Applications of holistic ship theory for the simulation driven optimization of the design and operation of large bulk carriers

Nikolopoulos, L and Boulougouris, E and Khorasanchi, M (2016) Applications of holistic ship theory for the simulation driven optimization of the design and operation of large bulk carriers. In: Energy Efficient Ships 2016, 2016-11-23 - 2016-11-24, RINA.

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Abstract

The change of scenery in shipping has been evident over the past 20 years. The changing fuel costs, tough and volatile market conditions, the constant societal pressure for a «green» environmental footprint combined with ever demanding international safety regulations create the new framework in which commercial ship designs are subject to. As a result of this current status of shipping commercial a change of attitude in the philosophy and process of ship design is required in order to shift towards new approaches where holistic approaches are deemed necessary. Apart from considering all the interrelationships between the subsystems that consist the vessel lifecycle and supply chain considerations are the key in successful and «operator oriented» designs. The methodology herein presented is built within the computer aided engineering (CAE) software CAESES that integrates in the design process CFD codes. It can be successfully used for the optimization of either of the basic design of a vessel or the operation of an existing vessel with regards to the maximization of the efficiency, safety and competitiveness of the final design. The model is created based on the design of a large bulk carrier and a simulation model consisting of modules that cover most aspects of ship design. Stability, strength, powering and propulsion, safety, economics, operational and maintenance and in service management considerations are tightly integrated within a fully parametric model. This tight integration enables the user to simulate the response of the model in variations of the geometrical, design variables of the vessel (including its propeller) under conditions of simulation and uncertainty. The uncertainty modelling is extensive and in several levels including but not limited to Economic, Environmental, and Operational uncertainty as well an accuracy modelling of the methodology itself.