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MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling
Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.
Finite element analysis of steady and transiently moving/rolling nonlinear viscoelastic structure. II - Shell and three-dimensional simulations
In a three-part series of papers, a generalized finite element solution strategy is developed to handle traveling load problems in rolling, moving and rotating structure. The main thrust of this section consists of the development of three-dimensional and shell type moving elements. In conjunction with this work, a compatible three-dimensional contact strategy is also developed. Based on these modeling capabilities, extensive analytical and experimental benchmarking is presented. Such testing includes traveling loads in rotating structure as well as low- and high-speed rolling contact involving standing wave-type response behavior. These point to the excellent modeling capabilities of moving element strategies.
Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption (Research Performance Final Report)
This is the research performance final report for the project entitled: Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption This project was able to achieve the DOE’s goals of developing new modeling tools to understand MDHD vehicle operation and adoption. The first modeling tool is a fleet-level techno-economic analysis model capable of estimating energy use and associated environmental and cost impacts for electrified and conventional vehicles of any MDHD vocation, using real-world cost and operations data, including approaches to optimizing schedules for charging and/or vehicle dispatch. The second modeling tool is a system-level, bottom-up, agent-based adoption model capable of generating geographically-resolved estimates of market projections for MDHD vehicles and charging infrastructure. These tools will be developed and published to serve dual purposes as analysis tools for researchers, and decision-support tools for decision makers within the MDHD system.
A Fast, Accurate Prediction for System-Wide Damage Due to Dynamic Wind Loading
The complex relationship between photovoltaic (PV) hardware configurations, overall system dynamics, and turbulent aerodynamic phenomena generates highly unsteady, non-uniform loads that can lead to damaging instabilities. These effects may result in glass breakage, cell cracking, and structural failures in frames and mounting systems, even under moderate wind conditions. Addressing industry concerns about premature system failures in field conditions deemed survivable, our research aims to develop a fast and accurate predictive model for system damage. This model integrates configurable hardware choices with advanced simulation tools to represent the overall system-specific dynamics effectively. Using this model, we predict responses under varying weather conditions and hardware setups, translating these predictions into pre-trained surrogate models capable of accurately identifying failure risks and rapidly testing new system hardening measures. In this presentation, we will showcase preliminary results in capturing system dynamics through our customizable library of PV hardware configurations. Additionally, we will highlight how these new tools build upon PVade's established wind load modeling capabilities and foster the development of advanced AI/ML surrogates for improving system robustness.
Thermal Effects Modeling Developed for Smart Structures
Applying smart materials in aeropropulsion systems may improve the performance of aircraft engines through a variety of vibration, noise, and shape-control applications. To facilitate the experimental characterization of these smart structures, researchers have been focusing on developing analytical models to account for the coupled mechanical, electrical, and thermal response of these materials. One focus of current research efforts has been directed toward incorporating a comprehensive thermal analysis modeling capability. Typically, temperature affects the behavior of smart materials by three distinct mechanisms: Induction of thermal strains because of coefficient of thermal expansion mismatch 1. Pyroelectric effects on the piezoelectric elements; 2. Temperature-dependent changes in material properties; and 3. Previous analytical models only investigated the first two thermal effects mechanisms. However, since the material properties of piezoelectric materials generally vary greatly with temperature (see the graph), incorporating temperature-dependent material properties will significantly affect the structural deflections, sensory voltages, and stresses. Thus, the current analytical model captures thermal effects arising from all three mechanisms through thermopiezoelectric constitutive equations. These constitutive equations were incorporated into a layerwise laminate theory with the inherent capability to model both the active and sensory response of smart structures in thermal environments. Corresponding finite element equations were formulated and implemented for both the beam and plate elements to provide a comprehensive thermal effects modeling capability.
FY26 Progress on Demonstration of a Multiphysics Steady State Capability for Modeling Core Radial Expansion in SFRs
Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. This report summarizes recent progress on developing a multiphysics, MOOSE-based workflow to predict core bowing and associated reactivity feedback. Significant new capabilities in the reactor physics code Griffin - sodium backfill and pin power reconstruction for deformed geometries - were applied in this effort. This year’s work included verification, code comparisons, sensitivity studies, and coupled demonstrations that advance the state of MOOSE-based core bowing workflow. Griffin’s sodium backfill capability was verified by demonstrating that its automated treatment of geometry expansion and material-density updates reproduces manual calculations exactly, confirming solid mass conservation and proper coolant backfilling in expanded geometries. Reconstructed pin powers were compared for Griffin’s ductheterogeneous and ring-heterogeneous treatments in single-, seven-, and nineteen-assembly cases, with best agreement observed in lower-leakage configurations and the duct-heterogeneous approach offering substantially lower computational cost. Thermal-hydraulic sensitivity sensitivities showed that MOOSE SCM, SAM, and CFD are expected to produce similar deformation predictions despite variances in their temperature predictions, and that explicit treatment of inter-assembly flow becomes increasingly important as gap flow rate increases. Finally, coupled demonstrations on small multi-assembly configurations using Griffin, MOOSE Solid Mechanics, MOOSE SCM, and Heat Conduction produced physically consistent reactivity feedback from thermal expansion and bowing. The coupled demonstrations simulated grid plate expansion as well as resultant core bowing at full power conditions. Simplifications were made in current workflow, namely the assumption of instantaneous full power conditions following hot zero power, and pre-expanding the Griffin geometry axially due to lack of an axial fuel pin expansion model and temperature feedback to Griffin.
NASA Air Force Cost Model (NAFCOM): Capabilities and Results
NAFCOM is a parametric estimating tool for space hardware. Uses cost estimating relationships (CERs) which correlate historical costs to mission characteristics to predict new project costs. It is based on historical NASA and Air Force space projects. It is intended to be used in the very early phases of a development project. NAFCOM can be used at the subsystem or component levels and estimates development and production costs. NAFCOM is applicable to various types of missions (crewed spacecraft, uncrewed spacecraft, and launch vehicles). There are two versions of the model: a government version that is restricted and a contractor releasable version.
Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene
Abstract We present a way to dramatically accelerate Gaussian process models for interatomic force fields based on many-body kernels by mapping both forces and uncertainties onto functions of low-dimensional features. This allows for automated active learning of models combining near-quantum accuracy, built-in uncertainty, and constant cost of evaluation that is comparable to classical analytical models, capable of simulating millions of atoms. Using this approach, we perform large-scale molecular dynamics simulations of the stability of the stanene monolayer. We discover an unusual phase transformation mechanism of 2D stanene, where ripples lead to nucleation of bilayer defects, densification into a disordered multilayer structure, followed by formation of bulk liquid at high temperature or nucleation and growth of the 3D bcc crystal at low temperature. The presented method opens possibilities for rapid development of fast accurate uncertainty-aware models for simulating long-time large-scale dynamics of complex materials.
Validation of a Multiphase Computational Fluid Dynamics Model for Vapor Pull-Through in Normal and Low Gravity
On-orbit fluid transfer such as refueling of propellant tanks and life-support systems can enable long-duration space missions. For safe and efficient liquid transfer operations, prior knowledge of liquid positioning and liquid-vapor interface behavior while draining in a low-gravity environment is required. Numerical models capable of predicting vapor ingestion (or vapor pull-through) can be used to design liquid transfer operations while reducing liquid residuals, mission risk and settling thrust required to prevent vapor ingestion. An experimental program conducted in the 2.2 Second Drop Tower facility at NASA Glenn Research Center investigated the vapor ingestion phenomenon for a range of outflow rates and tank sizes providing a database for validation. This study presents a Computational Fluid Dynamics model capable of accurately predicting the vapor ingestion using the Volume-of-Fluid multiphase solver in commercial code STAR-CCM+. A description of the experimental setup and general trends from similar studies are presented. Comparisons of the numerical prediction and test data in normal and low gravity show good agreement and give confidence in pursuing design of full-scale propellant transfer systems.
Validation of a Multiphase Computational Fluid Dynamics Model for Vapor Pull-Through in Normal and Low Gravity
On-orbit fluid transfer such as refueling of propellant tanks and life-support systems can enable long-duration space missions. For safe and efficient liquid transfer operations, prior knowledge of liquid positioning and liquid-vapor interface behavior while draining in a reduced-gravity environment is required. Numerical models capable of predicting vapor ingestion (or vapor pull-through) can be used to design liquid transfer operations while reducing liquid residuals, mission risk and settling thrust required to prevent vapor ingestion. An experimental program conducted in the 2.2 Second Drop Tower facility at NASA Lewis Research Center in 1969 investigated the vapor ingestion phenomenon for a range of outflow rates and tank sizes providing a database for validation. This study presents a Computational Fluid Dynamics model capable of accurately predicting the vapor ingestion using the Volume-of-Fluid multiphase solver in commercial code STAR-CCM+. A description of the experimental setup and general trends from similar studies are presented. Comparisons of the numerical prediction and test data in normal and low gravity show good agreement and give confidence in pursuing design of full-scale propellant transfer systems.
Validation of A Multiphase Computational Fluid Dynamics Model for Vapor Pull-Through in Normal and Low Gravity
On-orbit fluid transfer such as refueling of propellant tanks and life-support systems can enable long-duration space missions. For safe and efficient liquid transfer operations, prior knowledge of liquid positioning and liquid-vapor interface behavior while draining in a reduced-gravity environment is required. Numerical models capable of predicting vapor ingestion (or vapor pull-through) can be used to design liquid transfer operations while reducing liquid residuals, mission risk and settling thrust required to prevent vapor ingestion. An experimental program conducted in the 2.2 Second Drop Tower facility at NASA Lewis Research Center in 1969 investigated the vapor ingestion phenomenon for a range of outflow rates and tank sizes providing a database for validation. This study presents a Computational Fluid Dynamics model capable of accurately predicting the vapor ingestion using the Volume-of-Fluid multiphase solver in commercial code STAR-CCM+. A description of the experimental setup and general trends from similar studies are presented. Comparisons of the numerical prediction and test data in normal and low gravity show good agreement and give confidence in pursuing design of full-scale propellant transfer systems.
Clinical Decision Support Software: Modeling and Capabilities
With its distance from Earth and communication delays, exploration space flight will place new demands for crew autonomy. Crewmembers operating during such missions require a dedicated Clinical Decision Support System (CDSS) that enhances their earth independence by augmenting their knowledge, skills, and abilities in different medical scenarios. A CDSS is a software application that must function optimally in diverse and varied scenarios (while interfacing with and providing actionable information to appropriate vehicle systems) to augment crew performance by enhancing or adding knowledge, skills, and abilities that preserve health and wellness and ultimately helping to ensure mission success. In addition, the software tool should provide various functions and computational models to meet the demands of astronauts beyond low earth orbit.
Optical systems integrated modeling
An integrated modeling capability that provides the tools by which entire optical systems and instruments can be simulated and optimized is a key technology development, applicable to all mission classes, especially astrophysics. Many of the future missions require optical systems that are physically much larger than anything flown before and yet must retain the characteristic sub-micron diffraction limited wavefront accuracy of their smaller precursors. It is no longer feasible to follow the path of 'cut and test' development; the sheer scale of these systems precludes many of the older techniques that rely upon ground evaluation of full size engineering units. The ability to accurately model (by computer) and optimize the entire flight system's integrated structural, thermal, and dynamic characteristics is essential. Two distinct integrated modeling capabilities are required. These are an initial design capability and a detailed design and optimization system. The content of an initial design package is shown. It would be a modular, workstation based code which allows preliminary integrated system analysis and trade studies to be carried out quickly by a single engineer or a small design team. A simple concept for a detailed design and optimization system is shown. This is a linkage of interface architecture that allows efficient interchange of information between existing large specialized optical, control, thermal, and structural design codes. The computing environment would be a network of large mainframe machines and its users would be project level design teams. More advanced concepts for detailed design systems would support interaction between modules and automated optimization of the entire system. Technology assessment and development plans for integrated package for initial design, interface development for detailed optimization, validation, and modeling research are presented.
Nonlinear magnetohydrodynamic modeling of current-drive-induced sawtooth-like crashes in the W7-X stellarator
Sawtooth-like core electron temperature crashes have been observed in W7-X experiments with electron cyclotron current drive. Here we present nonlinear single-fluid magnetohydrodynamic simulations of this phenomenon using the newly developed stellarator modeling capability of the M3D-C 1 code. The near-axis current drive gives rise to two ι = 1 resonances in the equilibrium rotational transform profile so that two consecutive (1, 1) internal kink modes are seen in the simulations. A small-amplitude crash at the inner resonance occurs first, which may correspond to the sawtooth precursors observed in the experiments. A bigger crash at the outer resonance then flattens the core temperature profile, which shows semi-quantitative agreements with experimental measurements on certain metrics such as the crash amplitude and the inversion radius of the temperature change. These results illustrate a likely mechanism of the current-drive-induced sawtooth-like crashes in W7-X and, to some extent, validate the stellarator modeling capability of M3D-C 1 .
Supporting Space Weather with the Geospace Dynamics Constellation
The Geospace Dynamics Constellation (GDC) mission, planned to launch at the end of the decade, is a six-satellite constellation that will fly through the ionosphere and thermosphere at around 400 km. While GDC is a science mission, its comprehensive instrumentation will not only contribute to our understanding of space weather phenomena in the ionosphere-thermosphere system, but will also provide valuable, space weather-relevant data. Data from GDC will be made available at low latency via real-time space weather data stream. We are working with operational partners to identify space weather data products and coordinate reception of the space weather beacon data. Alongside preparations for real-time GDC data streams, we are working to identify current model capabilities and needs, to ensure that space weather models that can make use of GDC measurements are moving along the Research-toOperations pipeline. Before GDC launch, Observing System Simulation Experiments (OSSEs) carried out with synthetic GDC data can be used to demonstrate the capabilities of models and to predict the impact of GDC data. Following launch, Observing System Experiments (OSEs) will demonstrate the impact of GDC space weather data. In preparation for GDC, the ITM space weather community should establish baseline metrics for space weather parameters of scientific and operational interest. These metrics, tracked over time before and after the launch of GDC, will allow us to track advancements in forecasting, nowcasting, and hindcasting of the ITM system and to trace the impact of scientific progress from space weather research into operations. By demonstrating the impact of real-time GDC data, specific data needs can be identified and prioritized for long term investment on future observing systems.
Grounding our Understanding of the Impacts of Boreal Forest Expansion on Shallow Cumulus Clouds with a Simple Modeling Framework
Abstract The expansion of the boreal forest poleward is a potentially important driver of feedbacks between the land surface and Arctic climate. A growing body of work has highlighted the importance of differences in evaporative resistance between different possible future Arctic land covers, which in turn alters humidity and cloudiness in the boundary layer, for these feedbacks. While thus far this problem has been studied primarily with complex Earth system models, we turn to a locally focused, idealized model capable of diagnosing and testing the sensitivity of first-order processes connecting vegetation, the atmospheric boundary layer, and low clouds in this critical region. This allows us to benchmark the mechanisms and results at the center of predictions from larger-scale simulations. A surface dominated by broadleaf trees, characterized by higher albedo and lower surface evaporative resistance, drives cooling and moistening of the boundary layer relative to a surface of needleleaf trees, characterized by lower albedo and higher surface evaporative resistance. Differences in evaporative resistance between these hypothetical Arctic vegetation covers are of equal importance to changes in albedo for the initial response of the boundary layer to boreal expansion, even with our idealized approach. However, compensation between the elevation of the lifting condensation level (LCL) and more rapid growth of the mixed layer over higher evaporative resistance surfaces can minimize changes in the favorability of shallow clouds over different land cover types under some conditions. We then perform two tests on the sensitivity of this compensating effect, to changes in water availability, represented first by a reduction in boundary layer humidity and then by both a reduction in humidity and soil moisture available to our vegetation surface. Finally, given the importance of this potential LCL–mixed-layer height compensation in our idealized modeling results, we look to determine its relevance in observational data from a field campaign in boreal Finland. These observations do confirm that such a coupling plays an important role in cumulus-topped boundary layers over a needleleaf forest surface. While our results confirm some underlying mechanisms at the center of prior work with Earth system models, they also provide motivation for future work to constrain the impact of boreal forest expansion. This will include both large eddy simulations to examine the impact of processes and feedbacks not resolved by a mixed-layer model, as well as a more systematic evaluation and comparison of relevant observations at the site in Finland and sites from prior boreal field campaigns. Significance Statement Clouds and vegetation are both important components of the climate system that interact across a range of scales. These interactions are central to understanding how changes at the land surface feedback on climate. For example, if a forest expands or recedes, diagnosing how that will impact clouds will determine whether you predict warming or cooling temperatures from that shift in the forest area. These predictions are often made with complex Earth system models, but we look to a more idealized representation of the land–atmosphere system to diagnose how shallow clouds should respond to changes in surface properties with different scenarios of boreal forest expansion at a more foundational level. This both grounds our understanding of previous analysis and provides helpful direction for future studies of this relevant and impactful land cover change.