Coming soon
Why Coupled RANS–BEM is the Sweet Spot for Propulsion Simulation
Lessons from my MSc thesis — near-full-RANS accuracy for hull–propeller–rudder interaction at a fraction of the cost.
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Daniel Akinmulewo
Welcome aboard
This is where I build, experiment, and occasionally break things. ⚓
This is where I build, experiment, and occasionally break things. ⚓
I'm a Naval Architect and Hydrodynamic Engineer, currently a PhD researcher at Universität Rostock. This site is a space where I share my work, research, and thoughts on the future of computational ship design, AI and AUVs.
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Current Work
PhD on AI-driven ship hydrodynamics + CFD Engineer at SVA Potsdam.
Current Read
TripOptimizer: Generative 3D Shape Optimization and Drag Prediction using Triplane VAE Networks.
Research Focus
Learning first principles, and shaping Intelligence.
Projects
projects.json — research & industry work
research @ SVA Potsdam
Full project details available on the SVA Potsdam research page ↗
R&D · AI / Ship Design · 2025–2028
ShipNET — AI Ship Modelling for Multidimensional Design
Developing an AI-driven, modular workflow for ship hull optimisation, where adaptive RL and surrogate AI agents act as copilots — autonomously generating hull variants, predicting hydrodynamic performance, and eliminating infeasible designs to replace expensive CFD iterations.
R&D · Underwater Acoustics · 2025–2027
AkuOpt — Acoustic Forecasts for Route & Sailing Profile Optimisation
Building a real-time acoustic forecasting tool that dynamically determines a ship's noise emissions to enable noise reduction through active route and speed adjustments during operation — balancing environmental protection with fuel efficiency.
R&D · Propulsion · 2024–2026
KonRo — Design & Optimisation Tool for Contra-Rotating Propellers
Developing a reliable CFD-based methodology for designing and optimising twin-shaft contra-rotating propellers (CRP), addressing prediction discrepancies under high load and small blade spacing. Initial investigations cover lateral bearing forces and manoeuvring behaviour.
R&D · Cavitation · 2021–2023
ProCup2 — Propeller Design Methods for Low Cavitation Numbers
Extended the parametric SVA profile family to include cup profiles for high-speed vessels, integrating them into propeller optimisation programs (VTXopt). Focused on preventing leading-edge cavitation, validating CFD analyses against experimental results, and assessing scaling corrections specific to cup propellers.
MSc thesis — TUHH & HSVA
MSc Thesis · HSMV 2023
Hull–Propeller–Rudder Interaction via Coupled RANS–BEM
Numerical investigation of propeller axial position effects on propulsion performance. HSVA. Presented at HSMV 2023, Naples.
AUV & Autonomous Systems
Research · AUV · GII
Autonomous Navigation — BlueROV2
Computer-vision-based autonomous control for an underwater vehicle (BlueROV2) at GII, University of A Coruña. OpenFOAM multiphase simulations.
Curriculum
Vitae
Vitae
experience
05/2023 — Present
Project Manager & Research Engineer (CFD)
Schiffbau-Versuchsanstalt Potsdam GmbH (SVA), Potsdam, Germany
- Managing industry-funded research in ship hydrodynamics and propulsion.
- SBDO and ML-driven ship design optimisation workflows.
- Developing OpenFOAM solvers, ML models, and data pipelines for early-stage performance and cavitation prediction.
- Key projects: ShipNET · AkuOpt · KonRo · ProCup2
09/2022 — 03/2023
Research Intern
Hamburgische Schiffbau-Versuchsanstalt (HSVA), Hamburg
- RANS-based CFD framework for early-stage propulsion simulation accuracy.
- Propeller optimisation tool in CAESES. Experimental validation in towing and ice tanks.
07/2022 — 08/2022
Research Intern
Grupo Integrado de Ingeniería (GII), University of A Coruña, Spain
- OpenFOAM multiphase simulations for marine hydrodynamic phenomena.
- Autonomous navigation and computer-vision control for BlueROV2.
02/2019 — 04/2023
Co-Founder & Lead Engineer
BlueMach Engineering Limited, Lagos, Nigeria
- Naval architecture and CAE consultancy. Hydrodynamic design of high-speed craft including rescue boats and patrol vessels.
03/2020 — 06/2021
Project Engineer & Naval Architect
Marine Engineering Supports Limited, Lagos, Nigeria
- Technical integration of propulsion and steering systems for NNS SDB3.
education
2025 — Present
PhD — Sustainable Maritime Engineering
Universität Rostock · Faculty of Mechanical Engineering & Naval Architecture
Topic: AI-Agents for Multi-Objective Optimization in Ship Hydrodynamics and Design.
Supervisors: Prof. F. Sprenger (Rostock) · Prof. M. Abdel-Maksoud (TUHH)
Supervisors: Prof. F. Sprenger (Rostock) · Prof. M. Abdel-Maksoud (TUHH)
2021 — 2023
M.Sc. — Sustainable Ship & Shipping 4.0
Erasmus Mundus — TUHH · University of A Coruña · University of Naples Federico II
Thesis: Numerical investigation of propeller axial position on propulsion performance and hull–propeller–rudder interaction using coupled RANS–BEM.
2013 — 2018
B.Eng. — Marine Engineering
Federal University of Petroleum Resources, Effurun, Nigeria
Thesis: Design and construction of an ultra-modern fast ferry (14-seater) in glass-reinforced fibre.
technical skills
CFD Solvers
Scientific Computing
Ship Design & CAE
Viz & Mesh
memberships
Royal Institution of Naval Architects (2024)
GMNSE — Nigerian Society of Engineers (2020)
SOLIDWORKS Certified Associate
SOLIDWORKS Champion
Publications
publications.bib — conference papers & presentations
conference papers
October 2024
Propeller Prediction in Behind Condition using a RANS-Based Artificial Body Force Method ↗ View
Numerical Towing Tank Symposium 2024 — Mülheim an der Ruhr, Germany
2023
Numerical Investigation of Propeller Axial Position on Propulsion Performance and Hull–Propeller–Rudder Interaction Using Coupled RANS–BEM ↗ View
HSMV 2023 — High Speed Marine Vehicles, Naples, Italy
2023
RANS-Based CFD Framework for Early-Stage Propulsion Simulation Accuracy
HSVA Hamburg 2023
in progress
2025 —
AI-Agent Frameworks for Multi-Objective Ship Hydrodynamics Optimisation
PhD Research — Universität Rostock · in preparation
Writing
blog.md — technical notes & essays
Sharing insights from research, towing tank experiments, and thoughts on the future of CFD and AI in naval architecture.
upcoming
Coming soon
SBDO for Ship Hulls: A Practical Primer
What SBDO is, how it fits into the design spiral, and how we use it at SVA Potsdam.
Coming soon
What Towing Tank Experiments Teach You That CFD Doesn't
The practical realities of cavitation testing, scale effects, and the limits of numerical validation.
// Blog launching soon.
Contact
contact.sh — let's connect
Open to research collaborations and connecting with engineers across the maritime community.
Send a Message
Direct Links
LinkedIn
Twitter / X
Institutions
Universität Rostock · SVA Potsdam
Location
Berlin, Germany
$ echo "Languages"
English (Native) · German (B1)
$ echo "Response time"
Within 2 working days.
Conference Paper · NUTTS 2024 · SVA Potsdam
Propeller Prediction in Behind Condition using a RANS-Based Artificial Body Force Method
⬇ Download PDF
A method to predict propeller performance in behind condition without modelling the ship hull is investigated. Using a calibrated body force approach, the wake field from a prior RANS simulation is applied upstream of the propeller plane. Propeller performance and cavitation pattern predictions in this artificial wake are compared to full RANS simulations in both steady and unsteady conditions. Computed errors for propeller thrust and torque are less than 2%, with simulations 1.7× faster than the behind-hull condition.
Key Results
The artificial body force method accurately reproduces the nominal wake field on the propeller disk. Using a normalised formulation with a prescribed thickness of 0.15Dp, the wake velocities are nearly fully reconstructed. In steady and unsteady simulations, propeller thrust (KT) and torque (10KQ) errors remain below 2% compared to full hull–propeller RANS simulations. Computational cost is reduced by 1.7× — with the main overhead coming from the body force interpolation algorithm.
References
| Author(s) | Title | Venue | Type |
|---|---|---|---|
| Baltazar et al. | Propeller Performance Prediction in an Artificially Generated Wake Field Using RANSE | NuTTS, 2019 | Numerical |
| Mikkelsen et al. | Modeling of behind condition wake flow in RANS computation on a conventional and high skew propeller | NuTTS, 2007 | Numerical |
| Shin et al. | Cavitation simulation on conventional and highly-skewed propellers in the behind-hull condition | smp'11, 2011 | CFD |
BibTeX
BibTeX Citation
@inproceedings{akinmulewo2024propeller,
title = {Propeller Prediction in Behind Condition using a RANS-Based Artificial Body Force Method},
author = {Akinmulewo, Daniel and Froitzheim, Simon},
booktitle = {26th Numerical Towing Tank Symposium (NuTTS)},
year = {2024},
address = {Mülheim an der Ruhr, Germany},
institution= {Schiffbau-Versuchsanstalt Potsdam GmbH}
}
Conference Paper · HSMV 2023 · TUHH & HSVA
Numerical Investigation of the Influence of the Axial Position of the Propeller on the Propulsion Performance and the Hull-Propeller Interaction Using the Body-Force-Method
⬇ Download PDF
A numerical analysis assessing the influence of propeller axial position on propulsion performance and hull–propeller interaction using a coupled RANS–BEM (VLM) approach. The study integrates CAESES for parametric propeller geometry variation, FreSCo+ (HSVA/TUHH) for hydrodynamic evaluation, and QCM (HSVA) as the propeller potential solver. Four axial positions on a model-scale container ship are evaluated in calm water and validated against HSVA experimental results. Results identify position 3 (x = 6.25m full scale) as optimal, yielding open-water efficiency improvements of 0.40% and power savings of 0.41%.
Key Results
Hull resistance prediction shows 1.5% error against EFD. Wake fraction and thrust deduction factor trends are consistent between CFD and EFD. Self-propulsive coefficients show minimal variation across positions, with position 3 showing the best open-water efficiency. Relative rotative efficiency slightly improves as propeller moves further aft. Total resistance and self-propulsion results validated against HSVA towing tank experiments.
References
| Author(s) | Title | Venue | Type |
|---|---|---|---|
| Sanada et al. | Assessment of EFD–CFD capability for KRISO Container Ship added power | Ocean Engineering, 2022 | EFD |
| Rijpkema et al. | Numerical simulation of propeller-hull interaction using hybrid RANS-BEM | smp'13, 2013 | Numerical |
| Villa et al. | Ship Self Propulsion with different CFD methods | ICHD, 2012 | CFD |
| Bekhit | Numerical simulation of ship self-propulsion using body force method | IOP Conf., 2018 | Numerical |
| Knutsson & Larsson | Large Area Propellers | smp'11, 2011 | CFD |
| ITTC | Recommended Procedures 7.5-02-03-01.4 — 1978 ITTC Performance Prediction Method | ITTC, 2011 | EFD |
BibTeX
BibTeX Citation
@inproceedings{akinmulewo2023propeller,
title = {Numerical Investigation of the Influence of the Axial Position of the Propeller on the Propulsion Performance and the Hull-Propeller Interaction Using the Body-Force-Method},
author = {Akinmulewo, Daniel and Rubino, Ginevra and Gosda, Roland and Abdel-Maksoud, Moustafa and Grashorn, Henning},
booktitle = {High Speed Marine Vehicles (HSMV 2023)},
year = {2023},
address = {Naples, Italy},
doi = {10.3233/PMST230033}
}
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