Multi-Modal Foundation Model for Biogenic Flux Mapping
Presentation detailing our methods for biogenic flux mapping and uncertainty quantification, as well as our results on these topics
Del Regno, Kai Antonio [Sandia National Laboratori↗
SEARCH · Search NASA
Results for “FLUX MAPPING”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Multi-Modal Foundation Model for Biogenic Flux Mapping
A recorded talk on our project "Multi-Modal Foundation Model for Biogenic Flux Mapping", using slides from SAND2025-09463C
Del Regno, Kai Antonio [Sandia National Laboratori↗
Ecosystem foundation model for biogenic flux mapping
Explore the source record for details and available documents.
Krofcheck, Daniel Joseph [Sandia National Laborato↗
Q3 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment
This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q3: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis. • Benchmark between two first wall heat flux mapping methods, identify importance of various heat flux sources and physics impact of using fully coupled CESOL vs post-analysis evaluation. 2. Generate medium fidelity parametrized CAD. • Generate parametrized CAD components for the CAT example case via either user-defined modules called within the geometry generation or by defeatured/parametrized CAD, including DCLL blanket matched to divertor boundary and magnets. Define materials, labels, and boundary conditions for passing the mesh to CFD tools. 3. Demonstrate multiphysics magnet analysis. • Demonstrate magnet analysis workflow called from the FREDA workflow, and 4. Demonstrate nuclear analysis. • Add model to OpenFOAM and/or other codes possibly including Diablo to account for tritium diffusion in solids.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Effect of Magnetic Islands on Neoclassical Heat Diffusivity in a Global Tokamak Simulation
Resonant magnetic perturbations (RMPs) alter magnetic field topology via island formation and can modify core transport in toroidal fusion devices. Using the global gyrokinetic particle‐in‐cell code XGC‐S, originally developed for stellarator geometries, we quantify how island topology affects neoclassical heat transport in a circular tokamak with ($m,n$) = (5,2) RMP‐induced islands. Electron radial heat diffusivity exhibits a two‐peak structure with a dominant enhancement near the O/X‐point region and a secondary peak at the outer island boundary, whereas ion transport remains close to the neoclassical prediction. The observed electron diffusivity is strongly enhanced over the neoclassical baseline but remains well below the Rechester–Rosenbluth estimate, consistent with the non‐ergodic character of the island topology. The density dependence of diffusivity is weaker inside the islands than outside, indicating the presence of topology‐driven transport channels that do not depend strongly on collisionality. Two‐dimensional heat flux maps reveal an up–down antisymmetric structure at the island separatrices consistent with magnetic gradient and curvature drift effects, in contrast to the symmetric temperature flattening inside the islands. These results identify topology‐dependent avenues for electron heat transport in RMP‐perturbed cores and suggest regimes in which island geometry, rather than collisions alone, governs radial transport.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Updates on MURAVES Project at Mt. Vesuvius
The MUon RAdiography of VESuvius (MURAVES) project aims to employ muography imaging techniques to investigate the internal structure of the summit of Mount Vesuvius, an active volcano located near Naples, Italy. This paper reports recent advancements in data analysis and simulation tools that significantly improve the quality and reliability of the experiment’s results. A new track selection method, referred to as the Golden Selection, has been developed to identify high-quality muon tracks by applying an improved χ 2 -based criterion. This method enhances the signal-to-background ratio and improves the resolution of the resulting muographic images. Moreover, the simulation framework has been upgraded through the integration of the MULDER (MUon simuLation for DEnsity Reconstruction) library, which consolidates the functionalities of previously used libraries into a single, unified platform. MULDER enables efficient and accurate modeling of muon flux variations induced by topographical features. A good agreement is observed between the simulated and measured muon flux maps, validating the effectiveness of the new analysis and simulation approaches.
Cosmic rays↗
Q1 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment
This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q1: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis: $/circ$ Initially run CESOL with SOLPS and map heat flux using simple HEAT method: ▪ Generate SOLPS grid for CAT reference case, ▪ Implement and apply ‘lower’ fidelity method of using HEAT-like analytic method to map SOLPS heat flux from charged particles to first wall, and ▪ Provide initial heat flux + neutron loading for further engineering analysis. 2. Demonstrate multiphysics magnet analysis: $/circ$ Demonstrate validation of the Elmer workflow by comparing induced stresses due to EM forces generated by TF coils using multiple codes.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A Monte Carlo Laplace Transform Estimator for Radiation Transport
This work formulates and implements a Laplace transform estimator in a simple Monte Carlo radiation transport code. The estimator maps flux-based quantities of interest, like reaction rates, from a desired phase-space dimension to the complex Laplace domain. This on-the-fly Monte Carlo integration technique enables the spectral analysis of arbitrary nuclear systems via the Laplace transform. A simple code tests the estimator in neutron slowing-down problems across various infinite media, and the results compare well with Ganapol’s uninverted analytical solution of the neutron slowing-down equation.
97 MATHEMATICS AND COMPUTING↗
Inverse Mapping of the Collision Kernel and Wall Flux Scaling in a Tall Convection‐Cloud Chamber Using Local Sensors and Knowledge‐Informed Deep Learning
Droplet collision–coalescence is a crucial process in cloud physics, but accurately representing this process under different dynamical conditions remains challenging. A proposed future convective‐cloud chamber aims to investigate this key process, but the method for observing it remains unclear, even though it is theoretically established that collision‐coalescence will occur. This study serves as a proof‐of‐concept demonstration of how knowledge‐informed deep learning, combined with measurement data from local sensors in the chamber, can be used to estimate the collision kernels, which determine how the droplet size distribution evolves during collision‐coalescence. In addition to estimating the collision kernel, we also address wall fluxes, another uncertain but important process that acts as a source of heat and moisture in the chamber. Ensemble runs of large‐eddy simulations are conducted by scaling the wall fluxes and the collision kernel, while the measured flow and cloud properties are used as inputs for a neural network. Results indicate that this approach successfully maps the scaling of wall fluxes and the collision kernel with biases of approximately 1% or less relative to the range of the target data. This proof‐of‐concept lays the groundwork for future applications; when the real measurements are available, real sensor data combined with the trained model presented in this work will enable estimation of the actual wall fluxes and collision kernel.
cloud chamber↗
Magnetic flux imaging in a 3D superconductor integrated circuit
We report on imaging magnetic flux distributions in a multilayered superconductor integrated circuit which emerge during magnetization and after field cooling of the circuit in the DC magnetic field. The obtained complicated field maps expose the flux propagation across the patterned superconducting ground planes sandwiching layers with Josephson junction-based logic cells, fine wire grid around the functional units, and multiple superconducting fill structures located in different inner layers. The observed intricate flux distributions are explained by specific patterns of Meissner screening currents and superconducting critical currents in different mutually interacting parts of the integrated circuit. Our results provide important insights into possible ways of improving the protection of superconductor integrated circuits from magnetic fields and their resilience against flux trapping.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Modeling of injected current stream-induced 3D perturbations in local helicity injection plasmas
Solenoid-free tokamak startup techniques are essential for spherical tokamaks and offer a pathway to cost reduction and design simplification in fusion energy systems. Local helicity injection (LHI) is one such approach, employing compact edge current sources to drive open field line current that initiates and sustains tokamak plasmas. The recently commissioned Pegasus-III Experiment provides a platform for advancing this and other solenoid-free startup methods. This study investigates the effect of LHI on magnetic topology in Pegasus-III plasmas. A helical filament model represents the injected current, and the linear plasma response to its three-dimensional field is calculated with M3D-C1. Poincaré mapping reveals substantial flux surface degradation in all modeled cases. The onset of overlapping magnetic structures and large-scale surface deformation begins near Ψ N ≈ 0.37, indicating a broad region of perturbed topology extending toward the edge. In rotating plasmas, both single-fluid and two-fluid models exhibit partial screening of the n = 1 perturbation, with two-fluid calculations showing stronger suppression near the edge. In contrast, the absence of rotation leads to strong resonant field amplification in the single-fluid case, while the two-fluid case with zero electron rotation mitigates this amplification and preserves edge screening. Magnetic probe measurements indicate that modeling the stream with spatial spreading—representing distributed current and/or oscillatory motion—better reproduces measured magnetic power profiles than a rigid filament model. The results underscore the role of rotation and two-fluid physics in screening stream perturbations and point to plasma flow measurements and refined stream models as key steps toward improving predictive fidelity.
Schaefer, Carolyn E. [Univ. of Wisconsin, Madison,↗
Spectral Properties of Globally Distributed ENA Fluxes across Diverse Regions of the Heliosphere
This study analyzes energetic neutral atom (ENA) spectral properties across distinct regions of globally distributed flux (GDF) sky maps, using Interstellar Boundary Explorer data from a full solar cycle, corrected for time dispersion. By time-shifting the data to the heliosheath using GDF source distances from D. B. Reisenfeld et al., we achieve a more accurate representation of heliosheath GDF energy spectra. We quantify ENA spectral characteristics, heliosheath line-of-sight-integrated proton pressure, and heliosheath proton temperature, comparing these to solar wind properties at 1 au and interplanetary scintillation-derived solar wind data. Our findings show that the spectral index is generally anticorrelated with heliosheath proton temperature and pressure, except in the central tail, where a partial positive correlation is observed. The lowest spectral index values occur when high-latitude heliosheath regions are dominated by fast solar wind from polar coronal holes. The south pole exhibits the flattest energy spectra due to plasma heating from both fast solar wind and a late-2014 pressure pulse. The central tail shows shorter variability (5–6 yr) for spectral index and heliosheath proton temperature, while proton pressure follows the 11 yr solar cycle. Most spectral shapes exhibit a “knee” distribution, peaking during solar maximum, with an “ankle” shape observed only at the south pole during solar cycle transitions. Asymmetry in proton pressure in the lobes is driven by the draping effect of the local interstellar magnetic field. This study provides insights into the energetic properties of GDF across the heliosphere, enhancing our understanding of the heliospheric environment.
79 ASTRONOMY AND ASTROPHYSICS↗
Material Selection and Heat Transfer Model for PTUHS Device
The Path to Ultimate Heat Sink Device (PTUHS) is a passive safety system that utilizes a radiative heat transfer valve to control the rate at which heat is removed from a nuclear reactor pressure vessel (RPV) and dispersed into surrounding soil. The material selection for the PTUHS device is investigated, where the thermophysical properties are either maximized or minimized bases on what section of the PTUHS that material is being used for. Final recommendations of material choice are then presented. The heat transfer model of the PTUHS device is solved in ABAQUS, where a normal operating conditions and SCRAM conditions are solved. These temperature maps and heat flux of the system show the system's ability, where minimal heat is lost during normal operating conditions and system failure in a SCRAM scenario due to temperatures that were reached.
42 - ENGINEERING↗
A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks
Atmospheric methane (CH4) concentrations are accelerating global warming as net emissions increase. Observing systems that quantify sources remain too sparse and fragmented to detect trends—especially in remote regions where climate‐driven natural emissions may be rising. We provide a framework for quantifying uncertainty reductions through the implementation of a global ecosystem‐methane observing system designed to: (i) substantially lower uncertainty in sectoral and regional emissions, (ii) separate co‐occurring anthropogenic and natural fluxes, and (iii) trend detection at regional scales to verify mitigation progress and provide early warning of natural feedbacks. Using bottom‐up inventories and process‐model ensembles for 2014–2023, we show that anthropogenic emissions remain uncertain by ∼32% globally, while natural sources—tropical and boreal‐arctic wetlands, fires, and inland waters—carry far larger uncertainties (+ 70%) and trend uncertainties reaching ∼200%. Additional observations must match spatial emission structure to increase observability of emissions: high‐resolution satellite constellations for point sources combined with expanded flux networks and wetland mapping for diffuse sources, and denser ground‐based atmospheric column measurements to restore observability in under‐sampled tropics and high latitudes. Notional analyses indicate that targeted additions of flux towers and ∼20 in situ atmospheric column concentration instruments per key tropical region could reduce continental‐scale uncertainties at modest cost. Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and enables early detection of climate‐driven feedbacks from wetlands, fires, permafrost, agriculture, and fossil‐fuel emissions.
Ciais, P↗
Flux Channeling Induced Nanoconfinement and Enhancement of Microwaves Imaged by Rabi Oscillation Mapping
With rapid advances in qubit technologies, techniques for localizing, modulating, and measuring RF fields and their impact on qubit performance are of the utmost importance. Here, we demonstrate that flux-channeling from a permalloy nanowire can be used to achieve localized spatial modulation of an RF field and that the modulated field can be mapped with high resolution by using the Rabi oscillations of an NV center. Rabi maps reveal ∼100 mm wavelength microwaves concentrated in sub-300 nm regions with up to ∼16× power enhancement. This modulation is robust over a 20 dBm power range and has no adverse impact on NV T 2 coherence time. Micromagnetic simulations confirm that the modulated field results from the nanowire’s stray field through its constructive/destructive interference with the incident RF field. Our findings provide a new pathway for controlling qubits, amplifying RF signals, and mapping local fields in various on-chip RF technologies.
Diamond↗
The key role of forest disturbance in reconciling estimates of the northern carbon sink
Northern forests are an important carbon sink, but our understanding of the driving factors is limited due to discrepancies between dynamic global vegetation models (DGVMs) and atmospheric inversions. We show that DGVMs simulate a 50% lower sink (1.1 ± 0.5 PgC yr –1 over 2001–2021) across North America, Europe, Russia, and China compared to atmospheric inversions (2.2 ± 0.6 PgC yr –1 ). We explain why DGVMs underestimate the carbon sink by considering how they represent disturbance processes, specifically the overestimation of fire emissions, and the lack of robust forest demography resulting in lower forest regrowth rates than observed. We reconcile net sink estimates by using alternative disturbance-related fluxes. We estimate carbon uptake through forest regrowth by combining satellite-derived forest age and biomass maps. We calculate a regrowth flux of 1.1 ± 0.1 PgC yr –1 , and combine this with satellite-derived estimates of fire emissions (0.4 ± 0.1 PgC yr –1 ), land-use change emissions from bookkeeping models (0.9 ± 0.2 PgC yr –1 ), and the DGVM-estimated sink from CO 2 fertilisation, nitrogen deposition, and climate change (2.2 ± 0.9 PgC yr –1 ). The resulting ‘bottom-up’ net flux of 2.1 ± 0.9 PgC yr –1 agrees with atmospheric inversions. The reconciliation holds at regional scales, increasing confidence in our results.
54 ENVIRONMENTAL SCIENCES↗
Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]
This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).
Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X
Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO 2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr −1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr −1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×10 3 ± 0.9×10 3 km 3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.
Nelson, Jacob A.↗