Estimation Method for Dragged Anchor Accident Frequency on Subsea Pipelines in Busy Port Areas

Abstract

Recently, many subsea pipelines have been developed in busy port areas, including industrial ports, recreational areas, fishing areas, and other port facilities. Under busy ship traffic conditions, these subsea pipelines are likely to be exposed to the risk of damage by a dragged anchor or other dropped objects. In this paper, a model is proposed to estimate the dragged anchor accident frequency on subsea pipelines based on the concept introduced by Fujii. The proposed model is approached by estimating the number of dragged anchor candidates on subsea pipelines, Na, based on an analysis of the anchor stopping distance in a critical subsea pipeline area. The causation probability Pc is estimated using a Bayesian network method that is modified from the model of Det Norske Veritas (DNV) and Hanninen. Various factors are considered to estimate Pc, including the human factor, weather factor, technical factor, and support factor. Automatic Identification System (AIS) and Geographic Information System (GIS) data are combined to estimate the lateral probability distribution of the ship traffic around a subsea pipeline area. A case study of anchors dragging on the subsea pipeline in the Madura Strait of Indonesia is performed to demonstrate the implementation of the proposed model. The proposed model is validated by comparing the results for the estimated dragged anchor accident frequency on the subsea pipeline using the proposed model with the actual accidents recorded in the Madura Strait. The results of this validation analysis show that there is reasonable agreement.