a holistic methodology for the optimization of tanker design and

A Holistic Methodology for the Optimization of Tanker

Design and Operation and its Applications

National Technical University of Athens-School of Naval Architecture and Marine Engineering Ship Design Laboratory

Better Economics with a Safer Tanker (BEST++)

Diploma Thesis Lampros Nikolopoulos, MEng Thenamaris Ships Management Inc.

Prof. Dr. Ing. Apostolos Papanikolaou

Director Ship Design Laboratory http://www.naval.ntua.gr/sdl

Professor Kostas Spyrou, Associate Professor George Zaraphonitis

SNAME Greek Section Thesis Competition-17.01.2013

http://www.naval.ntua.gr/sdl

"A Holistic Method for the Optimization of Tanker Design and Operation and its Applications" , SNAME Thesis Competition, Lampros Nikolopoulos, NTUA-SDL, 17.01.2013

Contents

Introduction-Background to the Tanker Shipping Industry

Developed Methodology and Sensitivity Analysis

Case Studies on the Optimization of AFRAMAX Tankers

Perspective: Case Study on the Optimization of a VLCC

Conclusions, Discussion and Future Perspectives

Introduction: Background to the Tanker Shipping Industry

Background to the Tanker Shipping Industry

The Evolution of a Giant: First crude oil carrier: Glucklauf (1910), 3000 tonnes of Kerozene in 16 tanks

1945: T-2 and T-3 Tankers, 16000 and 18000 DWT

1966: Idemitzu Maru , 206000 DWT Large magnitude of scale economies

1975: Batillus Class, 550000 DWT

A re-active regulatory framework: 1967: Torrey Canyon (navigational error-grounding)

1978: Amoco Cadiz (loss of steering gear-grounding)

1989: Exxon Valdez OPA 90 and introduction of Double Hull

1998: Erika

2002: Prestige

Evolution of Tank Arrangement:


MARPOL 73/78

Phase out of Single Hull, SIRE and Vetting Inspections

Modern Tanker categories: Charter Rates Development:

Trade Routes: New Building Prices:


Background to the Tanker Shipping Industry Modern Economic Challenges

New Regulations for Ship Emissions Control: MARPOL Annex VI for Emission Control Areas (ECAs).

SOx and Nox limits for new engines (Tiered reduction)

Regulations for Efficiency (CO2 and fuel consumption performance): Technical Measures: EEDI, EEOI, SEEMP

Market Based Measure: CO2 fund, Fuel Levy etc.

International Convention for Ballast Water Management: Applicable from 2016.

Need for use of treatment technologies.


Background to the Tanker Shipping Industry Modern Environmental Challenges


Thesis Objectives Diploma Thesis of L. Nikolopoulos at NTUA:

“A Holistic Methodology for the Optimization in Tanker Design and Operation and its Applications”, supervised by Prof. A. Papanikolaou

Emphasis of method on the following design aspects:

Safety, especially minimization of probabilistic oil outflow

Efficiency , minimization of emissions, fuel costs

Competitiveness, increased profitability with reduced OPEX

Global and Risk-Based Approach, with the aim to generate a safer tanker which is also more competitive.

Holistic: Aristotle definition of «όλον» being greater than the sum of all parts

Employed software platform for this project is the Friendship Framework

Two Case Studies:

Innovative, shallow draft, twin skeg/screw AFRAMAX Tanker of 5X3 Tank Arrangement .

Conventional, single screw VLCC with a 6X3 Tank Arrangement (less detailed application-proof of applicability)

Design Methodology and Theory

The computations, assumptions and workflow of the analytical model

Calculations Workflow


Geometric Model

Initial Hydrostatic Calculation

Lackenby Variation

Tank Arrangement Modeling

Capacity Calculation

Water Ballast Calculation

Resistance Prediction

Machinery Calculations

Lightship Calculation

Deadweight Analysis

Capacity and Cargo Special Gravity Check

Stability and Loadline Check

Oil Outflow Calculation

Required Freight Rate Calculation

EEDI Calculation

lackenby.pptx

ResistancePrediction.pptx

Machinery Calculations.pptx

Lightship Calculations.pptx

Deadweight Analysis.pptx

Oil Outflow Calculation.pptx

RFR Calc.pptx

RFR Calc.pptx

Sensitivity Analysis of the Developed Methodology RFR Sensitivity


Case Study on the Holistic Optimizaiton of

AFRAMAX Tankers


HOLISTIC OPTIMIZATION STUDIES

OF TWIN SCREW AFRAMAX TANKER

MINIMIZATION OF: RFR

OOI

EEDI

TOTAL NUMBER OF GENERATED DESIGNS:20000

The G5 Tanker:

Tender Preliminary Concept Study

(VISIONS 2011)

Investigation of the Potential Use

of Deep Well Pumps for

AFRAMAX Tankers

(BEST++ Project)

Investigation of Structural Aspects

of NX3 Tank Arrangements for

AFRAMAX Tankers

(BEST++ Project)

MULTI VENTURE

Enviromentally Friendly and Efficient Tankers:

LNG as a fuel

Optimal Operating Speed

Bulb Optimization

New Propulsion Systems

(VISIONS 2012)

CASE STUDIES ON AFRAMAX TANKERS

PART THREE

PART TWO

PART ONE

Part One: Initial Design, Research and Analysis

Part One of Case Study The G5 Tanker

Original concept for shallow draft, twin skeg tanker with two longitudinal bulkheads was submitted as a proposal (“The G5 Tanker”) for the VISIONS Olympics Competition in March 2011.

Shortlisted idea, took the 4th place in the competition.

No optimization, just a concept illustrating the potential.

Need for better and more efficient hullform.


Part One of Case Study Potential Use of Deep Well Pumps

Undertaken for the joint BEST++ project.

Indicated a 2.5 mil $ additional costs for the installation of the pumps at a 6x2 AFRMAX tanker, without taking into account possible shipyard savings (cost estimates acc. to pump supplier).

Superior efficiency (shorter time at port) and drastic reduction of fuel costs for unloading (from 80000$/discharge to 27000 $/discharge, when operating in an ECA area)

Faster port operations means a better RFR performance (more annual trips, with the payback time of the equipment being approx. one year)

Estimated (then) cargo capacity increase of 2-3% due to the elimination of the pump room.


Part One of Case Study Structural Weight Comparison for NX3 Designs

Undertaken in 11.2011 in order to validate the assumptions taken in the previous related projects (BEST, BEST+).

Used an available 6X3 Reference Design, M/T NAVION BRITANNIA.

Modeled in POSEIDON as a reference design by use of the BEST+ structural design template.


Design I.D Longitudinal Members (t/m)

Longitudinal Members (tonnes)

Trans. Members (tonnes)

Trans. BHD (tonnes)

Total (tonnes)

Template_6X3 54,8 1932,92 383,7 230,1 2546,72

Template_5X3 54 1905,2 252,4 233,5 2391,10

Template_6X2 53,1 1888,48 392,5 167,8 2448,78

BEST_Optimized 50 1773,2 251 154,8 2179

Part Two: Global Optimization Studies

Design Concept Twin Skeg Arrangement


Elliptic Bilge of the midship section:


Design Concept Elliptic Bilge

Geometrical Modeling

Design Concept Tank Arrangement

NX3 tank arrangement was herein chosen by default: due to the superior performance in terms of accidental oil outflow (as

indicated by the TANKOPT results).

Number of longitudinal tanks reduced to 5 (instead of 6): compensate the increase in structural weight due to the introduction of a

second longitudinal bulkhead (approx. 200 tones weight).

Other ways to compensate the increase of structural weight: increase the tank size and capacity together

increase in displacement (due to a bigger Cb thanks to twin skeg).

Use of deep well pumps (instead of conventional pump room): Engine room bulkhead moved towards the aft of the ship.

Initial estimation of 2-3% increase

Increase was up to 6%.

Tank Variables: Double Bottom height

Double Hull Width

Mid Tank Width

Hopper angle and length in accordance with BEST+ results


Design Concept Tank Arrangement-Modeling


Optimization Principles


Design Variables

Design Constraints

Generation of Design Variants

Design Engine: NSGA II

Design Evaluation: -Oil Outflow Index

-Required Freight Rate -EEDI

Constraint Limit Upper Special Cargo Gravity <0.92 Lower Special Cargo Gravity >0.82 Deadweight <125000 tonnes Double Bottom Height (MARPOL limit) >2.0m Double Hull Width (MARPOL limit >2.0m Accidental Oil Outflow Parameter (MARPOL limit) <0.015 Draft (Port Restrictions) <14.8m


B FOB

FOS

D

T

Design Variables


Design Variable Lower Bound Upper Bound

Length Between Perpendiculars (m) 230 245

Beam (m) 43 48

Deck Height (m) 21.5 22.5

Draft (m) 14.2 14.7

Cb 0.855 0.87

LCB (% Lbp) 0.515 0.525

FOB (% B) 0.7 0.85

FOS (%D) 0.65 0.85

End of Parallel Midbody (% Lbp)

0.2 0.22 Beggining of Parallel Midbody (% Lbp)

0.7 0.75 Bulb Length (% Lbp)

0.025 0.03 Double Bottom Height (Tanks 2-5, m)

2.2 2.8 Double Hull Width (m)

2.1 3 Mid Tank Width (% Bcargo)

30 52 Design Speed (knots)

13 16

Optimization Stages A multi-staged Approach


1st Stage: Design Space Exploration Design of Experiment (DoE)

Sobol Algorithm producing 3000 variants

2nd Stage: Design Space Exploration DoE 2 and Design Speed Effect Investigation


3rd Stage: Formal Optimization with Genetic Algorithms NSGA II Design Engine producing 2500 variants

4th Stage: Formal Optimization with Genetic Algorithms ( I.D 2515)

NSGA II Design Engine producing 3000 (150X20) and 4500 (150X30) variants

I.D 314

I.D 2590, 1838,2515,2738

Dominant Variants for 2500 variants: I.D 2896, 1943, 2294, 2210, 1686, 2954

Dominant Variants for 4500 variants: I.D 3210, 1431, 4567, 4416, 4247, 559, 2111







3rd Stage: Formal Optimization with Genetic Algorithms NSGA II Design Engine producing 2500 variants (100X25)



I.D 314

I.D 2590, 1838,2515,2738









3rd Stage: Formal Optimization with Genetic Algorithms NSGA II Design Engine producing 2500 variants



I.D 314

I.D 2590, 1838,2515,2738



Two runs were made: First: 3000 variants generated by 150 Generations of 20 Population

Second: 4500 variants generated by 150 Generations of 30 Population

Reason for two runs: see the effect of population size on the solution and push the boundaries of

optimization

The variables, constraints and boundaries were the same for both runs.

First Run (150X20): Gaps in certain areas indicate that the population size was not adequate

Two peaks created: low OOI and low RFR values.

Designs dominate the 6X2, both in terms of OOI and cargo capacity.

Large cargo capacity for the majority

EEDI-RFR pattern almost constant.

RFR dominant variants appear to be EEDI dominant too

Inferior RFR-OOI performance


4th Stage: 2nd Genetic Algorithm Run Background


4th Stage: 2nd Genetic Algorithm Run 150 Generations with 30 Population: RFR vs. Oil Outflow

7

7,2

7,4

7,6

7,8

8

8,2

8,4

8,6

8,8

9

9,2

9,4

9,6

9,8

10

0,007 0,008 0,009 0,01 0,011 0,012 0,013 0,014 0,015

Req

uir

ed F

reig

ht

Ra

te (

US

D/t

on

ne,

10

00

$/t

)

Accidental Oil Outflow (Acc. MARPOL Reg. 23)

Second Optimization (150X30 Designs, Design Speed 15knots)

RFR vs. Oil Outflow 5X3 Twin Skeg

(4500 variants)

BEST+

I.D 2590 (a)

I.D 2515 (a)

I.D 3210 (b)

I.D 1431 (b)

I.D 4567 (b)

I.D 4416 (b)

I.D 4247 (b)

I.D 559 (b)

I.D 2111 (b)

6X2 Reference

Improvement of 40% in OOI

BEST OOI

BEST RFR

Possible compromise


4th Stage: 2nd Genetic Algorithm Run 150 Generations with 30 Population: EEDI vs. RFR

2,9

3

3,1

3,2

3,3

3,4

3,5

3,6

3,7

3,8

3,9

4

6 6,2 6,4 6,6 6,8 7 7,2 7,4 7,6 7,8 8 8,2 8,4 8,6 8,8 9

EE

DI

(Acc

. IM

O M

EP

C 6

2)

Required Freight Rate (USD/tonne, HFO 1000 $/t)

Second Optimization (150X30 Designs, Design Speed 15 knots)

EEDI vs. RFR

5X3 Twin Skeg

(4500 variants)

BEST+

ID 2590 (a)

I.D 2515 (a)

I.D 3210 (b)

I.D 1431 (b)

I.D 4567 (b)

I.D 4416 (b)

I.D 4247 (b)

I.D 559 (b)

I.D 2111 (b)

BEST OOI BEST RFR BEST EEDI

Frequent Dominant Variants indicated by utility functions


4th Stage: 2nd Genetic Algorithm Run 150 Generations with 30 Population: Vcargo vs. Oil Outflow

0,008

0,009

0,01

0,011

0,012

0,013

0,014

0,015

100000 110000 120000 130000 140000 150000 160000

Acc

iden

tal

Oil

Ou

tflo

w (

MA

RP

OL

Reg

. 23)

Cargo Carrying Capacity (cubic meters)

Second Optimization (150X30 Designs, Design Speed 15 knots)

Cargo Capacity vs. Oil Outflow 5X3 Twin Skeg (4500 variants)

BEST+

I.D 2590 (a)

I.D 2515 (a)

I.D 3210 (b)

I.D 1431 (b)

I.D 4567 (b)

I.D 4416 (b)

I.D 4247 (b)

I.D 559 (b)

I.D 2111 (b)

6X2 Reference

The scatter diagrams now are more dense.

V-shaped pareto front instead of peaks

The EEDI-RFR pattern remains the same.

The Lowest OOI has a satisfactory RFR performance

The Lowest RFR is at the upper boundaries of the variants size.

BEST-Trade-off: Frequently appeared in the ranking of the utility functions

Better RFR, OOI and EEDI performance than 6X2 AFRAMAX designs.


4th Stage: 2nd Genetic Algorithm Run 150 Generations with 30 Population-Comments


4th Stage: 2nd Genetic Algorithm Run 150 Generations with 30 Population-Design Ranking

0,697

0,698

0,699

0,7

0,701

0,702

0,703

0,704

0,705

0,706

3210 1431 2111 4604 3421 1812 3680 3240 2838 3675

U1: 1/3 EEDI, 1/3RFR, 1/3 OOI

0,756

0,758

0,76

0,762

0,764

0,766

0,768

0,77

U2:0.1 EEDI, 0.8 RFR, 0.1 OOI

0,665

0,67

0,675

0,68

0,685

0,69

0,695

U3: 0.2 EEDI, 0.2 RFR, 0.6 OOI

0,7

0,701

0,702

0,703

0,704

0,705

0,706

0,707

0,708

0,709

U4: 0.4 EEDI, 0.3 RFR, 0.3 OOI

0,692

0,693

0,694

0,695

0,696

0,697

0,698

0,699

0,7

0,701

0,702

U5: 0.2 EEDI, 0.4 RFR, 0.4 OOI

Optimization Results Dominant Variants Comparison

Results indicate an increase of the cargo structural weight which however is not influencing the RFR value which is decreased:


6X2

Reference I.D 2515 I.D 3210

OOI 0.0138 0.00841 -39.057% 0.009139 -33.78% Wst cargo 11077 t 13590 +18.49% 14261 t +22.32% Cargo Capacity 126764.7 m3 135154 m3 +6.21% 146642.7 m3 +15.68% RFR 8.347 $/t 6.7209 $/t -19.38% 6.513 $/t -21.97% Ballast Water 35378 m3 18699 m3 -47% 29287 m3 -17.2%

BEST+ I.D 2515 OOI 0.0142 0.00841 -40.77% Wst cargo 12132 t 13590 +10.72% Cargo Capacity 129644m3 135154 m3 +4.07% RFR 6.7299 $/t 6.7209 $/t -0.1% Ballast Water 35378 m3 18699 m3 -47%

EEDI 3.2814 gCO2/t 3.1843 gCO2/t -2.95%

Comparison of OOI performance with previous concepts


0,006

0,007

0,008

0,009

0,01

0,011

0,012

0,013

0,014

0,015

90000 100000 110000 120000 130000 140000 150000 160000

6X2 Flat (TANKOPT)

6X2 Corrugated (TANKOPT)

6X3 Corrugated (TANKOPT)

6X3 Flat (TANKOPT)

7X2 Flat (TANKOPT)

5X3 Twin Skeg

BEST+

Optimization Results Main Particulars


Principal Particular BEST+ I.D 2515 (a) I.D 4416 (b-2)

L (m) 250 244.41 244.94621 B (m) 44 45.843 47.949111 D (m) 21.5 22.04 22.139643 T (m) 14.8 14.6516 14.643671 Cb 0.85 0.85775 0.85667224 LCB (m) Not available 0.52354 0.52317235 FOB (%B) Not available 0.7028 0.815679 FOS (%D) Not available 0.6769 0.709159 Bulb Length (m) Not available 0.03077 0.026359 Displacement (tonnes) Not available 144332 151022 Height DB (m) 2.1 2.239 2.219 Width DH (m) 2.65 2.989 2.111 No. of Tanks 12 (6X2) 15 (5X3) 15 (5X3) Mid Tank Width (% B) NaN 45.643 45.164843 Cargo Capacity 98% 129644 135154 149214.1 Design Speed (knots) 15.6 15 15 Installed Power (kW) 13560 13955 14286 Lightship Weight (tonnes) 22070 22938 Deadweight (tonnes) 114923 122263 128084 Payload (tonnes) Not available 118511 124257 EEDI (t CO2/tonne*mile) 3.2814 3.184332 3.070161 RFR (USD/tonne) 7.54 7.623023 7.20385 Reg.23 Oil Outflow Index

0.0142 0.008476 0.010464

Operational Analysis-Optimal Speed Investigation of the optimal ship speed:

The ship were the RFR is minimum!

Three scenarios for fuel cost: 500, 750 (current price) and 1000 USD/tonne.

The 1000 $/t is very likely to come in effect with Ultra Low Sulphur Fuels

Speed Curves:


5

5,2

5,4

5,6

5,8

6

6,2

6,4

6,6

6,8

7

7,2

7,4

7,6

7,8

8

8,2

8,4

8,6

8,8

9

6 7 8 9 10 11 12 13 14 15 16 17

Req

uir

ed F

reig

ht

Ra

te (

US

D/t

on

ne)

Operating Speed (knots)

Speed-RFR Curves

HFO 1000 $/t

HFO 750$/t

HFO 500$/t

10.75 knots

11.7 knots

13 knots

Part Three: Multi Venture

All Electric, Dual Fuel Hybrid Propulsion System for a Tanker

Part Two: Multi Venture The All Electric Tanker

Participation in VISIONS 2012 Ship Design Olympics

Team: Lampros Nikolopoulos, Nikos Mantakos, Michalis Pytharoulis

Objectives for the Competition: Energy Efficient Tanker

Use of Alternative Fuels

Multi Venture: Hull Efficiency:

Results of Global Optimization

Optimized Bow

Propulsion Efficiency:

Wake Adapted Propeller

Use of LNG as a fuel

Use of Hybrid Technologies (e.g Fuel Cells)

Lifecycle Assessment of Environmental Performance

"A Holistic Method for the Optimization of Tanker Design and Operation and its Applications" ,

SNAME Thesis Competition, Lampros Nikolopoulos, NTUA-SDL, 17.01.2013

Bulb Optimization

Objectives:

Reduction of Wetted Surface,

Reduction of Wave Making Resistance

Computation:

Geometry built in FFW,

Minimization of Wetted Surface with NSGA II

Assessed by CFD code SHIPFLOW, using Potential Flow Theory (XPAN code)

Constraints: Displacement and Deadweight Constraint (up to 1% deviation)

Tank Capacity Constraint (up to +1% deviation).

Result: 42% reduction of the Wave Making Resistance (compared to original)

1.5% reductional of total resistance and installed power


Multi Venture

I.D 2515

All Electric Tanker Load Analysis

Propulsion Loads: as before (2stroke)

Use of redued resistance from bulb optimization

Auxilliary Loads: calculated based on equivalent size Bulk carrier data

Normal Sea going, Maneuvering, Cargo Unloading and Harbour Conditions

FRAMO power pack for cargo pumps

Propulsion Motors: Chosen from ABB according to Azipod range (same internal motor)

Type 25 : ~12 MW at 100 RPM

Generators: Medium Voltage (6600 V, 60 Hz)


All Electric Tanker Hybrid Dual Fuel Electric Propulsion


LIGHTING

M

SHORE CONNECTION

FRAMO PUMPS POWER PACK

2048 kW

6600

440220

6600

FUEL CELLS

6600 V, 60 Hz

G G

GENSET 1 8L50 DF

GENSET 2 6L34 DF

7330 kW

2610 kW

PROPULSION LOAD

6646 kW

LIGHTING

M

SHORE CONNECTION

FRAMO PUMPS POWER PACK

2048 kW

6600

440220

6600

6600 V, 60 Hz

G G

GENSET 4 8L50 DF

GENSET 3 6L34 DF

7330 kW

2610 kW

PROPULSION LOAD

6646 kW

STEAM TURBINE

GENERATOR FUEL CELLSSTEAM TURBINE

GENERATOR

All Electric Tanker Engine Room and LNG tank Arrangement

Engine Room Arrangement:

Upper Deck

Fire proof Type A60 longitudinal bulkhead Design for Safety

Daily and Settling tanks modeled

Control Room aft of the Generator Room Design for Security

Steering Gear in the same position

LNG Tank Arrangement: IMO C-Type tanks

4X400 m3 Tanks on deck

3X200 m3 Vertical tanks in E.R

LNG Range: 4000nm

Combined Range: 15000nm

Modularized Engine Room Concept: Retractable Roof on main deck and hatches,

Easily accessible engine room

Engine Leasing Program


All Electric Tanker Engine Room and LNG tank Arrangement


S.G/Control Room

Generator Room

Vertical LNG tanks

Gas Preparation

Room

All Electric Tanker Steam Turbine


All Electric Tanker Steam Turbine

Waste Heat from Generators

Exhaust Gas Boiler, used in LNG and Diesel modes,

LNG mode can have better heat recovery (bigger LHV)

Approx. 6.5 MW of exhaust gas energy

Preheater, Evaporator and Superheater

Single, High Pressure System

Steam Turbine: High pressure turbine

Steam pressure (inlet): 15bar

Outlet pressure:0.05 bar

Electrical Output of approx. 1.7 MW

Combined with fuel cells 2MW of hybrid propulsion (15% of installed power)


All Electric Tanker Economic Asessment

Increased CAPEX: 6.6 mil cost for LNG bunker installation

Initial 15% twin screw extra taken to 20% for Diesel Electric Drive

Reduced Lightship

Reduced OPEX, VOYEX: Cheaper Fuel (LNG)

Better engine loading in laden and ballast legs

RFR difference from I.D 2515: HFO as fuel (750$/t): +1.41%

LNG as fuel (500$/t): -11.7%

HFO and LNG (eq. 650$/t): -4.16%


All Electric Tanker Environmental Assessment

Environmental Assessment:

EEDI is not applicable for DE applications!

Need for Lifecycle Assesment Tool of Machinery Emissions

Thesis of Mr. Nikos Mantakos (super. By Prof. Ventikos)

Estimated Ship Life 25 years

Emissions Breakdown:

CO2, SOx, NOx, PM

Increase of CH4 by 39%

Major improvement in comparison with existing AFRAMAX ships

Methane Slip can be tackled by: Improvement in combustion technology

Use of afterburner



0,000E+00

2,000E+05

4,000E+05

6,000E+05

8,000E+05

1,000E+06

1,200E+06

Single Skeg HFO TwinSkeg HFO

(I.D 2515) Multi Venture

1,05E+06 -6.3 %

-22.95 %

Life Cycle CO2 Emissions (Operation)

0,000E+00

1,000E+04

2,000E+04

3,000E+04

4,000E+04

Single Skeg HFO TwinSkeg HFO

(I.D 2515) Multi Venture

3,160E+04 -3.28%

-88.18%

Life Cycle NOX Emissions (Operation)

0,000E+00

1,000E+03

2,000E+03

3,000E+03

Single Skeg HFO

TwinSkeg HFO (I.D

2515)

Multi Venture

1,886E+04 -3.33%

-95%

Life Cycle PM Emissions (Operation)

0,000E+00

5,000E+03

1,000E+04

1,500E+04

2,000E+04

Single Skeg HFO TwinSkeg HFO (I.D 2515)

Multi Venture

2,840E+03 -3.29%

-100%

Life Cycle S02 Emissions (Operation)

Overview of AFRAMAX Case Study Final Product


122000

124000

126000

128000

130000

132000

134000

136000

Cargo Capacity (m3)

Increased Profitability

Conventional

Multi Venture

0

5000

10000

15000

20000

25000

30000

35000

40000

Ballast Water Amount Required

(m3)

"Semi-Ballast Free" Tanker

Conventional

Multi Venture

0

2

4

6

8

10

Required Freight Rate ($/t)

Competitiveness

Conventional

Multi Venture

0

0,005

0,01

0,015

Accidental Oil Outflow Index

(MARPOL Reg. 23)

Safer Crude Oil Transport

Conventional

Multi Venture

Case Study of a VLCC Optimization

A case study to illustrate the applicability of the method and provide future research potential

Scope of Work

Need to demonstrate the applicability and robustness of the method.

Try different size and more conventional geometry.

Less detailed application: Only a few runs in DoE (1500 variants)

Optimization using MOSA (Multi Objective Simulation Annealing) algorithm (1500 variants)

Bigger Room for improvement: No applicable navigational restrictions for VLCCs

Need for smaller tanks: 6 Transverse Bulkheads used (instead of 5)

More impressive results are expected for smaller tank sizes (7X3)


VLCC Optimization Initial Results


0,0114

0,0119

0,0124

0,0129

0,0134

0,0139

0,0144

0,0149

4 4,2 4,4 4,6 4,8 5 5,2 5,4 5,6 5,8 6 Acc

iden

tal

Oil

Ou

tflo

w I

nd

ex (

Acc

. to

MA

RP

OL

Reg

. 2

3)

Required Freight Rate (USD/t, HFO price at 1000 $/t)

Optimization Run with MOSA (1500 variants)

RFR vs. OOI

6X3 VLCC

Aiolos Hellas (baseline)

2

2,2

2,4

2,6

2,8

3

3,2

4,5 4,6 4,7 4,8 4,9 5 5,1 5,2 5,3

EE

DI

(Acc

. to

IM

O M

EP

C 6

2)

Required Freight Rate (USD/t, HFO price 1000 $/t)

Optimization Runs with MOSA (1500 variants)

EEDI vs. RFR

6X3 VLCC

Aiolos Hellas (Baseline)

Conclusions, Discussion and Perspectives

Conclusion, Perpsectives

Conclusion: A novel, holistic methodology was developed, using a Risk Based Approach and

holistic ship theory in order to systematically assess and optimize Tanker Design.

The application resulted in improved and innovative designs that illustrate the potential and applicability of the method.

The method was entirely programmed in the Friendship Framework, with a fully parametric model using principles of Simulation Driven Design.

The sensitivities of the model can be provided as design directives for the preliminary choice of the main dimensions.

Awards/Perspectives: Pending Publication for methodlogy in peer reviewed journal (02.2013 submission)

Further VLCC Optimization (spring 2013 publication)

Ongoing adaptation of methodology for the case of containerships (OptiCON research project together with GL): Refinement of Lightship Calculation and Resistance Prediction Tools

ABS Award for 2012/Collaboration with GL (BEST+, BEST++)


Acknowledgements The author needs to acknowledge the help and support of the following

people, whose contributions have been critical for the completion of this work at various stages:

Professor Dr.Ing. Habil. Apostolos Papanikolaou,

Dr. Evangelos Bouloungouris (NTUA-SDL),

Associate Professor Dr. George Zaraphonitis (NTUA-SDL),

Professor Kostas J. Spyrou (NTUA)

Assistant Professor Nikolaos Ventikos (NTUA),

Professor Christos Frangopoulos (NTUA),

Associate Professor John Prousalidis (NTUA) and Mr. Elias Sofras,

Mr. Dimitrios Heliotis (Target Marine)

Dr. Pierre C. Sames (GL) and Germanischer Lloyd SE,

Dr. Harries, Mr. Park and Mr. Brenner from Friendship Systems

Mr. Utvaer Alf-Morten (FRAMO)

Mr. Kostas Anastasopoulos (NTUA-SDL)

Ship Design Laboratory: Dr. Eliopoulou, Dr. Liu, Mr. Papatzanakis, Ms. Alisafaki

My family and friends for their support and patience.



Thank you for your kind attention !

Questions ?

Accidental Oil Outflow: Tank variables:

Oil Outflow Index entirely dependent on the tank size, position and geometry.

Double bottom height is much less influencing the OOI than the side tank width

Collision accidents more frequent and have bigger consequences than grounding accidents

Main dimensions: influence on tank size and displacement

Local hullform parameters: no influence on the Index (negligible changes of displacement only).

Required Freight Rate: General impression: larger vessel sizes have a positive influence to the RFR thanks to the

strong correlation to the tank capacity.

Tank Variables:

Larger Tank Sizes correspond to smaller RFR

Local Hullform Parameters:

Decrease of wetted surface leads to smaller RFR

Correlation with EEDI sensitivities

IMO Energy Efficiency Design Index (EEDI): General impression: the larger vessel sizes have a positive influence to the EEDI thanks to

the strong correlation to the deadweight and the smaller increase of the installed power.

Local hullform parameters via the wetted surface and thus the installed power


Sensitivity Analysis of the Developed Methodology

Annex I

Sensitivity Analysis of the Developed Methodology EEDI Sensitivity


Sensitivity Analysis of the Developed Methodology OOI Sensitivity



1st Stage: Design Space Exploration Design of Experiment-Sensitivities

EEDI performance: Promising results due to the strong correlation to the design speed.

Robustness: The favored designs remained to be favored but, by using the lowest

design speed.

Final Decision: Not to include the speed in the calculations,

Separate study of the optimal operating speed for a range of scenarios (depending on the fuel price).

Some of the constraints were made more tight in order to make sure that the feasible designs are in fact feasible.

The lower boundary for the double bottom was slightly increased.

Selected Variants (by means of an objective function):

Design I.D 314 and exported to be the baseline for the genetic algorithm runs (Stages 3 and 4).



2nd Stage: Design Space Exploration Investigating the Effects of Design Speed

Structural Analysis

The effects of new dimensions, of the elliptic bilge and the new position of the longitudinal bulkheads needed to be examined.

One of the dominant variants modeled in POSEIDON

The functional elements and bulkheads were taken the same as in the structural weight investigation done.

Results:

Under-estimation of the structural weight by 4.5%

It is lost within the correction factors which are up to 15%.

Transverse weight is lower than expected.


Item I.D 2515 Calculated

in FFW I.D 2515 Calculated

in POSEIDON BEST+ NX3 Model

in POSEIDON

Longitudinal

Members Weight

58.68 t/m 62.83 t/m 54 t/m

Transverse

Members Weight

8.19 t/m 5.8 t/m 8.19 t/m

Hydrodynamic Analysis

Due to uncertainties in the powering estimations and the design ranking, a CFD calculation had to take place.

The focus was to see any irregular wave patterns with extreme bow and stern waves (due to bulky bow form and twin skeg stern).

The SHIPFLOW package was used, and the XPAN code.

The evaluation of the wave making resistance is done using wave cuts.

The wave patterns of each subject is also examined in order to see any strange effects.

The convergence was fast and the results were accurate.

The effect of panel density and transom modeling were also taking into account.

The trends are verified and the preliminary method can be considered accurate.

The absolute values of Holtrop seem to be more conservative than the SHIPFLOW results.

Current work: benchmark several CFD codes using I.D 2515 as a reference design.



Hydrodynamic Analysis Results Table

Design I.D Lbp B T Fn Wetted

Surface Cw wavecut Cw Holtrop

2515 244.41 45.8492 14.6516 15444.39 0.000018533 2.96783*10-5

1838 244.411 47.8340 14.67552 0.15759 15779.25 2.00328E-05 2.70299*10-5 2590 244.411 47.93 14.6989 0.15759 15677.6 0.00002074 2.70934*10-5

2738 244.4117 47.992 14.69896 0.157592 15827.76 0.00002128 2.67772*10-5

2896-2a 244.473 47.998 14.6563 0.157572 15879.56 2.00588E-05 2.58295*10-5

1943-2a 244.24 47.588 14.65428 0.15764 15852.92 0.000024577 2.76644*10-5

2294-2a 244.94 47.997 14.65856 0.15742 15954.25 1.70883E-05 2.58859*10-5

2210-2a 244.758 47.919 14.65474 0.15748 15935.93 0.000018847 2.6232*10-5

1686-2a 242.730 47.920 14.68798 0.158137 15827.07 0.000023244 2.66271*10-5

2954-2a 244.963 47.607 14.64061 0.157414 16088.02 0.000018341 2.66116*10-5

a holistic methodology for the optimization of tanker design and

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