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Appl. Sci. 2018, 8(7), 1107; https://doi.org/10.3390/app8071107

Using Ultrasonic Pulse and Artificial Intelligence to Investigate the Thermal-Induced Damage Characteristics of Concrete

1
Department of Civil Engineering, National Taipei University of Technology, Taipei 10608, Taiwan
2
Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
3
Architecture and Building Research Institute, Ministry of the Interior, Taipei 23143, Taiwan
4
Department of Computer Science, National Chengchi University, Taipei 11605, Taiwan
*
Author to whom correspondence should be addressed.
Received: 30 May 2018 / Revised: 5 July 2018 / Accepted: 6 July 2018 / Published: 9 July 2018
(This article belongs to the Special Issue Selected Papers from the 2017 International Conference on Inventions)
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Abstract

Using the traditional assessment method considering single-input and single-output variables, the correlation between ignition loss and maximum temperature is usually used to evaluate the fire-damage degree of concrete. To improve this method, multi-input and multi-output variables are examined in this study using a newly-developed experiment consisting of a thermo-induced damage test, ultrasonic pulse (UP) measurement technique, and uniaxial compressive test. The input variables include the designed strength, rate of heating, maximum temperature, and exposure time. The output variables include the stiffness, strength, toughness, and ratio of shear wave velocity to pressure wave velocity (Vs/Vp). Artificial intelligence (AI) is used to assess these variables. The test results show that the stiffness, strength, and toughness decreased with an increase in maximum temperature. The measured Vs/Vp has a high positive correlation with maximum temperature and the reduced ratio of stiffness, strength, and toughness. This correlation was also identified using AI analysis. The findings in this study suggest that the wave velocity ratio obtained using the UP technique can be applied to quantitatively evaluate thermal-induced damage in concrete. View Full-Text
Keywords: thermal-induced damage; fire disaster; ultrasonic pulse; wave-velocity ratio; artificial intelligence; WEKA thermal-induced damage; fire disaster; ultrasonic pulse; wave-velocity ratio; artificial intelligence; WEKA
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Chen, L.-H.; Chen, W.-C.; Chen, Y.-C.; Lin, H.-J.; Cai, C.-F.; Lei, M.-Y.; Wang, T.-C.; Hsu, K.-W. Using Ultrasonic Pulse and Artificial Intelligence to Investigate the Thermal-Induced Damage Characteristics of Concrete. Appl. Sci. 2018, 8, 1107.

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