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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.

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At least 91 records · Page 5

Very high elevation water ice clouds on Mars: Their morphology and temporal behavior

Quantitative analysis of Viking images of the martian planetary limb has uncovered the existence and temporal behavior of water ice clouds that form between 50 and 90 km elevation. These clouds show a seasonal behavior that may be correlated with lower atmosphere dynamics. Enhanced vertical mixing of the atmosphere as Mars nears perihelion is hypothesized as the cause of the seasonal dependence, and the diurnal dependence is explained by the temporal behavior of the martian diurnal thermal tide. Viking images also provide a data set of the vertical distribution of aerosols in the martian atmosphere. The temporal and spatial distribution of aerosols are characterized.

Jaquin, Fred↗

The use of ultrasonic property measurements as the basis for finite element analysis of composite materials

In this work, the use of ultrasonic property measurements as the basis for finite element analysis of full scale composite components is presented. The approach utilizes multiple velocity measurements at oblique angles of incidence and quantitative analysis of radiographic images for the local determination of each of the nine orthotropic moduli in a woven carbon-carbon composite. These values were then used as input into a finite element code (NASTRAN) to analyze the response of the material to load: here, diametric compression. The predicted response was then compared with strain gage results at several locations to validate the approach.

Madaras, E. I.↗

Advanced IR System For Supersonic Boundary Layer Transition Flight Experiment

Infrared thermography is a preferred method investigating transition in flight: a) Global and non-intrusive; b) Can also be used to visualize and characterize other fluid mechanic phenomena such as shock impingement, separation etc. F-15 based system was updated with new camera and digital video recorder to support high Reynolds number transition tests. Digital Recording improves image quality and analysis capability and allows for accurate quantitative (temperature) measurements and greater enhancement through image processing allows analysis of smaller scale phenomena.

Banks, Daniel W.↗

Quantitative analysis of properties and spatial relations of fuzzy image regions

Properties of objects and spatial relations between objects play an important role in rule-based approaches for high-level vision. The partial presence or absence of such properties and relationships can supply both positive and negative evidence for region labeling hypotheses. Similarly, fuzzy labeling of a region can generate new hypotheses pertaining to the properties of the region, its relation to the neighboring regions, and finally, the labels of the neighboring regions. In this paper, we present a unified methodology to characterize properties and spatial relationships of object regions in a digital image. The proposed methods can be used to arrive at more meaningful decisions about the contents of the scene.

Krishnapuram, Raghu↗

Geometric and radiometric preprocessing of airborne visible/infrared imaging spectrometer (AVIRIS) data in rugged terrain for quantitative data analysis

A geocoding procedure for remotely sensed data of airborne systems in rugged terrain is affected by several factors: buffeting of the aircraft by turbulence, variations in ground speed, changes in altitude, attitude variations, and surface topography. The current investigation was carried out with an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene of central Switzerland (Rigi) from NASA's Multi Aircraft Campaign (MAC) in Europe (1991). The parametric approach reconstructs for every pixel the observation geometry based on the flight line, aircraft attitude, and surface topography. To utilize the data for analysis of materials on the surface, the AVIRIS data are corrected to apparent reflectance using algorithms based on MODTRAN (moderate resolution transfer code).

Meyer, Peter↗

Thermal Imaging with Novel Infrared Focal Plane Arrays and Quantitative Analysis of Thermal Imagery

We have developed a single long-wavelength infrared (LWIR) quantum well infrared photodetector (QWIP) camera for thermography. This camera has been used to measure the temperature profile of patients. A pixel coregistered simultaneously reading mid-wavelength infrared (MWIR)/LWIR dual-band QWIP camera was developed to improve the accuracy of temperature measurements especially with objects with unknown emissivity. Even the dualband measurement can provide inaccurate results due to the fact that emissivity is a function of wavelength. Thus we have been developing a four-band QWIP camera for accurate temperature measurement of remote object.

Thermography↗

Interactive Image-Analysis Program

BLOBTOOL computer program used to prepare image for analysis and generates various quantitative measurements of objects or structures present in images. Includes basic input/output capabilities, option to display built-in color tables, and access to on-line help. Written in C Language.

Leonard, Desiree M.↗

Quantitative assessment of particle dispersion in polymeric composites and its effect on mechanical properties

In this work, an automated image analysis tool is developed to establish quantitative correlations between the particle/cluster size distribution and the mechanical properties of particle reinforced polymer composites (PRPC).This automated image analysis tool is developed within python programming software to process and analyze the microstructural images of the polymerbased composite materials. The spent coffee bean powder (SCBP) reinforced poly-propylene carbonate (PPC) polymer composite with differing wt.% of the filler is selected for the analysis. Detailed statistical analysis of the microstructural images reveals that ‘clustering of clusters’ is also presented in addition to the most commonly reported ‘clustering of particles’, and the distribution of particle/clusters is bimodal. Based on these findings, an effective volume fraction for the filler material is proposed to mainly capture the agglomeration effect. With this effective volume fraction, the standard rule-of-mixture model correctly captures the experimentally measured tensile strength and modulus as a function of filler wt.%. Further, the applicability of this effective volume fraction for other theoretical models is also analyzed. The detailed statistical analysis of the microstructure and the proposed effective volume fraction helps to develop a deeper quantitative understanding of the PRPC than the conventional qualitative correlation of microstructural features with the properties and failure processes.

36 MATERIALS SCIENCE↗

Quantitative Analysis of Venus Radar Backscatter Data in ArcGIS

Ongoing mapping of the Ganiki Planitia (V14) quadrangle of Venus and definition of material units has involved an integrated but qualitative analysis of Magellan radar backscatter images and topography using standard geomorphological mapping techniques. However, such analyses do not take full advantage of the quantitative information contained within the images. Analysis of the backscatter coefficient allows a much more rigorous statistical comparison between mapped units, permitting first order selfsimilarity tests of geographically separated materials assigned identical geomorphological labels. Such analyses cannot be performed directly on pixel (DN) values from Magellan backscatter images, because the pixels are scaled to the Muhleman law for radar echoes on Venus and are not corrected for latitudinal variations in incidence angle. Therefore, DN values must be converted based on pixel latitude back to their backscatter coefficient values before accurate statistical analysis can occur. Here we present a method for performing the conversions and analysis of Magellan backscatter data using commonly available ArcGIS software and illustrate the advantages of the process for geological mapping.

Long, S. M.↗

Quantitative analysis of drainage obtained from aerial photographs and RBV/LANDSAT images

Data obtained from aerial photographs (1:60,000) and LANDSAT return beam vidicon imagery (1:100,000) concerning drainage density, drainage texture, hydrography density, and the average length of channels were compared. Statistical analysis shows that significant differences exist in data from the two sources. The highly drained area lost more information than the less drained area. In addition, it was observed that the loss of information about the number of rivers was higher than that about the length of the channels.

Dejesusparada, N.↗

Tutorial: Machine Learning and Artificial Intelligence in Batteries

Machine learning (ML) promises to compress the time needed to characterize battery performance, lifetime and safety. By coupling ML with physical models and metrics, that learning can bridge across materials, chemistries and cell designs. This tutorial will discuss the most popular ML techniques and resources and review recent work in the electrochemical literature. Applications include materials discovery, image recognition for quantitative microscopy analysis, fast charge algorithm development and life prediction.

47 OTHER INSTRUMENTATION↗

Three-dimensional imaging of grain boundaries via quantitative fluorescence X-ray tomography analysis

Abstract Three-dimensional visualization of material composition within multiple grains and across complex networks of grain boundaries at nanoscales can provide new insight into the structure evolution and emerging functional properties of the material for diverse applications. Here, using nanoscale scanning X-ray fluorescence tomography, coupled with an advanced self-absorption correction algorithm developed in this work, we analyze the three-dimensional gain distributions and compositions in a Ce 0.8 Gd 0.2 O 2-δ -CoFe 2 O 4 mixed ionic-electronic conductor system with high accuracy and statistical significance. Our systematic investigation reveals an additional emergent phase and uncovers highly intriguing composition stability ranges for the multiple material phases within this system. The presented visualization of composition variations across complex interfaces, supported by our quantitative composition analysis, discloses mechanistic pathways of the diverse phase transformations occurring in the material synthesis, providing insights for the optimization of transport properties in the mixed ionic-electronic conductor system.

36 MATERIALS SCIENCE↗

Self‐Assembled LuFeO 3 /LuFe 2 O 4 Heterostructure with Emergent Ferroic Orderings

Abstract Achieving self‐assembling structures that exhibit emergent properties and functionalities is one of the holy grails in nanotechnology and holds great promise for a wide range of potential applications. Herein, a self‐assembled LuFeO 3 –(1/3)LuFe 2 O 4 –LuFeO 3 heterostructure that consists of two model multiferroics, i.e., hexagonal LuFeO 3 and rhombohedral LuFe 2 O 4 , is reported in single‐layer epitaxial LuFeO 3 thin films. Atomic‐scale electron microscopy investigations reveal the spontaneous organization of ferroelectric polarization in each building block, which forms a series of polar configurations. Specifically, the charge and lattice of neighboring LuFeO 3 and LuFe 2 O 4 blocks are closely coupled with competing degrees of freedom. A combination of the quantitative analysis of atomically resolved images and spectroscopy with theoretical calculations determines how charge‐ordering‐induced polarization accommodates charge naturality across the interfaces to reduce the system energy and unravels the formation mechanism of this heterostructure. The results point to the possibilities of generation and control of multiferroic self‐assembled systems, which may provide a basis for engineering novel materials with emergent properties.

Deng, Shiqing↗

Quantifying biofilm propagation on chemically modified surfaces

Conditions affecting biofilm formation differ among bacterial species and this presents a challenge to studying biofilms in the lab. This work leverages functionalized silanes to control surface chemistry in the study of early biofilm propagation, quantified with a semi-automated image processing algorithm. These methods support the study of Pantoea sp. YR343, a gram-negative bacterium isolated from the poplar rhizosphere. We found that Pantoea sp. YR343 does not readily attach to hydrophilic surfaces but will form biofilms with a “honeycomb” morphology on hydrophobic surfaces. Our image processing algorithm described here quantified the evolution of the honeycomb morphology over time, and found the propagation to display a logarithmic behavior. This methodology was repeated with a flagella-deficient fliR mutant of Pantoea sp. YR343 which resulted in reduced surface attachment. Quantifiable differences between Pantoea WT and ΔfliR biofilm morphologies were captured by the image processing algorithm, further demonstrating the insight gained from these methods.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative and qualitative bone imaging: A review of synchrotron radiation microtomography analysis in bone research

All levels of the unique hierarchical structure of bone, consisting of collagen and hydroxyapatite crystals at the nanoscale to osteon/lamellae structures at the microscale, contribute to its characteristic toughness and material properties. Elements of bone's density and size contribute to bone quantity (or bone mass), whereas elements of bone's material composition, material properties, internal structure, and organization describe bone quality. Furthermore, bone quantity and quality can be degraded by factors such as aging, disease, treatments, and irradiation, compromising its ability to resist fracture and sustain loading. Accessing the morphology and architecture of bone at the microscale to quantify microstructural features and assess the degree of mineralization and path of crack propagation in bone provides crucial information on how these factors are influencing bone quantity and quality. Synchrotron radiation micro-computed tomography (SRμCT) was first used to assess bone structure at the end of the 1990's. One of the main advantages of the technique is that it enables accurate three-dimensional (3D), non-destructive quantification of structure while traditional histomorphometry on histological sections is inherantly destructive to the sample and two-dimensional (2D). Additionally, SRμCT uses monochromatic, high-flux X-ray beams to provide high-resolution and high-contrast imaging of bone samples. This allows the quantification of small microstructural features (e.g. osteocyte lacunae, canals, trabeculae, microcracks) and direct gray value compositional mapping (e.g. mineral quantification, cement lines) with greater speed and fidelity than lab-based micro-computed tomography. In this article, we review how SRμCT has been applied to bone research to elucidate the mechanisms by which bone aging, disease, and other factors affect bone fragility and resistance to fracture.

60 APPLIED LIFE SCIENCES↗

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

36 MATERIALS SCIENCE↗