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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.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ion Acceleration and the Development of a Power-law Energy Spectrum in Magnetic Reconnection

How charged particles are accelerated efficiently and form a power-law energy spectrum in magnetic reconnection is a problem that is not well understood. In a previous paper, it was shown that the electron Kelvin–Helmholtz instability (EKHI) in force-free magnetic reconnection generates fast-expanding vortices that can accelerate electrons in a few tens of ion gyroperiods (less than 1 ms in the solar corona) to form a power-law energy distribution. In this paper, we present a particle-in-cell (PIC) simulation study of ion acceleration in force-free magnetic reconnection in the presence of the EKHI-induced turbulence. We find that ions are not significantly accelerated by the EKHI-induced stochastic electric field until the magnetic vortices expand to sizes comparable to the ion gyroradius. The Alfvén waves generated by the EKHI couple with the magnetic vortices, leading to resonance between the ions inside the magnetic vortices and Alfvén waves and enhanced ion heating. The induced Alfvén wave resonance results in a broken power-law energy spectrum with a breakpoint at $\sim {m}_{i}{v}_{A}^{2}$, where v A is the Alfvén velocity. Here, we show that the process that forms the nonthermal tail is a second-order Fermi mechanism and the mean spectral index is α = (1 + 4 a 2 D/R) /2, where D is the spatial scale of the inductive electric field, R is that of vortices, and a = B g /B 0 , with ratio of guide field B g and asymptotic B 0 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Description of historical and future projection simulations by the global coupled E3SMv1.0 model as used in CMIP6

Abstract. This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea ice, and land. Due to its high equilibrium climate sensitivity (ECS of 5.3 K), E3SMv1.0 is one of the Coupled Model Intercomparison Project phase 6 (CMIP6) models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated with the global temperature change, while the spatial pattern of the change in runoff is consistent with the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The annual mean Atlantic meridional overturning circulation (AMOC) is overly weak with a slower change from ∼ 11 to ∼ 6 Sv (Sverdrup) relative to other CMIP6 models. The sea ice, especially in the Northern Hemisphere, decreases rapidly with large seasonal variability. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes transient accelerated warming in the all-forcing experiment in the first half of the 21st century. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions, e.g., southern North America, southern Africa, central Africa, and eastern Asia. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Control of intense light with avalanche-ionization plasma gratings

High-peak-power lasers are fundamental to high-field science: increased laser intensity has enabled laboratory astrophysics, relativistic plasma physics, and compact laser-based particle accelerators. However, the meter-scale optics required for multi-petawatt lasers to avoid light-induced damage make further increases in power challenging. Plasma tolerates orders-of-magnitude higher light flux than glass, but previous efforts to miniaturize lasers by constructing plasma analogs for conventional optics were limited by low efficiency and poor optical quality. We describe a new approach to plasma optics based on avalanche ionization of atomic clusters that produces plasma volume transmission gratings with dramatically increased diffraction efficiency. We measure an average efficiency of up to 36% and a single-shot efficiency of up to 60%, which is comparable to key components of high-power laser beamlines, while maintaining high spatial quality and focusability. These results suggest that plasma diffraction gratings may be a viable component of future lasers with peak power beyond 10 PW.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A hybrid CNN-LSTM surrogate model for hyper-resolution spatiotemporal flood forecasting in Norfolk, Virginia

Study region: Norfolk, Virginia, United States Study focus: Accurate and timely flood forecasting is essential for enhancing resilience in coastal urban areas in the context of increasing frequency and intensity of rainfall, sea level rise and urbanization. This study presents a hybrid deep learning-based surrogate model that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to enable real-time spatiotemporal flood forecasting. The model leverages CNN to capture spatial features from inputs such as elevation and Topographic Wetness Index (TWI), while LSTM processes time-series inputs of rainfall and tide data to capture temporal features. New hydrologic insights for the region: The hybrid CNN-LSTM model was trained using the physics-based hydrodynamic model simulations obtained from the Two-dimensional Unsteady FLOW (TUFLOW) model for Norfolk, Virginia, and achieved high predictive accuracy across diverse flood-prone areas. The reduced computational time from four to six hours using TUFLOW to 3.2 min per event using CNN-LSTM enables rapid flood inundation mapping and early warning applications. The model effectively captured both spatial flood extents and their temporal evolution across different flooding scenarios, providing forecasts at a 2.5-m spatial resolution and 15-min temporal resolution and a one-hour-ahead prediction horizon. While challenges remain in terms of transferability to new regions and real-time data assimilation, this approach demonstrates strong potential for supporting operational flood risk management in coastal urban environments.

Coastal urban flooding↗
DOE OSTI2024

Design and performance of a magnetic bottle electron spectrometer for high-energy photoelectron spectroscopy

We describe the design and performance of a magnetic bottle electron spectrometer (MBES) for high-energy electron spectroscopy. Our design features a 2 m long electron drift tube and electrostatic retardation lens, achieving sub-electronvolt (eV) electron kinetic energy resolution for high energy (several hundred eV) electrons with a close to 4π collection solid angle. A segmented anode electron detector enables the simultaneous collection of photoelectron spectra in high resolution and high collection efficiency modes. This versatile instrument is installed at the time-resolved molecular and optical sciences instrument at the Linac Coherent Light Source x-ray free-electron laser (XFEL). In this paper, we demonstrate its high resolution, collection efficiency, and spatial selectivity in measurements where it is coupled to an XFEL source. These combined characteristics are designed to enable high-resolution time-resolved measurements using x-ray photoelectron, absorption, and Auger–Meitner spectroscopy. We also describe the pervasive artifact in MBES time-of-flight spectra that arises from a periodic modulation in electron collection efficiency and present a robust analysis procedure for its removal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Three-dimensional modeling of hyphal fusion, branching, and nutrient transport in filamentous fungi

Fungi exhibit behaviors distinct from other microbes. Filamentous fungi grow by extending complex networks of branched filaments collectively referred to as the mycelium. These networks can expand over large distances and traverse low-nutrient areas by translocating nutrients through the filament network. This spatial characteristic makes filamentous fungi crucial for soil ecosystems, supporting stable microbial communities and promoting plant growth. However, simulating these behaviors is complex. The elongated nature of fungal compartments results in different mechanical interactions compared to the commonly modeled spherical bacteria. These detailed hyphal mechanics require specialized consideration and are often excluded from conventional fungal simulation packages. Additionally, the extensive fungal networks in nature demand computationally intensive simulations, necessitating high-performance algorithms. Therefore, realistic fungi simulations require specialized software. Here, we introduce a fungal modeling expansion to the high-performance biological modelling and interface exchange (bmx) software suite. bmx leverages adaptive mesh refinement in AMReX for chemical diffusion and incorporates a full mechanical model for bacterial cells, accelerated by GPUs. By extending bmx to model filamentous particles, we demonstrate the formation of complex filament networks through interactions like hyphal branching and fusion (anastomosis). We show that the networks produced match real-world fungal structures through various metrics. This work supports computational studies of fungal growth dynamics and can be adapted to investigate the growth of other filamentous structures in biology or materials science. The expanded-BMX package is open-sourced and is available online.

Cell mechanics↗
DOE OSTI2022

Distributed Fiber Optic Sensing to Identify Locations of Resistive Transitions in REBCO Conductors and Magnets

High-temperature superconductors such as REBa 2 Cu 3 O 7-x (REBCO, RE = rare earth) can generate strong magnetic fields that are promising for applications in particle accelerators and compact fusion reactors. Traditionally, voltage taps are installed in superconducting magnets to measure the voltage signals due to resistive transitions. The voltage-tap-based diagnostics is important for the development of magnet technology as it can help pinpoint the locations in the magnet windings that limit the magnet performance. The architecture of the multi-tape REBCO cable such as CORC wires, however, makes it difficult to apply the voltage-tap-based diagnostics to identify the locations of resistive transitions. Distributed fiber optic sensing (DFOS) has the potential to address this issue. In this paper, we report the measurements of thermal strain along a CORC wire based on optical frequency domain reflectometry with a maximum spatial resolution of 0.65 mm and a temporal resolution of 10 Hz. The optical fiber is co-wound with the CORC wire that is epoxy impregnated. During the test, current was increased until a resistive transition occurred in the conductor. The spectrum shift of the reflected light along the fiber was recorded. The results suggested that with proper thermal isolation from the cryogen, DFOS can be used to identify the locations of resistive transitions in CORC wires and magnets. In conclusion, the results will allow a better understanding of the causes of resistive transitions in REBCO conductors and magnets, which will help improve the REBCO magnet technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Improving deep learning performance for predicting large-scale geological ${{CO}_{2}}$ sequestration modeling through feature coarsening

Physics-based reservoir simulation for fluid flow in porous media is a numerical simulation method to predict the temporal-spatial patterns of state variables (e.g. pressure p) in porous media, and usually requires prohibitively high computational expense due to its non-linearity and the large number of degrees of freedom (DoF). This work describes a deep learning (DL) workflow to predict the pressure evolution as fluid flows in large-scale 3-dimensional(3D) heterogeneous porous media. In particular, we develop an efficient feature coarsening technique to extract the most representative information and perform the training and prediction of DL at the coarse scale, and further recover the resolution at the fine scale by spatial interpolation. We validate the DL approach to predict pressure field against physics-based simulation data for a field-scale 3D geologic CO 2 sequestration reservoir model. We evaluate the impact of feature coarsening on DL performance, and observe that the feature coarsening not only decreases the training time by >74% and reduces the memory consumption by >75%, but also maintains temporal error 0.63% on average. Besides, the DL workflow provides predictive efficiency with 1406 times speedup compared to physics-based numerical simulation. The key findings from this research significantly improve the training and prediction efficiency of deep learning model to deal with large-scale heterogeneous reservoir models, and thus it can also be further applied to accelerate workflows of history matching and reservoir optimization for close-loop reservoir management.

58 GEOSCIENCES↗
DOE OSTI2024

Longitudinal Solid P Longitudinal Solid Polarized Target for CL get for CLAS12 and Study of Spin AS12 and Study of Spin Structure of Nucleons

A suite of experiments measuring target-spin observables in electron-nucleon scattering (dubbed Run Group C) was conducted at Jefferson Lab's Hall B in Newport News, VA with a new polarized nuclear target known as 'APOLLO' (Ammonia POLarized LOngitudinally). This innovative target is engineered to seamlessly integrate with the advanced 12GeV CEBAF (Continuous Electron Beam Accelerator Facility) accelerator and the Hall B CLAS12 (12 GeV CEBAF Large Acceptance Spectrometer) detector array. The 'APOLLO' target harnesses the power of Dynamic Nuclear Polarization (DNP) to achieve longitudinal polarization of solid ammonia, thereby creating a net polarization in both protons (NH3) and deuterons (ND3). These samples are subjected to a 5 Tesla magnetic field produced by the CLAS12 spectrometer central solenoid, cooled to 1 K using helium evaporation, and subsequently exposed to microwave radiation at a frequency of 140 GHz. This project was made possible through a collaborative partnership between the Jefferson Lab Target Group, Old Dominion University, University of Virginia, Christopher Newport University, and the CLAS Collaboration. Integrating the APOLLO target into CLAS12 presented unique challenges because of its specific spatial and dimensional constraints. This dissertation will highlight the innovative solutions developed to address these challenges, including the creation of a new target material transport system, the incorporation of superconducting magnetic correction coils, and the development of a customized Nuclear Magnetic Resonance (NMR) system. In addition to a detailed description of the development and operation of APOLLO, and an overview of RGC, this document also describes the global data fitting of proton asymmetries in the Deep Inelastic scattering (DIS) and the Resonance regions, and it offers insights into the comprehensive analysis of target polarization data.

Pandey, Pushpa↗
DOE OSTI2026

Trihydrogen Formation on Gold Nanoparticles in Strong Laser Fields

The tri-hydrogen cation (H+ 3 ) plays a central role in proton-transfer chemistry, astrochemical pathways, and hydrogen plasma environments, acting as a key indicator of ultrafast proton rearrangement. Although H+ 3 formation is studied extensively in the gas phase, its surface-mediated generation and its sensitiv- ity to nanoparticle morphology remain largely unexplored. Gold nanoparticles (AuNPs), which can localize surface charge and sustain strong electric fields, offer an ideal platform to probe such nonequilibrium reaction pathways. Us- ing reaction nanoscopy, we spatially map H+ 3 production on AuNPs exposed to intense femtosecond laser fields. By comparing spherical and faceted nanopar- ticles, we demonstrate how morphology modulates charge density and governs reaction efficiency. We find that sharp features on faceted particles concen- trate charge more effectively, promoting molecular fragmentation and enabling proton rearrangement and migration that enhance H+ 3 yields. This work opens new directions for exploiting strong-field interactions at metal interfaces to drive nanoscale reactivity and photocatalysis.

Dagar, Ritika [SLAC National Accelerator Laborator↗
DOE OSTI2026

Low-Rate Cycling Regeneration Sustains NMC811–Graphite Battery Performance through Extreme Ultrafast Charging

Urban air mobility (UAM) systems, such as electric vertical takeoff and landing (eVTOL) aircraft, require batteries capable of extreme ultrafast charging to support high-frequency operations. Here, in this work, we evaluate the electrochemical stability of NMC811–graphite full cells using a complex mixed-modal protocol designed to simulate the aggressive turnaround demands of UAM missions. We demonstrate that incorporating a periodic low-rate (0.3C) “regeneration” cycle enables cells to maintain 96% capacity retention over 900 cycles, despite repeated exposure to ultrafast pulses. To validate the efficacy of this regeneration mechanism, we performed simplified control experiments comparing continuous 10C charging against a 10C–0.3C interleaved protocol. Advanced characterization reveals that while mechanical particle fracture is pervasive at these rates, the regeneration cycles decelerate the electrochemical degradation by resolving spatially heterogeneous Ni oxidation states and relaxing lithium-ion concentration gradients. These findings provide a vital mechanistic framework for battery operation, proving that restorative charging can effectively delay and mitigate failure in demanding UAM applications.

batteries↗
DOE OSTI2025

Accumulation of Soil Microbial Necromass Controlled by Microbe–Mineral Interactions

Soil organic matter (SOM) is a key reservoir for global carbon (C), supporting soil fertility and influencing greenhouse gas emissions. Microbial residues, composed of dead cells and cellular fragments, are major contributors to SOM formation. Yet, mechanisms by which minerals enhance the accumulation of microbial residues remain poorly understood. Here, we used 13 C-labeled glucose in a year-long incubation to trace microbial residue in sandy and silty soils. Across both soils, approximately 89% of retained microbial 13 C was recovered in the fine (<53 μm) mineral-associated organic matter (MAOM) pool. Within this pool, the light MAOM fraction, enriched in poorly crystalline Fe minerals, held 4.3 times more 13 C than the heavy, phyllosilicate-dominated MAOM fraction, despite accounting for only 17.2% of the total MAOM mass and 12.3% of the total soil mass. Along with 13 C enrichment, the light MAOM fraction showed greater abundance of N-containing groups, e.g., (amides and amino groups), indicative of microbial-derived compounds like proteins and amino sugars. Fe oxides in light MAOM from both soils were spatially dispersed. Microbial residue accumulation was greater in finer-textured silty soil. These findings demonstrate that mineral composition and texture jointly regulate microbial necromass accrual, highlighting light MAOM as a key pool for enhancing soil C storage.

13C isotope labeling↗
DOE OSTI2020

Simultaneous Observations of Electromagnetic Ion Cyclotron (EMIC) Waves and Pitch Angle Scattering During a Van Allen Probes Conjunction

On 22 December 2015, the two Van Allen Probes observed two sets of electromagnetic ion cyclotron (EMIC) wave bursts during a close conjunction when both Probe A and Probe B were separated by 0.57 to 0.68 R E . Here, the EMIC waves occurred during an active period in the recovery phase of a coronal mass ejection-driven geomagnetic storm. Both spacecraft observed EMIC wave bursts that had similar spatial structure within a 1–2 min time delay. The EMIC waves occurred outside the plasmasphere, within ΔL ≈ 1–2 of the plasmapause and within a few degrees in magnetic latitude of the equatorial plane. The spatial structure of the EMIC wave bursts may have been related to the proton drift paths outside the plasmasphere and influenced by total magnetic field strength variations associated with solar wind pressure enhancements. The EMIC waves were observed in a narrow L shell region from L ≈ 4.55–5.32 between 10 and 11 magnetic local time (MLT) on the outbound halves of the spacecraft orbits and from L ≈ 4.82–5.51 between 13 and 14 MLT on the inbound halves of the spacecraft orbits. However, Pc1 pulsations were observed on the ground over a broad range of local times. The anisotropy of the proton pitch angle distributions was enhanced when the EMIC waves were observed. Although the overall radiation belt response during this storm was dominated by acceleration and transport processes, the EMIC waves produced local pitch angle scattering of 13–15 keV protons and 2.1–2.6 MeV electrons, consistent with calculations of the expected resonant energies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Focussing Protons from a Kilojoule Laser for Intense Beam Heating Using Proximal Target Structures

Proton beams driven by chirped pulse amplified lasers have multi-picosecond duration and can isochorically and volumetrically heat material samples, potentially providing an approach for creating samples of warm dense matter with conditions not present on Earth. Envisioned on a larger scale, they could heat fusion fuel to achieve ignition. We have shown in an experiment that a kilojoule-class, multi-picosecond short pulse laser is particularly effective for heating materials. The proton beam can be focussed via target design to achieve exceptionally high flux, important for the applications mentioned. The laser irradiated spherically curved diamond-like-carbon targets with intensity 4×10 18 W/cm 2 , producing proton beams with 3MeV slope temperature. A Cu witness foil was positioned behind the curved target, and the gap between was either empty or spanned with a structure. With a structured target, the total emission of Cu Kα fluorescence was increased 18 fold and the emission profile was consistent with a tightly focussed beam. Transverse proton radiography probed the target with ps order temporal and 10 μm spatial resolution, revealing the fast-acting focussing electric field. Complementary particle-in-cell simulations show how the structures funnel protons to the tight focus. The beam of protons and neutralizing electrons induce the bright Kα emission observed and heat the Cu to 100eV.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The Eel Pulsar Wind Nebula: A PeVatron-candidate Origin for HAWC J1826-128 and HESS J182-130

HAWC J1826–128 is one of the brightest Galactic TeV γ-ray sources detected by the High Altitude Water Cherenkov (HAWC) observatory, with photon energies extending up to nearly ~100 TeV. This HAWC source spatially coincides with the H.E.S.S. TeV source HESS J1826–130 and the "Eel" pulsar wind nebula (PWN), which is associated with the GeV pulsar PSR J1826–1256. In the X-ray band, Chandra and XMM-Newton revealed that the Eel PWN is composed of both a compact nebula (~15'') and diffuse X-ray emission (~6' × 2') extending away from the pulsar. Our NuSTAR observation detected hard X-ray emission from the compact PWN up to ~20 keV and evidence of the synchrotron burn-off effect. In addition to the spatial coincidence between HESS J1826–130 and the diffuse X-ray PWN, our multiwavelength spectral energy distribution (SED) analysis using X-ray and γ-ray data establishes a leptonic origin of the TeV emission associated with the Eel PWN. Furthermore, our evolutionary PWN SED model suggests (1) a low PWN B-field of ~1 μG, (2) a significantly younger pulsar age (t ~ 5.7 kyr) than the characteristic age (τ = 14.4 kyr), and (3) a maximum electron energy of ${E}_{\max }=2$ PeV. The low B-field, as well as the putative supersonic motion of the pulsar, may account for the asymmetric morphology of the diffuse X-ray emission. Our results suggest that the Eel PWN may be a leptonic PeVatron particle accelerator powered by the ~6 kyr old pulsar PSR J1826–1256 with a spin-down power of 3.6 × 10 36 erg s –1 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

MACHINE LEARNING BASED CHEMICAL EXPLOSIVE MODE ANALYSIS (ML-CEMA)

The software consists of a Machine Learning based Chemical Explosive Mode Analysis (ML-CEMA) tool for advanced computational flame diagnostics. CEMA, originally based on eigen-analysis of the local thermochemical system, is capable of identifying reaction fronts and limit phenomena such as auto-ignition and extinction in practical combustion systems, such as internal combustion engines and gas turbine combustors. However, the original CEMA is computationally expensive for large reaction mechanisms that are typically needed to describe fuel chemistry of practical large-hydrocarbon fuels. This novel ML-CEMA tool employs a ML technique to accelerate the eigen-analysis of the basic CEMA approach by orders of magnitude, thus making it suitable for practical fuels. In ML-CEMA,zero-dimensional (0D) reactors and one-dimensional (1D) premixed flames are first used to generate a large number of data points for neural network based ML training. The trained ML model is then used to perform CEMA prediction. This ML-CEMA tool has been demonstrated in canonical 0D and 1D configurations as well as highly-transient three-dimensional spray flames exhibiting multi-mode turbulent combustion, showing promising results. ML-CEMA, as a standalone tool, can be used for computationally-efficient diagnostics of massive datasets generated from both experiments and simulations. For example, based on spatially resolved measurements of a small set of reactive scalars(such as temperature, hydroxyl radical and formaldehyde), ML-CEMA can effectively identify flame fronts and rare events. ML-CEMA also provides a robust online or offline flame feature detection tool. When used for on-the-fly simulations, ML-CEMA further enables zone-adaptive combustion modeling, in which the predicted eigenvalue is used as a robust mode indicator for judicious assignment of locally-valid combustion models. This ML-CEMA based zone-adaptive model can lead to substantial computational cost savings when used for large-scale simulations of multi-mode combustion systems. Third Party Code Web Page to Download Code Web Page Location of Third Party License

Xu, Chao↗
DOE OSTI2023

Using Direct Laboratory Measurements of Electron Temperature Anisotropy to Identify the Heating Mechanism in Electron-Only Guide Field Magnetic Reconnection

Anisotropic electron heating during electron-only magnetic reconnection with a large guide magnetic field is directly measured in a laboratory plasma through in situ measurements of electron velocity distribution functions. Electron heating preferentially parallel to the magnetic field is localized to one separatrix, and anisotropies of 1.5 are measured. The mechanism for electron energization is identified as the parallel reconnection electric field because of the anisotropic nature of the heating and spatial localization. These characteristics are reproduced in a 2D particle-in-cell simulation and are also consistent with numerous magnetosheath observations. A measured increase in the perpendicular temperature along both separatrices is not reproduced by our 2D simulations. Here, this work has implications for energy partition studies in magnetosheath and laboratory reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A GPU ‐Accelerated 3D Unstructured Mesh Based Particle Tracking Code for Multi‐Species Impurity Transport Simulation in Fusion Tokamaks

ABSTRACT This paper presents the multi‐species global impurity transport capability developed in a GPU‐accelerated fully 3D unstructured mesh‐based code, GITRm, to simultaneously track multiple impurity species and handle interactions of these impurities with mixed‐material surfaces. Different computational approaches to model particle‐surface interaction or surface response have been developed and compared. Sheath electric field is taken into account by employing a fast distance‐to‐boundary calculation, which is carried out in parallel on distributed or partitioned meshes on multiple GPUs without the need for any inter‐process communication during the simulation. Several example cases, including two for the DIII‐D tokamak, that is, one with the SAS‐V divertor and the other with the collector probes, are used to demonstrate the utility of the current multi‐species capability. For the DIII‐D probe case, the capability of GITRm to resolve the spatial distribution of particles in localized regions, such as diagnostic probes, within non‐axisymmetric tokamak geometries is demonstrated. These simulations involve up to 320 million particles and utilize up to 48 GPUs.

Nath, Dhyanjyoti D. [Scientific Computation Resear↗