✦ LIBER ✦

Predicting the Crushing Behavior of Axially Loaded Elliptical Composite Tubes Using Artificial Neural Networks

✍ Scribed by Hany El Kadi

Publisher: Springer Netherlands
Year: 2008
Tongue: English
Weight: 635 KB
Volume: 15
Category: Article
ISSN: 0929-189X
DOI: 10.1007/s10443-008-9074-2

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Predicting the Fatigue Life of Different

Predicting the Fatigue Life of Different Composite Materials Using Artificial Neural Networks

✍ M. Al-Assadi; H. El Kadi; I. M. Deiab 📂 Article 📅 2009 🏛 Springer Netherlands 🌐 English ⚖ 439 KB

Prediction of the functional properties

Prediction of the functional properties of ceramic materials from composition using artificial neural networks

✍ D.J. Scott; P.V. Coveney; J.A. Kilner; J.C.H. Rossiny; N.Mc N. Alford 📂 Article 📅 2007 🏛 Elsevier Science 🌐 English ⚖ 296 KB

We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorganic, non-metallic materials and are investigated on the basis of their dielectric and ionic properties. Dielectric mater

Use of neural networks for the predictio

Use of neural networks for the prediction of frictional drag and transmission of axial load in horizontal wellbores

✍ Tanvir Sadiq; Ridha B. Gharbi; Hans C. Juvkam-Wold 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 909 KB

Using Artificial Neural Networks to Pred

Using Artificial Neural Networks to Predict the Fatigue Life of Different Composite Materials Including the Stress Ratio Effect

✍ Mohamed Al-Assadi; Hany A. El Kadi; Ibrahim M. Deiab 📂 Article 📅 2010 🏛 Springer Netherlands 🌐 English ⚖ 526 KB