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Our research is motivated by the desire to better understand, model and simulate complex vibrations and waves. Complexity here often arises from multi-scale and multi-physics problems, and the interplay between nonlinearity, problem size, and non-stationarity. Application fields include the structural and wave dynamics of mechanical systems from mechanical, aerospace, and offshore engineering. We study novel phenomena, including rare and extreme events. And we develop new engineering methods for complex dynamical systems. Often integrating physics based approaches with data driven methods from machine learning.

Complex Machine and System Dynamics

Complex machines and systems operate under unsteady loads and exhibit highly nonlinear, irregular, non-stationary, and multi-scale dynamics. We investigate those dynamics using advanced signal processing techniques and machine learning (ML) for system identification and behavior prediction. Particular focus of our research lies in the combination of physics-based simulations with data-driven methods: physics-informed learning, digital twins and explainable artificial intelligence (XAI).

Offshore Dynamics

The Dynamics Group is focussing on the untameable power of the sea and addresses all aspects that arise from this complex environment. The research comprises the investigation of complex non-linear sea state processes in order to understand and predict the genesis of critical or extreme wave events as well as to evaluate the respective consequences on offshore structures in terms of wave-structure-investigations….

Research Projects


The development of a real-time deterministic decision support system (DSS) prototype is the objective of this research project.

Machine learning for simulating soft tissue materials

The I3-Lab „Model guided machine learning for simulating soft tissue materials in medicine“ was initiated as part of the TUHH I3-Lab programm.

Nonlinear Wave-Ice Interaction

This research project addresses the fundamental question of nonlinear wave-ice interaction under solid ice focusing on nonlinear wave propagation and dispersion of waves.

Excitability of Ocean Rogue Waves

The vision is to predict the sea state evolution and the occurrence of rogue wave events up to the limit given by the theoretical horizon of predictability of the specific chaotic sea state.

Energy dissipation and vibration damping in structures subject to self-excited irregular vibrations

Linking data driven approaches with modelling - Understanding and improving energy dissipation and vibration damping in structures subject to self-excited irregular vibrations.

Predicting Ship Hydrodynamics to Enable Autonomous Shipping: Nonlinear Physics and Machine Learning

This I3-project addresses hydrodynamics of autonomous ships in waves as one of the key steps along the development path leading to fully autonomous ships.

Exploring and exploiting complex nonlinear dynamical states in friction-excited mechanical systems

The project studies the localized and propagating nonlinear dynamical states of friction-excited dynamical systems to gain a deeper phenomenological understanding of how friction-excited dynamical systems evolve through multiple transitory states.

Nonlinear Vibration Localization in Cyclic Structures

This project aims at identifying and investigating locally confined nonlinear vibrations in cyclic structures like rotors, turbines, compressors etc.

PI-CUBE: AI-based emission reduction of electric vehicle braking systems

"PI-CUBE" is an international research project in the field of applied artificial intelligence, funded through BMBF. This project aims at developing a novel control strategy for electric cars to reduce potentially harmful emissions (particulate,…

Complex network perspectives on nonlinear dynamics

Integrating tools and methods from complex network analysis with the study of mechanical structures and their dynamics in order to better understand the underlying mechanisms is the aim of this interdisciplinary research project.

Completed projects

Over the years the Dynamics Group has participated in a number of projects. Here you can find a brief overview of these completed projects.

Key Publications

Deep learning for brake squeal: Brake noise detection, characterization and prediction

M. Stender, M. Tiedemann, D. Spieler, D.Schoepflin, N. Hoffmann, S. Oberst

Mech. Syst. Signal Process., 149, 2021, 107181

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On the Deterministic Prediction of Water Waves

M. Klein, M. Dudek, G. F. Clauss, S. Ehlers, J. Behrendt, N. Hoffmann, M.Onorato

Fluids 2020, 5, 9.


Nonlinear real time prediction of ocean surface waves,

N. Köllisch, J. Behrendt, M. Klein, N. Hoffmann

Ocean Engineering 157, 387-400, 2018


Peregrine breathers as design waves for wave-structure interaction

M. Klein, G. F. Clauss, S. Rajendran, C. G. Soares, M. Onorato

Ocean Engineering 128, 199-212, 2016


Rogue wave observation in a water wave tank

A. Chabchoub, N. Hoffmann, and N. Akhmediev

Phys. Rev. Lett. 106, 204502

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A minimal model for studying properties of the mode-coupling type instability in friction induced oscillations

N. Hoffmann, M. Fischer, R. Allgaier, L. Gaul

Mech. Res. Commun. 29.4, 2002, 197-205

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Researchgate Lab

You can also visit our Researchgate Lab, where you can find further information on featured projects and research topics.