Scipedia

Edwards*, H.

Chen, X.

Vogel, C.

Willden, R.

XI International Conference on Computational Methods in Marine Engineering
Comparing actuator line and disc models for the hydrodynamic design of tidal
stream turbine rotors
Huw A. Edwards1,∗, Xiaosheng Chen1, Christopher R. Vogel1 and Richard H. J. Willden1
1 Department of Engineering Science, University of Oxford
Parks Road, Oxford, OX1 3PJ, UK
∗ huw.edwards@eng.ox.ac.uk
ABSTRACT
Actuator methods are a computationally efficient ap-
proach to wind and tidal turbine simulation, as the ro-
tor can be modelled without the need to resolve the
blade geometry and its boundary layers. This is ben-
eficial when carrying out iterative rotor design pro-
cesses as the blade geometry can be modified with-
out mesh alteration. While the actuator line method
requires more computational resource than the actu-
ator disc approach, the discrete blade representation
more closely matches the physics of a real rotor as
tip vortices and helical wake structures are generated.
Previous studies, such as those of Porté-Agel et al.
(2011) and Martı́nez-Tossas et al. (2015), have com-
pared actuator line and actuator disc models for spe-
cific rotor geometries with a focus on the power out-
put and wake quantities. The current study is focused
on the use of actuator methods as tools for iterative
rotor design, so analysis prioritises the spanwise dis-
tribution of force and flow components, particularly
in the tip vicinity. A novel rotor design algorithm is
presented which implements the same design criteria
as the McIntosh et al. (2011) design tool, but mod-
elling the rotor using actuator lines as opposed to an
actuator disc. RANS simulations using both actuator
methods are compared against blade resolved results.
The force predictions are improved by the use of tip
corrections in both cases. However, the resulting dis-
tribution of streamwise velocity requires that no tip
correction is used with the actuator disc-based design
tool, and indicates that the disc-based design criteria
of McIntosh et al. (2011) are incompatible with actu-
ator line modelling.
Figure 1: Comparison of the axial (left) and tangential (right) sectional force distributions predicted by actuator line
(orange), actuator disc (green) and blade resolved (purple) RANS simulations with and without tip correction applied.
References
F. Porté-Agel, H. Lu and YT. Wu, A large-eddy simulation framework for wind energy applications, in Fifth
International Symposium on Computational Wind Engineering, Chapel Hill, 2010.
L. A. Martı́nez-Tossas, M. J. Churchfield and S. Leonardi, Large eddy simulations of the flow past wind tur-
bines: Actuator line and disk modeling, Wind Energy, 18:1047–1060, 2015.
S. C. Mcintosh, C. F. Fleming, and R. H. J. Willden, Embedded RANS-BEM Tidal Turbine Design, in Pro-
ceedings of the 9th European Wave and Tidal Energy Conference, Southampton, 2011.


Comparing actuator line and disc models for the hydrodynamic design of tidal stream turbine rotors

Chernyshev*, L.

Kabaliuk, N.

Jermy, M.

 
 
XI International Conference on Computational Methods in Marine Engineering 
 
 On the Merits of a Lifting Line Model for Simulating Hydrofoil Hydrodynamics 
 
Lev Chernyshev1,*, Natalia Kabaliuk1 and Mark Jermy1 
 
1 Department of Mechanical Engineering, University of Canterbury 
Ilam, Christchurch, Canterbury, 8041, New Zealand 
 
* lev.chernyshev@pg.canterbury.ac.nz 
 
ABSTRACT 
In the last decade, the popularity of hydrofoils on marine craft has increased significantly, particularly in the 
yachting industry and on recreational products. With a widespread push for more efficient, low-emission 
transport, commercial applications for fast ferrying of passengers and cargo are also being explored. Hydrofoil 
design poses a significant challenge to naval architects, due to complex hydrodynamics and operating regimes 
which are challenging to analyse (Faltinsen, 2005). Marine engineers employ a range of tools to study hydrofoil 
hydrodynamics, ranging from experimental methods in water tunnels and tow tanks; to simulation-based 
approaches such as computational fluid dynamics (CFD) and other numerical models. To reduce cost, much 
of the preliminary design is done using the latter (Newman, 2018). Accurate and validated methods for 
simulating hydrofoils are therefore crucial for engineers seeking to develop efficient and performant designs. 
In this study, we showcase the development, validation, and application of a numerical lifting-line (LL) model 
for simulating hydrofoil hydrodynamics (Chernyshev et al., 2024). This model was adapted to simulate free 
surface and wave-making effects by employing a Green’s function for a source in steady motion under a free 
surface, originally derived by Newman (1987).  High-fidelity steady Reynolds-Averaged Navier Stokes 
(RANS) simulations were used as a benchmark to verify the LL model’s accuracy. This was done by first 
validating the RANS model against experimental datasets, and then using it to simulate a rectangular 
NACA4412 hydrofoil submerged one chord-length beneath the free surface at Reynolds numbers between 
2.57×105 and 2.06×106 (Froude numbers between 0.5 and 4) and comparing the results with the LL model.  
Overall reasonable agreement between LL and RANS was seen when comparing the lift, drag and moment 
coefficients across all simulated Froude numbers. The LL model also simulated the downstream induced 
velocities behind the hydrofoil with fidelity that was on par with RANS. This increased our confidence that 
the LL model can be relied upon for dictating design choices and direction at the preliminary stage of design. 
Its key advantage over RANS was its efficiency with compute resources, permitting extensive parametric 
design studies (e.g. exploring how different taper/twist combinations affect the resistance) and optimisation. 
However, great care should be taken when interpreting the LL results as the theoretical models employed, 
especially for the free surface effects, were difficult to validate and still showed considerable discrepancies 
with RANS, particularly when simulating regimes with intermediate Froude numbers.  
References 
Chernyshev, L., Kabaliuk, N., Jermy, M., Corkery, S., & Bernasconi, D. (2024). Evaluating Hydrofoil 
Resistance Components from RANS and Lifting-Line Fluid Simulations SNAME Maritime 
Convention,  https://doi.org/10.5957/SMC-2024-033 
Faltinsen, O. M. (2005). Hydrodynamics of high-speed marine vehicles. Cambridge university press.  
Newman, J. N. (1987). Evaluation of the Wave-Resistance Green Function: Part 1—The Double Integral. 
Journal of ship research, 31(02), 79-90. https://doi.org/10.5957/jsr.1987.31.2.79  
Newman, J. N. (2018). Marine hydrodynamics. The MIT Press.  
 


On the Merits of a Lifting Line Model for Simulating Hydrofoil Hydrodynamics

McCullough*, D.

Soban, D.

Schmitt, P.

XI International Conference on Computational Methods in Marine Engineering
Actuator Line Simulations of a Foiling Boat
Daniel Lalanza McCullough∗1, Danielle Soban1, Pal Schmitt2
1 School of Mechanical and Aerospace Engineering, Queen’s University Belfast, UK
∗ dlalanzamccullough01@qub.ac.uk
2 School of Natural and Built Environment, Queen’s University Belfast, UK
ABSTRACT
Foiling boats are becoming ever more popular,
yet the use of numerical design tools and the
relevance of their respective limitations are still a
topic of discussion. Actuator Lines are being used
successfully to model slender bodies like wind and
tidal turbine blades and can be expected to capture the
wake interaction between hydrofoils well. However,
hydrofoils operate in surface proximity and the related
loss in lift and increase in drag poses a complex
problem. This project explores the use and limitations
of the ALFEA toolbox [1] for the design of a foiling
boat.
First comparisons against experimental data from
[2] indicate that free surface effects are captured
implicitly due to the changing flowfield and related
changes in angle of attack 1. This might seem
surprising since the AL method itself does not contain
any physical model of the free surface.
0 2 4 6 8 10
0
0.2
0.4
0.6
0.8
1
h/c
c L
/c
I
n
f
panMARE
ALFEA
Exp
Wadlin
Payne
Figure 1: Normalised coefficient of lift over submergence
depth
This paper presents a validation of simulation results for a scaled foiling boat model developed and field tested
at QUB and explores hull-foil and free-surface foil interactions.
References
[1] Pal Schmitt and Desmond Robinson. “A Coupled Actuator Line and Finite Element Analysis Tool”. In:
OpenFOAM® Journal 2 (May 2022), pp. 81–93.
DOI: 10.51560/ofj.v2.51. URL: https://journal.openfoam.com/index.php/ofj/
article/view/51.
[2] Mark Daskovsky. “The hydrofoil in surface proximity, theory and experiment”. In: Ocean Engineering
27.10 (2000), pp. 1129–1159. ISSN: 0029-8018.
DOI: https://doi.org/10.1016/S0029-8018(99)00032-3. URL: https://www.
sciencedirect.com/science/article/pii/S0029801899000323.


Actuator Line Simulations of a Foiling Boat

Ponkratov*, D.

Wheeler, M.

Annamalai, T.

 
 
XI International Conference on Computational Methods in Marine Engineering 
 
 
How to use JoRes ship scale open data for CFD validation? 
Dmitry Ponkratov1*, Miles Wheeler1 and Tamizharuvi Maniyan Annamalai2 
 
1 Siemens Digital Industries Software, 
200 Shepherds Bush Road, London, W6 7NL, UK  
 
2 Cybermaster Ltd, 34-35 Hatton Garden Suite 2227 Unit 3a,  
34-35 Hatton Garden, Holborn, London, England, EC1N 8DX. 
 
* Dmitry.Ponkratov@siemens.com 
 
ABSTRACT 
CFD made its way into the maritime community a few decades ago and has since become an integral part of 
it. Thousands of calculations are conducted globally to design new hulls, optimise propellers, etc. The 
International Maritime Organization (IMO) provided significant encouragement in 2021 by officially 
recognising CFD as an alternative to model tests. However, it is important to validate CFD methods to make 
sure the simulations provide realistic results. This realisation led to the establishment of the JoRes Joint 
Research project in 2019. Within the JoRes project, the global community developed a collection of ship-scale 
validation cases consisting of seven vessels. The access to the website jores.net became public in December 
2024, and there is an opportunity to participate in international workshops to validate your CFD methods. The 
conference presentation aims to delve into the background of the JoRes project, discuss the collected results, 
and suggest the best strategy for using them.  
    
MV 
Regal 
JoRes1 
Tanker 
JoRes2 
RoRo 
ferry 
JoRes3 
Cruise 
liner 
JoRes4 
Deniz  
tug 
JoRes5 
bulk 
carrier 
Lucy 
Ashton 
 Geometry files formats 
.igs .stp 
.stl 
.igs .stp 
.stl 
.3dm 
.igs .stp 
.stl .dbs 
.igs .stp 
.stl 
.igs .stp 
.stl 
.igs .stp 
.stl 
.igs .stp 
.x_t 
Dimensions 
Length between perpendiculars, m 138.0 178.5 170.0 226 18.28 182.0 58.1 
Breadth moulded, m 23.0 32.26 27.7 32.2 7.46 32.26 6.4 
Model tests Model tests at the trials draughts 
SINTEF 
and 
CSSRC 
SSPA 
and 
HSVA 
N N N N 
6 
models 
  
  
Geometry 
details 
  
  
Energy Saving Device (ESD) N 
PBCF, 
skeg, 
rudder 
plate 
Twisted 
rudders 
Twisted 
rudders 
Ducts 
Pre 
Swirl 
Stators 
N 
Propeller 
1FPP, 
4 blades 
1FPP, 
4 blade 
2CPP,    
4 blades 
2FPP,    
5 blades 
2FPP,    
4 blades 
1FPP,    
4 blades 
No :) 
Average Weld seams width, mm N 24.5 22.2 N N N N 
Information about Anodic protection Y Y Y Y Y N Y 
Information about Bulge keels Y Y Y Y Y N Y 
Roughness 
Equivalent sand grain hull roughness, µm 440 53 17 15 66 53 59 - 97 
Equivalent sand grain rudder roughness, µm 440 63 22 230 132 63 N 
Equivalent sand grain propeller roughness, µm 6 4 3 Y Y 4 n/a 
Trials 
condition 
Deep water trials Y Y Y Y Y Y Y 
Shallow water trials N N N Y N N N 
Speed and 
Power trials 
Sea trials speeds, kn 
9.03 
10.96 
11.76 
12.82 
8.96 
11.25 
13.34 
14.14 
16.66 ~12 
~6 
~7.5 
~8.5 
~10 
13.65 
15.25 
16.02 
16.32 
5-15 
Draughts Ballast Loaded Ballast Ballast n/a Ballast n/a 
Propeller torque measurements Y Y Y Y Y Y n/a 
Propeller thrust measurements  Y N Y Y N N n/a 
 2 
PIV flow measurements  N Y N N N N N 
Cavitation observations Y N N N N Y n/a 
Pressure pulses measurements Y N N N N N n/a 
Drone videos of wave pattern Y N N N Y N N 
Bridge videos of wave pattern Y N N N N N N 
Trials with and without ESD N N N N N Y Y 
  
Manoeuvring 
trials 
  
  
Zig-zag 10 deg tests N N N Y Y N N 
Zig-sag 20 deg tests N N N Y Y N N 
Turning circle N N N N Y N N 
Inertia Stop N N N N Y N Y 
Acceleration N N N N Y N Y 
Crash Stop N N N N Y N N 
  Bollard pull N N N N Y N N 
 Long-term monitoring data Y N Y Y N N N 
 


How to use JoRes ship scale open data for CFD validation?

Womack, K.

Schultz*, M.

XI International Conference on Computational Methods in Marine Engineering
Ship Biofouling Drag Penalty Prediction with the Wind-shade Roughness Model
Kristofer M. Womack∗ and Michael P. Schultz
School of Engineering, Computing, and Weapons
United States Naval Academy, Annapolis, Maryland 21402-5025
∗ womack@usna.edu
ABSTRACT
Global shipping significantly contributes to green-
house gas emissions and incurs substantial economic
costs. Some of this results from increased drag due to
hull fouling. Accurately predicting these drag penal-
ties is crucial for environmental sustainability and
economic efficiency. While existing models based
solely on surface statistics have limited applicability,
a recent wind-shade roughness model by Meneveau et
al. (2024) offers a promising alternative by incorpo-
rating both surface topography and flow physics.
This study investigates the potential of the wind-shade
roughness model to improve biofouling drag penalty
predictions. We utilize truncated cone hydrodynamic
drag results from Womack et al. (2022) as a proxy
for ship hull barnacle fouling. Fig 1 shows a com-
parison of the truncated cone experimental data and
wind-shade model results over a range of roughness
planform densities. Additionally, a process similar to
Monty et al. (2016) will be used to predict the in-
crease in hydrodynamic drag for a mid-sized naval
surface ship. By comparing the model predictions to
experimental data, we aim to:
1. Evaluate the accuracy and applicability of the
wind-shade roughness model for predicting
biofouling penalties.
2. Quantify the ship drag penalty associated with
biofouling using both experimental and model-
based results.
3. Identify areas for improvement in the wind-
shade roughness model to enhance its predictive
capabilities.
Figure 1: Equivalent sandgrain roughness, ks, normalized
by roughness height, k = 3.15mm, for all planform densi-
ties, λp. See Womack et al. (2022) Fig 9 for plot data not
included here.
References
C. Meneveau, N. Hutchins, and D. Chung. The Wind-shade Roughness Model for Turbulent Wall-bounded
Flows. Journal of Fluid Mechanics, 1001:A3, 2024. doi: 10.1017/jfm.2024.971.
URL https://doi.org/10.1017/jfm.2024.971.
J. P. Monty, E. Dogan, R. Hanson, A. J. Scardino, B. Ganapathisubramani, and N. Hutchins. An Assessment
of the Ship Drag Penalty Arising from Light Calcareous Tubeworm Fouling. Biofouling, 32:4, 451-464, 2016.
doi: 10.1080/08927014.2016.1148140. URL https://doi.org/10.1080/08927014.2016.1148140.
K. M. Womack, R. J. Volino, C. Meneveau, and M. P. Schultz. Turbulent Boundary Layer Flow Over Reg-
ularly and Irregularly Arranged Truncated Cone Surfaces. Journal of Fluid Mechanics, 933:A38, 2022. doi:
10.1017/jfm.2021.946. URL https://doi.org/10.1017/jfm.2021.946.


Ship Biofouling Drag Penalty Prediction with the Wind-shade Roughness Model

Khaware*, A.

Kelecy, F.

Harding, R.

Munholand, L.

 
Numerical Analysis of DARPA SUBOFF Submarine for Self-Propulsion  
using ANSYS Fluent GPU Solver 
Alok Khaware1),*, Frank Kelecy2), Richard Harding3), Luke Munholand4) 
1) Ansys Software Pvt. Ltd., Pune, India 
2) Ansys Inc., Lebanon, USA 
3) Ansys Inc., Horsham, UK 
4) Ansys Inc., Lebanon, USA 
*Corresponding author, E-mail: alok.khaware@ansys.com 
Keywords: DARPA Suboff, INSEAN E1619, Propeller performance, Self-propulsion, ANSYS Fluent 
GPU solver 
Abstract 
This paper presents a comprehensive numerical analysis focused on key design parameters for sub-
marine performance, including resistance, propeller efficiency, and self-propulsion point. The study ex-
plicitly examines the DARPA (Defense Advanced Research Projects Agency) Suboff submarine model, 
which is propelled by the INSEAN E1619 propeller from the Italian Ship Model Basin. 
Initially, steady-state RANS simulations were conducted to evaluate the underwater resistance of 
the bare hull DARPA submarine. Results were validated against experimental data at various speeds.  
Following this, the open-water performance of the INSEAN E1619 propeller was analyzed under non-
cavitating conditions. Validation over a broad range of advanced ratios was achieved through steady-
state RANS simulations and a moving reference frame. Subsequently, the self-propulsion point was 
determined by attaching the E1619 propeller to the DARPA submarine. ITTC (International Towing 
Tank Conference) standards were followed to align propeller thrust with hull resistance. These steady-
state solutions employ the coupled solver along with the SST k-ω turbulence model and a pseudo-
transient approach.  
 All simulations leveraged the ANSYS Fluent GPU solver, yielding significant performance 
improvements when compared to CPU-based solutions. 
 
 
 


Numerical Analysis of DARPA SUBOFF Submarine for Self-Propulsion  using ANSYS Fluent GPU Solver

Bayik, B.

Ragheb*, H.

Varelis, G.

 
 
XI International Conference on Computational Methods in Marine Engineering 
 
 
Accelerating Level-3 Fitness-For-Service Assessments for Pipeline Metal Loss 
Using Machine Learning 
 
B. Bayik1, *, H. Ragheb1 and G. E. Varelis1, 
 
1 Worley 
27 Great West Road, TW8 9BW, London, UK. 
 
* bugra.bayik@worley.com 
 
ABSTRACT 
 
Level-3 Fitness-For-Service (FFS) assessments for metal loss in pipelines, as outlined in API 579, often 
require complex finite element analysis (FEA) which are computationally expensive and time-consuming. 
This research introduces a novel approach to accelerate the FFS process by integrating a localized feature 
extraction method with a machine learning algorithm. The process begins with collecting high-dimensional 
ultrasonic (UT) thickness data. FEA is performed on this data to generate pass/fail labels. A localized feature 
extraction technique is then applied to identify regions with low thickness and their spatial distribution, 
reducing data dimensionality while preserving key features that impact FFS results. The reduced feature set 
is used to train a machine learning model to predict FFS outcomes. Once trained, the model can perform 
real-time assessments on new UT scan data, eliminating the need for repeated FEA simulations. This 
approach significantly reduces the time required for Level-3 FFS assessments, offering substantial gains in 
computational efficiency and practicality, which consequently reduces the costs associated with these 
assessments. 


Accelerating Level-3 Fitness-For-Service Assessments for Pipeline Metal Loss Using Machine Learning

Lee*, K.

Kim, S.

Lee, H.

 
 
XI International Conference on Computational Methods in Marine Engineering 
 
 
High-fidelity Simulation of the Turbulence Flow Around a Rotor Sail 
 
Kyobin Lee1*, Sanghyeon Kim1 and Hyoungsuk Lee1 
 
1 Hyundai Maritime Research Institute, 
HD Hyundai Heavy Industries, 44032 Ulsan, Korea. 
 
* kyobinlee@hd.com 
 
ABSTRACT 
This study investigates the turbulent flow around a rotor 
sail through high-fidelity numerical simulations. Key 
flow phenomena, such as boundary layer separation, 
vortex shedding, and wake stability, were analyzed. 
The simulations are validated against experimental data 
conducted by Bordogna, G. to assess their accuracy in 
predicting aerodynamic performance, including lift and 
drag forces. 
Numerical simulation shows significant discrepancies in 
lift predictions depending on the turbulence models. The 
IDDES model more accurately captured unsteady vortex 
structures and turbulence interactions in the wake, while 
the SST model showed limitations, particularly at high 
rotational speeds, resulting in greater deviations.  In 
contrast, drag predictions showed good agreement with 
experimental data across both turbulence models. 
The findings emphasize the critical influence of 
turbulence model on capturing the complex interactions 
between flow structures and the Magnus effect.  
 
References 
Bordogna, G. (2020). Aerodynamics of wind-
assisted ships: Interaction effects on the aerodynamic performance of multiple wind-propulsion systems. 
https://doi.org/10.4233/uuid:96eda9cd-3163-4c6b-9b9f-e9fa329df071. 
Figure 1: Turbulence structure around a rotor sail 
 


High-fidelity Simulation of the Turbulence Flow Around a Rotor Sail

Kjellberg*, M.

Li, D.

Werner, S.

 
 
XI International Conference on Computational Methods in Marine Engineering 
 
Challenges in performance prediction of ships equipped with wind propulsion  
 
Martin Kjellberg1, Da-Qing Li1 and Sofia Werner1,* 
 
1 Maritime Department | SSPA Maritime Center, 
RISE Research Institutes of Sweden, SE-412 58 Göteborg, Sweden. 
 
 
* sofia.werner@ri.se  
 
ABSTRACT 
Facing the urgent need to decrease greenhouse gas 
emissions from shipping, the maritime industry has shown 
a growing interest in design and/or retrofitting various 
wind propulsion devices to assist the propulsion of ships 
recently. On the one hand, experience in design and 
operation of large cargo ships equipped with wind 
propulsion devices is still lacking. On the other hand, CFD 
methods have the potential to predict the performance of 
such ships (Kontos et al., 2023), however, not without 
issues at current stage. Challenges in predicting the aero- 
and hydrodynamic performance of ships equipped with 
wind propulsion systems (WPS) are discussed in this paper. 
It addresses the questions of scale effects from wind tunnel 
scale to full scale Reynolds number, influence of atmospheric boundary layer, flow separation, stall, and 
interaction between multiple propulsion units and hull superstructure.  
To assess dynamic loads, roll motions and the manoeuvrability of WPS equipped vessels, the unsteady panel 
code SHIPFLOW MOTIONS was further developed to couple the aerodynamic and hydrodynamic forces for 
6 DOF simulations. Example applications of SHIPFLOW MOTIONS, the pros and cons of the method are 
discussed. 
Fig. 1 shows an example of flow pattern on a plane cutting through the rotor install location in beam reach 
condition from Kontos et al. (2023), highlighting the interaction effect between rotor and hull superstructure. 
References 
S. Kontos, D.-Q. Li, C. Wielgosz, L. Marimon Giovannetti, F. Gerhardt, S. Werner and V. Paakkari. 
Comparison of full-scale Flettner rotor performance prediction methods with sea trial data . In the 15th 
Symposium on High-Performance Marine Vehicles HIPER’23, 2023, Bernried, Germany.  
F. W. Lanchester. Aerodynamics: Constituting the First Volume of a Complete Work on Aerial Flight,  volume 
1. London, A. Constable & Co., Ltd., 1907.  
I. M. Viola, A. Arredondo-Galeana, and G. Pisetta. The Force Generation Mechanism of Lifting Surfaces with 
Flow Separation. Ocean Engineering, 239:109749, 2021. ISSN 00298018.  doi: 
10.1016/j.oceaneng.2021.109749.  
Figure 1: Flow feature on a transversal plane 
cutting the rotor install location (to be replaced) 
 


Challenges in performance prediction of ships equipped with wind propulsion

Ruggeri*, F.

Sampaio, C.

Pinto, M.

Pritzelwitz, P.

Lindao, H.

 
 
XI International Conference on Computational Methods in Marine Engineering 
 
 
 
Comparison of different rotor sails configuration into large ore carriers 
navigation performance 
 
 
Felipe Ruggeri1*, Claudio Mueller Prado Sampaio2, Heinz Bill Galdos Lindao 2,  
Mariana Lopes Pinto3 and Philip von Pritzelwitz 3  
 
1 Argonautica Engineering & Research, São Paulo, Brazil 
 
2 Numerical Offshore Tank, University of São Paulo, São Paulo, Brazil. 
 
3 Vale Institute of Technology (ITV), Ouro Preto, Brazil 
 
* Corresponding. ruggeri@argonautica.com.br . 
 
 
ABSTRACT 
The reduction of CO2, NOx, and SOx emissions has become 
important in recent years for the maritime industry, with various 
technologies being applied to different vessels, of which rotor sails 
have been one of the most successful recently. However, when 
several of these devices are installed on a vessel, constructive and 
destructive interaction effects arise due to the wakes generated by 
the vessel and the devices themselves in the inflow of another rotor 
sail, changing the performance significantly from the experimental 
predictions of a single rotor alone or by simplified 
formulations/regressions. This study presents a comparative 
analysis of different positioning alternatives for rotor sails 
on large ore carriers, aiming to verify the performance 
variations considering the expected wind conditions on the 
route between Brazil and China in laden and ballast 
conditions. The behavior of the rotor sails was studied 
applying computational fluid dynamics, which provides the thrust produced in the direction of advance per 
device, allowing to identify the increase and reduction of performance due to the interaction with other devices 
or the ship hull, as well as the torques generated during rotation, which are used to calculate the energy required 
for the operation of the device. A simulation tool was developed to combine the different rotor sails 
configurations with the wind conditions found during the complete navigation cycle, which is evaluated using 
a statistical approach considering the 40 years of modelled conditions to provide the best alternative. Since the 
vessel speed also changes the relative wind condition, thus the rotor sails performance, a sensitivness analysis 
was performed to verify the robustness of the solutions. 
 Figure 1: Streamline of rotor sails. 
 


Comparison of different rotor sails configuration into large ore carriers navigation performance

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