Search NASA⌕ Search

SEARCH · Search NASA

Results for “quantitative image analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Application of Scanning-Imaging X-Ray Microscopy to Fluid Inclusion Candidates in Carbonates of Carbonaceous Chondrites

In order to search for such fluid inclusions in carbonaceous chondrites, a nondestructive technique using x-ray micro-absorption tomography combined with FIB sampling was developed and applied to a carbonaceous chondrite. They found fluid inclusion candidates in calcite grains, which were formed by aqueous alteration. However, they could not determine whether they are really aqueous fluids or merely voids. Phase and absorption contrast images can be simultaneously obtained in 3D by using scanning-imaging x-ray microscopy (SIXM). In refractive index, n=1-sigma+i(beta), in the real part, 1-sigma is the refractive index with decrement, sigma, which is nearly proportional to the density, and the imaginary part, beta, is the extinction coefficient, which is related to the liner attenuation coefficient, mu. Many phases, including water and organic materials as well as minerals, can be identified by SIXM, and this technique has potential availability for Hayabusa-2 sample analysis too. In this study, we examined quantitative performance of d and m values and the spatial resolution in SIXM by using standard materials, and applied this technique to carbonaceous chondrite samples. We used POM ([CH2O]n), silicon, quartz, forsterite, corundum, magnetite and nickel as standard materials for examining the sigma and mu values. A fluid inclusion in terrestrial quartz and bi-valve shell (Atrina vexillum), which are composed of calcite and organic layers with different thickness, were also used for examining the spatial resolution. The Ivuna (CI) and Sutter's Mill (CM) meteorites were used as carbonaceous chondrite samples. Rod- or cube-shaped samples 20-30 micron in size were extracted by using FIB from cross-sectional surfaces of the standard materials or polished thin sections of the chondrites, which was previously observed with SEM. Then, the sample was attached to a thin W-needle and imaged by SIXM system at beamline BL47XU, SPring-8, Japan. The slice thickness was 109.3 nm and the pixel size was mostly 100 nm.

Tsuchiyama, Akira↗
DOE OSTI2021

Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Abstract Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dataset for Leveraging CryoEM and AI-Driven Morphological Feature Analysis for Insights on Bacterial Structures

This repository hosts an AI-assisted image segmentation and analysis pipeline for Pantoea sp. YR343 cryo-electron microscopy (cryoEM) datasets. The workflow automates membrane thickness measurements, flagella detection, and field-of-view (FOV) screening from low-dose, high-resolution cryoEM micrographs eliminating the need for slow manual annotation. By integrating deep-learning based segmentation (YOLOv11) with quantitative post-processing, this toolkit provides a scalable and reproducible way to study bacterial morphology under hydrated, near-native conditions. The GitHub repository for AI-based tools for cryoEM bacteria ultrastructures can be found here: https://github.com/Sireesiru/Cryo-EM-Ultrastructures/tree/main

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

Full field flow visualization and computer-aided velocity measurements in a bank of cylinders in a wind tunnel

The full field flow tracking (FFFT) method that is presented in this paper uses a laser-generated, mechanically strobed planar sheet of light, a low luminosity TV camera coupled with a long distance microscope, and a computer-controlled video recorder to study nonintrusively and qualitatively the flow structures in a bank of cylinders that are placed in a wind tunnel. This setup simulates an upscale version of the geometry of internal cooling passageways characteristic of small air-cooled radial turbines. The qualitative images supplied by the FFFT system are processed by means of a computer-integrated image quantification (CIIQ) method into quantitative information, trajectories and velocities, that describe the flow upstream of and within the bank of cylinders. The tracking method is Lagrangian in concept, and permits identification and tracking of the same particle, thus facilitating construction of time dependent trajectories and the calculation of true velocities and accelerations. The error analysis evaluates the accuracy with which the seed particles follow the flow and the errors incurred during the quantitative processing of the raw data derived from the FFFT/CIIQ method.

Braun, M. J.↗
NASA NTRS2012

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Roberts, Yolanda↗
DOE OSTI2025

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗
DOE OSTI2022

U Metal Oxidation with Steam (U)

The Savannah Rive National Laboratory 9SRNL) is evaluating a method to produce uranium oxide (UO 2 ) from uranium metal using steam. The typical methods for making UO 2 yield powders with particle-size ranges of 1 to 50 micron. The goal of the steam oxidation is to produce a depleted uranium (DU) product with a larger particle size that can be used as a surrogate for testing physical and mechanical process techniques to refine uranium and/or plutonium bearing residues. Several studies in the literature indicated that reactions between uranium metal and steam will yield UO 2 as fine powders in the 160 to 500 °C range, but granular materials form above 500°C. Above 880 °C, a hard compact scale forms on the U metal. Furthermore, sintering of UO 2 occurs at about 1300 °C, but it has been stated that the presence of steam enhances the sintering characteristics of UO 2 . Initial studies into the oxidation of DU metal in an atmosphere of argon and steam have been completed. Oxidation of depleted uranium metal in Ar/steam at 600, 710, 700, and 830 °C yielded at UO 2 product with little or no impurity at each temperature. Although not enough sample was available to perform sieve analysis for particle size distribution, SEM images reveal that a significant volume fraction of the products at 710, 770, and 830 °C exceeds 100 microns. The material produced at 600 °C was too fine for programmatic needs. Questions associated with the UO 2 include morphology of product, mechanical strength of the particles, and performance in milling operations. The size of the samples produced in these tests did not allow for quantitative assessment of particle size of mechanical strength. A qualitative assessment of the particles formed at 710, 770, and 830 °C was that the samples produced at 710 and 770 °C were friable, and the sample produced 830 °C had more mechanical strength. Sintering of the samples in Ar/steam at 970 °C appeared to increase the strength of the particles without changing their general particle size characteristics. Due to the small sample sizes, the increase in strength could not be quantified. If the sintering at 970 °C is inadequate, higher sintering temperatures in Ar/steam can be evaluated. Future work will increase scale of the steam oxidation conditions which yield the most-favorable particle-size distributions with sufficient mechanical strength for programming usage. Further consideration will be given to oxidation temperature, steam addition to the reaction vessel, U metal pretreatment, and sintering conditions after oxidation. The UO 2 production could involve a two-step process where particles are formed in steam at lower temperatures (700-850 °C) and then sintered in Ar/steam at elevated temperatures (950-1200 °C). Larger samples (50-100 g each) will provide sufficient UO 2 product for sieve analysis and assessment of mechanical strength relatives to subsequent milling operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1984

Quantitation of heavy ion damage to the mammalian brain - Some preliminary findings

For several years, studies have been conducted regarding late effects of particulate radiations in mammalian tissues, taking into account the brains of rodents and lagomorphs. Recently, it has become feasible to quantify pathological damage and morpho-physiologic alterations accurately in large numbers of histological specimens. New investigative procedures make use of computer-assisted automated image analysis systems. Details regarding the employed methodology are discussed along with the results of the information. The radiations of high linear energy transfer (LET) cause apparently earlier and more dramatic shrinkage of olfactory glomeruli in exposed rabbit brains than comparable doses of Co-60 gamma photons.

Cox, A. B.↗
DOE OSTI2021

Electrochemically Induced Strain Evolution in Pt–Ni Alloy Nanoparticles Observed by Bragg Coherent Diffraction Imaging

Strain is known to enhance the activity of the oxygen reduction reaction in catalytic platinum alloy nanoparticles, whose inactivity is the primary impediment to efficient fuel cells and metal–air batteries. Here, Bragg coherent diffraction imaging (BCDI) was employed to reveal the strain evolution during the voltammetric cycling in Pt–Ni alloy nanoparticles composed of Pt 2 Ni 3 , Pt 1 Ni 1 , and Pt 3 Ni 2 . Analysis of the 3D strain images using a core–shell model shows that the strain as large as 5% is induced on Pt-rich shells due to Ni dissolution. The composition dependency of the strain on the shells is in excellent agreement with that of the catalytic activity. The present study demonstrates that BCDI enables quantitative determination of the strain on alloy nanoparticles during electrochemical reactions, which provides a means to exploit surface strain to design a wide range of electrocatalysts.

36 MATERIALS SCIENCE↗
NASA NTRS2008

A Stereo Imaging Velocimetry Technique for Analyzing Structure of Flame Balls at Low Lewis-Number (SOFBALL) Data

Stereo Imaging Velocimetry (SIV) is a NASA Glenn Research Center (GRC) developed fluid physics technique for measuring threedimensional (3-D) velocities in any optically transparent fluid that can be seeded with tracer particles. SIV provides a means to measure 3-D fluid velocities quantitatively and qualitatively at many points. This technique provides full-field 3-D analysis of any optically clear fluid or gas experiment using standard off-the-shelf CCD cameras to provide accurate and reproducible 3-D velocity profiles for experiments that require 3-D analysis. A flame ball is a steady flame in a premixed combustible atmosphere which, due to the transport properties (low Lewis-number) of the mixture, does not propagate but is instead supplied by diffusive transport of the reactants, forming a premixed flame. This flame geometry presents a unique environment for testing combustion theory. We present our analysis of flame ball phenomena utilizing SIV technology in order to accurately calculate the 3-D position of a flame ball(s) during an experiment, which can be used as a direct comparison of numerical simulations.

McDowell, Mark↗
NASA NTRS1998

Model Analysis of an Aircraft Fueslage Panel using Experimental and Finite-Element Techniques

The application of Electro-Optic Holography (EOH) for measuring the center bay vibration modes of an aircraft fuselage panel under forced excitation is presented. The requirement of free-free panel boundary conditions made the acquisition of quantitative EOH data challenging since large scale rigid body motions corrupted measurements of the high frequency vibrations of interest. Image processing routines designed to minimize effects of large scale motions were applied to successfully resurrect quantitative EOH vibrational amplitude measurements

Fleming, Gary A.↗
DOE OSTI2020

Topological analysis of X-ray CT data for the recognition and trending of subtle changes in microstructure under material aging

X-ray computed tomography (CT) is an established non-destructive tool for 3D imaging of multiphasic composites. Numerous applications of X-ray CT in medical diagnosis and materials characterization have been reported, many involving field-specific innovations in the imaging technology itself. Yet, quantitative summarization to link image features to properties of interest has been rare. Here we address this issue by employing state-of-the-art technics in scalar field topology for the summarization of X-ray CT images of an example biphasic system. By varying processing-parameters we create different microstructures, evolve them through accelerated thermal aging, CT-image them pre- and post-aged, and demonstrate the ability of our image summarization method to systematically track process- and age-related changes, which can often be very subtle. A novel aspect of the algorithm involves recognition over multiple resolution levels, which provides deeper insight into the pattern relationship between grain-like features and their neighbors. The method is general, adaptable to diverse image reconstruction methods and materials systems, and particularly useful in applications where practical constraints on the sample-size limits the reliable use of more complex models, e.g., convolutional neural networks.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Computer simulation of the effects of transmission-averaging in microdensitometry

One of the principal advantages of electrography when compared to photography is the nearly linear relationship between source intensity versus resulting image density. This property allows for simplified and more accurate photometric calibration and permits a certain degree of extrapolation of the calibration to beyond the limits of the faintest photoelectric standard on an exposure. The desires to extract quantitative photometric information from electrographic (or photographic) negatives and to convert this information into a digital format for computer analysis or enhancement led to the widespread use of scanning microdensitometers to perform this A-to-D conversion. Therefore it is of vital importance to understand and, if practical, to avoid any nonlinearities which may be introduced during microdensitometry of electrographic emulsions.

Heckathorn, H. M.↗
NASA NTRS1993

Quantitative Mapping of Pore Fraction Variations in Silicon Nitride Using an Ultrasonic Contact Scan Technique

An ultrasonic scan procedure using the pulse-echo contact configuration was employed to obtain maps of pore fraction variations in sintered silicon nitride samples in terms of ultrasonic material properties. Ultrasonic velocity, attenuation coefficient, and reflection coefficient images were obtained simultaneously over a broad band of frequencies (e.g., 30 to 110 MHz) by using spectroscopic analysis. Liquid and membrane (dry) coupling techniques and longitudinal and shear-wave energies were used. The major results include the following: Ultrasonic velocity (longitudinal and shear wave) images revealed and correlated with the extent of average through-thickness pore fraction variations in the silicon nitride disks. Attenuation coefficient images revealed pore fraction nonuniformity due to the scattering that occurred at boundaries between regions of high and low pore fraction. Velocity and attenuation coefficient images were each nearly identical for machined and polished disks, making the method readily applicable to machined materials. Velocity images were similar for wet and membrane coupling. Maps of apparent Poisson's ratio constructed from longitudinal and shear-wave velocities quantified Poisson's ratio variations across a silicon nitride disk. Thermal wave images of a disk indicated transient thermal behavior variations that correlated with observed variations in pore fraction and velocity and attenuation coefficients.

Roth, Don J.↗
NASA NTRS2007

Multispectral Imaging Broadens Cellular Analysis

Amnis Corporation, a Seattle-based biotechnology company, developed ImageStream to produce sensitive fluorescence images of cells in flow. The company responded to an SBIR solicitation from Ames Research Center, and proposed to evaluate several methods of extending the depth of field for its ImageStream system and implement the best as an upgrade to its commercial products. This would allow users to view whole cells at the same time, rather than just one section of each cell. Through Phase I and II SBIR contracts, Ames provided Amnis the funding the company needed to develop this extended functionality. For NASA, the resulting high-speed image flow cytometry process made its way into Medusa, a life-detection instrument built to collect, store, and analyze sample organisms from erupting hydrothermal vents, and has the potential to benefit space flight health monitoring. On the commercial end, Amnis has implemented the process in ImageStream, combining high-resolution microscopy and flow cytometry in a single instrument, giving researchers the power to conduct quantitative analyses of individual cells and cell populations at the same time, in the same experiment. ImageStream is also built for many other applications, including cell signaling and pathway analysis; classification and characterization of peripheral blood mononuclear cell populations; quantitative morphology; apoptosis (cell death) assays; gene expression analysis; analysis of cell conjugates; molecular distribution; and receptor mapping and distribution.

Source record↗
NASA NTRS1980

Comparisons between wave directional spectra from SAR and pressure sensor arrays

Simultaneous directional wave measurements were made at Torrey Pines Beach, California, by a synthetic aperture radar (SAR) and a linear array of pressure sensors. The measurements were conducted during the West Coast Experiment in March 1977. Quantitative comparisons of the normalized directional spectra from the two systems were made for wave periods of 6.9-17.0 s. The comparison results were variable but generally showed good agreement of the primary mode of the normalized directional energy. An attempt was made to quantify the physical criteria for good wave imaging in the SAR. A frequency band analysis of wave parameters such as band energy, slope, and orbital velocity did not show good correlation with the directional comparisons. It is noted that absolute values of the wave height spectrum cannot be derived from the SAR images yet and, consequently, no comparisons of absolute energy levels with corresponding array measurements were intended.

Pawka, S. S.↗
DOE OSTI2024

Full-field quantitative visualization of shock-driven pore collapse and failure modes in PMMA

The dynamic collapse of pores under shock loading is thought to be directly related to hot spot generation and material failure, which is critical to the performance of porous energetic and structural materials. However, the shock compression response of porous materials at the local, individual pore scale is not well understood. This study examines, quantitatively, the collapse phenomenon of a single spherical void in PMMA at shock stresses ranging from 0.4 to 1.0 GPa. Using a newly developed internal digital image correlation technique in conjunction with plate impact experiments, full-field quantitative deformation measurements are conducted in the material surrounding the collapsing pore for the first time. The experimental results reveal two failure mode transitions as shock stress is increased: (i) the first in situ evidence of shear localization via adiabatic shear banding and (ii) dynamic fracture initiation at the pore surface. Numerical simulations using thermo-viscoplastic dynamic finite element analysis provide insights into the formation of adiabatic shear bands (ASBs) and stresses at which failure mode transitions occur. Further numerical and theoretical modeling indicates the dynamic fracture to occur along the weakened material inside an adiabatic shear band. Finally, analysis of the evolution of pore asymmetry and models for ASB spacing elucidate the mechanisms for the shear band initiation sites, and elastostatic theory explains the experimentally observed ASB and fracture paths based on the directions of maximum shear.

42 ENGINEERING↗
DOE OSTI2022

Segmentation of tomography datasets using 3D convolutional neural networks

Dendritic microstructures are ubiquitous in nature and are the primary solidification morphologies in metallic materials. Techniques such as X-ray computed tomography (XCT) have provided new insights into dendritic phase transformation phenomena. However, manual identification of dendritic morphologies in microscopy data can be both labor intensive and potentially ambiguous. The analysis of 3D datasets is particularly challenging due to their large sizes (terabytes) and the presence of artifacts scattered within the imaged volumes. Here, in this study, we trained 3D convolutional neural networks (CNNs) to segment 3D datasets. Three CNN architectures were investigated, including a new version of FCDenseNet which we extended to 3D. We show that using hyperparameter optimization (HPO) and fine-tuning techniques, both 2D and 3D CNN architectures outperform the previous state of the art. The 3D U-Net architecture trained in this study produced the best segmentations according to quantitative metrics (intersection-over-union of 95.56% and a boundary displacement error of 0.58 pixels), while 3D FCDense produced the smoothest boundaries and best segmentations according to visual inspection. The trained 3D CNNs are able to segment entire 852 × 852 × 250 voxel 3D volumes in only ~60 s, thus hastening the progress towards a deeper understanding of phase transformation phenomena such as dendritic solidification.

36 MATERIALS SCIENCE↗