scholarly journals Estudio experimental del comportamiento a compresión de hormigones autocompactantes reforzados con fibras de acero = Experimental study of performance self-compacting concrete reinforced with steel fibers

2015 ◽  
Vol 1 (2) ◽  
pp. 17
Author(s):  
J. L. Sánchez ◽  
A. Cobo ◽  
B. Díaz ◽  
I Mateos
Keyword(s):  
High Performance ◽  
Steel Fibers ◽  
Non Destructive Testing ◽  
Compression Tests ◽  
Self Compacting Concrete ◽  
Destructive Testing ◽  
Speed Of Ultrasound ◽  
The Difference ◽  
Non Destructive ◽  
Non Destructive Techniques

Resumen El hormigón autocompactante reforzado con fibras de acero presenta simultáneamente las ventajas de los hormigones autocompactantes y de los reforzados con fibras. Se consigue un material de altas prestaciones en cuanto a su colocación en obra, tenacidad y ductilidad. En este trabajo se ha estudiado el comportamiento mecánico de un hormigón autocompactante reforzado con fibras de acero. Se han realizado ensayos a compresión a distintas edades, así como ensayos no destructivos (medida de la velocidad de ultrasonidos e índice esclerométrico). Los resultados muestran la variación de la respuesta del hormigón con el tiempo, la diferencia existente con los hormigones tradicionales y la viabilidad del empleo de técnicas no destructivas para el control de este tipo de hormigones.AbstractSelf-compacting steel fibers reinforced concrete simultaneously has the advantages of self-compacting concrete and reinforced with fibers. A material of high performance in their laying on site, toughness and ductility is achieved. This paper has studied the mechanical behavior of a self-compacting concrete reinforced with steel fibers. Have been made compression tests, as well as non-destructive testing (measuring the speed of ultrasound and sclerometer test). The results show the variation of the response of concrete with time, the difference with the traditional concrete and the feasibility of using non-destructive techniques for controlling this type of concrete.

Development of a Portable near Infrared Sugar-Measuring Instrument

2002 ◽  
Vol 10 (1) ◽  
pp. 77-83 ◽  
Author(s):  
Tsuyoshi Temma ◽  
Kenkoh Hanamatsu ◽  
Fujitoshi Shinoki
Keyword(s):  
Fruits And Vegetables ◽  
Near Infrared ◽  
Sugar Content ◽  
Processing Unit ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
General Chemical ◽  
The Difference ◽  
Brix Value ◽  
Non Destructive

Industries from agriculture to petrochemistry have found near infrared (NIR) spectroscopic analysis useful for quality control and quantitative analysis of materials and products. The general chemical, polymer chemistry, petrochemistry, agriculture, food and textile industries are currently using NIR spectroscopic methods for analysis. In this study, we developed a portable NIR instrument for the non-destructive testing of products in the field, which has resulted in an instrument for commercial sale and use. The instrument consists of a light source, a polychromator, a wave-guide (optical fibre bundle) and a data processing unit. We tested the performance of the portable NIR instrument in determining the sugar content of apples. The performance was also examined at full width at half maximum ( FWHM) of the spectrum. The difference in the absorption of quartz and plastic fibres in the NIR was also compared. The sugar content measurements were confirmed by a high correlation to the Brix value of the apples, and the calibration showed the accuracy of the instrument in practice. Application of this instrument to fruits and vegetables other than apples was explored.

Data augmentation by CycleGAN-based extra-supervised for non-destructive testing

2021 ◽  
Author(s):  
Jiangshan Ai ◽  
Lulu Tian ◽  
Libing Bai ◽  
Jie Zhang
Keyword(s):  
High Performance ◽  
Field Data ◽  
Large Scale ◽  
Data Augmentation ◽  
Learning Method ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Deep Convolutional Neural Networks ◽  
X Ray ◽  
Non Destructive

Abstract Deep learning method is widely used in computer vision tasks with large scale annotated datasets. However, it is a big challenge to obtain such datasets in most directions of the vision based non-destructive testing (NDT) field. Data augmentation is proved as an efficient way in dealing with the lack of large-scale annotated datasets. In this paper, we propose CycleGAN-based extra-supervised (CycleGAN-ES) to generate synthetic NDT images, where the ES is used to ensure that the bidirectional mapping are learned for corresponding label and defect. Furthermore, we show the effectiveness of using the synthesized images to train deep convolutional neural networks (DCNN) for defects recognition. In the experiments, we extract numbers of X-ray welding images with both defect and no-defect from the published GDXray dataset, CycleGAN-ES are used to generate the synthetic defect images based on a small number of extracted defect images and manually drawn labels which are used as a content guide. For quality verification of the synthesized defect images, we use a high-performance classifier pre-trained using big dataset to recognize the synthetic defects and show comparability of the performances of classifiers trained using synthetic defects and real defects respectively. To present the effectiveness of using the synthesized defects as an augmentation method, we train and evaluate the performances of DCNN for defects recognition with or without the synthesized defects.

The Behavior of Non-Destructive Test for Different Grade of Concrete

2020 ◽  
Vol 12 (9) ◽  
Author(s):  
Mustaqqim Abdul Rahim ◽  
◽  
Shahiron Shahidan ◽  
Lee Choon Onn ◽  
Nur Amira Afiza Saiful Bahari ◽  
...  
Keyword(s):  
Target Strength ◽  
Non Destructive Testing ◽  
Compression Tests ◽  
Destructive Testing ◽  
Rebound Hammer ◽  
Testing Method ◽  
General Series ◽  
Rebound Number ◽  
Water Curing ◽  
Non Destructive

Rebound hammer tests are generally preferred as a non-destructive testing method as compared to destructive testing methods such as compression tests. In this study, a general series of rebound hammer tests and destructive tests were carried on in a heavy concrete laboratory. A set of concrete cubes measuring 100 x 100 x 100 mm were cast and subjected to water curing for 7, 14 and 28 days to obtain the cube strength and rebound number. Three grades of concrete, namely M20, M25 and M30 were used in this experiment. At 28 days, the minimum target strength should be 30 MPa. The rebound hammer tests were conducted before the compression tests. The data obtained for each test was evaluated and tabulated in the findings of this study. It was found that the variation between predicted strength and experimental strength for the rebound hammer test was 0.18%. This indicates that the rebound hammer test is able to predict strength with acceptable accuracy.

Static and Dynamic Backcalculation Analyses of an Inverted Pavement Structure

2013 ◽  
Vol 723 ◽  
pp. 196-203 ◽  
Author(s):  
James Maina ◽  
Wynand JvdM Steyn ◽  
Emile B. van Wyk ◽  
Frans le Roux
Keyword(s):  
South African ◽  
Maintenance Strategy ◽  
Falling Weight Deflectometer ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Back Calculation ◽  
The Difference ◽  
Falling Weight ◽  
Non Destructive ◽  
Crucial Part

A crucial part of any maintenance strategy is an intricate understanding of the material characteristics of the pavement, so that the current level of damage may be accurately assessed and an appropriate plan implemented. Advances in the precision to which these parameters can be determined, as well as improvements in how these results are interpreted under varying conditions of measurement and analysis, are essential in the effective execution of a maintenance strategy. Results from Falling Weight Deflectometer (FWD), which is a Non-Destructive Testing (NDT) device, can be used to predict elastic modulus of any layer by comparing measured deflection data to calculated values through an iterative process referred to as back-calculation. This paper presents a comparison between static and dynamic back-calculation procedures, specifically with regard to typical South African inverted pavements. The analysis indicates a dynamic analysis provides results of greater accuracy than a static analysis, although the effect of the difference requires further investigation.

Evaluation of Railway Rails with Non-Destructive Techniques

2014 ◽  
Vol 605 ◽  
pp. 641-644
Author(s):  
Anastasia Karahaliou
Keyword(s):  
Stress State ◽  
Barkhausen Noise ◽  
Non Destructive Testing ◽  
Magnetic Barkhausen Noise ◽  
Testing Methods ◽  
Destructive Testing ◽  
Residual Stress State ◽  
Non Destructive ◽  
Non Destructive Techniques ◽  
Scanning Electron

Non-destructive testing methods, such as Magnetic Barkhausen Noise method, are widely used on railways for examining the stress state of running railway rails. Detailed information about the morphology of the microstructure features of the rail surface is derived by Scanning Electron Microscopy. Phase composition, hardness and residual stress state of the rails are determined by MBN signal.

Development and Application of Neutron Imaging Technique at China Advanced Research Reactor

2016 ◽  
Vol 850 ◽  
pp. 153-160 ◽  
Author(s):  
Lin Feng He ◽  
Song Bai Han ◽  
Guo Hai Wei ◽  
Mei Mei Wu ◽  
Yu Wang ◽  
...  
Keyword(s):  
Research Reactor ◽  
Neutron Imaging ◽  
Non Destructive Testing ◽  
Transmission Characteristics ◽  
Destructive Testing ◽  
Two Phase ◽  
Penetration Length ◽  
X Ray Imaging ◽  
The Difference ◽  
Non Destructive

Neutron imaging (NI) has unique feature compared with X-ray imaging for the difference of the transmission characteristics through matters. The sensitivity to light elements, especially hydrogen, and the large penetration length through metals give it special advantages. NI has become a particularly useful universal technique for scientific and applied studies in various research disciplines. This article reviews the recent development of neutron imaging at China Advanced Research Reactor (CARR), including the instrumentations for indirect and real-time imaging and their application for non-destructive testing of nuclear fuel rod, two-phase flow, fuel cell, rock and concrete, etc.

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