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TOWARDS OPTIMAL DESIGN OF SHIP HULL SHAPES

J.J.MAISONNEUVE1, S.HARRIES2 , J.MARZI3, H.C.RAVEN4, U.VIVIANI5,H.PIIPPO6

1 SIREHNA, France, jean-jacques.maisonneuve@sirehna.ec-nantes.fr2TU Berlin, Germany, Stefan.Harries@ism.tu-berlin.de

3HSVA, Germany, marzi@hsva.de4MARIN, The Netherland, H.C.Raven@marin.nl

5 FINCANTIERI, Italy, umberto.viviani@fincantieri.it6NAPA OY, Finland, heikki.piippo@napa.fi

ΑΒSTRACT

The recent increase in information technologies dedicated to optimal design, associated with theprogress of the numerical tools for predicting ship hydrodynamic performances, allows significantimprovement in ship design. A consortium of fourteen European partners – bringing together shipyards, model basins, consultants, research centres and universities – has therefore conducted a threeyears European R&D project (FANTASTIC) with the goal to improve the functional design of shiphull shapes. The following key issues were thus considered: parametric shape modelling wasworked on through several complementary approaches, CFD tools and associated interfaces wereenhanced to meet efficiency and robustness requirements, appropriate design space exploration andoptimisation techniques were investigated. The resulting procedures where then implemented, forpractical assessment purposes, in some end-users design environments, and a number ofapplications were undertaken.. Significant gains can be expected from this approach in design, interm of time used for performance analysis and explored range of design variations.

1 OBJECTIVES

The principal objective of FANTASTIC is to improve ship design by applying parametric shapemodelling and state-of-the-art CFD analysis tools to predict ship hull performance. These functionalaspects are integrated in an optimisation environment. The approach is expected to i) allow for asubstantially larger coverage of design alternatives and ii) by using most recent CFD analysis toolsit will improve the quality of the design finally found optimal.

This was focused on the hydrodynamic prediction of steady performance, through two main typesof flow calculation tools: potential flow panel methods for a short term target in terms of practicalimplementation, and RANSE methods, in view of a longer term application. Seakeeping was alsopartially addressed as a major issue for some ship types. It was also implicit that the other aspects ofship design assessment, like hydrostatics, manoeuvring, structural resistance, even if not explicitlydeveloped in the project, also had to be kept in mind during the optimisation process, for the sake ofrealism.

The key issues with respect to these objectives are described in the following sections and in figure1. The first one deals with the best way to model the ship with a restricted set of parameters so thata wide range of variations can be investigated, while taking into account as many constraints aspossible regarding the shape and its feasibility. The second challenge is to make CFD methodssufficiently accurate, robust, automatic and fast to be used in an efficient design search. The lastissue consists in defining the best tools, from the IT as well as from the algorithmic point of view sothat the integration of the parametric modelling and assessment tools be as easy as possible, and thesearch for optimal design be as efficient as possible.

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Assessment process: calculation chains

Ship parametricrepresentation

Design criteria

Design space

exploration

Param

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modell

ing

Gridgen

erat

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Solver

Data

extra

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Figure 1: Description of the approach

2 PARAMETRIC MODELLING

Within the project the primary aim of parametric modelling has been to facilitate the modificationof hull shapes to be improved and, eventually, to optimise a ship’s hydrodynamic performance. Aparametric description captures the essence of the intended shapes and their possible variations and,thus, reduces the number of unknowns within the modelling process. The shape is determined fromfewer data – e.g. points that define a specific location, control points that influence a certain hullarea – and/or data that represent information on higher levels – e.g. angle of entrance of the designwaterline, centre of floatation. This is achieved by formulating dependencies and constraints apriori. Inherently, in a parametric approach the diversity of possible hull forms is confined by thetopology and the design rules established in the parametric set-up. Nevertheless, once a suitable set-up is implemented, variations can be accomplished in less time and with higher quality.

Several approaches were pursued regarding parametric modelling. They range from thedevelopment of a ship parametric modelling tool (FRIENDSHIP-Modeler) via the integration ofparametric capabilities in a well established ship design system (NAPA) to more restricted butsimpler methods like the parametric definition of shape deformation functions (GMS/Facet). Inaddition, the exploitation of general purpose CAD systems was investigated. This resulted in a setof tools available for practical use, from which a user may choose depending on the designenvironment and the optimisation task at hand.

2.1 Ship parametric modelling – FRIENDSHIP-Modeler

The FRIENDSHIP-Modeler [7] , developed by the Technical University Berlin since 1995, wassubstantially extended and adapted to the needs of practical design environments. The approachfavoured within the modeller differs from the methodology pursued in most general purpose CADtools, for details see Abt et al. (2001). Traditionally, the hull geometry is built up from points vialines to surfaces. A change in geometry is evoked by manipulating several points in spaceconcertedly which often is an interactive and time-consuming undertaking.

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In the FRIENDSHIP-Modeler the classic naval architect’s technique is adopted, see [2]: A set oflongitudinal lines – so-called basic curves – is layed out from which all information can be retrievedto subsequently establish the geometry. This is done in a three stage process:

1. Parametric design of a suitable set of basic curves such as deck, design waterline, flat-of-side, flat-of-bottom, centerplane etc. The basic curves are built in agreement with a fewprominent transversal curves like the main frame section, the transom, and, optionally,additional sections in the forward or aft body.

2. Parametric modelling of design sections derived from the basic curves.3. Generation of a set of surfaces that interpolate or closely approximate the design sections.

All curves and surfaces are modelled as B-splines. All B-splines are calculated by geometricallyoptimising for fairness while meeting the desired form parameters. In this way large flexibility andhigh shape quality can be accomplished. The design of complex hull shapes featuring bulbs,gondolas and skegs is provided for by attaching appendages to a bare hull, the appendages havingtheir individual and problem-oriented parameterisations. Efficient and effective form variations canthus be achieved and the approach is well-suited for automated optimisation, see e.g. [3] and [6].

During the project the Technical University Berlin has improved the features available within theFRIENDSHIP-Modeler with respect to the export of geometry via IGES files and several tool-specific file formats, the import via offset files, a graphical user interface (GUI) – which wasimplemented under GiD by CIMNE – and, most importantly, new modelling features to betterreflect local and global shape characteristics. The range of hull shapes that can be produced hasbeen extended from a topological point of view. Furthermore, the way the generation process ishandled has been improved by introducing an intelligent structure of parameters and theirdependencies. A human readable file format has been established which contains the entire shipgeometry in terms of form parameters. A form parameter file may incorporate just a few parameterswhen designing from scratch and building up the hull geometry step by step. It may also containquite many parameters to fine tune the shape in a manual or, alternatively, an automated process.

Figure 2 depicts two hull forms – i.e., bare hull plus bulb with the skeg omitted – produced from theFRIENDSHIP-Modeler. By varying just one parameter a substantial but well-behaved change ingeometry is obtained. As can be seen this enables the designer to manipulate specific features whiledeliberately keeping others. In the example of figure 2 the area coefficient of the design waterline ofthe forebody was reduced while the displacement was kept. The hull forms depicted are generatedfully automatically without touching any B-spline vertices by hand. Changes are exaggerated toshow the approach’s potential.

Figure 2: FRIENDSHIP-Modeler – Example parametric variation of forebody

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2.2 Template Approach – NAPA

The second CAD system that played a central role in the project was NAPA, the NavalArchitectural Package from NAPA Oy [9]. NAPA is a CAE system for initial and basic ship design,comprising, among other things, hull surface definition, production-level fairing, definition of theship’s compartmentation and naval architectural calculations.

In the NAPA system the hull surface is defined by a grid of curves, see figure 3. In the parametricrepresentation sets of geometric parameters have been utilised in the definition of these grid curves.As the grid structure varies significantly for different ships, templates for several ship types havebeen created within the project. The templates available comprise fast ferries, cruise liners,passenger/Ro-Ro ferries, container ships and frigates as well as single screw tankers and bulkers.

In order to be able to work with the parametric hull description in the NAPA system, a user friendlyand efficient graphical interface has been developed. The graphical user interface offers the endusers an easy way of adapting the templates to their own needs and, moreover, supports the creationof totally new parametric hull surface definitions. Partial surfaces or local areas of the ship hull, forinstance the bulb area, can also be parameterised while leaving the rest of the hull surface without aparametric definition.

The parametric approach has been made part of NAPA’s hull editor which is intended for themodification of hull surfaces or any surface defined by a curve grid. The curves and surfaces aredefined by alphanumeric descriptions. Instead of purely manipulating these alphanumericdescription, however, the hull editor works directly with the geometric components as shown on thegraphics display, and the effect of each change can be seen immediately. Further to the basic actionsapplicable to individual points and angles, the hull editor has other editing functions for executingmore complex actions.

Figure 3 presents the main window of the hull editor with the parametrically described hull of acontainer ship. The stem curve is highlighted to show its definition. Via the parametric descriptionconcerted changes in geometry can be brought about with fewer entities than with NAPA’sconventional shape representation.

Figure 3: NAPA – Main window of hull editor

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2.3 Shape Transformation Functions – GMS/Facet

A third option developed and applied in the project does not rely on a complete parametricdescription of the hull shape itself, but on a shape definition consisting of the original shape plusparametric deformations applied to it. This development has been done by MARIN, andimplemented in GMS, Marin's CAD system for hydrodynamic hull form design.

The incentive for this alternative development was as follows. Suppose that one already has aninitial hull form given as a surface description in the CAD system. Optimisation using a parametricdescription then would first require a redefinition of the same hull form, which takes time and maymean a loss of detail and precision.

Instead, a procedure has now been created in which a designer defines parametric deformations tothe original hull. Rather than manipulating control points individually, a group of control points isselected that will be affected by the deformation. Secondly, the deformation is specified as a set ofsingle-parameter translation functions that will be applied to the selected control points.

This being done, a one-parameter family of hull forms is defined. By subsequent furtherdeformation specifications, more parameters can be involved. Once a family of hull shapevariations has been defined that is considered sufficient for the next optimisation step, theinteractive design session is closed, and any hull form variation, including a suitable hull panelling,can be generated in batch by a single command giving the desired values of all parameters.

Figure 4 shows some examples of variations of an initial bulbous bow shape, all defined bydifferent single-parameter deformations. It has appeared that the system provides a large flexibilityand freedom in shape generation, retains the smoothness of the original hull, and can be appliedimmediately to practical cases. On the other hand, the deformation modes need to be specified forevery case anew, and efficiency of this process is crucial; a requirement satisfied by theimplementation in the Graphical User Interface of GMS, with instant visualisation of thecorresponding hull shapes. Current experience indicates the approach is very well suited toincorporation in a design cycle in which a limited number of parameters is addressed at a time, andthe designer still has an important role in the decision on what variations to consider.

Figure 4 : GMS/Facet - a variety of bulbous bow shapes, defined by different single-parameterdeformations to an original shape.

3 CFD ENHANCEMENT

For hydrodynamic assessment of ship hulls in the optimisation process, CFD codes play animportant role. Their use in the optimisation chain requires they are accurate, fast, reliable,automatic, and that they communicate with the other components in the chain. In the first stage ofthe project, (potential flow) panel codes have been used, which already largely satisfied thesecriteria and provided immediate results. Due to the substantially higher computational effortassociated with RANSE computations, these required a greater effort to achieve solutions that lendthemselves to practical application in an automated optimisation environment. Today, practical

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optimisation applications can already be envisaged using panel codes and mean term exploitationcan be expected for RANSE methods. This work concerned a set of the most widespread CFD toolsfrom several European institutes. A summary of the main tools involved in the project is given intable 1.

3.1 Panel methods

Panel codes are probably the most widely used CFD tools in ship design. Given their robustness,versatility and price / performance ratio they have been adopted by a large number of model basins,shipyards and consultants. Ease of use and especially the speed of computations make them idealcandidates for use in the automated optimisation environment in FANTASTIC. The latter aspect isof great importance, especially in view of computer capacity usually available among thecompanies and institutes in the marine branch.

Three widely used non-linear panel codes for wave resistance predictions have mainly been used inthe project: RAPID from MARIN, X-PAN / SHIPFLOW from FLOWTECH , ν-SHALLO fromHSVA

All of these have already a long history of development and a long record of successfulapplications. Although the theoretical background of all three codes is quite comparable – all ofthem are using singularity distributions to model the ship hull and further de-singularised sourcesfor the modelling of the free surface – the individual prerequisites for setting up a computationalmodel and running the code for a specific case are quite different.

The panel codes need as input a description of the hull form (variations) as generated by a CADsystem; usually in the form of a panel mesh. The generation of suitable hull panel meshes is a majorissue. Some of the codes imbed own mesh generators, other rely on external tools, while also someof the CAD systems have mesh generation capabilities.

As the project involves two major CAD systems for marine applications, NAPA and FRIENDSHIP,as well as additional tools in use with other partners, the first issue was to interface the CAD toolswith the panel codes. Table 1 shows the range of CAD-, mesh generation and CFD (panel codes) -tools finally used in the context of FANTASTIC. Two kinds of connections could be established:either, via an IGES file written by the CAD system and read in by the panel generator; or by directgeneration of a panelling suitable for the different panel codes inside the CAD system.

In a second step, the automation of the panel mesh generation has been addressed by the codeproviders. This aspect is of utmost importance when using the CFD tools in an optimisationenvironment which would be almost useless when the process would be dependent on a manual oruser driven mesh generation. Templates and macros have been developed that allow for meshgeneration of parametric variants of a given design. These have been applied to several test cases inthe course of the project.

Due to the work in this field, a significant number of combinations of the tools mentioned in Table1 was made possible, especially between the parametric modellers and panel codes, with direct orIGES links. Consequently, a variety of optimisation chains could be composed. These were thenused in the project in massive, automated, calculation of design variations, and proved to be robustenough for actual exploitation.

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3.2 RANSE methods

Hullform optimisation for a ship is a complex problem involving a range of dependencies. Certainlythe viscous dominated flow at the stern of the ship and the propeller inflow are decisive factors forthe final performance of the ship. Therefore, parallel to the work on panel codes the enhancement ofRANSE codes to be used in an optimisation environment has been addressed.

Again three main codes have been selected by FANTASTIC’s CFD partners. These encompassMARIN’s PARNASSOS, SHIPFLOW/CHAPMAN from FLOWTECH and COMET which hasbeen used by HSVA. RANSE codes require 3-d volume grids as inputs. Today these grids do notlend themselves easily to totally automatic grid generation. The work in the project has addressed apartial automation of the process, and modification of volume grids based on templates. In addition,due to developments on the solver, a greater flexibility in grid generation has been created to reducethe time spent on grid generation.

Computational performance is a major issue when speaking RANSE codes. Other than panel codeswhich can perform non-linear free surface computations in the order of a few minutes only, hereseveral hours are usually required for a single case computation, which is hardly bearable in anautomatic optimisation when a large number of design variants must be computed. Thusperformance and efficiency matters have been addressed. Improvement in the Parnassos solutionalgorithms have substantially speeded up multiblock computations. Also parallelisation is anappropriate means to increase speed. For the Parnassos solver, the turnaround time has beenreduced to 20 minutes, for a full-scale RANS computation (without free surface) on a grid of 1million cells, using 8 processors on a supercomputer. Such computation times bring optimisationwithin reach, and steps in that direction are being taken now. Significant advances have been maderunning RANSE codes on parallel PC-clusters, e.g. at HSVA.

Shape generation and variationNapa ;Friendship ;GMS ;E4;Catia

Grid generationSpecific; GiD; Facet; Newpangeo;ICEM; GridGen

Calculationν−shallo (HSVA): Rapid (Marin);Shipflow (Flowtech); Parnassos;Chapman; Comet; Warp; Soap;FluentData extraction-Post-processingSpecifically developed; Tecplot;GiD; FieldView

Main involved tools and links

OptimisationXopt(MMA); Chwarismi ;modeFRONTIER

Table 1: Overview of main tools and links worked on in the project (left), list of tools involved in applications (right)

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An alternative approach to reduce the computational effort is to reduce the number of computationsneeded in an optimisation. With this objective, Chalmers University investigated the use of adjointequation approaches for the assessment of sensitivities of the flow to elementary variations, withRanse methods. This is to be used to outline trends around given design points, and also in gradientbased optimisation methods.

4 OPTIMAL DESIGN TECHNIQUES

The objective within the project was to call for optimisation techniques in view of the enhancementof ship design procedures, especially applied to hydrodynamics. It was thus necessary to findapproaches that ensure the global validity of optimal design approaches, and that allow morededicated and refined hydrodynamic design optimisation.

As regards optimal design approaches, and after some years of investigations [5], it is now obviousthat each optimisation problem has its own specificity that cannot be dealt with by any universalalgorithm, and that a real optimisation problem is basically multi-objective. So it appears thatrelevant systems must offer an environment and a set of tools that allow the best choice of tools, orcombination of tools, to achieve possibly conflicting goals and allow decision making. This mustinclude:- intuitive tools for the integration of calculation chains, allowing complex logics, and thus able to

address real life cases where conditional process must be ensured (eg stopping calculation assoon as some criteria are not satisfied, to avoid useless computation…)

- exploitation of most recent technologies in order to address remote calculations inheterogeneous environments, concurrent calculations, maintenance and readability of full designdatabase, portability of software and data, etc…

- tools and algorithms for an efficient exploration and analysis of the design space, including:- design of experiments- response surfaces, including classical approximation functions but also more elaborate ones,

able to deal with non regular functions involved in real problems (e.g. neural networks)- optimisation algorithms, adapted to local search involving smooth functions (e.g. gradient

based methods…) but also able to search in complicated design spaces involving nonregular functions (e.g. genetic algorithms), and to really deal with multiple objectivesproblems. This last point is of prime importance for practical design problems, which arevery rarely naturally mono-objective ones.

- multi-criteria decision making tools, that help the designer to investigate pareto fronts andoutline trade-offs.

- efficient analysis tools for a quick and good understanding of the design space.All these features have to be easily combined to best fit to requested search strategies.

Numerous tools and algorithms were investigated in the project, and used in optimisation searches(e.g. Method of Moving Asymptotes, by Chalmers university). Some were specifically developed inexisting environment (e.g. simplex and moga, by Napa Oy). More integrated optimisationenvironments, that meet most of the above requirements, were also investigated. One of these, themodeFRONTIER package, initially developed on the basis of an EC funded project [8], was chosenas the central optimisation package in most applications in the project.

5 APPLICATIONS

The development done in parametric modelling, CFD enhancement, optimal design approaches, andthe communication between all these components, made it possible to set up several ship

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optimisation chains in practical design environments. A number of end users thus have validatedand evaluated the approach. Examples are given below.

5.1 Optimisation of a fast monohull

Applications tested at FINCANTIERI concerned fast ro-ro vessels, frigates and fast ferries. Whilefor some ship types, the hull form is often optimised for resistance and propulsion only, in the caseof a fast ferry seaworthiness is an important goal and needs to be tackled early in the designprocess. The hull shape needs to have both low resistance and good seakeeping qualities, withparticular attention to passengers’ comfort.

We here consider a Medium Deep Vee (MDV) monohull developed by FINCANTIERI, that in thelast years has designed and built a number of MDV's for the Mediterranean. The one consideredhere has Lpp between 128 m and 138 m. (varied during the optimisation), a required transportcapacity of about 1800 passengers and 460 cars, and a design speed of 40 knots. The ship wasmodelled as shown in table 2. The optimisation was carried out with modeFRONTIER on theFRIENDSHIP-NEWPANGEO-WARP/SOAP calculation chain, and consisted of two phases.

Phase I was a preliminary investigation at the beginning of the design process, when the target hullwas defined only in terms of transport capacity. The objective was to identify the main particularsto minimise the calm water resistance while maximising the comfort of the passengers. The comfortis measured through the Motion Sickness Index (MSI) evaluated at 4 different locations on the shipand considering all headings and the probability of occurrence of each Sea State in the geographicalarea where the vessel will operate. The calm water performance, i.e. RT/cars, is evaluated at thedesign speed of 40 knots, while the MSI is evaluated for 30 knots to take into account the voluntaryspeed reduction in the higher Sea States.

Free variablesLength +/- 10%Beam +/- 1 carDraft +/- 10%

KNdraftTran +/-15%KNzMaxBeam +/-200%KNmaxBeam 0.85 Beam

Constraints Figures of meritDisplacement +/-8% RT/cars at 40 knots RT/ ∆ at 40 knots

GMT Monitored Averaged MSI at 30 knotsTable 2: problem definition

The investigation of the design space started with a Design of Experiments (DoE) of 100individuals created by the parametric modeler and evaluated with the CFD and seakeeping codes.Fig. 5 clearly shows the effect of the main dimensions. The best design here is nr. 50 (highlighted inthe figure). Compared with the worst feasible designs, design nr. 50 means a gain in RT/cars of26%, while the improvement in terms of MSI amounts to 19%.

Phase II consists in a refinement of design 50. Here the main dimensions are fixed, thedisplacement is allowed to vary in a +-1% range and the variable parameters are related to morelocal features of the ship geometry. In this case the measures of merit are total resistance (RT) at 40knots, vertical acceleration at stern and bow in sea state 4, at 30 knots; and number of bow

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slamming events per hour, in sea state 4 at 30 knots; and are, therefore, mostly related to seakeepingcharacteristics.

RT/cars vs Length RT / ∆ vs Draft

MSI vs KnzMaxBeam MSI vs LengthFigure 5: Effect of main parameter on performances

In this case the optimisation was made using a multi-objective genetic algorithm (MOGA) followedby a gradient search. For the latter a global figure of merit has been used, combining all measures ofmerit mentioned above, non-dimensionalised with respect to the values of design 50.

The result of this combined search is a design that has a seakeeping improved by 6% in terms ofvertical accelerations and 10% in terms of number of slamming events, but has a 3% increase intotal resistance compared with design 50. This is considered acceptable, being a reasonable trade-off between seakeeping and resistance.

These studies have been carried out at the technical departments of FINCANTIERI and CETENA.The optimisation approach proved to be robust, to lead to realistic designs and to give relevant andpromising improvements. While verification in a towing tank has not been done for this particularoptimisation, past experience has already proved the realism of CFD calculations.

5.2 Other applications

IZAR has carried out an optimisation of a frigate type ship, with goals addressing resistance,calculated with the FRIENDSHIP+FACET+RAPID calculation chain, as well as manoeuvring andseakeeping performance assessed by formulas specific for this type of ship, all being involved in themodeFRONTIER environment. The search was done using MOGA algorithms, response surfaces,and a number analysis tools like t-student analysis that gives information on the sensitivity to freevariables. Multi-criteria decision making tools were also used to help defining trade-offs among thePareto set. Efficient calculation chains could be set up in the existing design environment, and thebenefit of optimisation approaches could be assessed, and ways of improvement defined.

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Many other practical applications, e.g. for ro-ro, naval, and container ships, were made toinvestigate the capabilities and performance of the design approaches; many different combinationsof the tools listed in Table 1 were applied. As regards RANSE methods, most of the work addressedimprovement of performance and automation; but some first restricted, optimisations weresuccessfully performed. This in particular demonstrated the applicability of genetic algorithms,combined with response surface techniques, to CPU-intensive applications.

All these applications brought, for the first time, a significant experience on the different aspects ofthe developed approaches.

5.3 Common demonstration case

In order to demonstrate the applicability and potential benefits of the developed methodology, afinal common optimisation exercise was undertaken, on a “generic” hull form for a medium speedROPAX vessel (Fig. 6), supposed to be representative for a class of modern ships, at a FroudeNumber FN = 0.311. The initial design was a transformed version of an existing ship, but mainparameters and design speed were modified. So the initial design was sub-optimal and providedsufficient room for improvement. Three parametric hull form modification approaches and threepanel codes were used to optimise the hull form from the resistance point of view. The initial designand the – agreed – optimised version will be compared in a model test, which was not accomplishedat the time of this paper. Some results will be presented at the conference.

Total resistance vs design id

Figure 6: common fanta_ro test case, some variations and first investigations

6 CONCLUSIONS

A large amount of work was dedicated to the enhancement of tools and links, that can be combinedin many different calculation chains which can be operated with reduced manpower. This is alreadya very positive outcome of the project, even if it is only a necessary condition to go further in thefield of optimal design.

Initial shape

Alternative 1

Alternative 2

1

2

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Major progress was made in parametric modelling, which is of prime importance regardingcapabilities to consistently investigate numerous variations during design, and especially whenoptimisation techniques are involved. Several approaches, each one corresponding to specific needs,are now available. The FRIENDSHIP-Modeler describes and generates the entire hull surface froma limited parameter set related to higher-level geometrical properties. NAPA, meanwhile, assemblescontrol points by prescribing explicit relations between control point coordinates, and puts these ina template which then defines a family of shapes for a limited number of parameters. GMS/Facetgroups control points in terms of a user-selected box and applies user-defined transformationfunctions with a few parameters.

The next step consisted in providing tools that actually exploit these modelling and calculationtools, towards optimal design. Advantage was there taken of the most recent technologies in thisarea, that allow efficient integration of calculation chains, extensive exploration of the design space,including multi-objective search that are of prime importance for real life problems. The projectmade it possible to largely investigate all the possible techniques, identify best strategies for givenproblems, and produce guidelines for further exploitation.

The first applications to relevant test case show the relevance of these approaches, and theircapacity to be actually used and to bring benefits, in the ship design areas where calculation toolsare already valid and current practice. Immediate use of this can be expected after the project.

As regards more complicated applications, eg involving Ranse solvers, some work is remaining tomake it current practice, but some promising applications let expect it in the near future.

7 ACKNOWLEDGEMENTThe work presented in this paper was performed within the EC funded Project FANTASTIC,G3RD-CT 2000-00096, a R&D project on ‘Functional Design and Optimisation of Ship HullForms’. The Project Partners are FINCANTIERI, SIREHNA, FSG, IZAR, HSVA, TUB, NAPA,MARIN, FLOWTECH, SSPA, CHALMERS, CIMNE, SINTEF, CETENA.

8 REFERENCES1. Abt, C.; Bade, S.D.; Birk, L.; Harries, S. (2001) “Parametric Hull Form Design – A Step

Towards One Week Ship Design,” 8th International Symposium on Practical Design of Shipsand Other Floating Structures ·PRADS 2001, Shanghai.

2. Harries, S. (1998) “Parametric Design and Hydrodynamic Optimization of Ship Hull Forms,”Dissertation, Technische Universität Berlin; Mensch & Buch Verlag.

3. Harries, S.; Valdenazzi, F.; Abt, C.; Viviani, U. (2001) “Investigation on OptimizationStrategies for the Hydrodynamic Design of Fast Ferries,” FAST'01, Southampton.

4. Larsson, L. et. Al., (2000) “Gothenburg 2000 – A workshop on numerical ship hydrodynamics”,Gothenburg, Sweden, Chalmers University, Report CHA/NAV/R-02/0073

5. Maisonneuve, J.J., (2002), "Sirehna's background in optimal design", internal report.

6. Valdenazzi, F.; Harries, S.; Viviani, U. Abt, C. (2002) “Seakeeping Optimisation of FastVessels by Means of Parametric Modeling,” HSMV02, Naples.

7. FRIENDSHIP-Modeler Web Site: http://www.FRIENDSHIP-Systems.com

8. modeFRONTIER Web Site: http://www.esteco.it

9. NAPA Oy’s Web Site: http://www.napa.fi