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CASD: Computer Aided Ship Design

Panagiotis Kaklisjoint work with

A.-A.I. Ginnis, K.V. Kostas & C. Feurer

National Technical University of Athens (NTUA)School of Naval Architecture and Marine Engineering (Sname)

Ship Design Laboratory (SDL)

October 5, 2010

(NTUA/SDL - CAGD/CAD/VR Group) SAGA, Fall School 2010 October 5, 2010 1 / 26

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preamble

a bit of history

in Farin’s ”History of Curves and Surfaces in CAGD” it is stated: Theearliest recorded use of curves in a manufacturing environment seems togo back to early AD Roman times, for the purpose of shipbuilding.

A ship’s ribs were produced based ontemplates which could be reused manytimes. Thus a vessel’s basic geometry couldbe stored and did not have to be recreatedevery time. These techniques were perfectedby the Venetians from the 13th to the 16thcentury.

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preamble

a bit of history

The form of the ribs was defined in terms of tangent continuous circulararcs, NURBS in modern parlance.

Ship hull was obtained by varying theribs’ shapes along the keel, an earlymanifestation of today’s tensorproduct surface definitions.

No drawings existed to define a shiphull; these became popular inEngland in the 1600s.

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preamble

a bit of history

The classical spline, awooden beam which is usedto draw smooth curves, wasprobably invented then. Theearliest available mention of aspline seems to be from 1752by Monceau.

This shipbuilding connection, described by Horst Nowacki (2000), was theearliest use of constructive geometry to define free-form shapes.

More modern developments linking marine and CAGD techniques may be found in, e.g.,Theilheimer and Starkweather (1961), Berger et al (1966), Mehlum and Sorenson(1971) and Rogers and Satterfield (1980).

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preamble

a special issue on CASD (Elsevier, JCAD, vol. 42, 2010)

CASD: Some Recent Results and Steps ahead inTheory, Methodology and Practice

dedicated to Prof. H. NowackiG. Holbach (TUB, DE), X. Ye (Zhejiang Univ., CN) and PK (NTUA, GR)

1 Five Decades of Computer-Aided Ship Design

2 Mesh-based Morphing Method for Rapid Hull Form Generation

3 Hull-form Optimization in Calm and Rough Water

4 An Integrated Method for Predicting Resistance of Low-cB Ships

5 Springback Adjustment for Multi-point Forming of Thick Plates inShipbuilding

6 Application of a New Multi-agent Hybrid Co-evolution Based ParticleSwarm Optimization Methodology in Ship Design

7 Holistic Ship design Optimization

8 VELOS: a VR Platform for Ship-evacuation Analysis

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preamble

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preamble

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preamble

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preamble

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preamble

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preamble

CASD as a MOP

CASD as a Multiobjective Optimization Problem (MOP)

Given a set of geometric, engineering and operational constraints findan optimal, versus a set of costs, ship hull.

There is no unique optimalsolution but rather a set ofefficient solutions, also knownas Pareto-optimal solutions,characterized by the fact thattheir cost cannot be improvedin one dimension withoutbeing worsened in another.

The set of all Pareto solutions,the Pareto front, represents theproblem trade-offs.

Sampling this set in arepresentative manner is a veryuseful aid in decision making.

CASD as a MOP

a MOP example in CASD

2 costs: an energy- and anenvironment-oriented cost(Papanikolaou(2010)):

1 Rt = Rf + Rw where Rfdenotes the frictional and RWthe wave resistance

2 W: the average wave heightalong a longitudinal wave cutat a certain distance from thevessel’s center line.

CASD as a MOP

basic elements of MOP in CASD

design parameters:

• ship’s main dimensions (length, beam, side depth, draft) or ratiosbetween them, possibly extended to include the entire ship’s hullform→ SHIP PARAMETRIC MODEL

• the arrangement of spaces

• (main) structural elements

• networking elements (piping, electrical, etc)

costs (criteria, merit functions, goals):

• economic (profit of the initial investment)

• performance (in calm water and in seaways)

• safety

• ships’s strength (including fatigue)

CASD as a MOP

basic elements of MOP in CASD

constraints:

• owners’s specifications related to:• cargo capacity (deadweight, payload)• service speed, range• financial data (profit expectations, interest rates),• market conditions (demand and supply data)• costs for major materials (steel, fuel), etc.• the above list may be extended with criteria characterized by uncertainty

with respect to their actual values and being assessed by probabilistic models

• inequalities/equalities resulting from regulatory frameworks pertainingto safety

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an OP in CASD

optimizing a parent container ship versus wave resistance

Given a parent container ship, modifyappropriately its geometry so thatthe cost functional

∑3i=1wiR(vi) is

minimized, with R(v) denoting thewave resistance of a ship advancingwith constant forward speed v.

speed vi (knots) 20 25 27weight wi 0.35 0.50 0.15

Container ships represent commercially interesting ship hulls while at thesame time are slender enough to ensure that the Neumann-Kelvin modelwill provide a satisfactory approximation of the ship wave resistance.

slenderness ⇐⇒ BL = T

L = o(1), L : length, B : beam, T : draft︸︷︷︸(NTUA/SDL - CAGD/CAD/VR Group) SAGA, Fall School 2010 October 5, 2010 10 / 26

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an OP in CASD

optimizing a parent container ship versus wave resistance

Given a parent container ship, modifyappropriately its geometry so thatthe cost functional

∑3i=1wiR(vi) is

minimized, with R(v) denoting thewave resistance of a ship advancingwith constant forward speed v.

speed vi (knots) 20 25 27weight wi 0.35 0.50 0.15

Container ships represent commercially interesting ship hulls while at thesame time are slender enough to ensure that the Neumann-Kelvin modelwill provide a satisfactory approximation of the ship wave resistance.

slenderness ⇐⇒ BL = T

L = o(1), L : length, B : beam, T : draft︸︷︷︸(NTUA/SDL - CAGD/CAD/VR Group) SAGA, Fall School 2010 October 5, 2010 10 / 26

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an OP in CASD

Neumann-Kelvin model

basic hypotheses:

• ideal (⇔ incompressible, inviscid,irrotational) liquid → potential theoryfor the flow field

• linearized free-surface condition on theplane z = 0

• exact body-boundary condition

• radiation condition:outgoing waves decaying as

O(R−1/2), R =√(x2 + y2)

• Boundary Integral Equation (BIE) over the wetted hullsurface

• hybrid method: coupling the Finite Element Method(FEM) in a finite volume around the ship with amultipole expansion method in the exterior of the finitevolume

−→U : ship velocityϕ: disturbance potential

w =−→U +∇ϕ: total velocity

p = p∞ + ρ2(U2 −w2) − ρgz:

pressure

η = (U/g)ϕx(x, y, z = 0):

free-surface elevation

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an OP in CASD

basic hypotheses:

O(R−1/2), R =√(x2 + y2)

p = p∞ + ρ2(U2 −w2) − ρgz:

pressure

η = (U/g)ϕx(x, y, z = 0):

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an OP in CASD

basic hypotheses:

O(R−1/2), R =√(x2 + y2)

p = p∞ + ρ2(U2 −w2) − ρgz:

pressure

η = (U/g)ϕx(x, y, z = 0):

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an OP in CASD

basic hypotheses:

O(R−1/2), R =√(x2 + y2)

p = p∞ + ρ2(U2 −w2) − ρgz:

pressure

η = (U/g)ϕx(x, y, z = 0):

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ship-hull PM

ship-hull Parametric Model (PM)

“Given a parent container ship, modify appropriately its geometry”~w�the availability of a SHIP PARAMETRIC MODEL, that is able to:

• reconstruct the parent container hull

• construct a rich set of container hulls that:

1 fulfill a set of constraints inherited from the parent hull2 remain shape-similar to the parent hull.

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ship-hull PM

constraints inherited from the parent hull

global parameters constraintoverall length ±5%

draft ±10%displacement ±1%

length of parallel midbody ±10%start of the Flat Of Bottom (FOB) ±10%

• displacement: The weight of water of the

displaced volume of the ship, which equals

the weight of the ship and cargo.

Parallel Midbody

FOS Fore

FOS Aft.

FOB Aft.

FOB Fore

M0 M1

M2

M3

M4

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ship-hull PM

constraints inherited from the parent hull

local (bow, bulb, stern) parameters constraintbulb length +30%

transom behind AP ±10%stern root height ±10%stern root start ±10%

FPAP

Baseline

WLS_TransomSlopeAngle

S_TransomBehind

S_Pr

op

elle

rCle

aran

ce

S_Ro

otH

eig

ht

S_Sh

aftH

eig

ht

S_ShaftExit

S_RootStart

S_ShaftRadius

B_BulbRiseLength

B_BulbRise B_BulbLength

B_B

ulb

Top

Posi

tio

n

B_B

ulb

Cen

ter

B_ForwardOverhang

B_BulbRadius

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constructing a PM for container ships

constructing a parametric model for container ships

Design parameters can be classified into 4 groups:

1 The global group ← ship’s principal dimensions [effect: global]

2 The 2nd category ← parameters involved in the generation of themidship part [effect: global, as the midship part is both the initialand supporting entity in the construction of the hull parametricmodel]

3 3rd and 4th categories ← parameters involved in the generation ofthe bow and stern parts of the ship [effect: local]

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constructing the Control Curve Network (CCN)

Design parameters in conjunction with shape-preserving interpolationtechniques provide CCN(0) ← the initial version of Control CurveNetwork.

CCN(0) comprises ship’s profile, FOS & FOB boundary curves, midshipsection, sections capturing shape transition in bow and stern areas.

on shape-preserving interpolation techniques → the lecture by Prof. Menelaos

Karavelas on Thursday.

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constructing the Control Curve Network (CCN)

Design parameters in conjunction with shape-preserving interpolationtechniques provide CCN(0) ← the initial version of Control CurveNetwork.

CCN(0) comprises ship’s profile, FOS & FOB boundary curves, midshipsection, sections capturing shape transition in bow and stern areas.

on shape-preserving interpolation techniques → the lecture by Prof. Menelaos

Karavelas on Thursday.

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enhancing CCN(0) with tangent information

CCN(0) is used in conjunction with constraints apparently induced fromship’s geometry, e.g.,

• symmetry with respect to the ship’s center plane,

• planarity of FOB/FOS area,

for producing cross-tangent ribbons over its elements.

CCN(0)⋃{unit cross-tangent-vector ribbons} = CCN(0,t) ←

enhanced initial version of CCN

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enhancing CCN(0,t) with auxiliary curves

Using information inherited from CCN(0,t) and a set of internalparameters, CCN(0) is enriched with a set of auxiliary curves in order to:

• use them as shape stabilizers in the transitional areas of bow andstern, where shape changes rapidly,

• eventually have a network of principally quadrilateral topology

CCN(0)⋃{auxiliary curves} = CCN(1) ←

semifinal version of CCN

as with CCN(0), CCN(1) can be enhancedalong its elements with unit cross-tangent-vector ribbons →

CCN(1,t) ←final version of CCN.

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examples of auxiliary curves:

• guide curves c W1,c W2 andc W3 secure and control the saddleshape the waterline-entry area.

• guide curve c BowG1 separates thebulbous part from the bow area andpasses through the inflection pointof c S2.

c_S1

c_W

c_W1

c_W3c_W2

c_BowProfile

2

4

3

c_BOW

SEP

c_S1c_S2

c_W

c_W1

c_W3c_W2

c_BowProfile

c_BowG1

c_Deck

Midship Sectionc_FOB_bow

c_FOS_bow

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container-ship hull generation

The sought-for G1−continuous surface is then obtained by solving a seriesof Hermite-type local problems of the form: construct a patch thatinterpolates a closed boundary along with its tangent-plane distribution,defined by CCN(1,t).

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a PM implementation

implementing the proposed PM for container ships

parent ship

KRISO Container Ship (KCS) is part of the CFD Workshop benchmarksuit of problems; see at the home page of the CFD Workshop in Tokyo2005.

KCS has been proposed by the Norwegian

Classification Society DNV (Det Norske

Veritas), NTUA’s partner in the FP7

project EXCITING: EXACT GEOMETRY

SIMULATION FOR OPTIMIZED

DESIGN OF VEHICLES AND VESSELS

(2008-2011), coordinated by Professor Bert

Juttler (JKU).

http://www.nmri.go.jp/cfd/cfdws05/

http://exciting-project.eu

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a PM implementation

basic features of PM implementation

• parametric-modeling environment: CATIAr

• generation process controlled by 29 design (exposed) and 46 internalparameters

• the final Control Curve Network CCN(1,t) consists of quintic NURBScurves

• the generated semi-hull is at least G1−continuous and comprises 34surface patches that are principally tensor-product NURBS surfaces ofdegree 5x5

• generation of a hull instance for a given parametric set takes less than5 sec on a modern pc

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a PM implementation

performance issues

is PM able to reproduce the parent hull KCS satisfactorily?

KCS (above) and PM instance (below)

integral properties KCS PM instance

∇(m3) 79, 727.00 79, 719.00

LCB (m) 107.49 107.49

Cb (m) 0.677 0.677

• ∇: volume displacement

• LCB: Longitudinal Center of Buoyancy

• block coefficient Cb=∇/LBT

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a PM implementation

performance issues

can PM guarantee the integrity of the outcome?

is PM able to produce a rich set of container hulls that remainsimilar with the parent hull KCS?

hull instances with significantly varying length between perpendiculars:

Lpp = 146m (above), Lpp = 470m (below)

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a PM implementation

performance issues

hull instances with varying the design parameter Bulblength:

B BulbLength=8.8m (above), B BulbLength=6.5 (below)

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a PM implementation

issues of interest

1 investigate/modify/enrich the methodology for solving theHermite-type local problems versus the:• self-intersection risk• need to handle shape constraints

2 measure shape similarity between PM instances

3 introduce a notion of measurable ”richness” of PM-outcome sets

4 develop an optimization-oriented LOD approach for PM instances

5 investigate the compatibility/efficiency of the geometryrepresentation, provided by PM, versus the method used for solvingthe NK problem ← isogeometric analysis

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references

[1] G. Farin, A History of Curves and Surfaces in CAGD.

[2] H.L. Duhamel du Monceau. Elements de l’Architecture Navale ouTraite Pratique de la Construction des Vaissaux. 1752. Paris.

[3] H. Nowacki. Splines in shipbuilding. Proc. 21st Duisburgcolloquium on marine technology, May 2000.

[4] F. Theilheimer and W. Starkweather. The fairing of ship lines on ahigh speed computer. Numerical Tables Aids Computation, vol. 15,pp. 338-355, 1961.

[5] S. Berger, A. Webster, R. Tapia, and D. Atkins. Mathematical shiplofting. J Ship Research, vol. 10, pp. 203-222, 1966.

[6] E. Mehlum and P. Sorenson. Example of an existing system in theshipbuilding industry: the AUTOKON system. Proc. Roy. Soc.London, Series A, vol. 321, pp. 219-233, 1971.