Implementation of Zero Emission Fast Shortsea Shipping

The paper describes the implementation of state-of-the-art “Industry 4.0” methods and tools, a holistic ship design optimization and modular production methods, as well as advanced battery technologies to enable a fully electrical, fast zero-emission waterborne urban transport. The design of a fast catamaran passenger ferry demonstrator planned for operation as a waterborne shuttle in the Stavanger/Norway area and of a replicator for operation at Thames River/London are elaborated, including infrastructural issues for their operation. The presented research is in the frame of the H2020 funded project “TrAM – Transport: Advanced and Modular” (www.tramproject.eu)

Review and historical overview of experimental facilities used in hull coating hydrodynamic tests

The prediction of hydrodynamic performance of hull coatings with different surface conditions is a challenging task. Moreover, with the emergence of new prototype coatings that are relatively smooth in terms of roughness characteristics, the accurate estimation of their drag is particularly important, as this will enable a good grading of drag reducing benefits of coatings. In the context of coating studies, the experimental methods are considered as the backbone and results obtained from experimental facilities with the required performance will enable accurate scaling of test results to full-scale ship results. Although numerical simulations like computational fluid dynamics have acquired the level of accuracy good enough to replace some of the systematic model testing used for ship design optimization, it is still not evident whether the simulations will be able to replicate the physical reality such as coating type, its roughness and biofilms accurate enough to enable predictions of the power requirements for ships. Therefore, this article gives insight into various coating hydrodynamic testing facilities and methods that are capable of measuring drag characteristics of coatings. The work highlights the details of each method and identifies the concepts and parameters needed to describe, implement and analyze hydrodynamic coating drag measurements. This article also summarizes the merits and demerits of each type of facility based on reports and studies reported in open literature. Finally, the authors propose a recommendation that can be incorporated into the design of the new hydrodynamic facility.

An Effective Approximation Modeling Method for Ship Resistance in Multidisciplinary Ship Design Optimization

Ship design is related to several disciplines such as hydrostatic, resistance, propulsion and economic. The traditional ship design process only involves independent design optimization with some regression formulas within each discipline and there is no guarantee to achieve the optimum design. At the same time, it is crucial to improve the efficiency of modern ship design. Nowadays, the methods of computational fluid dynamics (CFD) has been brought into the ship design optimization. However, there are still some problems such as calculation precision and time consumption especially when CFD software is inlaid into the optimization procedure. Modeling is a far-ranging and all-around subject, and its precision directly affects the scientific decision in future. How to establish an accurate approximation model instead of the CFD calculation will be the key problem. The Support Vector Machines (SVM), a new general machine learning method based on the frame of statistical learning theory, may solve the problems in sample space and be an effective method of processing the non-liner classification and regression. The classical SVR has two parameters to control the errors. A new algorithm of Support Vector Regression proposed in this article has only one parameter to control the errors, adds b2/2 to the item of confidence interval at the same time, and adopts the Laplace loss function. It is named Single-parameter Lagrangian Support Vector Regression (SPL-SVR). This effective algorithm can improve the operation speed of program to a certain extent, and has better fitting precision. In practical design of ship, Design of Experiment (DOE) and the proposed support vector regression algorithm are applied to ship design optimization to construct statistical approximation model in this paper. The support vector regression algorithm approximates the optimization model and is updated during the optimization process to improve accuracy. The result indicates that the SPL-SVR method to establish approximate models can effectively solve complex engineering design optimization problem. Finally, some suggestions on the future improvements are proposed.