The Institute of Fluid Dynamics and Ship Theory offers ongoing

Bachelor/Project/Master theses as well as HiWi activities

in various subject areas.

The topics offered include

1) numerical,

2) theoretical,

3) experimental and

4) artificial intelligence

methods and are applied to fluid mechanics, often in combination with other disciplines, such as structural mechanics, soil mechanics or medical engineering. Several methods can be combined, such as performing flow simulations and experiments.

Detailed examples might refer to the analysis of ship resistance and propulsion, maneuvering in seaways conditions, freak wave simulations, aircraft ditching analysis, floating offshore wind turbines, wave-energy converters, alternative propulsion concepts such as sails, hydrogen transport and storage, patient-assisting medical devices, future urban climate scenarios and climate-related geophysical problems.

Numerical and theoretical topics can include

• Simulations of complex engineering problems
  Examples refer to reducing the resistance and the fuel consumption of ships, increasing the efficiency of renewable energy generating devices or ensuring the safety of applications in the medical, vehicle or aviation sector. Students deepen their knowledge in complex applications and become familiar with sophisticated methods & tools to solve challenging related problems.

• PDE-constraint optimization methods
  Topics include obtaining the best geometry for given constraints. Students will get familiar with modern simulation-based optimization procedures and the related mathematical concepts.

• Algorithmic developments
  Code development is offered for a variety of mesh-based and mesh-free methods, e.g., potential methods, spectral methods, finite-volume methods, lattice-Boltzmann or smoothed particle hydrodynamics methods. Students will acquire a comprehensive knowledge of a specific numerical method and its implementation.

• Investigations of modern & future hardware architectures
  Topics are related to high-performance computing, e.g., GPU and hybrid GPU-CPU implementations, or the design of quantum computer algorithms. Such topics substantially deepen the student’s knowledge in IT and numerical analysis.

• Physical modeling and understanding
  The topics promote the understanding and modeling of fluid physics phenomena, e.g., turbulence, cavitation, hemodynamics, surface roughness, fluid-structure interaction, soil-suspensions or the occurrence of rogue waves etc.. Strategies usually result in either analytical or PDE-based mathematical models that are calibrated with empirical data. Students will acquire sound theoretical knowledge in flow physics and PDE-based mathematical modeling.

• Developing (faster-than) real-time tools
  Topics include deriving analytical or semi-empirical solutions concerning both fundamental research and real-world problems. Examples include developing ‘digital twins’ of maritime structures, seakeeping of ships or optimal control of sails on ships under realistic conditions.

Experimental topics can include

• Preparing, performing and evaluating experiments
  The institute operates a wind tunnel, capable of producing wind speeds of more than 100km/h, as well as an 80-meter-long towing tank, equipped with a snake wave-maker and maneuvering basin. Topics include determining forces and moments acting on ships, racing cars, airplanes or offshore structures, as well as tracking the motions of floating bodies in extreme wave conditions.

• Design and manufacturing of model-scale prototypes
  Topics develop skills in computer-aided design (CAD) software, 3D-printing, construction and measurement technology.

Artificial intelligence topics can include

• Development of decision support systems
  Decision support systems assist system operations in real time, e.g. ship routing. Students will acquire comprehensive knowledge of developing and feeding AI methods with data from sources, e.g., IoT, and participate in the development of digital twins.

• AI-supported numerical modeling
  Topics address features not resolved/captured in numerical/experimental frameworks, e.g. unresolved propulsion systems, or the AI-supported modeling of peak, life-cycle or unrecorded loads. Applications refer to maritime, energy-technology, medical or vehicle and aviation problems. Students will acquire comprehensive knowledge of networking AI methods with simulation techniques and participate in the development of digital twins.

• Reverse engineering, AI-based parameterizations and model-order reductions
  Applications include particularly efficient solutions to high-dimensional engineering problems. Topics will deepen students’ understanding of applied mathematics, reduced-order modeling and the assembly of digital twins.