DOUBLE CRACKS IDENTIFICATION IN FUNCTIONALLY GRADED BEAMS USING ARTIFICIAL NEURAL NETWORK

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

NAZARI F.; ABOLBASHARI M.H.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF SOLID MECHANICS Year:2013 | Volume:5 | Issue:1 Page(s): 14-21

Download Full-Text

View:

334

Download:

122

Cites:

Information Journal Paper

Title

DOUBLE CRACKS IDENTIFICATION IN FUNCTIONALLY GRADED BEAMS USING ARTIFICIAL NEURAL NETWORK

Author(s)

NAZARI F. | ABOLBASHARI M.H. | Issue Writer Certificate

Keywords

DOUBLE CRACKS

FUNCTIONALLY GRADED BEAM

ARTIFICIAL NEURAL NETWORK

MODEL ANALYSIS

Abstract

This study presents a new procedure based on ARTIFICIAL NEURAL NETWORK (ANN) for identification of DOUBLE CRACKS in FUNCTIONALLY GRADED BEAMs (FGBs). A cantilever beam is modeled using Finite Element Method (FEM) for analyzing a double-cracked FGB and evaluation of its first four natural frequencies for different cracks depths and locations. The obtained FEM results are verified against available references. Furthermore, four Multi-Layer Perceptron (MLP) neural networks are employed for identification of locations and depths of both cracks of FGB. Back-Error Propagation (BEP) method is used to train the ANNs. The accuracy of predicted results shows that the proposed procedure is suitable for DOUBLE CRACKS identification detection in FGBs.

Cites

No record.

References

No record.

Cite

APA: Copy

NAZARI, F., & ABOLBASHARI, M.H.. (2013). DOUBLE CRACKS IDENTIFICATION IN FUNCTIONALLY GRADED BEAMS USING ARTIFICIAL NEURAL NETWORK. JOURNAL OF SOLID MECHANICS, 5(1), 14-21. SID. https://sid.ir/paper/319297/en

Vancouver: Copy

NAZARI F., ABOLBASHARI M.H.. DOUBLE CRACKS IDENTIFICATION IN FUNCTIONALLY GRADED BEAMS USING ARTIFICIAL NEURAL NETWORK. JOURNAL OF SOLID MECHANICS[Internet]. 2013;5(1):14-21. Available from: https://sid.ir/paper/319297/en

IEEE: Copy

F. NAZARI, and M.H. ABOLBASHARI, “DOUBLE CRACKS IDENTIFICATION IN FUNCTIONALLY GRADED BEAMS USING ARTIFICIAL NEURAL NETWORK,” JOURNAL OF SOLID MECHANICS, vol. 5, no. 1, pp. 14–21, 2013, [Online]. Available: https://sid.ir/paper/319297/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops