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Journals / Technology / 2005 / Cilt: 8 - Sayı: 1

Determination of member stiffness of bolted joints using finite element method and artificial neural network system

Civatalı bağlantıların eleman direngenliğin sonlu elemanlar yöntemi ve yapay sinir ağları ile belirlenmesi

MURAT TOLGA ÖZKAN
Kürşad DÜNDAR
Journal
Technology
Pages
33–41
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

A program has been prepared in Visual Basic Language.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, member stiffness of bolted joints determined using finite element method (FEM) and Artificial Neural Network System (ANNS).
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Key Findings & Data:Many analysis have been conducted for different materials and thicknesses using FEM.
💡
Conclusion & Impact:A program has been prepared in Visual Basic Language.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, member stiffness of bolted joints determined using finite element method (FEM) and Artificial Neural Network System (ANNS). Many analysis have been conducted for different materials and thicknesses using FEM. Analysis results have been collected in a data file. This data file have been used training of ANNS. Thus, according to design parameters member stiffness of bolted joints have been determined. A program has been prepared in Visual Basic Language.

Özet

Bu çalışmada, civatalı bağlantıların eleman direngenliği, Sonlu Elemanlar Yöntemi ve Yapay Sinir Ağları Sistemi ile belirlenmiştir. Farklı malzemeler ve farklı eleman kalınlıkları için Sonlu Elemanlar Yönteminde bir çok analiz yapılmıştır. Analiz sonuçları bir veri dosyasında toplanmıştır. Bu veri dosyası yapay Sinir Ağları Sistemi tarafından öğrenilmiştir. Böylece tasarım parametrelerine bağlı olarak eleman direngenliği belirlenmiştir. Visual Basic programlama dilinde bir program hazırlanmıştır.

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Cite This Article

ÖZKAN, M. T., DÜNDAR, K. (2005). Determination of member stiffness of bolted joints using finite element method and artificial neural network system. Technology, Cilt: 8 - Sayı: 1, 33–41. https://ajindex.com/articles/359691

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References (1)

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