Defect extraction and quantitative analysis of composite materials based on infrared detection

2020 ◽  
Author(s):  
Bingwei Liu ◽  
Mian Zhong ◽  
Hangjun Fu ◽  
Bin Zhou ◽  
Hucheng Qiu ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Composite Materials ◽  
Infrared Detection ◽  
Defect Extraction

scholarly journals Numerical computation of lightning transfer functions for layered, anisotropically conducting shielding structures by the method of moments

2016 ◽  
Vol 14 ◽  
pp. 107-114
Author(s):  
Fabian Happ ◽  
Heinz-D. Brüns ◽  
Gazmend Mavraj ◽  
Frank Gronwald
Keyword(s):  
Quantitative Analysis ◽  
Composite Materials ◽  
Method Of Moments ◽  
Transfer Functions ◽  
Aircraft Design ◽  
Equivalent Conductivity ◽  
Conducting Composite ◽  
Lightning Channel ◽  
Layer Technique ◽  
Airplane Fuselage

Abstract. A formalism for the computation of lightning transfer functions by the method of moments, which involves shielding structures that may consist of layered, anisotropically conducting composite materials, is presented in this contribution. The composite materials, being of a type that is widely used in space- and aircraft design, are electrically characterized by an equivalent conductivity. As basis for the quantitative analysis the method of moments is used where shielding surfaces can be treated by a thin layer technique which utilizes analytical solutions inside the layer. Also the effect of an extended lightning channel can be taken into account. The method is applied to geometries that resemble an actual airplane fuselage.

Mechanical and thermal properties of polymer micro- and nanocomposites

2011 ◽  
Vol 31 (2-3) ◽  
Author(s):  
Stephan J. Picken ◽  
Alexander V. Korobko ◽  
Eduardo Mendes ◽  
Ben Norder ◽  
Veronika V. Makarova ◽  
...  
Keyword(s):  
Experimental Data ◽  
Thermal Conductivity ◽  
Thermal Properties ◽  
Quantitative Analysis ◽  
Composite Materials ◽  
Shape Factor ◽  
Tensile Modulus ◽  
Particle Aggregation ◽  
Mechanical And Thermal Properties ◽  
Single Model

Abstract We have analyzed the thermal conductivity and the tensile modulus of composite materials within the framework of the Halpin-Tsai and Lewis-Nielsen models. The parameter linking thermal conductivity and tensile modulus together is the shape factor of the (nano)filler. Model analysis based on experimental data shows that particle aggregation into a weak mechanical network may be required to achieve good correlation between thermal conductivity and the Young’s modulus when analyzing the data within the framework of a single model and requiring the same value of the shape factor. We believe this approach will make quantitative analysis of nanocomposite thermal properties possible.

The Quantitative Analysis of Composite Materials by the RIETVELD Method with Texture Correction

2002 ◽  
Vol 408-412 ◽  
pp. 215-220 ◽  
Author(s):  
Jin Ho Bae ◽  
Gyun Heo ◽  
Seung Taik Oh ◽  
Eun Joo Shin ◽  
Baek Seok Seong ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Composite Materials ◽  
Rietveld Method

Comparative Microstructures of Ion Milled and Electrochemically Thinned Composite Materials

1974 ◽  
Vol 32 ◽  
pp. 546-547
Author(s):  
R.R. Russell
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Composite Materials ◽  
Great Difficulty ◽  
Ion Milling ◽  
Transmission Electron ◽  
Ion Damage ◽  
Intermetallic Composite

Transmission electron microscopy of metallic/intermetallic composite materials is most challenging since the microscopist typically has great difficulty preparing specimens with uniform electron thin areas in adjacent phases. The application of ion milling for thinning foils from such materials has been quite effective. Although composite specimens prepared by ion milling have yielded much microstructural information, this technique has some inherent drawbacks such as the possible generation of ion damage near sample surfaces.

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

Quantification of Silica Uptake by Alveolar Macrophages - An Emperical Scanning Electron Microprobe Method

1982 ◽  
Vol 40 ◽  
pp. 332-333
Author(s):  
V. V. Damiano ◽  
R. P. Daniele ◽  
H. T. Tucker ◽  
J. H. Dauber
Keyword(s):  
Quantitative Analysis ◽  
Alveolar Macrophages ◽  
Bulk Sample ◽  
Silica Particles ◽  
Empirical Method ◽  
Phagocytic Cells ◽  
Calibration Standards ◽  
X Ray ◽  
Accurate Quantitative Analysis ◽  
Scanning Electron

An important example of intracellular particles is encountered in silicosis where alveolar macrophages ingest inspired silica particles. The quantitation of the silica uptake by these cells may be a potentially useful method for monitoring silica exposure. Accurate quantitative analysis of ingested silica by phagocytic cells is difficult because the particles are frequently small, irregularly shaped and cannot be visualized within the cells. Semiquantitative methods which make use of particles of known size, shape and composition as calibration standards may be the most direct and simplest approach to undertake. The present paper describes an empirical method in which glass microspheres were used as a model to show how the ratio of the silicon Kα peak X-ray intensity from the microspheres to that of a bulk sample of the same composition correlated to the mass of the microsphere contained within the cell. Irregular shaped silica particles were also analyzed and a calibration curve was generated from these data.

Lateral resolution of the electron microbeam analysis

1978 ◽  
Vol 36 (1) ◽  
pp. 542-543
Author(s):  
H.J. Dudek
Keyword(s):  
Quantitative Analysis ◽  
Depth Resolution ◽  
Lateral Resolution ◽  
Cylindrical Particle ◽  
Correction Procedure ◽  
X Ray ◽  
Element Concentrations ◽  
Microbeam Analysis ◽  
The Matrix

The chemical inhomogenities in modern materials such as fibers, phases and inclusions, often have diameters in the region of one micrometer. Using electron microbeam analysis for the determination of the element concentrations one has to know the smallest possible diameter of such regions for a given accuracy of the quantitative analysis.In th is paper the correction procedure for the quantitative electron microbeam analysis is extended to a spacial problem to determine the smallest possible measurements of a cylindrical particle P of high D (depth resolution) and diameter L (lateral resolution) embeded in a matrix M and which has to be analysed quantitative with the accuracy q. The mathematical accounts lead to the following form of the characteristic x-ray intens ity of the element i of a particle P embeded in the matrix M in relation to the intensity of a standard S

Transmission electron microscopy of composite materials

1988 ◽  
Vol 46 ◽  
pp. 1012-1015
Author(s):  
K.P.D. Lagerlof
Keyword(s):  
Composite Materials ◽  
Physical Properties ◽  
Structural Defects ◽  
Structural Composites ◽  
Multiphase Materials ◽  
Structural Reinforcement ◽  
Transmission Electron ◽  
Reinforced Fiber ◽  
Particulate Reinforced Composites ◽  
Definition Of

Although most materials contain more than one phase, and thus are multiphase materials, the definition of composite materials is commonly used to describe those materials containing more than one phase deliberately added to obtain certain desired physical properties. Composite materials are often classified according to their application, i.e. structural composites and electronic composites, but may also be classified according to the type of compounds making up the composite, i.e. metal/ceramic, ceramic/ceramie and metal/semiconductor composites. For structural composites it is also common to refer to the type of structural reinforcement; whisker-reinforced, fiber-reinforced, or particulate reinforced composites [1-4].For all types of composite materials, it is of fundamental importance to understand the relationship between the microstructure and the observed physical properties, and it is therefore vital to properly characterize the microstructure. The interfaces separating the different phases comprising the composite are of particular interest to understand. In structural composites the interface is often the weakest part, where fracture will nucleate, and in electronic composites structural defects at or near the interface will affect the critical electronic properties.

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

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