scholarly journals Fatigue Life of RC Bridge Decks Affected by Non-Uniformly Dispersed Stagnant Water

2019 ◽  
Vol 9 (3) ◽  
pp. 607 ◽  
Author(s):  
Eissa Fathalla ◽  
Yasushi Tanaka ◽  
Koichi Maekawa
Keyword(s):  
Fatigue Life ◽  
Great Influence ◽  
Severe Case ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Stagnant Water ◽  
Fatigue Lifetime ◽  
Testing Technology ◽  
Non Destructive ◽  
Remaining Fatigue Life

Stagnant water on reinforced concrete (RC) decks reduces their life significantly compared to the case of dry states. Fully submerged states have been investigated as the most severe case, which is however rarely experienced in reality. Currently, it is possible to simulate concrete–water interactions for lifetime prediction of RC decks. In this study, fatigue lifetime is systematically computed for various locations of stagnant water at the upper layer of RC decks. It is found that the patterns of wet and dry areas have a great influence on the remaining fatigue life even though the same magnitude of cracking develops. Then, a hazard map for the wetting locations with regard to the remaining fatigue life is presented based on the systematically arranged simulation. Finally, a nonlinear correlation is introduced for fatigue life prediction based upon site inspected wetting locations, which can be detected by non-destructive testing technology.

scholarly journals Research on road engineering detection method based on GPR technology

2020 ◽  
Vol 165 ◽  
pp. 04014
Author(s):  
Liu Tao ◽  
Li Jia ◽  
Zheng Zhi-gang ◽  
Huang Zhi ◽  
Jiang Jian ◽  
...  
Keyword(s):  
Parameter Setting ◽  
Non Destructive Testing ◽  
Practical Application ◽  
Distribution Law ◽  
Destructive Testing ◽  
Road Engineering ◽  
The Road ◽  
Image Optimization ◽  
Testing Technology ◽  
Non Destructive

GPR is an effective non-destructive testing technology. This paper introduces its composition principle and operation method, explains the process of parameter setting and image optimization, obtains the dielectric constant of 10000 points, compares it with the density, and then obtains the uniformity distribution law of construction quality based on image. By calibrating the thickness of the road surface, the effective detection of road diseases can be realized, and the theoretical basis and practical application conditions of GPR technology can be clarified.

An Attempt at the Detection of a Flaw Using the Inverse Problem Solution of Impedance Imaging

1991 ◽  
Author(s):  
M. A. Hussain ◽  
M. McKee ◽  
J. Frankel
Keyword(s):  
Electrical Current ◽  
Problem Solution ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Impedance Imaging ◽  
Testing Technology ◽  
Connected Body ◽  
Simply Connected ◽  
Non Destructive ◽  
Single Flaw

Abstract In this paper we present some preliminary numerical simulations which allow us to predict a single flaw in a simply connected body. The purpose of this investigation was to detect flaws and cracks of engineering components using the method of electrical current computed tomography (ECCT), which is used in non-destructive testing technology. As in the previous paper, we have utilized the network analogy to detect a single flaw anywhere in the object. For detection of multiple flaws, the analysis has to be refined to give consistent results.

scholarly journals Pattern Deep Region Learning for Crack Detection in Thermography Diagnosis System

Metals ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 612 ◽  
Author(s):  
Jue Hu ◽  
Weiping Xu ◽  
Bin Gao ◽  
Gui Tian ◽  
Yizhe Wang ◽  
...  
Keyword(s):  
Crack Detection ◽  
Pattern Mining ◽  
Learning Method ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Pulsed Thermography ◽  
Testing Technology ◽  
Deep Region ◽  
Detection And Localization ◽  
Non Destructive

Eddy Current Pulsed Thermography is a crucial non-destructive testing technology which has a rapidly increasing range of applications for crack detection on metals. Although the unsupervised learning method has been widely adopted in thermal sequences processing, the research on supervised learning in crack detection remains unexplored. In this paper, we propose an end-to-end pattern, deep region learning structure to achieve precise crack detection and localization. The proposed structure integrates both time and spatial pattern mining for crack information with a deep region convolution neural network. Experiments on both artificial and natural cracks have shown attractive performance and verified the efficacy of the proposed structure.

Terahertz Non-destructive Testing Technology for Glass Fiber Honeycomb Composites

2019 ◽  
Vol 48 (2) ◽  
pp. 212002 ◽  
Author(s):  
张丹丹 ZHANG Dan-dan ◽  
任姣姣 REN Jiao-jiao ◽  
李丽娟 LI Li-juan ◽  
乔晓利 QIAO Xiao-li ◽  
顾健 GU Jian
Keyword(s):  
Glass Fiber ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Testing Technology ◽  
Non Destructive

scholarly journals Study on joint detection of fabricated concrete shear wall based on percussion method

2019 ◽  
Vol 277 ◽  
pp. 03019
Author(s):  
Bo Song ◽  
Jian Li ◽  
Man sheng Wang
Keyword(s):  
Great Influence ◽  
Peak Frequency ◽  
Joint Detection ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Knock Detection ◽  
The Time Domain ◽  
The Impact ◽  
Non Destructive ◽  
Peak Value

The knock detection method is one of the non-destructive testing methods for assembly prefabricated components. The knocker is used to knock on the concrete prefabricated components to be tested. The internal conditions of the tested components can be judged by analyzing the time-domain and frequency-domain diagrams of the knocker. In this paper, the impact of the change of the knock point on the detection is studied by using the knock detection experiment. It is found that the location of the knock point has a great influence on the detection. With the change of the position of the knock point, the peak frequency in the spectrum obtained by the detection changes correspondingly. According to the frequency information corresponding to the peak value in the spectrum, the depth of the void to the knock surface can be calculated.

scholarly journals Non-destructive testing technology for raw eggs freshness: a review

2020 ◽  
Vol 2 (6) ◽  
Author(s):  
Liang Qi ◽  
Mao-cheng Zhao ◽  
Zhong Li ◽  
De-hong Shen ◽  
Jun Lu
Keyword(s):  
Non Destructive Testing ◽  
Destructive Testing ◽  
Testing Technology ◽  
Non Destructive

Progress of laser-generated ultrasonic non-destructive testing technology

2011 ◽  
Author(s):  
Shi-tu Luo ◽  
Xiang-lin Tan ◽  
Meng-chun Pan ◽  
Cheng-guang Fan
Keyword(s):  
Non Destructive Testing ◽  
Destructive Testing ◽  
Testing Technology ◽  
Non Destructive

Sensibility Analysis of the Parameters Affecting Infrared Thermal Images for the Evaluation of Building Pathologies

2014 ◽  
Vol 353 ◽  
pp. 23-27
Author(s):  
E. Barreira ◽  
S.S. de Freitas ◽  
V.P. de Freitas ◽  
João M.P.Q. Delgado
Keyword(s):  
Infrared Thermography ◽  
Non Destructive Testing ◽  
Infrared Images ◽  
Destructive Testing ◽  
Testing Technology ◽  
Sensibility Analysis ◽  
Infrared Thermal Images ◽  
Building Physics ◽  
Non Destructive ◽  
Do So

Infrared thermography is a non destructive testing technology that has been applied to detect buildings pathologies for some decades. The thermograms are affected by several parameters and it is crucial to fully understand them in order to correctly interpret the temperature readings. The infrared radiation is affected by the radiation emitted by the surface and the radiation reflected and emitted by the surroundings. Therefore there are two kinds of parameters that affect the infrared images: parameters connected to the properties of the material itself and parameters connected with the environmental conditions. In this paper we present a sensibility study of the main parameters involved with infrared thermography evaluations to detect building pathologies. To do so, some simple experiments were carried out at the Building Physics Laboratory (LFC) of the Engineering Faculty of Porto University (FEUP). The sensibility study was performed with LFC’s equipment to evaluate how measurements are influenced by emissivity, reflections, absorptance and the meteorological conditions.

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