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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Refinement of Vortex Generators in a Streamline-Traced, External-Compression Supersonic Inlet

Computational simulations of the flow within a streamline-traced, external-compression supersonic inlet for Mach 1.664 without and with vortex generators were performed to refine the characterization of the inlet performance as measured by the total pressure recovery and the radial and circumferential total pressure distortion indices at the engine face. The refinement of the simulations concerned two aspects: 1) refinement of the grid for the simulations to evaluate and reduce uncertainty, and 2) refinement of the modeling and design of the vortex generators. The vortex generators studied were rectangular vane-type vortex generators arranged in co-rotating arrays within the subsonic diffuser. The vortex generator geometric factors of interest included the height, circumferential spacing, and angle-of-incidence. The flow through the inlet was simulated numerically through the solution of the steady-state, Reynolds-averaged Navier-Stokes equations on multi-block, structured grids using the Wind-US flow solver. The vortex generators were simulated using either a vortex generator model or with grids generated about each vortex generator. Statistical methods were used to compute confidence intervals and grid convergence indices to establish the uncertainties of the analyses with respect to grid refinement. Design-of-experiments methods were applied to quantify the effects of the geometric factors of the vortex generators. The analyses of the computed results illustrate the complexities of quantifying the uncertainties of the inlet performance and the implications of the uncertainties for the design of a vortex generator array for the STEX inlet.

Slater, John W.↗
NASA NTRS1993

Mass loading and velocity diffusion models for heavy pickup ions at comet Grigg-Skjellerup

We compare model predictions of cometary water group ion densities and the solar wind slow down with measurements made by the Giotto Johnstone plasma analyzer implanted ion sensor at the encounter with comet Grigg-Skjellerup (G-S) on July 10, 1992. The observed slope of the ion density profile on approach to the comet is unexpectedly steep. Possible explanations for this are discussed. We present also a preliminary investigation of the quasilinear velocity-space diffusion of the implanted heavy ion population at G-S using a transport equation including souce, convection, adiabatic compression, and velocity diffusion terms. Resulting distributions are anisotropic, in agreement with observations. We consider theoretically the waves that may be generated by the diffusion process for the observed solar wind conditions. At initial ion injections, waves are generated at omega approximately Omega(sub i) the ion gyrofrequency, and lower frequencies are predicted for diffusion toward a bispherical shell.

Huddleston, D. E.↗
DOE OSTI2024

Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI

Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.

Computer vision↗
DOE OSTI2025

Harnessing emergent multiple scattering resonances in a photonic glass structure for photoelectrochemical energy conversion

Light trapping nanostructures are often necessary to improve carrier collection yields in semiconductor photoelectrodes with intrinsically poor electron transport. Photonic crystal templates can generate tailorable light trapping via periodic and precise nanostructure, though this is not a scalable strategy for photoelectrochemical (PEC) applications. It is therefore critical to identify alternative mechanisms for light trapping that tolerate disorder. Light trapping in disordered media is generated by the diffusive transport caused by multiple scattering. In some cases, multiple scattering can generate resonances that resemble those observed in photonic crystals. While resonant multiple scattering is a disorder tolerant light trapping mechanism, it is unclear if the effect is sufficiently adaptable, or even useful, for PEC applications. Here, we describe a photonic omission glass, a nanostructure that can controllably induce resonances in multiple scattering transport. We characterized the emergence of these resonances after coating a disordered SiO 2 colloidal structure with a layer of TiO 2 , which functions both as dielectric contrast and as a light absorbing semiconductor. We show in finite element simulations and spectroscopic characterization that the resonant multiple scattering effect improves light trapping near the interface between the structure and the bulk electrolyte. This effect, coupled with the increased electrochemically active surface area, results in a hierarchically structured TiO 2 photoanode with orders of magnitude higher photocurrents compared to an equivalent planar photoanode for PEC reactions such as alkaline water oxidation. We show that controlling this resonant multiple scattering effect can be advantageous for improving PEC energy conversion in disordered photoelectrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Diffusion at the magnetopause: Hybrid simulations

Electromagnetic wave generation and resulting cross-field diffusion of plasma are considered at a tangential discontinuity, which characterizes the magnetopause for northward interplanetary magnetic field. Two-dimensional hybrid (particle ions, massless fluid electrons) simulations, in which the tangential discontinuity is generated self-consistently via a stream-stream interaction, are used to show that wave growth occurs when the ambient magnetic field is predominantly perpendicular to the direction of the density gradient. Low-frequency (much less than ion gyrofrequency) waves, with amplitudes delta B/B less than or equal to 0.2 and anticorrelated density fluctuations delta n/n less than or equal to 0.6, are generated at the discontinuity, resulting in cross-field diffusion that is comparable to the Bohm rate. Both the fluctuation level and the lack of ion heating in the calculations are consistent with observations at the magnetopause. The magnitude of the diffusion is considered in the presence of numerical effects and in the context of the inferred diffusion rate at the magnetopause. The relation of the low-frequency waves and their consequences to faster growing, short-wavelength waves due to the lower hybrid drift instability is also addressed. The overall conclusion of this initial study is that diffusion due to low frequency waves is not likely to be a major effect at the magnetopause.

Winske, D.↗
DOE OSTI2026

Flow matching meets biology and life science: a survey

Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

Characterization and Performance of the Suomi-NPP VIIRS Solar Diffuser Stability Monitor

We describe the on-orbit characterization and performance of the Solar Diffuser Stability Monitor (SDSM) on-board Suomi-NPP/VIIRS. This description includes the observing procedure of each SDSM event, the algorithms used to generate the Solar Diffuser degradation corrective factors, and the results for the mission to date. We will also compare the performance of the VIIRS SDSM and SD to the similar components operating on the MODIS instrument on the EOS Terra and Aqua satellites

Fulbright, Jon P.↗
NASA NTRS2003

Shearography for Non-destructive Inspection with applications to BAT Mask Tile Adhesive Bonding and Specular Surface Honeycomb Panels

The applicability of shearography techniques for non-destructive evaluation in two unique application areas is examined. In the first application, shearography is used to evaluate the quality of adhesive bonds holding lead tiles to the B.4T gamma ray mask for the NASA Swift program. Using a vibration excitation, the more poorly bonded tiles are readily identifiable in the shearography image. A quantitative analysis is presented that compares the shearography results with a destructive pull test measuring the force at bond failure. The second application is to evaluate the bonding between the skin and core of a honeycomb structure with a specular (mirror-like) surface. In standard shearography techniques, the object under test must have a diffuse surface to generate the speckle patterns in laser light, which are then sheared. A novel configuration using the specular surface as a mirror to image speckles from a diffuser is presented, opening up the use of shearography to a new class of objects that could not have been examined with the traditional approach. This new technique readily identifies large scale bond failures in the panel, demonstrating the validity of this approach.

Lysak, Daniel B.↗
NASA NTRS2003

Shearography for Non-Destructive Evaluation with Applications to BAT Mask Tile Adhesive Bonding and Specular Surface Honeycomb Panels

In this report we examine the applicability of shearography techniques for nondestructive inspection and evaluation in two unique application areas. In the first application, shearography is used to evaluate the quality of adhesive bonds holding lead tiles to the BAT gamma ray mask for the NASA Swift program. By exciting the mask with a vibration, the more poorly bonded tiles can be distinguished by their greater displacement response, which is readily identifiable in the shearography image. A quantitative analysis is presented that compares the shearography results with a destructive pull test measuring the force at bond failure. Generally speaking, the results show good agreement. Further investigation would be useful to optimize certain test parameters such as vibration frequency and amplitude. The second application is to evaluate the bonding between the skin and core of a honeycomb structure with a specular (mirror-like) surface. In standard shearography techniques, the object under test must have a diffuse surface to generate the speckle patterns in laser light, which are then sheared. A novel configuration using the specular surface as a mirror to image speckles from a diffuser is presented, opening up the use of shearography to a new class of objects that could not have been examined with the traditional approach. This new technique readily identifies large scale bond failures in the panel, demonstrating the validity of this approach. For the particular panel examined here, some scaling issues should be examined further to resolve the measurement scale down to the very small size of the core cells. In addition, further development should be undertaken to determine the general applicability of the new approach and to establish a firm quantitative foundation.

Lysak, Daniel B.↗
NASA NTRS2000

Postural control model interpretation of stabilogram diffusion analysis

Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS1982

User's manual for Axisymmetric Diffuser Duct (ADD) code. Volume 3: ADD code coordinate generator

This User's Manual contains a complete description of the computer codes known as the Axisymmetric Diffuser Duct (ADD) code. It includes a list of references which describe the formulation of the ADD code and comparisons of calculation with experimental flows. The input/output and general use of the code is described in the first volume. The second volume contains a detailed description of the code including the global structure of the code, list of FORTRAN variables, and descriptions of the subroutines. The third volume contains a detailed description of the CODUCT code which generates coordinate systems for arbitrary axisymmetric ducts.

Anderson, O. L.↗
NASA NTRS1999

Low Stretch Diffusion Flames Over a Solid Fuel

A unique new way to study low gravity flames in normal gravity has been developed. To study flame structure and extinction characteristics in low stretch environments, a normal gravity low-stretch diffusion flame is generated using a cylindrical PMMA sample of varying large radii. Foutch and T'ien used the radiative loss as well as a densimetric Froude number to characterize the blowoff (small Da) and quenching extinction (large Da) boundaries in stagnation-point diffusion flames under various convective conditions. An important conclusion of this study was that the shape and location of the extinction boundary, as well as a number of important flame characteristics, were almost identical for the buoyant, forced, and mixed convective environments they modeled. This theory indicates it should be possible to understand a material's burning characteristics in the low stretch environment of spacecraft (induced by fans and crew movements) by understanding its burning characteristics in an equivalent Earth-based stretch environment (induced by normal gravity buoyancy). Similarly, the material's burning characteristics in Lunar or Martian stretch environments (induced by partial gravity buoyancy) can be assessed. Equivalent stretch rates can be determined as a function of gravity, imposed flow, and geometry. A generalized expression for stretch rate which captures mixed convection includes both buoyant and forced stretch is defined as a = a(sub f) ((1 + (a(sub b))exp 2/(a(sub b))exp 2))exp 1/2. For purely buoyant flow, the equivalent stretch rate is a(sub b) = [(rho(exp e)-rho(exp *)/rho(sub e)][g/R](exp 1/2). For purely forced flow, the equivalent stretch rate is characterized by either a(sub f)= 2U(sub infinity)/R for a cylinder, or a(sub f)=U(sub jet)/d(sub jet) for a jet impinging on a planar surface. In these experiments, the buoyant stretch is varied through R, the radius of curvature, but the buoyant stretch could also be varied through g, the gravity level. In this way the effect of partial gravity, such as those found on the Moon (1/6 g) or Mars (1/3 g) can be captured in the definition of flame stretch.

Olson, S. L.↗
DOE OSTI2025

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗
DOE OSTI2025

Latent diffusion can map beam loss to two-dimensional phase-space projections

Beam loss monitors (BLMs) and beam current monitors (BCMs) are ubiquitous at particle accelerators around the world. These simple devices provide noninvasive high-level beam measurements but give no insight into the detailed 6D (𝑥,𝑦,𝑧,𝑝 𝑥 ,𝑝 𝑦 ,𝑝 𝑧 ) beam phase-space distributions or dynamics. We show that generative conditional latent diffusion models can learn intricate patterns to solve the extreme inverse problem of mapping waveforms of tens of BLMs or BCMs along an accelerator to detailed 2D projections of a charged particle beam’s 6D phase-space density. This transformational method can be used at any particle accelerator to transform simple noninvasive devices into detailed beam phase-space diagnostics. We demonstrate this concept via multiparticle simulations of the high-intensity beam in the kilometer-long Los Alamos Neutron Science Center linear proton accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Field-level reconstruction from foreground-contaminated 21-cm maps

Current and upcoming 21-cm experiments will soon be able to map 21-cm spatial fluctuations in three dimensions for a wide range of redshifts. However, bright foreground contamination and the nature of radio interferometry create significant challenges, making it difficult to access rich cosmological information from the Fourier modes that lie within the “foreground wedge”. Here, in this work, we introduce two approaches aiming to reconstruct the full 21-cm density field, including the missing modes in the wedge: (a) a field-level inference under an effective field theory (EFT) framework; (b) a diffusion-based deep generative model trained on simulations. Under the EFT framework, we implement a fully differentiable forward model that maps the initial conditions of matter fluctuations to the observed, foreground-filtered 21-cm maps. This enables a gradient-based sampler to simultaneously sample the initial conditions and bias parameters, allowing a physically motivated mode reconstruction. Alternatively, we apply a variational diffusion model to perform 21-cm density reconstruction at the map level. Our model is trained on semi-numerical simulations over a wide range of astrophysical parameters. Our results from both approaches should provide improved cosmological constraints from the field level and also enable cross-correlation between experiments that have little or no overlapping modes.

cosmological perturbation theory↗
NASA NTRS2016

Scattering of Gaussian Beams by Disordered Particulate Media

A frequently observed characteristic of electromagnetic scattering by a disordered particulate medium is the absence of pronounced speckles in angular patterns of the scattered light. It is known that such diffuse speckle-free scattering patterns can be caused by averaging over randomly changing particle positions and/or over a finite spectral range. To get further insight into the possible physical causes of the absence of speckles, we use the numerically exact superposition T-matrix solver of the Maxwell equations and analyze the scattering of plane-wave and Gaussian beams by representative multi-sphere groups. We show that phase and amplitude variations across an incident Gaussian beam do not serve to extinguish the pronounced speckle pattern typical of plane-wave illumination of a fixed multi-particle group. Averaging over random particle positions and/or over a finite spectral range is still required to generate the classical diffuse speckle-free regime.

radiative transfer theory↗