Concrete breakout strength of single anchors in tension using neural networks

Advances in Engineering Software

Volumn 36, Issue 2, 2005, Pages 87-97

  Ashour, A F ^a   Alqedra, M A ^b  

^a UNIVERSITY OF BRADFORD   (United Kingdom)

^b ISLAMIC UNIVERSITY OF GAZA   (Palestine)

Author keywords

Concrete; Embedment depth; Neural network

Indexed keywords

ANCHORS; CHARGE COUPLED DEVICES; COMPRESSIVE STRENGTH; DATABASE SYSTEMS; FINITE ELEMENT METHOD; INSTALLATION; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PERSONNEL TRAINING;

EMBEDMENT DEPTH; FRACTURE SURFACES; LOAD TRANSFER MECHANISM; MULTI-LAYER FEED-FORWARD;

NEURAL NETWORKS;

EID: 10444286741     PISSN: 09659978     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.advengsoft.2004.08.001     Document Type: Article

References (23)

1. ACI Committee 355. State-of-the-art report on anchorage to concrete. Detroit, USA: American Concrete Institute; 1991. Reapproved 1997.
2. Comite Euro-International du Beton (CEB), Task Group VI/5. Fastenings to concrete and masonry structures. London, UK: Thomas Telford Services Ltd; 1994. p. 249.
3. Flood I, Muszynski L, Nandy S. Rapid analysis of externally reinforced concrete beams using neural networks. Comput Struct 2001;79(17):1553-9.
4. Goh ATC. Prediction of ultimate shear strength of deep beams using neural networks. ACI Struct J 1995;92(1):28-32.
5. Sanad A, Saka MP. Prediction of ultimate shear strength of reinforced-concrete deep beams using neural networks. J Struct Eng, ASCE 2001;127(7):818-28.
6. Liqun R, Zhao Z. An optimal neural network and concrete strength modeling. Adv Eng Software 2002;33(3):117-30.
7. Hong-Guang N, Ji-Zong W. Prediction of compressive strength of concrete by neural networks. Cement Concrete Res 2000;30(8):1245-50.
8. Flood I, Kartam N. Neural network in civil engineering I: principles and understandings. J Comput Civil Eng, ASCE 1994;8(2):131-48.
9. Flood I, Kartam N. Neural network in civil engineering II: systems and applications. J Comput Civil Eng, ASCE 1994;8(2):149-62.
10. Kartam N, Flood I, Garrett JH. Artificial neural networks for civil engineers: fundamentals and applications. New York: ASCE; 1997.
11. Waszczyszyn Z. Some recent and current problems of neuro computing in civil and structural engineering. In: Topping BHV, editor. Advances in computational structures technology. Edinburgh: Civil-Comp Press; 1996. p. 43-58.
12. Carpenter WC, Barthelemy JF. Common misconceptions about neural networks as approximators. J Comput Civil Eng, ASCE 1994;8(3): 345-58.
13. Rafiq MY, Bugmann G, Easterbrook DJ. Neural network design for engineering application. Comput Struct 2001;79(17):1541-52.
14. ACI 318-02. Building code requirements for structural concrete (ACI318-02). MI, USA: ACI International; 2002.
15. Fuchs W, Eligehausen R, Breen JE. Concrete capacity design (CCD) approach for fastening to concrete. ACI Struct J 1995;92(1):73-94.
16. Cook RA, Collins DM, Klingner RE, Polyzois D. Load-deflection behavior of cast-in-place and retrofit concrete anchors. ACI Struct J 1992;89(6):639-49.
17. Klingner RE, Mendonca JA. Tensile capacity of short anchor bolts and welded studs: a literature review. ACI J 1982;79(4):270-9.
18. ACI Committee 349. Code requirements for nuclear safety related concrete structures (ACI 349-85). Detroit, USA: American Concrete Institute; 1985.
19. MathWorks Inc. MatLab the language of technical computing. Natick, MA, USA: MathWorks Inc; 1999. Version 6.
20. Farrow CB, Frigui I, Klingner RE. Tensile capacity of single anchors in concrete: evaluation of existing formulas on an LRFD basis. ACI Struct J 1996;93(1):128-37.
21. Shi JJ. Clustering technique for evaluating and validating neural network performance. J Comput Civil Eng, ASCE 2002;16(2):152-5.
22. Hagan MT, Dermuth HB, Beale M. Neural network design. Boston, MA, USA: PWS Publishing Co.; 1996.
23. Mukherjee A, Deshpande JM. Application of artificial neural networks in structural design expert systems. Comput Struct 1995; 54(3):367-75.