DEGREE PROJECT IN MECHANICAL ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2020 Performance Prediction Program for Wind-Assisted Cargo Ships Prestandaprognosprogram för fraktfartyg med vindassisterad framdrivning MARTINA RECHE VILANOVA KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ENGINEERING SCIENCES Performance Prediction Program for Wind-Assisted Cargo Ships MARTINA RECHE VILANOVA TRITA-SCI-GRU 2020:288 Degree Project in Mechanical Engineering, Second Cycle, 30 Credits Course SD271X, Degree Project in Naval Architecture Stockholm, Sweden 2020 School of Engineering Sciences KTH Royal Institute of Technology SE-100 44, Stockholm Sweden Telephone: +46 8 790 60 00 Per tu, Papi. Et trobem a faltar. Acknowledgements I wish to express my sincere appreciation to my supervisor from the Fluid Engineering Department of DNV GL, Heikki Hansen, for his wonderful support, guidance and honesty. I would also like to pay my special regards to Hasso Hoffmeister for his constant dedication and help and to everyone from DNV GL whose assistance was a milestone in the completion of this project: Uwe Hollenbach, Ole Hympendahl and Karsten Hochkirch. It was a pleasure to work with all of you. Furthermore, I wish to express my deepest gratitude to my supervisor Prof. Harry B. Bingham from the section of Fluid Mechanics, Coastal and Maritime Engineering at DTU, who always sup- ported, guided and steered me in the right direction. My thanks also go to my other supervisor, Hans Liwång from the Centre for Naval Architecture at KTH, who have always had an open ear for me since the first day we met. The contribution of Ville Paakkari from Norsepower Oy Ltd, who provided the Maersk Pelican data for the validation of this Performance Prediction Program, is truly appreciated. Finally, I would also like to acknowledge the love and the unconditional support of my family, my friends, my mother, Dolors; my father, Carlos; and my sister, Ariadna. Thank you! Abstract Due to the accelerating need for decarbonization in the shipping sector, wind-assisted cargo ships are able to play a key role in achieving the IMO 2050 targets on reducing the total annual GHG emissions from international shipping by at least 50%. The aim of this Master’s Thesis project is to develop a Performance Prediction Program for wind-assisted cargo ships to contribute knowledge on the performance of this technology. The three key characteristics of this model are its generic structure, the small number of input data needed and its ability to predict the performance of three possible Wind-Assisted Propulsion Systems (WAPS): Rotor Sails, Rigid Wing Sails and DynaRigs. It is a fast and easy tool able to predict, to a good level of accuracy and really low computational time, the performance of any commercial ship with these three WAPS options installed with only the main particulars and general dimensions as input data. The hull and WAPS models predict the forces and moments, which the program balances in 6 degrees of freedom to predict the theoretical sailing performance of the wind-assisted cargo ship with the specified characteristics for various wind conditions. The model is able to play with differ- ent optimization objectives. This includes maximizing sailing speed if a VPP is run or maximizing total power savings if it is a PPP. The program is based on semi-empirical methods and a WAPS aerodynamic database created from published data on lift and drag coefficients. All WAPS data can be interpolated with the aim to scale to different sizes and configurations such as number of units and different aspect ratios. A model validation is carried out to evaluate its reliability. The model results are compared with the real sailing data of the Long Range 2 (LR2) class tanker vessel, the Maersk Pelican, which was recently fitted with two 30 meter high Rotor Sails; and results from another performance prediction program. In general, the two performance prediction programs and some of the real sailing measurements show good agreement. However, for some downwind sailing conditions, the performance predictions are more conservative than the measured values. Results showing and comparing power savings, thrust and side force coefficients for the different WAPS are also presented and discussed. The results of this Master’s Thesis project show how Wind-Assisted Propulsion Systems have high potential in playing a key role in the decarboniza- tion of the shipping sector. WAPS can prove substantial power, fuel, cost, and emissions savings. Tankers and bulk-carriers are specially suitable for wind propulsion thanks to their available deck space and relatively low design speeds. The Performance Prediction Program for wind-assisted cargo ships developed in this Master’s Thesis shows promising results with a good level of accuracy despite its generic and small number of input data. It can be a useful tool in early project stages to quickly and accurately assess the potential and performance of WAPS systems. Abstrakt På grund av det accelererande behovet av att minska utsläppen från sjöfartssektorn, kan vindassis- terade lastfartyg spela en nyckelroll för att uppnå IMO 2050. Syftet med detta examensarbete är att utveckla ett prestandaprognosprogram för vindassisterade lastfartyg för att bidra med kunskap om denna teknik. De tre viktigaste egenskaperna för denna modell är dess generiska struktur, det lilla antalet inmatningsdata som behövs och dess förmåga att förutsäga prestandan för tre möjliga vindassisterade framdrivningssystem (WAPS): Rotorsegel, styva vingsegel och DynaRigs. Det är ett snabbt och enkelt verktyg som med en hög grad av noggrannhet och med kort beräkningstid kan bedöma prestanda för kommersiella fartyg med dessa tre WAPS-alternativ. Skrov- och WAPS-modellerna beräknar krafter och moment som balanseras i sex frihetsgrader. Modellen kan utgå från olika optimeringsmål. Detta inkluderar maximering av segelfarten eller maximeras totala energibesparingar. Programmet är baserat på semi-empiriska metoder och en WAPS aerodynamisk databas skapad från publicerad data om lyft- och motståndskoefficienter. Alla WAPS-data kan interpoleras med syftet att skala till olika storlekar och konfigurationer, så- som antal enheter och olika aspektförhållanden. En modellvalidering utförs för att utvärdera dess tillförlitlighet. Modellresultaten jämförs med verkliga seglingsdata för tankfartyget Maersk Pelican (klass Long Range 2, LR2), som nyligen utrustades med två 30 meter höga rotorsegel; och resultat från en andra data. Resultaten visar i allmänhet bra överensstämmelse. För vissa seglingsförhållanden är emellertid bedömningarna mer konservativa än de uppmätta värdena. Resultat som visar och jämför energibesparingar, tryckkraft och sidokraftkoefficienter för de olika WAPS presenteras och diskuteras också. Resultaten av detta examensarbete visar hur vindassister- ade framdrivningssystem har stor potential att spela en nyckelroll i utvecklingen för sjöfartssektorn. WAPS kan leda till betydande energi-, bränsle-, kostnads- och utsläppsbesparingar. Tankfartyg och bulkfartyg är speciellt lämpliga för vindframdrivning tack vare deras tillgängliga däckutrymme och relativt låga hastigheter. Prestandaprognosprogrammet för vindassisterade lastfartyg utvecklat här visar därmed lovande resultat trots dess generiska upplägg och lilla antal inmatningsdata. Det kan vara ett användbart verktyg i tidiga projektsteg för att snabbt utvärdera potential och prestanda för WAPS-system. Contents Acknowledgementsi Abstract ii Abstrakt iii Nomenclature v 1 Introduction 1 1.1 Background........................................1 1.2 Mission..........................................1 1.3 Goals...........................................1 2 Physics of Sailing2 2.1 Wind Velocity Triangle..................................2 2.2 Basic Steady State Condition..............................3 3 Performance Prediction Program6 3.1 Solution Algorithm....................................6 3.2 Free Variables.......................................9 3.3 Conventions........................................9 3.4 Force Modules...................................... 10 3.5 Parameters........................................ 11 3.6 Configurations...................................... 11 3.7 User-Friendly interface.................................. 12 4 Hull Model 13 4.1 Force Modules...................................... 13 4.1.1 Mass........................................ 13 4.1.2 Buoyant Force.................................. 13 4.1.3 Total Hull Resistance.............................. 14 4.1.4 Hull Roughness.................................. 15 4.1.5 Side Force..................................... 15 4.1.6 Windage of the Superstructure......................... 16 4.1.7 Propeller Thrust Force.............................. 16 4.1.8 Non-Moving Propeller Drag........................... 17 4.1.9 Rudder Hydrodynamic Loads.......................... 17 4.1.10 Added Resistance in Waves........................... 17 4.2 Input Data........................................ 18 5 Wind-Assisted Propulsion Systems Model 20 5.1 Rotor Sails........................................ 21 5.1.1 Configurations.................................. 22 5.1.2 Aerodynamic Loads............................... 23 5.1.3 Data Source and Data Fitting.......................... 26 5.1.4 Spinning Power Required............................ 27 5.1.5 Windage...................................... 27 5.1.6 Interaction.................................... 27 iv CONTENTS CONTENTS 5.1.7 Input Data...................................