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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

XFOL FY25 Omega 3 pager [Slides]

The XFOL campaign is continuing to study radiation flow in stochastic media. Purpose: Simultaneously measure the ionization state of the background and inclusions of a binary stochastic media using the COAX/OUTI diagnostic. Motivation: Radflow is stochastic media is of wide, growing interest and COAX is a new powerful diagnostic that can characterize the radflow physics and validate codes, models, and their underlying assumptions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Cassio Simulations of X-ray Flow Over Lumps (XFOL) Experiments [Slides]

Homogeneous media is not a good approximation for stochastic media with large clump sizes and therefore not valid for our experiments. The media created for these experiments is not Markovian distributed. Stochastic media transport methods don’t work well with non-Markovian mixtures. Sphere at various axial locations in the dmain encounter very different radflow characteristics and therefore result in different spectroscopic signatures. Ongoing analysis of tally surfaces will allow for better characterization of the radiation flow in radiation hydrodynamics simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Spatial Correlations of the Poisson Model for Radiation Transport

Characterizing the relationship between bulk physical properties and mixing in randomly heterogeneous media is a central challenge across many areas of science and engineering. A benchmark model for such studies is the Poisson model, a random tessellation of space by a Poisson process of hyperplanes. In radiation transport studies, the lack of exact expressions for the Poisson model’s spatial multipoint functions has led to approximate methods being used, introducing unquantified sources of error. Here, we recently introduced an exact solution for the Poisson model’s multipoint functions and closely related conditional probability functions (CPFs), providing a new opportunity to understand and reduce these sources of error. In this paper, we enable a more rigorous investigation of radiation transport in stochastic media by applying the recently introduced exact solution for the Poisson model’s CPFs. This paper consists of three main contributions. First, we introduce a unified framework for CPFs of the Poisson model, encompassing the recently introduced exact CPFs as well as the previously introduced atomic mix, nearest-neighbor, and combination CPFs. This framework also includes existing pruning techniques for the approximate CPFs, such as angular exclusion, as well as a novel form of angular exclusion suitable for the exact CPFs. Second, we use the exact CPFs to characterize the spatial regions where each approximate three-point CPF is most accurate, thereby explaining the observed hierarchy of accuracy among the approximate models. Finally, we evaluate material transmittance, reflectance, and flux in a three-dimensional test problem using conditional point sampling, demonstrating the relationship between CPF accuracy and transport simulation accuracy.

Poisson model↗
DOE OSTI2023

Roadmap for the exposé of radiation flows (Xflows) experiment on $\mathrm{NIF}$

Here, the goal of the Xflows experimental campaign is to study the radiation flow on the National Ignition Facility (NIF) reproducing the sensitivity of the temperature (±8 eV, ±23 μm) and density (±11 mg/cc) measurements of the COAX platform. This new platform will enable future astrophysical experiments involving supernova shock breakout, such as Radishock on OMEGA-60, and stochastic media (such as XFOL on OMEGA). Greater energy and larger physical scale on NIF will enable a greater travel distance of radiation flow, higher density, and more manufacturable foams and enable exploration of a greater range of radiation behavior than achievable in the prior OMEGA experiments. This publication will describe the baseline configuration for the Xflows experimental campaign and the roadmap to achieve its primary objectives.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Particle transport in Markov stochastic mixtures with spatial gradients

Markov geometries are a prototype class of stochastic media that are widely used to model complex disordered systems. In a series of recent works, we have shown that spatially homogeneous (but possibly non-isotropic) Poisson tessellations can be conveniently used in order to generate three-dimensional realizations of Markov media and thus characterize the features of particle transport e.g. in fragmented fuel elements following severe nuclear accidents or Rayleigh-Taylor turbulent mixing for inertial confinement fusion. In this paper we show that Poisson tessellations can be extended to take into account the presence of spatial gradients, which commonly occur in real-world applications due to material stratification. For this purpose, we will provide an explicit construction of spatially-non-homogeneous Poisson tessellations, fully characterize their statistical properties, and finally illustrate the behaviour of particle transport in such random media. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Stochastic Inversion of Gaussian Random Media Using Transverse Coherence Functions for Reflected Waves: Theory and Method

The transverse coherence functions (TCFs) of phase and amplitude fluctuations of a seismic wave are powerful to estimate the spatial distribution, length scales, and strength of random heterogeneities. However, TCFs have been formulated for transmitted waves only, not for reflected waves. In this paper, we derive reflection TCFs for Gaussian random media. Furthermore, we propose to invert for Gaussian random media using the reflection TCFs based on the grid search. We validate the new reflection TCF formulas using 2D finite-difference numerical experiments. The numerical example also illustrates the feasibility and efficiency of the inversion. The stochastic inversion using reflected waves can be used in both exploration and global seismology.

58 GEOSCIENCES↗