scholarly journals Evaluation of Impact Damage in Composite Structures Using Ultrasonic Testing

2018 ◽  
Vol 2018 (10) ◽  
pp. 82-92 ◽  
Author(s):  
Angelika Wronkowicz-Katunin ◽  
Krzysztof Dragan
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Impact Energy ◽  
Ultrasonic Testing ◽  
Composite Structures ◽  
Impact Damage ◽  
Visual Observation ◽  
Effective Evaluation ◽  
Wide Range ◽  
Variable Impact

Abstract Barely visible impact damage is one of the problems commonly occurring in composite elements during an aircraft operation. The authors described the mechanisms of impact damage formation and propagation in composite structures. The paper presents a performed analysis of an influence of impact parameters on the resulting damage, i.e. its detectability by means of visual observation as well as its extent determined based on ultrasonic tests results. The tests were conducted on the CFRP specimens with a wide range of impact damage cases obtained with combinations of variable impact energy and shapes of impactors. Additionally, an algorithm based on image processing and image analysis methods is proposed for the purpose of the effective evaluation of the ultrasonic data obtained.

Impact damage in composite aircraft structures-experimental testing and numerical simulation

1998 ◽  
Vol 212 (4) ◽  
pp. 245-259 ◽  
Author(s):  
X Zhang
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Composite Structures ◽  
Impact Damage ◽  
Experimental Testing ◽  
Laminated Composite ◽  
Element Model ◽  
Design Tool ◽  
Low Velocity Impact ◽  
Wide Range

This paper describes a strategy for predicting internal damage in a laminated composite structure, when subjected to low-velocity impact. The aim was to obtain a better understanding of and cure for the notorious reduction in strength of aircraft compression panels when they suffered barely visible impact damage (BVID). A finite element model is presented which incorporates the non-linear behaviour due to gross deformation, interlaminar delamination and in-plane fibre and matrix failure. The strategy is validated by impact tests for a wide range of carbon/epoxy composite structures ranging from small stiff plates to realistic aircraft compression panels. It is demonstrated that the finite element model is capable of predicting impact damage in laminated composite structures and thus could be used as a design tool.

scholarly journals Impact Damage Evaluation in Composite Structures Based on Fusion of Results of Ultrasonic Testing and X-ray Computed Tomography

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1867 ◽  
Author(s):  
Andrzej Katunin ◽  
Angelika Wronkowicz-Katunin ◽  
Krzysztof Dragan
Keyword(s):  
Computed Tomography ◽  
Ultrasonic Testing ◽  
Composite Structures ◽  
Structural Damage ◽  
Impact Damage ◽  
Estimation Accuracy ◽  
Fracture Mechanisms ◽  
Internal Damage ◽  
X Ray ◽  
X Ray Computed

Barely visible impact damage (BVID) is one of the most dangerous types of structural damage in composites, since in most practical cases the application of advanced non-destructive testing (NDT) methods is required to detect and identify it. Due to its character of propagation, there are minor signs of structural damage on a surface, while the internal damage can be broad and complex both in the point of view of fracture mechanisms and resulting geometry of damage. The most common NDT method applied e.g., in aircraft inspections is ultrasonic testing (UT), which enables effective damage detection and localization in various environments. However, the results of such inspections are usually misestimated with respect to the true damage extent, and the quantitative analysis is biased by an error. In order to determine the estimation error a comparative analysis was performed on NDT results obtained for artificially damaged carbon fiber-reinforced composite structures using two UT methods and X-ray computed tomography (CT). The latter method was considered here as the reference one, since it gives the best spatial resolution and estimation accuracy of internal damage among the available NDT methods. Fusing the NDT results for a set of pre-damaged composite structures with various energy values of impact and various types of impactor tips applied for introducing damage, the evaluation of estimation accuracy of UT was possible. The performed analysis allowed for evaluation of relations between UT and X-ray CT NDT results and for proposal of a correcting factor for UT results for BVID in the analyzed composite structures.

Investigation of Composite Materials Impact Damage by a Computer Tomography

2019 ◽  
Vol 822 ◽  
pp. 362-370
Author(s):  
O.N. Bezzametnov ◽  
Victor I. Mitryaykin ◽  
Valentin I. Khaliulin ◽  
E.O. Statsenko
Keyword(s):  
Computed Tomography ◽  
Composite Materials ◽  
Impact Energy ◽  
Computer Tomography ◽  
Ultrasonic Testing ◽  
Impact Damage ◽  
Material Damage ◽  
Initiation Energy ◽  
System A ◽  
The Impact

In this paper, a complex study of composite materials of different nature for the presence of internal defects after the application of impact damage was carried out. The dependence of the initiation energy on material damage from the magnitude of the impact energy is obtained. The areas of sample bundles were investigated by ultrasonic testing (UT). The structure of samples from composite materials was monitored using an industrial microtomography system. A technique was developed that allows highly accurate determining the size of internal sample defects by means of computed tomography (CT).

The Probabilistic Compliance Methodology for Damage Tolerance Design of Thicker Composite Structure

2011 ◽  
Vol 239-242 ◽  
pp. 872-875
Author(s):  
Tian Chun Zou ◽  
Peng Hao ◽  
Jia Rui Zhang ◽  
Zhen Yu Feng
Keyword(s):  
Impact Energy ◽  
Composite Structure ◽  
Composite Laminates ◽  
Composite Structures ◽  
Damage Tolerance ◽  
Impact Damage ◽  
Tolerance Design ◽  
Research Results ◽  
Certification Requirements

In this paper, the probabilistic compliance methodology for damage tolerance design of thicker composite structures were investigated, and the research results show that for the composite laminates withstanding impact energy below 90J, if it cannot produce barely visible impact damage (BVID), then using the probabilistic methodology can meet certification requirements of damage tolerance.

Recent Applications of High Resolution Electron Microscopy to Crystalline Arrays of Virus Particles

1978 ◽  
Vol 36 (3) ◽  
pp. 470-482 ◽  
Author(s):  
R.W. Horne
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Analytical Techniques ◽  
Staining Technique ◽  
High Resolution Electron Microscopy ◽  
Optical Diffraction ◽  
Full Potential ◽  
Virus Particles ◽  
Resolution Electron ◽  
Wide Range

The technique of surrounding virus particles with a neutralised electron dense stain was described at the Fourth International Congress on Electron Microscopy, Berlin 1958 (see Home & Brenner, 1960, p. 625). For many years the negative staining technique in one form or another, has been applied to a wide range of biological materials. However, the full potential of the method has only recently been explored following the development and applications of optical diffraction and computer image analytical techniques to electron micrographs (cf. De Hosier & Klug, 1968; Markham 1968; Crowther et al., 1970; Home & Markham, 1973; Klug & Berger, 1974; Crowther & Klug, 1975). These image processing procedures have allowed a more precise and quantitative approach to be made concerning the interpretation, measurement and reconstruction of repeating features in certain biological systems.

A Color Coded STEM/SEM Image Storage System

1981 ◽  
Vol 39 ◽  
pp. 272-273
Author(s):  
Y. Kokubo ◽  
W. H. Hardy ◽  
J. Dance ◽  
K. Jones
Keyword(s):  
Image Processing ◽  
Electron Beam ◽  
Storage System ◽  
Particle Analysis ◽  
Specific Information ◽  
X Rays ◽  
Sem Image ◽  
Backscattered Electrons ◽  
Wide Range ◽  
Scanning Electron

A color coded digital image processing is accomplished by using JEM100CX TEM SCAN and ORTEC’s LSI-11 computer based multi-channel analyzer (EEDS-II-System III) for image analysis and display. Color coding of the recorded image enables enhanced visualization of the image using mathematical techniques such as compression, gray scale expansion, gamma-processing, filtering, etc., without subjecting the sample to further electron beam irradiation once images have been stored in the memory.The powerful combination between a scanning electron microscope and computer is starting to be widely used 1) - 4) for the purpose of image processing and particle analysis. Especially, in scanning electron microscopy it is possible to get all information resulting from the interactions between the electron beam and specimen materials, by using different detectors for signals such as secondary electron, backscattered electrons, elastic scattered electrons, inelastic scattered electrons, un-scattered electrons, X-rays, etc., each of which contains specific information arising from their physical origin, study of a wide range of effects becomes possible.

scholarly journals Defects and uncertainties of adhesively bonded composite joints

2021 ◽  
Vol 3 (9) ◽  
Author(s):  
Sadik Omairey ◽  
Nithin Jayasree ◽  
Mihalis Kazilas
Keyword(s):  
Composite Materials ◽  
Composite Structures ◽  
Production Efficiency ◽  
Adhesive Bonding ◽  
Detection Methods ◽  
Bonded Joints ◽  
Adhesively Bonded ◽  
Adhesively Bonded Joints ◽  
Wide Range ◽  
Bonded Composite

AbstractThe increasing use of fibre reinforced polymer composite materials in a wide range of applications increases the use of similar and dissimilar joints. Traditional joining methods such as welding, mechanical fastening and riveting are challenging in composites due to their material properties, heterogeneous nature, and layup configuration. Adhesive bonding allows flexibility in materials selection and offers improved production efficiency from product design and manufacture to final assembly, enabling cost reduction. However, the performance of adhesively bonded composite structures cannot be fully verified by inspection and testing due to the unforeseen nature of defects and manufacturing uncertainties presented in this joining method. These uncertainties can manifest as kissing bonds, porosity and voids in the adhesive. As a result, the use of adhesively bonded joints is often constrained by conservative certification requirements, limiting the potential of composite materials in weight reduction, cost-saving, and performance. There is a need to identify these uncertainties and understand their effect when designing these adhesively bonded joints. This article aims to report and categorise these uncertainties, offering the reader a reliable and inclusive source to conduct further research, such as the development of probabilistic reliability-based design optimisation, sensitivity analysis, defect detection methods and process development.

Somatic cell count in buffalo milk using fuzzy clustering and image processing techniques

2021 ◽  
Vol 88 (1) ◽  
pp. 69-72
Author(s):  
Aline Silva Ramos ◽  
Cristiano Hora Fontes ◽  
Adonias Magdiel Ferreira ◽  
Camila Costa Baccili ◽  
Karen Nascimento da Silva ◽  
...  
Keyword(s):  
Image Processing ◽  
Somatic Cell ◽  
Cell Count ◽  
Fuzzy Clustering ◽  
Somatic Cell Count ◽  
Visual Observation ◽  
Buffalo Milk ◽  
Image Processing Techniques ◽  
Fuzzy Clustering Method ◽  
Processing Techniques

AbstractThis research communication presents an automatic method for the counting of somatic cells in buffalo milk, which includes the application of a fuzzy clustering method and image processing techniques (somatic cell count with fuzzy clustering and image processing|, SCCFCI). Somatic cell count (SCC) in milk is the main biomarker for assessing milk quality and it is traditionally performed by exhaustive methods consisting of the visual observation of cells in milk smears through a microscope, which generates uncertainties associated with human interpretation. Unlike other similar works, the proposed method applies the Fuzzy C-Means (FCM) method as a preprocessing step in order to separate the images (objects) of the cells into clusters according to the color intensity. This contributes signficantly to the performance of the subsequent processing steps (thresholding, segmentation and recognition/identification). Two methods of thresholding were evaluated and the Watershed Transform was used for the identification and separation of nearby cells. A detailed statistical analysis of the results showed that the SCCFCI method is able to provide results which are consistent with those obtained by conventional counting. This method therefore represents a viable alternative for quality control in buffalo milk production.

scholarly journals The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics

2021 ◽  
Vol 7 (8) ◽  
pp. 124
Author(s):  
Kostas Marias
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Medical Image ◽  
Biomarker Discovery ◽  
Medical Image Processing ◽  
Machine Learning Techniques ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
Precision Oncology

The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer.

scholarly journals Image Segmentation and Object-Based Image Analysis for Environmental Monitoring: Recent Areas of Interest, Researchers’ Views on the Future Priorities

2020 ◽  
Vol 12 (11) ◽  
pp. 1772
Author(s):  
Brian Alan Johnson ◽  
Lei Ma
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Image Segmentation ◽  
Online Survey ◽  
Accuracy Assessment ◽  
Learning Approaches ◽  
Special Issue ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Wide Range

Image segmentation and geographic object-based image analysis (GEOBIA) were proposed around the turn of the century as a means to analyze high-spatial-resolution remote sensing images. Since then, object-based approaches have been used to analyze a wide range of images for numerous applications. In this Editorial, we present some highlights of image segmentation and GEOBIA research from the last two years (2018–2019), including a Special Issue published in the journal Remote Sensing. As a final contribution of this special issue, we have shared the views of 45 other researchers (corresponding authors of published papers on GEOBIA in 2018–2019) on the current state and future priorities of this field, gathered through an online survey. Most researchers surveyed acknowledged that image segmentation/GEOBIA approaches have achieved a high level of maturity, although the need for more free user-friendly software and tools, further automation, better integration with new machine-learning approaches (including deep learning), and more suitable accuracy assessment methods was frequently pointed out.

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