategies and activities that will lead to continual energy, water, and waste reductions that move the INL site toward meeting DOE sustainability goals and requirements. The SSP summarizes energy and available fuel use reporting requirements and references criteria for instituting sustainable design. SSP requirements are integrated into each INL site contractor’s Integrated Safety Management System and Environmental Management System (EMS). Finally, the Sustainability Program directives, based on this SSP, are integrated into INL/LTD-21-62463, Annual Laboratory Plan 2021, and operations and acquisition systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Feasibility Assessment of a Natural-Circulation Salt Irradiation Loop in the Advanced Test Reactor

Molten-salt reactors will likely require some level of irradiation testing as part of their licensing basis. An ideal experiment would consider the integrated effect of neutron flux and fission product generation in addition to circulating flow conditions. The feasibility of a natural-circulation irradiation salt loop in the Advanced Test Reactor (ATR) is assessed here. The flow is induced by the innovative combination of gas gaps and fin gaps along the capsule wall to fine-tune radial heat conductance, and therefore drive an axial temperature gradient across the experiment height. Following multiple design optimizations, a promising configuration has been identified. The 45-kW experiment would generate a 0.15 m/s flow velocity with 6 kg of fuel-bearing salt. This demonstrates the possibility of generating appreciable flow rates within manageable experimental conditions (e.g., total size and heat generation). An initial assessment of species mass tracking inside the experiment was also performed to gain an understanding of radionuclide behavior within the system. Results showed that significant quantities of Xe can be extracted in the off-gas (1.7 kCi) for an 8% bubble removal efficiency rate. Here, these results highlight the potential value of such experiments. Further work will involve detailed engineering drawings and analyses of the loop, as well as more computationally expensive modeling of species mass tracking.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Machine Learning Classification of Molten Salt Heat Exchanger Channel Plugging using Synthetic Data

This report addresses the requirements of Milestone M3.4 AI capability to identify and predict maintenance events. Development of digital twins (DT) for molten salt reactor (MSR) components is crucial for reducing operating and maintenance costs (O&M) and ensuring commercial viability of these reactors. Our focus is on development of DT for MSR primary system heat exchanger (HX), a critical component, the fault in which can reduce operating efficiency and force reactor shutdown. We are investigating the feasibility of a conceptual DT of HX consisting of internal distributed temperature sensing with fiber optics and machine learning (ML) algorithms to detect and localize faults. To determine the optimal approach to detection and localization of channel plugging, we benchmark seven different ML models: Logistic Regression, K-Nearest Neighbors (KNN), Gaussian Naïve Bayes, Support Vector Machines (SVM), Decision Tree Classifier, Random Forest Tree Classifier, and Feed-Forward Neural Network. ML algorithms are benchmarked using synthetic HX plugging data generated with computational fluid dynamics COMSOL software, with added brown noise to represent experimental noise. We show that the best performance is obtained with the Decision Tree classifier.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Persistent Acoustic Sensing for Monitoring A Reactor Facility - Oral Presentation

Measurements over the past few years, taking place within the Multi-Informatics for Nuclear Operations Scenarios (MINOS) project, show that infrasound and low-frequency acoustic monitoring can detect, and often quantify, activities that occur on-site at a large research reactor. Observable activities include: crane translation, lifting, and lowering; differentiation between loaded and unloaded crane operations; access door opening and closing; vehicle operations; and cooling tower fan operation. Advanced data analytic and spectral feature extraction methods can be used to interpret selected signatures to reach a deeper understanding of different reactor activities. These measurements are being conducted using a network of smartphones that continuously operate in conjunction with cloud-based architectures. A recent addition to the system is the development and deployment of a real-time, cloud-based analytic framework that supports near-real-time alarming which can facilitate tip-and-cue protocols. This paper will present recent research advances in this area including studies to explore the transferability of learned parameters from one smartphone to another, the detectability of events from multiple sensors at different locations simultaneously, and the feasibility of porting analytical tools directly to the smartphones to allow edge computing with optimized configurations.

42 ENGINEERING↗
DOE OSTI2021

Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors

With the advances in computational power and numerical methods, analysts can now rely on first-principle simulations to predict ultra-fine details in a variety of applications. Advances in machine learning (ML) have produced algorithms that can now learn high-level abstractions via hierarchical models. This project aims to leverage advances in ML techniques and the available high-resolution simulation data to develop a novel modeling and simulation (M\&S) methodology for reactor safety analysis. While application-agnostic ML techniques are available, complex physics constraints need to be incorporated into ML techniques to build ML-based closures for computationally efficient predictive simulations. This project intends to develop a physics-guided data-driven multi-scale methodology for M\&S of advanced reactors. The project focuses on thermal fluid (T/F) phenomena, which play major roles in advanced reactor safety. Specifically, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor (SFR). The model has a coarse-mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data with Reynolds-averaged Navier-Stokes (RANS) turbulence model to ensure accuracy. Three different neural networks are developed and tested for loss-of-flow transients in the hot pool of SFR, i.e. the densely connected convolutional neural network (DCNN), long-short-term-memory network based on proper orthogonal decomposition (POD-LSTM), and the DCNN informed by LSTM (DCNN-LSTM). The performances of these three neural networks are evaluated based on baseline models. The DCNN-LSTM model has been chosen for further hyperparameter optimization. Furthermore, based on a simplified two-dimensional case, uncertainty quantification (UQ) of the developed ML-based closure are investigated with three methods, i.e. Monte Carlo dropout, deep ensemble, and Bayesian neural network. The developed ML-based turbulent viscosity closure relation based on deep ensemble is then integrated into the system analysis module SAM and serves as a term in the conservation equations. Such a SAM-ML based procedure guarantees that the obtained results are consistent with the physical constraints of the thermal-fluid system. The SAM-ML simulation on the same loss-of-flow transient showed comparable accuracy with the CFD simulation but with a much coarser mesh setup. Last but not least, the ML-based closure improvement with the support of higher-fidelity data from large eddy simulation (LES) is discussed. As a first step towards this direction, a baseline LES simulation is performed to obtain comparable data with RANS results. Based on the early results, future investigation on further improving the ML-based closure is discussed. We believe the developed approach that combines scientific machine learning with nuclear system analysis code can benefit the advanced reactor community as more accurate safety analyses will better characterize reactor safety margins and reduce licensing efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Accurate and Efficient Parametric Model-Order Reduction for Turbulent Thermal Transport

This project produced new algorithms and software for low-cost exploration of turbulent thermal-fluids behavior under parametric variation by using reduced-order models (ROMs). The ROMs numerically solve the governing equations for fluid motion by using a small set of basis functions (typically, N=20-200 modes) to represent the solution. The base modes are computed as optimal combinations of solutions from expensive high-fidelity "anchor-point" solutions involving millions of unknowns, which are typically generated by solving the full Navier-Stokes equations on a supercomputer. The ROM solution is itself a combination of the base modes, where the basis coefficients are determined by evolving an NxN system of nonlinear equations. The overarching idea is to use the inexpensive ROM to predict solutions under conditions where the parameters differ from the anchor-point conditions. Several ingredients are required to make ROMs useful for thermal hydraulics analysis. These include: a stable and accurate ROM that is capable of reproducing the large-scale dynamics of turbulent flow, error indicators than can guide the choice of anchor points, and low-cost mechanisms for evaluating nonlinear terms in the reduced equations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Oak Ridge National Laboratory Neutron Spin Echo Beamline on NB-2

Neutron Spin Echo (NSE) spectroscopy uniquely measures the Q-dependence of slow relaxation dynamics, and having such a machine at HFIR will advance polarized neutron spectroscopy and promote the study of biophysical and energy materials using neutrons. The 2018 Instrument Advisory Board (IAB) advises Neutron Sciences Directorate, ORNL to upgrade the cold neutron delivery system at HFIR, addressing geometrical challenges in neutron transfer from the bright cold source. This is being optimized now: the entrance to the guide system is moving closer to the source, and more guides are being added. However, there are still significant challenges to making the cold flux at the sample world-class. With the proposed guide system, NB-2 can deliver more than 10 6 polarized neutrons per cm 2 /sec below 8Å, and probably 10Å with further optimization. With no potential for running user experiments with neutrons longer than 15Å, the utility of such a machine for biological studies is limited. However, there is a large demand for this class of spectrometer in materials science, chemical engineering, and nanotechnology. Workshops held over the past decade and the three-source vision have highlighted the community's need for a low-angle, high-energy resolution spectrometer at HFIR. A detailed design study of this spectrometer is needed, focusing on optimizing the neutron delivery system for SANS-type studies. This neutron spectrometer would complement studies already performed on both SNSNSE and BASIS by overlapping and extend the dynamic range accessible, while acknowledging the proposed machine, EXPANSE, at the Second Target Station. Two technologies currently exist for such a spectrometer: traditional DC solenoids like those on BL-15 at SNS and IN15 at the ILL, and RF-flipper-based machines similar to RESEDA at FRMII. Either instrument would satisfy the scientific justification. However, there are strong business and scientific cases to utilize the thermal flux, the resonant expertise developed at ORNL, and the potential to utilize an entangled beam of neutrons to probe quantum matter by adopting the neutron resonant spin-echo configuration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Computing the Properties of Matter with Leadership Computing Resources (Closeout Report for DE-SC0018121)

In order to add more capabilities to Halide, we have designed a new framework called Tiramisu and integrated this framework into Halide. Since Tiramisu enables Halide to target heterogeneous architectures, our development efforts have been refocused on Tiramisu. Most high-performance computer systems today are complex and increasingly heterogeneous; they may have CPUs, GPUs and FPGAs. Achieving best performance requires taking full advantage of all these different architectures. To address this issue, we have designed Tiramisu, an optimization framework that enables Halide (and other DSLs) to target heterogeneous architectures. Tiramisu is an optimization framework that takes as input a high level, architecture-independent representation of code and a set of scheduling and data mapping commands that guide code transformation. The input can either be generated by a domain-specific language (DSL) compiler such as Halide or directly written by a programmer. Tiramisu then applies the user-specified code and data-layout transformations and generates an architecture-specific, low-level intermediate representation (IR) that takes advantage of modern architectural features such as multicore parallelism, non-uniform memory (NUMA) hierarchies, clusters, and accelerators like GPUs and FPGAs. We integrated Tiramisu within Halide and implemented a representative set of benchmarks to evaluate this integration. Tiramisu is now open source and is available for public use (http://tiramisu-compiler.org/). A paper about Tiramisu was published, it shows that Tiramisu extends Halide with many new capabilities and that Tiramisu can generate efficient code for multicores, GPUs, FPGAs and distributed heterogeneous systems. The performance of code generated by the Tiramisu backends matches or exceeds hand optimized reference implementations. For example, the multicore backend matches the highly optimized Intel MKL library on many kernels and shows speedups reaching 4x over the original Halide. In addition to making Tiramisu more robust, we have used Tiramisu to implement a set of representative tensor operation for constructing baryon building blocks required for multi baryon contractions in LQCD. In order to implement this code, we needed to generalize Tiramisu in two ways: first we needed to support indirect array accesses, and second, we needed to add support for complex numbers to Tiramisu. The code generated by Tiramisu is 6x faster than the reference code. Our efforts towards an MPI based multi-node version of tiramisu have matured and the resulting code scales well on multiple nodes (tests up to 512 KNL nodes have been undertaken).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Expanded Capabilities and Opportunities for Virtual Beamline Code

In the 25 years since LLNL broke ground on the National Ignition Facility (NIF) - a cornerstone of the National Nuclear Security Administration’s Stockpile Stewardship Program - the NIF and Photon Science (NIF&PS) Directorate has steadily pushed the boundaries of laser physics, nonlinear optics, and photonics in service of inertial confinement fusion experiments, and advanced photon sources development. Beyond the 192 beamlines of the primary laser facility with its world-record energy and fusion yields, NIF&PS capabilities have expanded to include chirped-pulse amplification, kilojoule petawatt-class short-pulse systems to generate hard x-ray radiographic probes, high-average power lasers as secondary sources for generation or wake field particle acceleration along directed energy applications, and other scientific pursuits. The Computing Directorate partners with NIF&PS on numerous projects and technologies from diagnostic measurements and high performance control systems to data analysis, information technology infrastructure, and scientific simulation code development. “This strong collaboration enables cutting-edge science, particularly with regard to physics-based modeling and simulation,” says physicist Jean-Michel Di Nicola. One crucial capability for NIF&PS is the Virtual Beamline (VBL) laser simulation code. It can model all the major laser physics and technology involved in the design optimization, commissioning, and operations of advanced laser architectures from tabletop to NIF-scale. VBL provides researchers with high-fidelity models and high-resolution calculations of laser performance predictions—including for the entire NIF laser system, the Advanced Radiographic Capability, parts of the High Repetition-Rate Advanced Petawatt Laser System laser delivered to the Czech Republic, and the Optical Science Laser. After more than two decades of experimentally verified physics and computing enhancements, this unique workhorse code is wrapping up another major milestone: migration from Java to C++ with a flurry of user interface and optimization features, as well as laser physics and high-resolution enhancements thanks to parallel execution on Livermore Computing platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Safety Analysis for Accident-Tolerant Fuels with Increased Enrichment and Extended Burnup

The ERP research and development efforts in FY22 focused on the safety analysis of ATF with increased enrichment and extended burnup to provide scientific knowledge of the ATF fuel performance, failure mechanism and source term analysis during severe accident of the NPP. FeCrAl clad ATF was selected as basis of the reactor fuel. An optimized equilibrium cycle was developed for 24-months extended burnup operation. A 4-loop PWR model under loss-of-coolant accident (LOCA) was assessed and the behavior of the major source term from failed ATF has been analyzed. The result showed that grace to enhanced mechanical characteristics of ATF, the fuel failure starts up to 200~500 seconds later than conventional Zr clad fuel. This time gives sufficient buffer until low pressure safety injection (LPSI) of the emergency core cooling system (ECCS) restarted by the operator which reduces fuel fragmentation, relocation and dispersal (FFRD). As a consequence, the total amount of major radioactive materials released from FeCrAl clad fuel into the reactor containment was found up to three times less compare to Zr clad fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Single-shot in-line x-ray phase-contrast imaging of void-shockwave interactions in fusion energy materials

Recent breakthroughs in nuclear fusion, specifically the report of reactions exceeding scientific breakeven at the National Ignition Facility (NIF), highlight the potential of inertial fusion energy (IFE) as a sustainable and virtually limitless energy source. However, further progress in IFE requires characterization of defects in ablator materials and how they affect fuel capsule compression. Voids within the ablator can degrade energy yield, but their impact on the density distribution has primarily been studied through simulations, with limited high-resolution experimental validation. To address this, we used the x-ray free-electron laser (XFEL) at the matter in extreme conditions (MECs) instrument at the Linac coherent light source (LCLS) to capture 2D x-ray phase-contrast (XPC) images of a void-bearing sample with a composition similar to inertial confinement fusion (ICF) ablators. By driving a compressive shockwave through the sample using MEC's long-pulse laser system, we analyzed how voids influence shockwave propagation and density distribution during compression. To quantify this impact, we extracted phase information using two phase retrieval algorithms. First, we applied the contrast transfer function (CTF) method, paired with Tikhonov regularization and a fast optimization approach to generate an initial phase estimate. We then refined the result using a projected gradient descent (PGD) method that works directly with the sample's refractive index. Comparing these results with radiation adaptive grid Eulerian (xRAGE) radiation hydrodynamic simulations enables identification of model validation needs or improvements. By calculating phase maps in situ, it becomes possible to reconstruct areal density maps, improving understanding of laser-capsule interactions and advancing IFE research.

Hodge, D. S. [Colorado State Univ., Fort Collins, ↗
DOE OSTI2020

Evolution of the ROOT Tree I/O

The ROOT TTree data format encodes hundreds of petabytes of High Energy and Nuclear Physics events. Its columnar layout drives rapid analyses, as only those parts (“branches”) that are really used in a given analysis need to be read from storage. Its unique feature is the seamless C++ integration, which allows users to directly store their event classes without explicitly defining data schemas. In this contribution, we present the status and plans of the future ROOT 7 event I/O. Along with the ROOT 7 interface modernization, we aim for robust, where possible compile-time safe C++ interfaces to read and write event data. On the performance side, we show first benchmarks using ROOT’s new experimental I/O subsystem that combines the best of TTrees with recent advances in columnar data formats. A core ingredient is a strong separation of the high-level logical data layout (C++ classes) from the low-level physical data layout (storage backed nested vectors of simple types). We show how the new, optimized physical data layout speeds up serialization and deserialization and facilitates parallel, vectorized and bulk operations. This lets ROOT I/O run optimally on the upcoming ultra-fast NVRAM storage devices, as well as file-less storage systems such as object stores.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗