Application of artificial neural networks to the prediction of critical buckling loads of helical compression springs

Strojniski Vestnik/Journal of Mechanical Engineering

Volumn 56, Issue 6, 2010, Pages

  Ibrikçi, Turgay ^a   Saçma, Selim ^a   Yildirim, Vebil ^a   Koca, Tarkan ^b  

^a CUKUROVA UNIVERSITY   (Turkey)

^b INONU UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Buckling; Coil spring; Critical buckling load; Design; Helical spring

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; COIL SPRING; CRITICAL BUCKLING LOAD; CRITICAL BUCKLING LOADS;

BUCKLING; DIFFERENTIAL EQUATIONS; FORECASTING; HELICAL SPRINGS; TRANSFER MATRIX METHOD;

NEURAL NETWORKS;

EID: 77954880749     PISSN: 00392480     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. Haringx JA. (1949) On highly compressible helical springs and rubber rods. and their application for vibration-free mountings. Philips Research Reports, 4, p. 49-80.
2. Tabarrok B. Xiong Y. (1989) On the buckling equations for spatial rods. Int. J. of Mech. Eng. Sci., 31(3), p. 179-192.
3. Tabarrok B. Xiong Y. (1992) A spatially curved and twisted rod element for buckling analysis. Int. ernational Journal of Solids and Structures, 29(23), p. 3011-3023.
4. Xiong Y. Tabarrok B. (1992) A finite element model for the vibration of spatial rods under various applied loads. Int. J. of Mech. Eng. Sci., 34(1), p. 41-51.
5. Pearson D. (1982) The transfer matrix method for the vibration of compressed helical springs. J. of Mech. Eng. Sci., 24, p. 163-171.
6. Haktanir V. (1990) The investigation of the statical dynamic and buckling behavior of helical rods by the transfer and stiffness matrices methods. Ph. D. Thesis. çukurova University. Mechanical Engineering Department (In Turkish).
7. Becker LE. Cleghorn WL. (1992) On the buckling of helical compression springs. Int. J. of Mech. Eng. Sci., 34(4), p. 275-282.
8. Becker LE. Cleghorn WL. (1994) The buckling behavior of rectangular-bar helical compression springs. Journal of Applied Mechanics 61, p. 491-493.
9. Chassie GG. Becker LE. Cleghorn WL. (1997) On the buckling of helical springs under combined compression and torsion. International Journal of Mechanical Sciences 39(6), p. 697-704.
10. Yildirim V. On the linearized disturbance dynamic equations for buckling and free vibration of cylindrical helical coil springs under combined compression and torsion. Meccanica (submitted for publication)
11. Yildirim. V. Determination of pre-buckled deformation of helical isotropic/composite coil springs under compression. On the buckling of helical springs under combined compression and torsion. Int. J. of Mech. Eng. Sci. (submitted for publication)
12. Yildirim V. (1999) An efficient numerical method for predicting the natural frequencies of cylindrical helical springs. Int. J. of Mech. Eng. Sci., 41(8), p. 919-939.
13. Ibrikci, T. (2000) Neural Networks Models for Protein Structure Prediction. PhD. Thesis, Cukurova University
14. Rumelhart, D. E. Hinton, G. E. Williams R. J. (1986) Learning internal representations by error propagation in Parallel Distributed Processing: Explorations in the microstructure of Cognition MIT Press, 1, p. 318-362
15. Alpaydin E. (2004) Introduction to Machine Learning, MIT Press, USA
16. Yeh-Liang Hsu, Shu-Gen Wang, Chia-Chieh Yu, (2003) A sequential approximation method using neural networks for engineering design optimization problems. Engineering Optimization, 35(5), p. 489-511.
17. The MathWorks Inc. (2006), Matlab Help 1984-2006