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At least 91 records · Page 5

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science

We present the Exascale Framework for High Fidelity coupled Simulations (EFFIS), a workflow and code coupling framework developed as part of the Whole Device Modeling Application (WDMApp) in the Exascale Computing Project. EFFIS consists of a library, command line utilities, and a collection of run-time daemons. Together, these software products enable users to easily compose and execute workflows that include: strong or weak coupling, in situ (or offline) analysis/visualization/monitoring, command-and-control actions, remote dashboard integration, and more. We describe WDMApp physics coupling cases and computer science requirements that motivate the design of the EFFIS framework. Furthermore, we explain the essential enabling technology that EFFIS leverages: ADIOS for performant data movement, PerfStubs/TAU for performance monitoring, and an advanced COUPLER for transforming coupling data from its native format to the representation needed by another application. Finally, we demonstrate EFFIS using coupled multi-simulation WDMApp workflows and exemplify how the framework supports the project’s needs. We show that EFFIS and its associated services for data movement, visualization, and performance collection does not introduce appreciable overhead to the WDMApp workflow and that the resource-dominant application’s idle time while waiting for data is minimal.

97 MATHEMATICS AND COMPUTING↗

A generic, geometric cocalibration method for a combined system of fluorescence molecular tomography and microcomputed tomography with arbitrarily shaped objects

Purpose: A combined system of fluorescence molecular tomography and microcomputed tomography (FMT and mCT) can provide molecular and anatomical information of small animals in a single study with intrinsically coregistered images. The anatomical information provided by the mCT subsystem is commonly used as a reference to locate the fluorophore distribution or as a priori structural information to improve the performance of FMT. Therefore, the transformation between the coordinate systems of the subsystem needs to be determined in advanced. Methods: A cocalibration method for the combined system of FMT and mCT is proposed. First, linear models are adopted to describe the galvano mirrors and the charge-coupled device (CCD) camera in the FMT subsystem. Second, the position and orientation of the galvano mirrors are determined with the input voltages of the galvano mirrors and the markers, whose positions are predetermined. The position, orientation and normalized pixel size of the CCD camera are obtained by analysing the projections of a point-like marker at different positions. Finally, the orientation and position of sources and the corresponding relationship between the detectors and their projections on the image plane are predicted. Because the positions of the markers are acquired with mCT, the registration of the FMT and mCT could be realized by direct image fusion. Results: The accuracy and consistency of this method in the presence of noise is evaluated by computer simulation. Next, a practical implementation for an experimental FMT and mCT system is carried out and validated. The maximum prediction error of the source positions on the surface of a cylindrical phantom is within 0.375 mm and that of the projections of a point-like marker is within 0.629 pixel. Finally, imaging experiments of the fluorophore distribution in a cylindrical phantom and a phantom with a complex shape demonstrate the feasibility of the proposed method. Conclusions: This method is universal in FMT and mCT, which could be performed with no restriction on the system geometry, calibration phantoms or imaging objects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A National Collaboratory to Advance the Science of High Temperature Plasma Physics for Magnetic Fusion

This report summarizes the work of the National Fusion Collaboratory (NFC) Project to develop a persistent infrastructure to enable scientific collaboration for magnetic fusion research. The original objective of the NFC project was to develop and deploy a national FES Grid (FusionGrid) that would be a system for secure sharing of computation, visualization, and data resources over the Internet. The goal of FusionGrid was to allow scientists at remote sites to participate as fully in experiments and computational activities as if they were working on site thereby creating a unified virtual organization of the geographically dispersed U.S. fusion community. The vision for FusionGrid was that experimental and simulation data, computer codes, analysis routines, visualization tools, and remote collaboration tools are to be thought of as network services. In this model, an application service provider (ASP provides and maintains software resources as well as the necessary hardware resources. The project would create a robust, user-friendly collaborative software environment and make it available to the US FES community. This Grid's resources would be protected by a shared security infrastructure including strong authentication to identify users and authorization to allow stakeholders to control their own resources. In this environment, access to services is stressed rather than data or software portability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine learning assisted prediction of tungsten heavy alloy plasma facing component performance for fusion energy applications

Tungsten and tungsten heavy alloys (WHAs), known for their remarkably high hardness, durability, and corrosion resistance, play a critical role in the thriving development of nuclear fusion reactors in recent years. However, the exploration in tungsten alloys for the nuclear-related applications has been limited by the difficulty of manufacturing and the complexity of experiments to reproduce the environment of nuclear reaction. Therefore, this project aims to utilize nanoscale simulation methods such as density functional theory (DFT) and molecular dynamics (MD) with the help of machine learning techniques to not only understand the mechanisms of tungsten alloys but also allow us to computationally predict their mechanical behaviors under extreme environments. One critical problem of the application of WHAs in nuclear reactors is the surface melting. In the current design of the SPARC reactor, the WHA, W97Ni2.1Fe0.9 or W97NiFe, is chosen to be the first wall components to confine the plasma where the particles are fiercely moving and colliding into each other to create nuclear fusion reaction. This process will generate extremely high heat flux onto these WHA tiles, leaving high surface temperature that could possibly melt the surface of the WHA tiles, As illustrated in Fig. 1(a). a laser experiment previously done illustrates that a rough surface damage would be made after the surface melting where the matrix area mainly composed of nickel and iron as shown in Fig. 1(b), will first melt and then leave vacancies between these tungsten grains. Unfortunately, these kinds of roughness on the first-wall components could be deadly to the plasma inside a Tokmak reactor because the heat that is supposed to dissipate at a designed ratio through the tiles may in turn be excessively absorbed and accumulated on any uneven area of the surface, which will eventually make the whole nuclear reaction fail. In this project, we will introduce a machine learning potential, Allegro, based on DFT calculation and then build a MD model for W-Ni-Fe alloys.

36 MATERIALS SCIENCE↗

Review of recent activities with MOOSE, an open-source finite element & finite volume multi-fidelity simulation framework

Modeling and simulation are an increasing part of engineering. This is undoubtedly driven by the high costs of constructing experimental facilities, but also enabled by the exponential increase in computing powers over the last decades, which allows computational models to be closer than ever to reality. One of the main drivers for the development of MOOSE is supporting advanced nuclear reactor simulations. A challenging aspect of modeling advanced nuclear reactors is the plurality of physics involved, including neutronics, thermal hydraulics and fuel performance. These physics are all coupled to some extent and are generally solved in a sequential but iterative fashion. The United States (U.S.) national laboratories have been developing MOOSE, an open source multiphysics framework since its inception at the Idaho National Laboratory (INL) in 2008. This framework enables seamless coupling of multiphysics simulations and facilitates the implementation of new physics and material governing laws. It is continuously expanded with novel numerical methods and new pre-implemented physics module. Numerous applications, developed within the Department of Energy (DOE) laboratories, academia, and industry, including outside of nuclear engineering, have been developed to study specialized physics problems. International collaborations are welcome on this open-source modeling and simulation project.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Simulating Dopant Diffusion in a Detalied Porous Structure

The National Ignition Facility (NIF) at Lawrence Livermore National Laboratory (LLNL) uses highpowered lasers to explore cutting edge fusion technology. Specialized optics, known as fiber lasers, generate and amplify the NIF’s high-powered lasers that facilitate fusion experiments. Fiber lasers are glass fibers that are doped with heavy elements to stimulate light emission. The fiber laser doping processing uses a predeposited layer of porous silica nanoparticles on the surface of the glass to absorb a dopant rich salt solution. Our project simulated the diffusion of dopants into porous silica with prescribed colloidal stacking geometries using COMSOL Multiphysics. With these simulations we identified the porosity and tortuosity of the porous nanoparticle structures as the primary parameters that will dictate how the dopants will diffusive into the porous surface of the glass. Porosity and Tortuosity are geometric parameters that can easily be input into more detailed simulations to estimate an effective diffusivity within the porous layer. Future work should account for surface reactions to accurately simulate the full-scale diffusion of the solution doping process.

36 MATERIALS SCIENCE↗

Photo-fusion reactions in a new compact device for ELI

In the last few years significant progress on technological, experimental and numerical studies on fusion process in high density and high temperature plasmas produced by a high intensity laser pulse interaction with clusters in a high external applied magnetic field, enable us to propose a compact photo-fusion magnetic device for high neutron production. For the purpose of the project a pulsed magnetic field driver with values up to 110 Tesla has been developed which allows increasing the trapping time of the high density plasma in the device and improving the neutron yield. Numerical simulations show that the proposed device is capable of producing up to 10{sup 9}-10{sup 10} neutrons per laser shot with an external magnetic field of 150 Tesla. The proposed device can be used for experiments and numerical code validation concerning different conventional and (or) exotic fusion fuels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

3D modeling of the Staged Z-pinch with the FLASH code

The Staged Z-pinch (SZP) fusion concept is a magneto-inertial compression scheme developed by Magneto-Inertial Fusion Technologies, Inc. (MIFTI), in which small amounts of fusion fuel are brought to fusion-relevant conditions by passing multi-million amperes strong current through a cylindrical shell of high atomic number material. One- and two-dimensional modeling performed by MIFTI with the MACH2 code, suggests that net fusion energy gain can be achieved when currents in the 10 million amperes range compress a 50%-50% mixture of deuterium and tritium gas. In this project we enhance and use the FLASH code to execute high-fidelity, simulations of various SZP configurations, a collaboration between the Flash Center for Computational Science at the University of Rochester and the Laboratory for Laser Energetics, and MIFTI. FLASH is a high-performance computing, multi-physics, radiation magnetohydrodynamic (MHD) code with extended physics capabilities, which is developed at the Flash Center. The goal of this project is to assess the shell/fuel stability of the pinch to two- and three-dimensional MHD instabilities and to utilize FLASH’s extended physics capabilities to understand how extended-MHD effects impact implosion dynamics and plasma conditions at stagnation. The project is a natural extension of an ongoing collaborative effort between MIFTI and the Flash Center through the U.S. DOE Advanced Research Projects Agency-Energy (ARPA-E) BETHE program and can provide MIFTI with simulation capabilities that are currently beyond their reach with MACH2. Ultimately, MIFTI wants FLASH to become one of their simulation workhorses for reliable, high-fidelity SZP platform design. During the project, the Flash Center team developed a suite of in one- and two-dimensional FLASH simulations to model different variants of the SZP platform, performed code-to-code comparisons with MACH2, and used the FLASH code to design and model SZP experiments like the Double Eagle experiments that MIFTI recently performed. Also, the Flash Center team developed the capabilities of FLASH to be able to do three-dimensional simulations of pulsed-power experiments with the code for the first time. Two publications from this effort are currently under review and two more are in preparation. MIFTI has also committed to the use of FLASH for future SZP simulation efforts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling the Interaction of Laser-Produced Proton Beams with Matter

A major goal of this project is to significantly increase our understanding of isochoric heating of matter using laser produced proton beams, and the associated high energy density (HED) and warm dense matter (WDM) regimes generated. This will benefit research fields such as planetary science, fusion energy, plasma physics, and material science. For example, it will enhance our understanding of WDM properties of iron and silica under conditions encountered in planetary interiors and diagnostic components in fusion devices exposed to high fluxes of energetic plasma ions. The project is motivated by recent experiments that irradiated Si targets with proton beams generated by the 20 TW-laser at the SLAC MEC end-station. The HED/WDM states are probed using the 50 fs hard X-rays available in the 3rd harmonic of the LCLS. As part of this project, results from the phase contrast X-ray imaging, which shows the generation of compression waves that produces rear surface spallation, are compared with results from the 3D multi-physics multi- material code, PISALE, that combines Arbitrary Lagrangian-Eulerian (ALE) hydrodynamics with Adaptive Mesh Refinement (AMR). This comparison required modifications to several physics models in the PISALE (Pacific Island Structured-AMR with ALE) code. An important aspect of this project is the continued training of graduate students in HED physics and in conducting complex multiphysics simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Magnetic Fields on the National Ignition Facility (MagNIF)

A magnetized target capability on the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory (LLNL) has been investigated. Stakeholders’ needs and project feasibility analysis were considered in order to down-select from a wide variety of different potential magnetic field magnitudes and volumes. From the large range of different target platforms, laser configurations, and diagnostics configurations of interest to the stakeholders, the gas-pipe platform has been selected for the first round of magnetized target experiments. Gas pipe targets are routinely shot on the NIF and provide unique value for external collaborators. High-level project goals have been established including an experimentally relevant 20Tesla magnetic field magnitude. The field will be achieved using pulsed power-driven coils. A system architecture has been proposed. The pulsed power drive system will be located in the NIF target bay. This decision provides improved maintainability and mitigates equipment safety risks associated with explosive failure of the drive capacitor. High-level and first-level subsystem requirements have been established. Requirements have been included for two distinct coil designs – full solenoid and quasi-Helmholtz. A Failure Modes and Effects Analysis (FMEA) has been performed and documented. Additional requirements have been derived from the mitigations included in the FMEA document. A project plan is proposed. The plan includes a first phase of electromagnetic simulations to assess whether the design will meet performance requirements, then a second phase of risk mitigation projects to address the areas of highest technical risk. The duration from project kickoff to the first magnetized target shot is approximately 29 months.

42 ENGINEERING↗

Toward digital design at the exascale: An overview of project ICECap

High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Initial Development of Fusion Magnet Simulation Capabilities for Performance and Safety Evaluation Using the MOOSE Framework

Fusion energy holds the promise of being a transformative technology as a carbon-neutral, sustainable source of energy. Whole device modeling and the development of fusion digital twins will be increasingly important for emerging fusion device concepts at both national laboratories and within the commercial fusion industry. However, meeting the challenge of whole device modeling of fusion energy devices requires robust, multiphysics, multiscale modeling and simulation technologies capable of running on large-scale supercomputers. Detailed analysis of individual systems at-scale is also required to ensure safe and efficient operation as well as provide the safety basis for future device designs and licensing activities. In a tokamak, toroidal and poloidal magnets confine and shape the fusion plasma to promote the fusion reaction. High plasma temperatures and high magnetic field requirements in modern design concepts (leading to high amounts of energy stored within each magnet) impose electrical, thermal, and mechanical loads on the magnet components, which in turn impacts the safety considerations of the magnet and their supporting systems. Idaho National Laboratory (INL) has a history of working in this space, including development and benchmarking of the Magnetic System Circuitry Analysis Program (MSCAP) and Magnet Arcing (MAGARC) codes to study magnet quench events; notably, MAGARC was used to study quenching during the ITER Engineering Design Activity. However, these legacy codes and capabilities are not parallel and scalable, and new tools are required for future advances in this area, which leads to the INL-developed Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Developed originally for fission reactor systems under United States Department of Energy, Office of Nuclear Energy modeling and simulation programs, the MOOSE framework has been well-suited to multiscale, multiphysics modeling and simulation needs for nuclear systems. The framework is open-source, well-tested, under continuous development and deployment, and developed to a Nuclear Quality Assurance, Level 1 software quality standard. MOOSE has also been used in the fusion space previously in several projects: INL’s Tritium Migration Analysis Program, Version 8 (TMAP8) for tritium migration, UK Atomic Energy Authority’s A Unified Resource for OpenMC (fusion) Reactor Applications (AURORA) code for fusion thermo-mechanical and neutronics analysis, and Argonne National Laboratory’s Cardinal for high-fidelity computational fluid dynamics and neutronics. However, to model superconducting magnets, several MOOSE enhancements are required: additions to the current MOOSE electromagnetic capabilities, new material libraries for superconductors of interest (such as YBCO), as well as fusion-specific models for thermo-mechanics. This talk will discuss initial development activities to build these capabilities in MOOSE, focusing on initial validation and benchmarking activities. Proposed coupling workflows and future work to support the simulation of fusion magnets and magnet structural assemblies for performance and safety evaluation in MOOSE will also be discussed.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hydrodynamic analysis of laser-driven cylindrical implosions

Three-dimensional hydrodynamic simulations are performed to study laser-driven cylindrical implosions in the context of experiments (F. Perez et al., Plasma Phys. Controlled Fusion 51, 124035 (2009)) carried out at the Rutherford Appleton Laboratory in the framework of the HiPER project. The analysis is carried out by using the 3D version of the hydrocode MULTI (R. Ramis et al., Comput. Phys. Commun. 49, 475-505 (1988)). The influence of the main laser parameters on implosion performance and symmetry is consistently studied and compared with the results of 2D analysis. Furthermore, the effects of uncertainties in laser irradiation (pointing, focusing, power balance, and time jitter) on implosion performance (average peak density and temperature) are studied by means of statistical analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Vision for Coupling Operation of US Fusion Facilities with HPC Systems and the Implications for Workflows and Data Management

The operation of large US Department of Energy (DOE) research facilities, like the DIII-D National Fusion Facility, results in the collection of complex multi-dimensional scientific datasets, both experimental and model-generated. In the future, it is envisioned that integrated data analysis coupled with large-scale high performance computing (HPC) simulations will be used to improve experimental planning and operation. Practically, massive data sets from these simulations provide the physics basis for generation of both reduced semi-analytic and machine-learning-based models. Storage of both HPC simulation datasets (generated from US DOE leadership computing facilities) and experimental datasets presents significant challenges. In this paper, we present a vision for a DOE-wide data management workflow that integrates US DOE fusion facilities with leadership computing facilities. Data persistence and long-term availability beyond the length of allocated projects is essential, particularly for verification and recalibration of artificial intelligence and machine learning (AI/ML) models. Because these data sets are often generated and shared among hundreds of users across multiple leadership computing facility centers, they would benefit from cross-platform accessibility, persistent identifiers (e.g. DOI, or digital object identifier), and provenance tracking. Here, the ability to handle different data access patterns suggests that a combination of low cost, high latency (e.g. for storing ML training sets) and high cost, low latency systems (e.g. for real-time, integrated machine control feedback) may be needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Statistical uncertainty of eddy covariance CO 2 fluxes inferred using a residual bootstrap approach

High-frequency eddy-covariance measurements of net ecosystem CO 2 exchange (NEE) with the atmosphere are valuable resources for model parameterization, calibration, and validation. However, uncertainties in measured data, i.e., data gaps and inherent random errors, create problems for researchers attempting to quantify uncertainties in model projections of terrestrial ecosystem carbon cycling. Here, we demonstrate that a model-data fusion method (residual bootstrap) produces defensible annual NEE sums, through mimicking the behavior of random errors, filling missing values, and simulating gap-filling biases. This study estimated annual NEE sums for 53 site-years based on nine eddy-covariance tower sites in the USA, and found that our annual estimates were, in most cases, comparable in magnitude with those obtained from AmeriFlux gap-filled data. Additionally, compared to the AmeriFlux standardized gap-filling, our approach provides better NEE estimates for moderate to longer, and more frequent, data gaps. Annual accumulated uncertainties in NEE at the 95% confidence level were ±30gCm -2 year -1 for evergreen needleleaf forests; ±60gCm -2 year -1 for deciduous broadleaf forests; and ±80gCm -2 year -1 for croplands. The residual bootstrap performed worst when gap length was greater than one month or data exclusion greater than 90% during the growing season, common to other gap-filling techniques. However, this study produced robust results for most site years when monthly data coverage during the growing season is not extremely low. We therefore suggest that the inclusion of NEE uncertainty estimates and better estimation for moderate to longer, and more frequent, data gaps as provided by the residual bootstrap approach can be beneficial for ecosystem model evaluation.

54 ENVIRONMENTAL SCIENCES↗

Adamantine 1.0: A Thermomechanical Simulator for Additive Manufacturing

Adamantine is a thermomechanical simulation code that is written in C++ and built on top of deal.II (Arndt et al., 2023), p4est (Burstedde et al., 2011), ArborX (Lebrun-Grandié et al., 2020), Trilinos (The Trilinos Project Team, 2020), and Kokkos (Trott et al., 2022). Adamantine was developed with additive manufacturing in mind and it is particularly well adapted to simulate fused filament fabrication, directed energy deposition, and powder bed fusion. Adamantine employs the finite element method with adaptive mesh refinement to solve a nonlinear anisotropic heat equation, enabling support for various additive manufacturing processes. It can also perform elastoplastic and thermoelastoplastic simulations. It can handle materials in three distinct phases (solid, liquid, and powder) to accurately reflect the physical state during different stages of the manufacturing process. To enhance simulation accuracy, adamantine incorporates data assimilation techniques (Asch et al., 2016). This allows it to integrate experimental data from sensors like thermocouples and infrared (IR) cameras. This combined approach helps account for errors arising from input parameters, material properties, models, and numerical calculations, leading to more realistic simulations that reflect what occurs in a particular print.

36 MATERIALS SCIENCE↗