Deep-Learning-Informed Design Scheme for Prediction of Interfacial Concrete Shear Strength

International Concrete Abstracts Portal

The International Concrete Abstracts Portal is an ACI led collaboration with leading technical organizations from within the international concrete industry and offers the most comprehensive collection of published concrete abstracts.

  


Title: Deep-Learning-Informed Design Scheme for Prediction of Interfacial Concrete Shear Strength

Author(s): Tarutal Ghosh Mondal, Nikkolas Edgmond, Lesley H. Sneed, and Genda Chen

Publication: Structural Journal

Volume: 122

Issue: 1

Appears on pages(s): 51-62

Keywords: deep learning; interfacial shear strength; learning-informed design; neural additive models; neural network; reinforced concrete; shear friction.

DOI: 10.14359/51743291

Date: 1/2/2025

Abstract:
Current design provisions pertaining to the shear transfer strength of concrete-to-concrete interfaces, including those of the AASHTO LRFD design specifications and ACI 318 Code, are based on limited physical test data from studies conducted decades ago. Since the development of these design provisions, many studies have been conducted to investigate additional parameters. In addition, modern concrete technology has expanded the range of materials available and often includes the use of high-strength concrete and high-strength reinforcing steel. Recent studies examined the applicability of current shear-friction design approaches to interfaces that comprise high-strength concrete and/or high-strength steel and identified a need for revision to the existing provisions. To this end, this study leveraged a comprehensive database of test results collected from the literature to propose a deep-learningbased predictive model for normalweight concrete-to-concrete interfacial shear strength. Additionally, a new computation scheme is proposed to estimate the nominal shear strength with a higher prediction accuracy than the existing AASHTO LRFD and ACI 318 design provisions.

Related References:

1. AASHTO, “AASHTO LRFD Bridge Design Specifications, 9th Edition,” American Association of State Highway and Transportation Officials, Washington, DC, 2020.

2. ACI Committee 318, “Building Code Requirements for Structural Concrete (ACI 318-19) and Commentary (ACI 318R-19) (Reapproved 2022),” American Concrete Institute, Farmington Hills, MI, 2019, 624 pp.

3. Kahn, L. F., and Mitchell, A. D., “Shear Friction Tests with High-Strength Concrete,” ACI Structural Journal, V. 99, No. 1, Jan.-Feb. 2002, pp. 98-103.

4. Hegger, J., and Görtz, S., “Nachträglich ergänzte Querschnitte mit horizontaler Fuge nach DIN 1045‐1,” Beton- und Stahlbetonbau, V. 98, No. 5, 2003, pp. 277-284. doi: 10.1002/best.200301450

5. Crane, C. K., “Shear and Shear Friction of Ultra-High Performance Concrete Bridge Girders,” PhD dissertation, Georgia Institute of Technology, Atlanta, GA, 2010.

6. Shaw, D. M., and Sneed, L. H., “Interface Shear Transfer of Lightweight-Aggregate Concretes Cast at Different Times,” PCI Journal, V. 59, No. 3, 2014, pp. 130-144. doi: 10.15554/pcij.06012014.130.144

7. Barbosa, A. R.; Trejo, D.; and Nielson, D., “Effect of High-Strength Reinforcement Steel on Shear Friction Behavior,” Journal of Bridge Engineering, ASCE, V. 22, No. 8, 2017, p. 04017038. doi: 10.1061/(ASCE)BE.1943-5592.0001015

8. Edgmond, N. J., and Sneed, L. H., “Examination of Shear-friction design Provisions,” Precast/Prestressed Concrete Institute (PCI), Chicago, IL, 2019, 147 pp.

9. Duan, Z.-H.; Kou, S.-C.; and Poon, C.-S., “Prediction of Compressive Strength of Recycled Aggregate Concrete Using Artificial Neural Networks,” Construction and Building Materials, V. 40, 2013, pp. 1200-1206. doi: 10.1016/j.conbuildmat.2012.04.063

10. Dantas, A. T. A.; Batista Leite, M.; and de Jesus Nagahama, K., “Prediction of Compressive Strength of Concrete Containing Construction and Demolition Waste Using Artificial Neural Networks,” Construction and Building Materials, V. 38, 2013, pp. 717-722. doi: 10.1016/j.conbuildmat.2012.09.026

11. Asteris, P. G.; Armaghani, D. J.; Hatzigeorgiou, G. D.; Karayannis, C. G.; and Pilakoutas, K., “Predicting the Shear Strength of Reinforced Concrete Beams Using Artificial Neural Networks,” Computers and Concrete, An International Journal, V. 24, No. 5, 2019, pp. 469-488.

12. Bashir, R., and Ashour, A., “Neural Network Modelling for Shear Strength of Concrete Members Reinforced with FRP Bars,” Composites. Part B, Engineering, V. 43, No. 8, 2012, pp. 3198-3207. doi: 10.1016/j.compositesb.2012.04.011

13. Demir, F., ��Prediction of Elastic Modulus of Normal and High Strength Concrete by Artificial Neural Networks,” Construction and Building Materials, V. 22, No. 7, 2008, pp. 1428-1435. doi: 10.1016/j.conbuildmat.2007.04.004

14. Agarwal, R.; Melnick, L.; Frosst, N.; Zhang, X.; Lengerich, B.; Caruana, R.; and Hinton, G. E., “Neural Additive Models: Interpretable Machine Learning with Neural Nets,” Advances in Neural Information Processing Systems, V. 34, 2021, pp. 4699-4711.

15. Murtagh, F., “Multilayer Perceptrons for Classification and Regression,” Neurocomputing, V. 2, No. 5-6, 1991, pp. 183-197. doi: 10.1016/0925-2312(91)90023-5

16. Hecht-Nielsen, R., “Theory of the Backpropagation Neural Network,” Neural Networks for Perception, Elsevier, 1992, pp. 65-93.

17. O’Shea, K., and Nash, R., “An Introduction to Convolutional Neural Networks,” arXiv Preprint arXiv:1511.08458, 2015.

18. Kingma, D. P., and Ba, J., “Adam: A Method for Stochastic Optimization,” arXiv Preprint arXiv:1412.6980, 2014.

19. Palieraki, V.; Vintzileou, E.; and Silva, J. F., “Interface Shear Strength under Monotonic and Cyclic Loading,” ACI Structural Journal, V. 119, No. 3, May 2022, pp. 17-28.

20. Palieraki, V.; Vintzileou, E.; and Silva, J., “Behavior of RC Interfaces Subjected to Shear: State-of-the Art Review,” Construction and Building Materials, V. 306, 2021, p. 124855 doi: 10.1016/j.conbuildmat.2021.124855

21. Saemann, J., and Washa, G. W., “Horizontal Shear Connections between Precast Beams and Cast-in-Place,” ACI Journal Proceedings, V. 61, No. 11, Nov. 1964, pp. 1383-1410.

22. Mattock, A. H., and Hawkins, N. M., “Shear Transfer in Reinforced Concrete—Recent Research,” PCI Journal, V. 17, No. 2, 1972, pp. 55-75. doi: 10.15554/pcij.03011972.55.75

23. Hofbeck, J.; Ibrahim, I.; and Mattock, A. H., “Shear Transfer in Reinforced Concrete,” ACI Journal Proceedings, V. 66, No. 2, Feb. 1969, pp. 119-128.

24. Bass, R. A.; Carrasquillo, R. L.; and Jirsa, J. O., “Shear Transfer across New and Existing Concrete Interfaces,” ACI Structural Journal, V. 86, No. 4, July-Aug. 1989, pp. 383-393.

25. Echegaray-Oviedo, J.; Cuenca, E.; Navarro-Gregori, J.; and Serna, P., “Influence of the Fiber Reinforcement in Concrete under Direct Shear,” 10th fib International PhD Symposium in Civil Engineering Proceedings, 2014, pp. 415-424.

26. Chatterjee, P., “Shear Transfer in Reinforced Concrete,” master’s thesis, University of Washington, Seattle, WA, 1971.

27. Hanson, N. W., Precast-Prestressed Concrete Bridges: 2. Horizontal Shear Connections. Portland Cement Association, Research and Development Laboratories, Skokie, IL, 1960.


ALSO AVAILABLE IN:

Electronic Structural Journal



  

Edit Module Settings to define Page Content Reviewer