Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs

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Izvoz citacije: ABNT
IBRIKÇI, Turgay ;SAÇMA, Selim ;YILDIRIM, Vebil ;KOCA, Tarkan .
Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 56, n.6, p. 409-417, october 2017. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/application-of-artificial-neural-networks-in-the-prediction-of-critical-buckling-loads-of-helical-compression-springs/>. Date accessed: 11 apr. 2021. 
doi:http://dx.doi.org/.
Ibrikçi, T., Saçma, S., Yıldırım, V., & Koca, T.
(2010).
Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs.
Strojniški vestnik - Journal of Mechanical Engineering, 56(6), 409-417.
doi:http://dx.doi.org/
@article{.,
	author = {Turgay  Ibrikçi and Selim  Saçma and Vebil  Yıldırım and Tarkan  Koca},
	title = {Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {56},
	number = {6},
	year = {2010},
	keywords = {buckling; critical buckling load; helical spring; artificial neural networks; design; coil spring; },
	abstract = {This paper proposes the use of artificial neural networks (ANN) to perfectly predict the critical buckling loads of cylindrical isotropic helical spring with fixed ends and with circular sections, and with large pitch angles. The buckling equations of cylindrical isotropic helical springs loaded axially consist of a set of twelve linear differential equations. As finding a solution in an analytical manner is too difficult, numerical solution in an exact manner based on the transfer-matrix method to collect consistent dimensionless numerical data for the training process is used. In this way almost perfect weight values are obtained to predict the non-dimensional buckling loads. A good agreement is observed with the data available in the literature. },
	issn = {0039-2480},	pages = {409-417},	doi = {},
	url = {https://www.sv-jme.eu/sl/article/application-of-artificial-neural-networks-in-the-prediction-of-critical-buckling-loads-of-helical-compression-springs/}
}
Ibrikçi, T.,Saçma, S.,Yıldırım, V.,Koca, T.
2010 October 56. Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 56:6
%A Ibrikçi, Turgay 
%A Saçma, Selim 
%A Yıldırım, Vebil 
%A Koca, Tarkan 
%D 2010
%T Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs
%B 2010
%9 buckling; critical buckling load; helical spring; artificial neural networks; design; coil spring; 
%! Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs
%K buckling; critical buckling load; helical spring; artificial neural networks; design; coil spring; 
%X This paper proposes the use of artificial neural networks (ANN) to perfectly predict the critical buckling loads of cylindrical isotropic helical spring with fixed ends and with circular sections, and with large pitch angles. The buckling equations of cylindrical isotropic helical springs loaded axially consist of a set of twelve linear differential equations. As finding a solution in an analytical manner is too difficult, numerical solution in an exact manner based on the transfer-matrix method to collect consistent dimensionless numerical data for the training process is used. In this way almost perfect weight values are obtained to predict the non-dimensional buckling loads. A good agreement is observed with the data available in the literature. 
%U https://www.sv-jme.eu/sl/article/application-of-artificial-neural-networks-in-the-prediction-of-critical-buckling-loads-of-helical-compression-springs/
%0 Journal Article
%R 
%& 409
%P 9
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 56
%N 6
%@ 0039-2480
%8 2017-10-24
%7 2017-10-24
Ibrikçi, Turgay, Selim  Saçma, Vebil  Yıldırım, & Tarkan  Koca.
"Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs." Strojniški vestnik - Journal of Mechanical Engineering [Online], 56.6 (2010): 409-417. Web.  11 Apr. 2021
TY  - JOUR
AU  - Ibrikçi, Turgay 
AU  - Saçma, Selim 
AU  - Yıldırım, Vebil 
AU  - Koca, Tarkan 
PY  - 2010
TI  - Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - buckling; critical buckling load; helical spring; artificial neural networks; design; coil spring; 
N2  - This paper proposes the use of artificial neural networks (ANN) to perfectly predict the critical buckling loads of cylindrical isotropic helical spring with fixed ends and with circular sections, and with large pitch angles. The buckling equations of cylindrical isotropic helical springs loaded axially consist of a set of twelve linear differential equations. As finding a solution in an analytical manner is too difficult, numerical solution in an exact manner based on the transfer-matrix method to collect consistent dimensionless numerical data for the training process is used. In this way almost perfect weight values are obtained to predict the non-dimensional buckling loads. A good agreement is observed with the data available in the literature. 
UR  - https://www.sv-jme.eu/sl/article/application-of-artificial-neural-networks-in-the-prediction-of-critical-buckling-loads-of-helical-compression-springs/
@article{{}{.},
	author = {Ibrikçi, T., Saçma, S., Yıldırım, V., Koca, T.},
	title = {Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {56},
	number = {6},
	year = {2010},
	doi = {},
	url = {https://www.sv-jme.eu/sl/article/application-of-artificial-neural-networks-in-the-prediction-of-critical-buckling-loads-of-helical-compression-springs/}
}
TY  - JOUR
AU  - Ibrikçi, Turgay 
AU  - Saçma, Selim 
AU  - Yıldırım, Vebil 
AU  - Koca, Tarkan 
PY  - 2017/10/24
TI  - Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 56, No 6 (2010): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - buckling, critical buckling load, helical spring, artificial neural networks, design, coil spring, 
N2  - This paper proposes the use of artificial neural networks (ANN) to perfectly predict the critical buckling loads of cylindrical isotropic helical spring with fixed ends and with circular sections, and with large pitch angles. The buckling equations of cylindrical isotropic helical springs loaded axially consist of a set of twelve linear differential equations. As finding a solution in an analytical manner is too difficult, numerical solution in an exact manner based on the transfer-matrix method to collect consistent dimensionless numerical data for the training process is used. In this way almost perfect weight values are obtained to predict the non-dimensional buckling loads. A good agreement is observed with the data available in the literature. 
UR  - https://www.sv-jme.eu/sl/article/application-of-artificial-neural-networks-in-the-prediction-of-critical-buckling-loads-of-helical-compression-springs/
Ibrikçi, Turgay, Saçma, Selim, Yıldırım, Vebil, AND Koca, Tarkan.
"Application of Artificial Neural Networks in the Prediction of Critical Buckling Loads of Helical Compression Springs" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 56 Number 6 (24 October 2017)

Avtorji

Inštitucije

  • Çukurova University, Electrical-Electronics Engineering Department, Turkey
  • Çukurova University, Mechanical Engineering Department, Turkey
  • Çukurova University, Mechanical Engineering Department, Turkey
  • University of İnönü, Arapgir Vocational School, Turkey

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 56(2010)6, 409-417

This paper proposes the use of artificial neural networks (ANN) to perfectly predict the critical buckling loads of cylindrical isotropic helical spring with fixed ends and with circular sections, and with large pitch angles. The buckling equations of cylindrical isotropic helical springs loaded axially consist of a set of twelve linear differential equations. As finding a solution in an analytical manner is too difficult, numerical solution in an exact manner based on the transfer-matrix method to collect consistent dimensionless numerical data for the training process is used. In this way almost perfect weight values are obtained to predict the non-dimensional buckling loads. A good agreement is observed with the data available in the literature. 

buckling; critical buckling load; helical spring; artificial neural networks; design; coil spring;