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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Validation of SOLPS-ITER simulations with kinetic, fluid, and hybrid neutral models for JET-ILW low-confinement mode plasmas

For JET L-mode plasmas in low-recycling conditions (electron temperature at the outer strike point, T e,ot ≳ 30 eV ), SOLPS-ITER simulations agree within the error bars for the experimental profiles at the low-field side (LFS) divertor target. The peak Balmer-α (Dα ) emission in the LFS divertor agrees within the error bars of the KS3 filterscope diagnostic, but is approximately 30% lower than the peak value of the KT1 spectrometer. Simulations have been performed with fluid, kinetic, and hybrid models for the neutrals. The large fluid-kinetic discrepancies of more than a factor 2 are successfully corrected by using a hybrid fluid-kinetic approach, for which kinetic atoms are transferred to the fluid population when the local Knudsen number of the atom becomes smaller than a user-defined transition Knudsen number Kn t . The hybrid-kinetic discrepancies are limited to a few % for Kn t ≤ 100 . When increasing the upstream density to high-recycling conditions, at the onset of detachment ( T e,ot ≈ 5 eV ), the simulations predict more than a factor 2 lower peak ion saturation current to the LFS divertor than the experiments. Also the Dα emission is underpredicted with approximately a factor 2. For these high-recycling conditions, the fluid-kinetic discrepancies are limited to maximum 50%, which are again corrected by using the hybrid approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

BRCore: an R package implementing flexible selection of core taxa using contribution to Bray-Curtis dissimilarity and neutral model fitting

Identifying core taxa in microbial ecology highlights groups likely to participate in a broad range of potential ecological interactions. Here, we present BRCore, an R package to identify core taxa using abundance-occupancy distributions and beta-diversity contributions across ecological niches, and predict stochastic and deterministic taxa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Modeling neutral defects in III-V ternary alloys with a special quasirandom structure: Analysis of As- and III-site point defects in InGaAs

While first-principles density functional theory modeling has become a vital tool to investigate defect properties in semiconductors, the lack of crystalline periodicity in pseudobinary random composition alloys, such as In 1−𝑥 ⁢Ga 𝑥 ⁢As, complicates such analyses. We present a simulation strategy to systematically take into account the variability in the local defect environment in order to predict statistical properties of neutral intrinsic defects in In 1−𝑥⁢ Ga 𝑥 ⁢As. We use a comprehensive sampling from a modest-sized 64-atom special quasirandom structure (SQS) to define a statistically representative set of defects, and use a 512-atom hypercell, a 2 × 2 × 2 supercell of SQS supercells, to achieve cell-size convergence. We articulate an equivalent site principle and describe how it constrains atomic chemical reference energies in computation of defect formation energies in pseudobinary alloys. A simple protocol for estimating reference energies for the Ga and In atoms sharing the III site succeeds in obtaining the equivalence of defects at Ga-sites and In sites in the SQS supercell, (<30 meV differences in average formation energies). For III-site defects, such as the As antisite As III , the statistical variability in formation energies is modest, ≈ 0.1–0.2 eV. The variability in formation energy at As-site defects, such as the As vacancy 𝑣 As , can be much larger, >1 eV. The As antisite is shown to be a low-energy defect and the most likely to be present in as-grown materials, just as in GaAs. All other defects are higher-energy defects unlikely to be important in native material, but potentially important in radiation-damaged material. With a strong variability in defect energies, especially on the As-site, explicit consideration of statistical variability due to compositional randomness will be imperative for meaningful and quantitative comparisons to experiment.

Density functional theory↗
DOE OSTI2026

Vacuum Neutral Transport Model in UEDGE for Tokamak Far Scrape‐Off Layer

A model for neutral transport in the far scrape-off layer (SOL) vacuum region (vacuum neutral model) has been developed and implemented in UEDGE. Free-streaming neutral trajectories between the outermost UEDGE boundary and the vessel wall are preprocessed using DEGAS2 to construct a tele-transport matrix that captures non-local neutral relocation through the vacuum. Here, this matrix is then used in UEDGE as a non-local boundary condition for the neutral equations, preserving the robustness and convergence of the implicit solver without introducing statistical noise. Simulations of a DIII-D lower single-null configuration show that the vacuum neutral model relocates neutrals from the divertor to the upstream region, increasing the outer midplane separatrix density required for detachment onset by about 30%. However, the characteristic target temperature at detachment (T e, osp ~ 3 - 4eV) and the radiation front behavior remain unchanged.

DEGAS2↗
DOE OSTI2023

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Machine Learning Approach to Modeling of Neutral Particles Transport in Plasma

A propagator‐based approach is investigated for Monte‐Carlo (MC) modeling of neutral particle transport in fusion boundary plasmas. The propagator is based on a Green's function for the neutral kinetic equation, which depends on the plasma profiles. A neural network (NN)‐based model for the propagator provides a fast and accurate solution for the neutral distribution function in plasma. Preliminary results from a small 1D test problem look encouraging. The proposed approach, a propagator‐based NN model for neutral transport in plasma, has potential for generalization to higher dimensions and efficient coupling with plasma models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Kinetic modeling of neutral transport for a continuum gyrokinetic code

In this work we present the first-of-its-kind coupling of a continuum full- f gyrokinetic turbulence model with a 6D continuum model for kinetic neutrals, carried out using the Gkeyll code. Our objective is to improve the first-principle understanding of the role of neutrals in plasma fueling, detachment, and their interaction with edge plasma profiles and turbulence statistics. Our model includes only atomic hydrogen and incorporates electron-impact ionization, charge exchange, and wall recycling. These features have been successfully verified with analytical predictions and benchmarked with the DEGAS2 Monte Carlo neutral code. We carry out simulations for a scrape-off layer (SOL) with simplified geometry and National Spherical Torus Experiment parameters. We compare these results to a baseline simulation without neutrals and find that neutral interactions reduce the normalized density fluctuation levels and associated skewness and kurtosis, while increasing auto-correlation times. A flatter density profile is also observed, similar to the SOL density shoulder formation in experimental scenarios with high fueling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Neural network model of neutral beam injection in the EAST tokamak to enable fast transport simulations

The neutral beam injection (NBI) system in EAST produces energetic neutral particles, which collide with electrons and ions in tokamak plasmas and heat the plasmas through Coulomb collisions. Moreover, it drives a non-inductive source of current, due to the charge-exchange collision between neutral particles and ions, and injects toroidal torque, which generates a toroidal rotation of the plasma. The effect caused by the NBI system, such as plasma heating, current drive, total neutron rate, momentum transfer, and shine-through, are modeled by a comprehensive module called NUBEAM. However, NUBEAM is computationally intensive since it relies on Monte Carlo methods. In this work, a neural network model has been developed as a surrogate model for NUBEAM in EAST. The database for neural-network model training, validation and testing is generated by running TRANSP for experimental discharges from recent EAST campaigns (after the latest NBI upgrade) while using the NUBEAM module. Simulation results illustrate that the trained neural network has the capability of replicating the predictions made by NUBEAM while demanding a significantly shorter execution time. Finally, these results indicate that surrogate models like the one proposed in this work could enable fast transport simulations for EAST after integrating them into a control-oriented predictive code such as COTSIM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Analytic model for neutral penetration and plasma fueling

Neutral atoms recycled from wall interaction interact with confined plasma, thereby refuelling it, most strongly in the region closest to the wall. This occurs near the X-point in diverted configurations, or else near the wall itself in limited configurations. A progression of analytic models is developed for neutral density in the vicinity of a planar or linear source in an ionising domain. First-principles neutral transport simulations with DEGAS2 are used throughout to test the validity and limits of the model when using equivalent sources. The model is further generalised for strong plasma gradients or the inclusion of charge exchange. An important part of the problem of neutral fuelling from recycling is thereby isolated and solved with a closed-form analytic model. A key finding is that charge exchange with the confined plasma can be significantly simplified with a reasonable sacrifice of accuracy by treating it as a loss. The several assumptions inherent to the model (and the simulations with which it is compared) can be adapted according to the particular behaviour of neutrals in the divertor and the manner in which they cross the separatrix.

fusion plasma↗
DOE OSTI2023

The present and future status of heavy neutral leptons

Abstract The existence of nonzero neutrino masses points to the likely existence of multiple Standard Model neutral fermions. When such states are heavy enough that they cannot be produced in oscillations, they are referred to as heavy neutral leptons (HNLs). In this white paper, we discuss the present experimental status of HNLs including colliders, beta decay, accelerators, as well as astrophysical and cosmological impacts. We discuss the importance of continuing to search for HNLs, and its potential impact on our understanding of key fundamental questions, and additionally we outline the future prospects for next-generation future experiments or upcoming accelerator run scenarios.

Abdullahi, Asli M.↗
DOE OSTI2022

Time-discretization of a plasma-neutral MHD model with a semi-implicit leapfrog algorithm

The semi-implicit leapfrog time-discretization is a workhorse algorithm for initial-value MHD codes to bridge between vastly separated time scales. Inclusion of atomic interactions with neutrals breaks the functional structure of the MHD equations that exploited by the leapfrog. In this work, we address how to best integrate atomic physics into the semi-implicit leapfrog. Following the Crank-Nicolson method, one approach is to time-center the atomic interactions in the linear solver and use a Newton method to include the nonlinear contributions. Alternatively, another family of methods are based on operator-splitting the terms associated with the atomic interactions using a Strang-splitting technique. These methods naturally break equations into constituent ODE and PDE parts and preserve the structure exploited by the semi-implicit leapfrog. We study the accuracy and efficiency of these methods through a battery of 0D and 1D cases and show that a second-order-in-time Douglas-Rachford inspired coupling between the ODE and PDE advances is effective in reducing the time-discretization error to be comparable to that of Crank-Nicolson with Newton iteration of the nonlinear terms. Splitting ODE and PDE parts results in independent matrix solves for each field which reduces the computational cost considerably and provides parallelization over species relative to Crank-Nicolson.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Virtual sensor supervised learning for cyber-attack neutralization

An industrial asset may have monitoring nodes that generate current monitoring node values. A dynamic, resilient estimator may split a temporal monitoring node space into normal and one or more abnormal subspaces associated with different kinds of attack vectors. According to some embodiments, a neutralization model is constructed and trained for each attack vector using supervised learning and the associated abnormal subspace. In other embodiments, a single model is created using out-of-range values for abnormal monitoring nodes. Responsive to an indication of a particular abnormal monitoring node or nodes, the system may automatically invoke the appropriate neutralization model to determine estimated values of the particular abnormal monitoring node or nodes (e.g., by selecting the correct model or using out-of-range values). The series of current monitoring node values from the abnormal monitoring node or nodes may then be replaced with the estimated values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Recycling Measurements for the Lithium Tokamak Experiment

The lithium tokamak experiment (LTX) is a spherical torus designed to investigate a low-recycling wall regime for magnetically confined plasmas. Traditional measurements of recycling using Dα emission are not feasible in LTX due to reflections off the plasma-facing-components: stainless-steel shell, liquid lithium layer, and molybdenum limiters. Since lithium has low VUV reflectivity, LTX will use Lyman-α emission to measure particle recycling. LTX will use 10- and 20-channel AXUV diode arrays with Lyman-α filters to view recycling off the inboard and outboard shells. A single detector views recycling off a limiter. Measurements will be used with neutral modeling to calculate recycling and neutral deposition. To investigate the performance of an AXUV diode with directly-deposited filter, measurements were obtained with this detector and a visible detector viewing a calibration plasma then compared with emission calculated using a collisional-radiative model.

Physics - Plasma physics↗
DOE OSTI2022

Simulation of plasma transport in MPS-LD linear plasma device by using BOUT++

Here a linear plasma device (LPD) module based on the 2D transport module under the BOUT++ framework is developed in this paper to simulate plasma transport in the LPD. The LPD module includes three parts, i.e. magnetic field calculation, simulation mesh generation and plasma transport setup. The magnetic field is calculated with the circular current loop using the location and current information of each coil. The mesh generation code can produce a simulation mesh for LPD by employing the magnetic field. The plasma transport model is based on the reduced Braginskii equations, which consist of the continuity equation, momentum equation, and energy equation. The fluid neutral model is applied for neutral particle simulation. Deuterium (D) and helium (He) ions and atoms can be simulated by the model. The first attempt to simulate plasma transport in the new LPD, called multiple plasma simulation linear plasma device (MPS-LD), is presented using the developed model. The D plasma transport in the MPS-LD is simulated and benchmarked against the two-point model, showing the validation of the BOUT++ simulation. The effects of radial transport on the heat load to the target are studied, which illustrates the significant impact of the radial diffusivities $D_⟂$ and $\mathcal{X}_{⟂i,e}$ on the plasma. Moreover, the He impurity injection process during the discharge is studied with emphasis on plasma–impurity interactions. The simulation results show that He injection can reduce the plasma energy load to the target significantly, and the efficiency depends on the He source density and injection velocity. The present work provides an alternative and flexible simulation tool for plasma transport in LPDs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Details of the neutral energy distribution and ionization source using spectrally resolved Balmer-alpha measurements on DIII-D

Spectrally resolved passive Balmer- α (D- α, H- α) measurements from the DIII-D 16 channel edge main-ion charge exchange recombination system confirm the presence of higher energy neutrals (“thermal” neutrals) in addition to the cold neutrals that recycle off the walls in the edge region of DIII-D plasmas. Charge exchange between thermal ions and edge neutrals transfers energy and momentum between the populations giving rise to thermal neutrals with energies approximating the ions in the pedestal region. Multiple charge exchange events in succession allow an electron to effectively take a random walk, transferring from ion to ion, providing a pathway of increasing energy and velocity, permitting a neutral to get deeper into the plasma before a final ionization event that contributes to the ion and electron particle fueling. Spectrally resolved measurements provide information about the density and velocity distribution of these neutrals, which has been historically valuable for validating Monte Carlo neutral models, which include the multi stage charge exchange dynamics. Here, in this study, a multi-channel set of such measurements is used to specifically isolate the details of the thermal neutrals that are responsible for fueling inside the pedestal top. Being able to separate the thermal from the cold emission overcomes several challenges associated with optical filter-based neutral density measurements. The neutral dynamics, deeper fueling by the thermal neutrals, and spectral measurement are modeled with the FIDASIM Monte Carlo collisional radiative code, which also produces synthetic spectra with a shape that is in close agreement with the measurements. By scaling the number of neutrals in the simulation to match the intensity of the thermal emission, we show it is possible to obtain local neutral densities and ionization source rates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗