Development of a Spectral Method and a Statistical Wave Model for Crack Propagation Prediction in Ship Structures
Journal article, 2014
As a result of the wide use of high-tensile steel and the imperfect fabrication process in ship construction as well as some uncertainties in ship fatigue design, cracks could be initiated much earlier than expected. The presence of fatigue cracks greatly affects a ship's structural safety and serviceability. To ensure structural safety and perform reliable crack inspection and maintenance planning, it is important to know how fast cracks can grow in ship structures. In the current study, the principles of fracture mechanics are used for crack propagation analysis in ships. By taking into account the special properties of a ship's stress response, an efficient spectral method is proposed and validated for the prediction of crack propagation in ship structures. In this spectral method, structural stresses are assumed to be narrow-band Gaussian processes. Furthermore, for crack inspection and maintenance planning based on crack growth, it is essential to know the wave environments encountered in a ship's future operations. Therefore, a spatiotemporal statistical wave model based on both satellite and buoy measurements is briefly introduced. It is developed to generate wave environments along arbitrary ship routes. Finally, the deck longitudinal stiffener of a 2800TEU containership is used to demonstrate the application of the spectral method and the wave model for the prediction of crack propagation in ships. The route information and operating conditions are taken from full-scale measurements of this ship. In the case study, the scatter of crack propagation associated with the wave environments encountered is also investigated. The results from this investigation indicate possible potentials of crack inspection and maintenance optimization to enable more efficient ship operation.
stress intensity factor
Paris law
crack maintenance
fatigue crack propagation
ship routes
wave environments
statistical wave model