Marine propeller optimisation tools for scenario-based design

The marine propulsion system is one of the most important components of a ship in order to cover the demanding operating needs of propulsion nowadays and to increase performance in a wide range of operating conditions. Marine propellers are designed with the purpose of matching the hull and machinery system, create the required thrust for the entire operational profile, and fulfil the techno-economical requirements that depend on the decision-making of several stakeholders. The final product must represent a unique propeller, designed for a specific vessel, and is a trade-off between all requirements. In an industrial framework, the marine propeller design process should therefore be straightforward and well-developed. The limited time under which the design process must be performed, plays a decisive role in the methods utilised to carry it out, as for example in the selection of the analysis tools, which must be fast and they usually involve semi-empirical evaluations. Since blade design is a multi-objective and multidisciplinary problem, automated optimisation has been used with the aim to search good solutions in the design space efficiently. However, automated optimisation has failed to be used in industrial applications due to obtaining solutions with high performance but with infeasible geometries, and as a method it proved to be inferior to the manual design process, something that shows the importance of the designer\u27s expertise. The main research question of this thesis is therefore related to incorporating optimisation in a systematic way in order to improve the propeller design process and assist the blade designers to obtain feasible and high-performing propellers in strict time constraints. A methodology is proposed that combines interactive optimisation with machine learning and in parallel new objectives are implemented for more complex scenarios. The designer is enabled to manually evaluate cavitation nuisance during the optimisation and guide the algorithm towards areas of the design space with satisfactory cavitation characteristics. Several scenario-based situations have been investigated by using the proposed methodology, that involve different propeller types, design and off-design conditions, several objectives and constraints, cavitation nuisance on the suction and the pressure side of the blade, and applications within conventional and wind propulsion. The results have shown that by involving the blade designer\u27s expertise in the design and optimisation process systematically, competitive propeller designs with feasible geometries can be obtained efficiently

Interactive Optimisation in Marine Propeller Design

Marine propeller design is a complex engineering problem that depends on the collaboration of several scientific disciplines. During the design process, the blade designers need to consider contradicting requirements and come up with one optimal propeller design as a solution to the specific problem. This solution is usually the trade-o between the stakeholders\u27 requirements and the objectives and constraints of the problem.The significant amount of design variables related to blade design problems requires a systematic search in a large design space. Automated optimisation has been utilised for a number of blade design applications, as it has the advantage of creating a large set of design alternatives in a short period of time. However, automated optimisation has failed to be used in industrial applications, due to its complex set-up and the fact that in more complex scenarios the majority of the non-dominated design alternatives are infeasible. This necessitates a way of enabling the blade designers to interact with the algorithm during the optimisation process.The purpose of this thesis is to develop a methodology that supports the blade designers during the design process and to enable them to interact with the design tools and assess design characteristics during the optimisation. The overall aim is to improve the design performance and speed. According to the proposed methodology, blade designers are called during intermediate stages of the optimisation to provide information about the designs, and then this information is input in the algorithm. The goal is to steer the optimisation to an area of the design space with feasible Pareto designs, based on the designer\u27s preference. Since there are objectives and constraints that cannot be quantified with the available computational tools, keeping the "human in the loop" is essential, as a means to obtain feasible designs and quickly eliminate designs that are impractical or unrealistic.The results of this research suggest that through the proposed methodology the designers have more control over the whole optimisation procedure and they obtain detailed Pareto frontiers that involve designs that are characterised by high performance and follow the user preference

Marine propeller optimisation through user interaction and machine learning for advanced blade design scenarios

The complexity of the marine propeller design process is well recognised and is related to contradicting requirements of the stakeholders, complex physical phenomena, and fast analysis tools, where the latter are preferred due to the strict time limitations under which the entire process is carried out. With all this in mind, an optimisation methodology has been proposed and presented earlier that combines user interactivity with machine learning and proved to be useful for a simple blade design scenario. More specifically, the blade designer manually evaluates the cavitation of the designs during the optimisation and this information is systematically returned into the optimisation algorithm, a process called interactive optimisation. As part of the optimisation, a machine learning pipeline has been implemented in this study, which is used for cavitation evaluation prediction in order to solve the user fatigue problem that is connected to interactive optimisation processes. The proposed methodology is investigated for two case studies of advanced design scenarios, relevant for a real commercial situation, that regard controllable-pitch propellers for ROPAX vessels, and the aim is to obtain a set of optimal, competent blade designs. Both cases represent scenarios with several design variables, objectives and constraints and with conditions that have either suction side or pressure side cavitation. The results show that the proposed methodology can be used as a support tool for the blade designers to, under strict time constraints, find a suitable set of propeller designs, some of which can be considered equal or even superior to the delivered design

Quantification of the maritime security problem onboard passenger ship

Given the large number of recent terror attacks worldwide, there is a growing concern over the security issue in the maritime world. Aim of this paper is to address a scenario pertinent to the maritime security problem using the evacuation simulation software tool EVI. The vessel chosen for this case study is a 13-deck cruise ship. The scenario investigated deals with the evacuation of a large density populated area within the vessel, where an explosive device has been placed and assesses the potential loss of life, according to the distance of the agents relative to the explosion blast. Three different positions of the explosive device are examined in this study and for each position six different cases are examined, in which the effect of prior warning to the explosion is taken into consideration. In the first case, the explosion takes place at the beginning of the simulation (t=0) in order to replicate such a scenario in which those agents within the restaurant are un-alerted to the presence of the explosive device. In the rest of the cases the explosion takes place after warning times of 0.5, 1, 1.5, 2 and 2.5 minutes respectively in order to assess the sensitivity of the fatality rate and evacuation to prior warning time

Propeller optimization by interactive genetic algorithms and machine learning

Marine propeller design can be carried out with the aid of automated optimization, but experience shows that a such an approach has still been inferior to manual design in industrial scenarios. In this study, the automated propeller design optimization is evolved by integrating human–computer interaction as an intermediate step. An interactive optimization methodology, based on interactive genetic algorithms (IGAs), has been developed, where the blade designers systematically guide a genetic algorithm towards the objectives. The designers visualize and assess the shape of the blade cavitation and this evaluation is integrated in the optimization method. The IGA is further integrated with a support-vector machine model, in order to avoid user fatigue, IGA\u27s main disadvantage. The results of the present study show that the IGA optimization searches solutions in a more targeted manner and eventually finds more non-dominated feasible designs that also show a good cavitation behaviour in agreement with designer preference

Controllable-pitch propeller design process for a wind-powered car-carrier optimising for total energy consumption

Wind-powered ship propulsion (WPSP) is the concept where the wind is the main source of thrust, while the traditional propulsion system operates when needed. This type of propulsion can lead to considerably reduced emissions, something that the shipping community is striving for. A well-known example of WPSP is the Oceanbird with the goal to cut emissions of up to 90%. In this study, the propeller design process for a wind-powered car-carrier (wPCC) such as the Oceanbird is investigated, what the various challenges of WPSP are and therefore how an automated optimisation procedure should be approached. A controllable-pitch propeller was selected as suitable propeller type for the operation of the wPCC, and various functions such as windmilling, feathering and harvesting have been explored. Regarding the optimisation procedure, an essential input is the definition of the operational profile, in order to determine the most important conditions for the route. The main objective of the optimisation is the minimisation of the total energy consumption (TEC), calculated based on a selection of conditions using the potential flow solver MPUF-3A. Cavitation has been evaluated by the blade designer, through an interactive optimisation method. The results showed that designing and optimising for the most highly loaded condition led to solutions with the lowest TEC

Cavitation nuisance identification through machine learning during propeller optimisation

The marine propeller design process runs under strict time limitations and even if it entails contradicting requirements from different stakeholders and complex physical phenomena, the analysis tools must be very fast. Cavitation nuisance is such a complex phenomenon that is hard to predict accurately from these tools and requires additional evaluation by the blade designer. Thus, a good blade design depends on approximate analysis tools and on the expertise of an experienced blade designer. Therefore, we previously developed an interactive optimisation methodology, where interactive genetic algorithms were utilised for blade design optimisation and cavitation was manually evaluated by the blade designer. However, since blade design involves a large design space, the optimisation requires populations of thousands of individuals, something that makes the manual evaluations by the blade designer very laborious. Accordingly in this study, a machine learning pipeline has been developed with the aim to reduce the number of manual evaluations and classify the cavitation nuisance automatically. Nested-cross validation has been used in order to identify the best classification algorithms combined with the most suitable hyperparameters for three different propellers with both suction and pressure side cavitation. The results have shown that using machine learning can be very beneficial in order to reduce user fatigue in interactive optimisation processes

Propeller design procedure for a wind-assisted KVLCC2

Wind-assisted ship propulsion (WASP) has received much attention lately with research focusing on the different sail technologies, ship-hull design optimisation and weather route optimisation. However, the traditional propulsion system is still needed for wind-assisted vessels and is associated with several challenges, related to the wide range of operating conditions and propeller loads due to the varying degree of wind-assistance that will occur. In this study we use an interactive design and optimisation methodology applied on propellers of wind-assisted vessels. The methodology involves handling the complete operating profile of the propeller, an optimisation method for interactive cavitation evaluation by the blade designer, and the use of a new objective, the total energy consumption (TEC) of the expected operation. We use a case study where the KVLCC2 tanker is retrofitted with six Flettner rotor sails, operating between two fixed destinations at constant speed. The purpose is to investigate to what extent a new propeller design can offer a significantly lower TEC when compared to the existing design. Based on the results of this study, approximately 0.9% further reduction in TEC was achieved with the WASP adapted propeller compared to the existing one