Showing 2 results for Platform
M. A. Lotfollahi Yaghin, K. Farzad and M. Naghipour,
Volume 23, Issue 1 (7-2004)
Abstract
Similar to random sea waves, forces on the offshore structures due to waves are random. These forces can be mainly divided into two components, namely, inline forces and transverse or lift forces. The random nature of lift forces is more complicated than that of inline forces and both should be combined for design purposes. In the present paper, two different approaches have been used to determine time series of lift forces. Along these lines, the determination of lift coefficients is discussed which have then been used to obtain transverse forces and compared with experimental data. The experimental data used in this study were collected at Delft Hydraulics Laboratory on a full-scale rough vertical cylinder.
A. Fathi, A. A. Aghakuchak, and Gh. A. Montazer,
Volume 26, Issue 2 (1-2008)
Abstract
In welded tubular joints, when the fatigue crack depth is less than 20% of chord wall thickness, the crack growing process is highly affected by weld geometry.
Hence, T-butt solution and weld magnification factor (Mk) are applicable tools for evaluating the crack growth rate in this domain. In this research, the capability of Artificial Neural Network (ANN) for estimating the Mk of weld toe cracks in T-butt joints is investigated. Four Multi-Layer Perceptron (MLP) networks are designed and trained to predict the Mk in deepest point and ends of weld toe cracks under membrane and bending stresses. Training and testing data of networks are extracted from a reputable resource on finite element modeling. Comparison of the results obtained and those from the most recently published equations shows that using ANN seems to be very beneficial in this field
