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Results for “Knudsen layer effect”

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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6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A physics-informed deep learning description of Knudsen layer reactivity reduction

A physics-informed neural network (PINN) is used to evaluate the fast ion distribution in the hot spot of an inertial confinement fusion target. The use of tailored input and output layers to the neural network is shown to enable a PINN to learn the parametric solution to the Vlasov–Fokker–Planck equation in the absence of any synthetic or experimental data. As an explicit demonstration of the approach, the specific problem of Knudsen layer fusion yield reduction is treated. Here, the predictions from the Vlasov–Fokker–Planck PINN are used to provide a non-perturbative solution of the fast ion tail in the vicinity of the hot spot, thus allowing the spatial profile of the fusion reactivity to be evaluated for a range of collisionalities and hot spot conditions. Excellent agreement is found between the predictions of the Vlasov–Fokker–Planck PINN and the results from traditional numerical solvers with respect to both the energy and spatial distribution of fast ions and the fusion reactivity profile, demonstrating that the Vlasov–Fokker–Planck PINN provides an accurate and efficient means of determining the impact of Knudsen layer yield reduction across a broad range of plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A Physics-Informed Deep Learning Description of Knudsen Layer Reactivity Reduction

A physics-informed neural network (PINN) is used to evaluate the fast ion distribution in the hot spot of an inertial confinement fusion target. The use of tailored input and output layers to the neural network is shown to enable a PINN to learn the parametric solution to the Vlasov–Fokker–Planck equation in the absence of any synthetic or experimental data. As an explicit demonstration of the approach, the specific problem of Knudsen layer fusion yield reduction is treated. Here, the predictions from the Vlasov–Fokker–Planck PINN are used to provide a non-perturbative solution of the fast ion tail in the vicinity of the hot spot, thus allowing the spatial profile of the fusion reactivity to be evaluated for a range of collisionalities and hot spot conditions. Excellent agreement is found between the predictions of the Vlasov–Fokker–Planck PINN and the results from traditional numerical solvers with respect to both the energy and spatial distribution of fast ions and the fusion reactivity profile, demonstrating that the Vlasov–Fokker–Planck PINN provides an accurate and efficient means of determining the impact of Knudsen layer yield reduction across a broad range of plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Gas Permeation and Separation Characteristics of Microporous TpHz COF Membranes Synthesized by Substrate-Assisted Interfacial Polymerization

Microporous two-dimensional covalent organic framework (2D COF) membranes offer promise for gas separation applications, but their gas transport mechanism remains unclear. In this study, a TpHz 2D COF membrane supported on a macroporous nylon substrate is prepared by substrate-assisted interfacial polymerization under mild conditions. The formation of a continuous and dense thin (~300 nm thick) TpHz layer is confirmed by scanning electron microscopy and Fourier transform infrared spectroscopy. Characterization by X-ray diffraction, grazing incidence wide-angle X-ray scattering, and N 2 porosimetry qualitatively reveals the microstructures of the supported TpHz membranes, i.e., they comprise partially oriented 2D COF lamellar crystallites with moderate crystallinity in an eclipsed (AA) stacking geometry, centering the effective membrane pore size distribution at ~1.1 nm. Further, single gas permeation data show that the transport of common molecular gases, including H 2 , He, CH 4 , N 2 , and CO 2 , through the synthesized TpHz membranes follows the Knudsen transport mechanism, where single gas permeance decreases with an increasing molecular weight and permeation temperature. Binary gas separation results show that in the equimolar CO 2 /N 2 mixture, the presence of the CO 2 surface flow slightly hinders the N 2 flow at room temperature due to the reduced membrane channel size by the adsorbed CO 2 gas layer on TpHz’s pore wall. In contrast, permeation of the equimolar CH 4 /N 2 binary mixture does not exhibit a discernible surface flow of both gases due to their much lower gas uptake on TpHz, and their transport mechanism follows Knudsen-like behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Kinetic study of strong shock waves in fully ionized plasmas

Fully kinetic simulations are used in this work to study strong shock waves in fully ionized plasmas for charge state 𝑍 ranging from 1 to 18. The ion stress tensor amplitude agrees well with classical predictions within the compression layer; however, its spatial structure is noticeably shaped by nonlocal transport effects. The electron stress tensor remains significantly smaller than that of the ions for all values of 𝑍 considered. Ion overheating in the compression layer is observed to scale approximately linearly with 𝑍. Both findings diverge from hydrodynamic models based on classical electron stress formulations. In conclusion, the electrons exhibit strong nonlocal behavior in the compression layer, with Knudsen numbers approaching unity for 𝑍 ≥ 6.

Physics - Plasma physics↗
DOE OSTI2026

ThermoPI—an Online Tool to Calculate Heat Transfer Through Foam Insulation

Thermal insulation materials with ultra-low effective thermal conductivity are crucial for a multitude of applications. Over the years, a significant amount of experimental work has been dedicated to creating new insulation materials with low thermal conductivity. Similarly, substantial efforts have been made to enhance the theoretical understanding of thermal transport mechanisms in thermal insulation materials and to push the boundaries of lower thermal conductivity. However, ample room remains for enhancing the thermal resistivity of closed-cell foam insulations. To aid in the development of ultra-low effective thermal conductivity foam insulations, Oak Ridge National Laboratory has introduced a unique online tool, ThermoPI. This tool calculates not only the effective thermal conductivity but also the thermal conductivity components for porous materials, including gases, solids, and radiative, based on the materials’ structural information (e.g., porosity, pore size, gas species, pressure, solid species, pore geometry, and temperature).This tool collected and improved the existing theoretical models for thermal insulation materials’ gas, solid, and radiative thermal conductivity. These improved models have been validated with experimental data. Effective medium theory and sound velocity softening effects are considered for solid thermal conductivity. The built-in solid materials include polystyrene, polyurethane, polyethylene, and silica. Users are allowed to input new solid materials that are not built inside the tool. For gas thermal conductivity, the subcontinuum Knudsen effect is considered. In addition to several built-in gases, users can input new gases. For solid and radiative thermal conductivity calculations, several models are available to select, and the tool can determine the best model to choose based on the materials that users input. Users are also allowed to change selections manually. In addition, the tool can also calculate the effect of interfacial resistance on the overall thermal conductivity of layered materials. This work will elaborate on the tool and discuss how it can guide the development of new insulation products.

Shrestha, Som [ORNL] (ORCID:0000000183993797)↗