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Abstract

The paper presents mathematical relationships that allow us to forecast the newbuilding price of new bulk carriers, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the price based on a gross tonnage capacity and a main engine power The approximations were developed using linear regression and the theory of artificial neural networks. The presented relations have practical application for estimation of bulk carrier newbuilding price needed in preliminary parametric design of the ship. It follows from the above that the use of artificial neural networks to predict the price of a bulk carrier brings more accurate solutions than linear regression.

damage cases. In order to perform the repairs the ship would need to go into a dry-dock. Aalbers (Aalbers, n.d.) provides an estimation of the costs of dry-docking of 1-2% of the newbuilding price of the ship, while Hansen (Hansen, 2013) shows that the actual costs of dry-docking are often underestimated. Therefore, conservatively, the costs of dry-docking are estimated as 3% of the newbuilding price. Next to the costs of dry-docking, the costs of repairs are estimated per meter of damage. The amount of steel per meter of ship length is estimated by dividing