The Potential for Material Property Characterization Using Physics-Informed Neural Networks and Ultrasonic Wave Data-Reference-Cited by-同舟云学术

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The Potential for Material Property Characterization Using Physics-Informed Neural Networks and Ultrasonic Wave Data

Published:2024-05-05 Issue:4 Volume:35 Page:211-231
ISSN:0934-9847
Container-title:Research in Nondestructive Evaluation
language:en
Short-container-title:Research in Nondestructive Evaluation

Author:

Lee Sangmin¹,Popovics John S.¹

Affiliation:

1. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09349847.2024.2350398

Reference55 articles.

1. S. Mindess, J. F. Young, and D. Darwin, Concrete (Hoboken, New Jersey, Prentice Hall, 2003).

2. T. J. Bruno et al. ASM Handbook, Volume 10-Materials Characterization (ASM International, Materials Park, OH, 2019).

3. Composite Materials

4. ASTM C805/C805M-18 Test method for rebound number of hardened concrete ASTM International 2018.

5. ASTM C1383-15, Test Method for Measuring the P-Wave Speed and the Thickness of Concrete Plates Using the Impact-Echo Method (West Conshohocken, Pennsylvania, ASTM International, 2015).

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