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At least 757 records · Page 42

Understanding grain refinement and intergranular gas bubble evolution in U-10Mo fuel using phase-field modeling

Monolithic U-10Mo fuel undergoes significant microstructural changes in the form of grain refinement and gas bubble formation during burnup, which degrades its mechanical properties. In this talk, I present a phase-field model for microstructure evolution in U-10Mo developed using the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Simulations demonstrate that grain refinement initiates at pre-existing grain boundaries (GBs) to eliminate the lattice distortion energy caused by the accumulation of self-interstitial loops. By employing an equation of state for xenon gas, we simulate the evolution of gas bubbles in the polycrystal microstructure. Large, interconnected bubbles are found to form along the triple junctions. The effects of defect production rate, diffusivities and GB mobility on the microstructure evolution are systematically studied. Homogenization is employed on the microstructures to obtain effective elastic constants and diffusivity as a function of fission density. The simulations provide critical insights on microstructure and property degradation in U-10Mo fuel.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Kinetic Plasma Simulation Capabilities in the MOOSE Framework: Verification of Particle-Particle Collisions

High-fidelity simulations of complex plasma systems allow researchers to gain key insights into and understanding of these systems. To facilitate massively parallel high-fidelity plasma simulations, finite-element-based particle-in-cell capabilities are being developed within the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) based framework called Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER). While SALAMANDER’s primary objective is modeling edge plasmas and plasma-facing components in fusion devices, the particle-in-cell capabilities being developed are general and will support modeling low-temperature plasmas as well. Previously, collisionless magnetostatic simulation capabilities have been verified with the two-stream and Dorey-Guest-Harris instabilities, and single particle motion. Collisions were implemented using the direct simulation Monte Carlo method, and verification of this capability will be presented here several verification problems: relaxation of a randomly initialized gas to a Maxwellian distribution, Fourier heat flow, and comparison of reaction rates to both analytic calculations and those calculated using a multi-term Boltzmann solver.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

Integrating Immersive Visualization in Molten-Salt Reactor Waste Management for Experimental Design and Planning

Molten-salt reactors (MSRs) represent a promising solution for next-generation nuclear energy, offering advantages in safety, fuel efficiency, and waste minimization. However, their liquid-fueled design presents unique challenges for spent fuel management, making post-shutdown waste characterization essential for developing effective strategies. Despite this need, there is a notable absence of visualization platforms specifically tailored to the unique characteristics and analytical requirements of MSR waste management. Existing tools in the nuclear industry are primarily designed for reactor operations or generic data exploration and lack both integration with MSR-specific multiphysics frameworks and the ability to simultaneously visualize time-dependent thermal fields, chemical composition evolution, and radiation distribution patterns. To address these limitations, this paper presents an immersive virtual reality (VR) visualization platform that processes and displays high-fidelity multiphysics simulation output from the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework in real-time, using Unity. The platform visualizes MSR waste characteristics such as nuclide decay, salt cooling, and corrosion by using Exodus II output data and running on a VR headset. It includes a user-friendly interface with features such as visibility toggling, cross-sectional slicing, and time-series animation for exploring simulation data. These capabilities support experimental design, stakeholder engagement, and public communication by making complex reactor behavior more accessible and understandable. By enhancing spatial reasoning and reducing cognitive load, this immersive environment fosters more effective communication and decision-making in MSR waste management.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗

NIRP Core Software Suite v.5.1

SAND2023-06610O The Nuclear Incident Response Program (NIRP) Core Software Suite is a set of code that supports multiple applications. It includes miscellaneous base code for data objects, mathematic equations, and user interface components that are used for developing large applications, including those used for data management. Among the types of applications: • Analyst Manager is used for managing contact information, which is also often included in reports and identifies the owners of calculations. • Radionuclide Viewer provides access to the Dose Coefficient File Package (DCFPAK) radiological data, and it complements the Mixture Manager tool. • Mixture Manager creates and manages radionuclides mixtures that are commonly used in other applications. • High Explosive Manager manages explosives and properties. • Chart Viewer is used for data charts such as meteorology charts and other charts specific to data needs. • Unit Converter converts numeric values to/from different units. This package includes object-oriented base code such as data objects describing the date, time, and location of an event; weather conditions; data types that support predefined ranges of values; a unit library, and others. The package also includes mathematic equations such as determining the distance between two points; erf functions; factorial functions; incidence fractions of probit curves; and others. Other features are customized user interface components for text fields; unit selectors (combo boxes); menus; panels; bug-tracking; and automated checks for software updates. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Collins, Ian↗

Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers

In recent years, the SUite of Nonlinear and DIfferential/ALgebraic equation Solvers (SUNDIALS) has been redesigned to better enable the use of application-specific and third-party algebraic solvers and data structures. Throughout this work, we have adhered to specific guiding principles that minimized the impact to current users while providing maximum flexibility for later evolution of solvers and data structures. The redesign was done through the addition of new linear and nonlinear solvers classes, enhancements to the vector class, and the creation of modern Fortran interfaces. The vast majority of this work has been performed “behind-the-scenes,” with minimal changes to the user interface and no reduction in solver capabilities or performance. These changes allow SUNDIALS users to more easily utilize external solver libraries and create highly customized solvers, enabling greater flexibility on extreme-scale, heterogeneous computational architectures.

97 MATHEMATICS AND COMPUTING↗

2.0 - MOOSE: Enabling massively parallel multiphysics simulation

The last 2 years have been a period of unprecedented growth for the MOOSE community and the software itself. The number of monthly visitors to the website has grown from just over 3,000 to now averaging 5,000. In addition, over 1,800 pull requests have been merged since the beginning of 2020, and the new discussions forum has averaged 600 unique visitors per month. The previous publication has been cited over 200 times since it was published 2 years ago. This paper serves as an update on some of the key additions and changes to the code and ecosystem over the last 2 years, as well as recognizing contributions from the community.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance on HPC Platforms Is Possible Without C++

Computing at large scales has become extremely challenging due to increasing heterogeneity in both hardware and software. More and more scientific workflows must tackle a range of scales and use machine learning and AI intertwined with more traditional numerical modeling methods, placing more demands on computational platforms. These constraints indicate a need to fundamentally rethink the way computational science is done and the tools that are needed to enable these complex workflows. The current set of C++-based solutions may not suffice, and relying exclusively upon C++ may not be the best option, especially because several newer languages and boutique solutions offer more robust design features to tackle the challenges of heterogeneity. In June 2023, we held a mini symposium that explored the use of newer languages and heterogeneity solutions that are not tied to C++ and that offer options beyond template metaprogramming and Parallel. For for performance and portability. In conclusion, we describe some of the presentations and discussion from the mini symposium in this article.

97 MATHEMATICS AND COMPUTING↗

MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING↗

COTS-based OO-component approach for software inter-operability and reuse (software systems engineering methodology)

The purpose of this research and study paper is to provide a summary description and results of rapid development accomplishments at NASA/JPL in the area of advanced distributed computing technology using a Commercial-Off--The-Shelf (COTS)-based object oriented component approach to open inter-operable software development and software reuse.

object-oriented components distributed computing a↗

A Multithreaded Scheduler for a High-Speed Spacecraft Simulator

The Cassini Spacecraft will soon journey to Saturn to perform a close-up study of the Saturnian system; its rings, moons, magneto-sphere, andf the planet itelf. Sequences of commands will be sent to the spacecraft by ground personnel to control every aspect of the mission. To validate and verify these command sequences, a bit-level, high-speed simulator (HSS) has been developed.

deadlock multiprocessing multithreaded object-orie↗

Remote Objects Message Exchange (ROME)

The performance of a single program running on a single processor is limited by the character of the processor. Moreover, the cost and difficulty of developing and sustaining programs tend to increase as their size and complexity increase. Clearly there ought to be some advantage in partitioning powerful application software in relatively small and simple components that can run in parallel on multiple processors; the software should run faster and it should be cheaper and easier to deploy. Remote Objects Message Exchange (ROME) is an attempt to provide a single relatively simple, universally available abstraction for data communication among C++ objects. It aims to enable the C++ application developer to specify objects' interactions with other objects wholly in terms of the application domain, without concern for details of interprocess communication. Every ROME-compliant object is conceptually a network peer of every other, as if each one were (for example) a separate UNIX process.

processors application software data communication↗

Development of a Commercially Viable, Modular Autonomous Robotic Systems for Converting any Vehicle to Autonomous Control

A Modular Autonomous Robotic System (MARS), consisting of a modular autonomous vehicle control system that can be retrofit on to any vehicle to convert it to autonomous control and support a modular payload for multiple applications is being developed. The MARS design is scalable, reconfigurable, and cost effective due to the use of modern open system architecture design methodologies, including serial control bus technology to simplify system wiring and enhance scalability. The design is augmented with modular, object oriented (C++) software implementing a hierarchy of five levels of control including teleoperated, continuous guidepath following, periodic guidepath following, absolute position autonomous navigation, and relative position autonomous navigation. The present effort is focused on producing a system that is commercially viable for routine autonomous patrolling of known, semistructured environments, like environmental monitoring of chemical and petroleum refineries, exterior physical security and surveillance, perimeter patrolling, and intrafacility transport applications.

guidepath position navigation control system↗

MOS 2.0: Modeling the Next Revolutionary Mission Operations System

Designed and implemented in the 1980's, the Advanced Multi-Mission Operations System (AMMOS) was a breakthrough for deep-space NASA missions, enabling significant reductions in the cost and risk of implementing ground systems. By designing a framework for use across multiple missions and adaptability to specific mission needs, AMMOS developers created a set of applications that have operated dozens of deep-space robotic missions over the past 30 years. We seek to leverage advances in technology and practice of architecting and systems engineering, using model-based approaches to update the AMMOS. We therefore revisit fundamental aspects of the AMMOS, resulting in a major update to the Mission Operations System (MOS): MOS 2.0. This update will ensure that the MOS can support an increasing range of mission types, (such as orbiters, landers, rovers, penetrators and balloons), and that the operations systems for deep-space robotic missions can reap the benefits of an iterative multi-mission framework.12 This paper reports on the first phase of this major update. Here we describe the methods and formal semantics used to address MOS 2.0 architecture and some early results. Early benefits of this approach include improved stakeholder input and buy-in, the ability to articulate and focus effort on key, system-wide principles, and efficiency gains obtained by use of well-architected design patterns and the use of models to improve the quality of documentation and decrease the effort required to produce and maintain it. We find that such methods facilitate reasoning, simulation, analysis on the system design in terms of design impacts, generation of products (e.g., project-review and software-delivery products), and use of formal process descriptions to enable goal-based operations. This initial phase yields a forward-looking and principled MOS 2.0 architectural vision, which considers both the mission-specific context and long-term system sustainability.

ground support systems↗