Lateral-torsional buckling capacity assessment of web opening steel girders by artificial neural networks – elastic investigation

doi:10.1007/s11709-014-0236-z

Frontiers of Structural and Civil Engineering

2014, Vol. 8

Issue (2): 167-177 https://doi.org/10.1007/s11709-014-0236-z

本期目录

Lateral-torsional buckling capacity assessment of web opening steel girders by artificial neural networks – elastic investigation

Yasser SHARIFI(

),Sajjad TOHIDI

Department of Civil Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

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Abstract：

Bridge girders exposed to aggressive environmental conditions are subject to time-variant changes in resistance. There is therefore a need for evaluation procedures that produce accurate predictions of the load-carrying capacity and reliability of bridge structures to allow rational decisions to be made about repair, rehabilitation and expected life-cycle costs. This study deals with the stability of damaged steel I-beams with web opening subjected to bending loads. A three-dimensional (3D) finite element (FE) model using ABAQUS for the elastic flexural torsional analysis of I-beams has been used to assess the effect of web opening on the lateral buckling moment capacity. Artificial neural network (ANN) approach has been also employed to derive empirical formulae for predicting the lateral-torsional buckling moment capacity of deteriorated steel I-beams with different sizes of rectangular web opening using obtained FE results. It is found out that the proposed formulae can accurately predict residual lateral buckling capacities of doubly-symmetric steel I-beams with rectangular web opening. Hence, the results of this study can be used for better prediction of buckling life of web opening of steel beams by practice engineers.

Key words： steel I-beams lateral-torsional buckling finite element (FE) method artificial neural network (ANN) approach

收稿日期: 2013-09-19 出版日期: 2014-05-19

Corresponding Author(s): Yasser SHARIFI

引用本文:

. [J]. Frontiers of Structural and Civil Engineering, 2014, 8(2): 167-177.
Yasser SHARIFI,Sajjad TOHIDI. Lateral-torsional buckling capacity assessment of web opening steel girders by artificial neural networks – elastic investigation. Front. Struct. Civ. Eng., 2014, 8(2): 167-177.

链接本文:

https://academic.hep.com.cn/fsce/CN/10.1007/s11709-014-0236-z
https://academic.hep.com.cn/fsce/CN/Y2014/V8/I2/167

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1	TimoshenkoS P, GereJ M. Theory of Elastic Stability. 2nd ed. New York: McGraw-Hill, 1961
2	ChenW F, LuiE M. Structural Stability: Theory and Implementation. New York: Elsevier, 1987
3	TrahairN S. The Behaviour and Design of Steel Structures. London: Chapman and Hall, 1977
4	ChajesA. Principles of Structural Stability. Englewood cliff, New jersey: Prentice-Hall Inc, 1974
5	TrahairN S, BradfordM A, NethercotD A, GardnerL. The Behaviour and Design of Steel Structures to EC3. 4nd ed. Taylor & Francis, 2008
6	KalkanI, BuyukkaragozA. A numerical and analytical study on distortional buckling of doubly-symmetric steel I-beams. Journal of Constructional Steel Research, 2012, 70: 289-297
7	GalambosT V. Guide to Stability Design Criteria for Metal Structures. 5nd ed. New York: John Wiley & Sons, 1998
8	BradfordM A, WeeA. Analysis of buckling tests on beams on seat supports. Journal of Constructional Steel Research, 1994, 28(3): 227-242
9	Standards Association of Australia. AS 4100 steel structures. Sydney, Australia, 1990
10	British Standards Institution. BS 5950 Part 1: Structural Use of Steelwork in Building. London, United Kingdom, 1990
11	ZirakianT, ShowkatiH. Experiments on distortional buckling of I-beams. Journal of Structural Engineering, 2007, 133(7): 1009-1017
12	AISC. Specification for structural steel buildings (AISC 360–05). Chicago (IL): American Institute of Steel Construction, March 9, 2005
13	SharifiY, PaikJ K. Ultimate strength reliability analysis of corroded steel-box girder bridges. Thin-walled Structures, 2011, 49(1): 157-166
14	SharifiY, PaikJ K. Environmental effects on ultimate strength reliability of corroded steel box girder bridges. Structural Longevity, 2010, 18(1): 1-20
15	SharifiY. Reliability of deteriorating steel box-girder bridges under pitting corrosion. Advanced Steel Construction, 2011, 7(3): 220-238
16	KulickiJM, PruczZ, SorgenfreiD F, MertzD R. Guidelines for Evaluating Corrosion Effects in Existing Steel Bridges. National Cooperative Highway Research Program Report333: NCHRP, 1990
17	KayserJ R, NowakA S. Capacity loss due to corrosion in steel-girder bridges. Journal of Structural Engineering, 1989, 115(6): 1525-1537
18	RedwoodR G, UenoyaM. Critical loads for webs with holes. Journal of the Structural Division, 1979, 105(ST10): 2053-2067
19	CoullA, AlvarezM C. Effect of openings on lateral buckling of beams. Journal of the Structural Division, 1980, 106(ST12): 2553-2560
20	NethercotD A, KerdalD. Lateral–torsional buckling of castellated beams. Structural Engineering Journal, 1982, 60B(3): 53-61
21	KerdalD, NethercotD A. Failure modes for castellated beams. Journal of Constructional Steel Research, 1984, 4(4): 295-315
22	ThevendranV, ShanmugamN E. Lateral buckling of narrow rectangular beams containing openings. Computers & Structures, 1992, 43(2): 247-254
23	ThevendranV, ShanmugamN E. Lateral buckling of doubly symmetric beams containing openings. Journal of Engineering Mechanics, 1991, 117(7): 1427-1441
24	ShanmugamN E, ThevendranV. Critical loads of thin-walled beams containing web openings. Thin-walled Structures, 1992, 14(4): 291-305
25	MohebkhahA. The moment-gradient factor in lateral–torsional buckling on inelastic castellated beams. Journal of Constructional Steel Research, 2004, 60(10): 1481-1494
26	AISC. Specification for Structural Steel Buildings (AISC 44–48). Chicago (IL): American Institute of Steel Construction, June 22, 2010
27	ABAQUS user's manual, version 6.9. Pawtucket, RI: Hibbit, Karlsson & Sorenson, 2005
28	HaykinS. Neural Networks: A Comprehensive Foundation. 2nd ed. New York: Macmillan College Publishing, 1998
29	Neural Network Toolbox 7 User’s Guide. Mark Hudson Beale Martin T. Hagan Howard B. Demuth, 2010
30	RumelhartD, McClellandJ. Parallel Distributed Processing. Cambridge, Mass: MIT Press, 1986
31	RojasR.Neural Networks-A Systematic Introduction. Springer-Verlag, 1996
32	PuY, MesbahiE. Application of artificial neural networks to evaluation of ultimate strength of steel panels. Engineering Structures, 2006, 28(8): 1190-1196
33	HajelaP, BerkeL. Neurobiological computational models in structural analysis and design. Computers & Structures, 1991, 41(4): 657-667
34	OkD, PuY, IncecikA. Artificial neural networks and their application to assessment of ultimate strength of plates with pitting corrosion. Ocean Engineering, 2007, 34(17-18): 2222-2230
35	GuzelbeyI H, CevikA, GögüşM T. Prediction of rotation capacity of wide flange beams using neural networks. Journal of Constructional Steel Research, 2006, 62(10): 950-961
36	FonsecaE T, VellascoP C G S, AndradeS A L, VellascoM M B R. da S Vellasco PCG, de Andrade SAL, Vellasco MMBR. Neural network evaluation of steel beam patch load capacity. Advances in Engineering Software, 2003, 34(11-12): 763-772

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