Publications
192 results found
Lünser H, Hartmann M, Desmars N, et al., 2021, Influence of sea state parameters on the accuracy of wave simulations of different complexity
The accurate description of the complex genesis and evolution of ocean waves as well as the associated kinematics and dynamics is indispensable for the design of offshore structures and assessment of marine operations. In the majority of cases, the water wave problem is reduced to potential flow theory on a somehow simplified level. However, the non-linear terms in the surface boundary conditions and the fact that they must be fulfilled on the unknown water surface make the boundary value problem considerably complex. On the one hand, the use of complex methods for solving the boundary value problem may give, at the expense of computational time, a very accurate representation of reality. On the other hand, simplified methods are numerically efficient but may only provide sufficient accuracy for a limited range of applications. This paper investigates the influence of different characteristic sea state parameters on the accuracy of irregular wave field simulations (based on a JONSWAP spectrum) by applying the high-order spectral method. Hereby, the underlying Taylor series expansion is truncated at different orders so that numerical simulations of different complexity can be investigated. The wave steepness, spectral-peak enhancement factor as well as directional spreading are systematically varied and truncation at fourth order serves as reference. It is shown that, for specific parameters in terms of wave steepness, enhancement factor and simulation time, the boundary value problem can be significantly reduced while providing sufficient accuracy.
Stender M, Wedler M, Hoffmann N, et al., 2021, Explainable machine learning: A case study on impedance tube measurements
Machine learning techniques allow for finding hidden patterns and signatures in data. Currently, these methods are gaining increased interest in engineering in general and in vibroacoustics in particular. Although ML methods are successfully applied, it is hardly understood how these black-box-type methods make their decisions. Explainable machine learning aims at overcoming this issue by deepen the understanding on the decision making process through perturbation-based model diagnosis. This paper introduces machine learning methods and reviews recent techniques for explainability and interpretability. These methods are exemplified on sound absorption coefficient spectra of one sound absorbing foam material measured in an impedance tube. Variances of the absorption coefficients measurements as a function of the specimen thickness and the operator are modeled by univariate and multivariate machine learning models. In order to identify the driving patterns, i.e., how and in which frequency regime the measurements are affected by the setup specifications, Shapley additive explanations are derived for the ML models. It is demonstrated how explaining machine learning models can be used to discover and express complicated relations in experimental data, thereby paving the way to novel knowledge discovery strategies in evidence-based modeling.
Ohlsen J, Neidhardt M, Schlaefer A, et al., 2021, Modelling shear wave propagation in soft tissue surrogates using a finite element‐ and finite difference method, PAMM, Vol: 20, ISSN: 1617-7061
<jats:title>Abstract</jats:title><jats:p>Shear Wave Elasticity Imaging (SWEI) has become a popular medical imaging technique [1] in which soft tissue is excited by the acoustic radiation forces of a focused ultrasonic beam. Tissue stiffness can then be derived from measurements of shear wave propagation speeds [2]. The main objective of this work is a comparison of a finite element (FEM) and a finite difference method (FDM) in terms of their computational efficiency when modeling shear wave propagation in tissue phantoms. Moreover, the propagation of shear waves is examined in experiments with ballistic gelatin to assess the simulation results. In comparison to the FEM the investigated FDM proves to be significantly more performant for this computing task.</jats:p>
Nitti A, Stender M, Hoffmann N, et al., 2021, Spatially localized vibrations in a rotor subjected to flutter, NONLINEAR DYNAMICS, Vol: 103, Pages: 309-325, ISSN: 0924-090X
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- Citations: 5
Desmars N, Hartmann M, Behrendt J, et al., 2021, RECONSTRUCTION OF OCEAN SURFACES FROM RANDOMLY DISTRIBUTED MEASUREMENTS USING A GRID-BASED METHOD, 40th ASME International Conference on Ocean, Offshore and Arctic Engineering (OMAE), Publisher: AMER SOC MECHANICAL ENGINEERS
Stender M, Hoffmann N, Papangelo A, 2020, The Basin Stability of Bi-Stable Friction-Excited Oscillators, LUBRICANTS, Vol: 8
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- Citations: 4
Stender M, Hoffmann N, Papangelo A, 2020, The Basin Stability of Bi-Stable Friction-Excited Oscillators
<jats:p>Stability considerations play a central role in structural dynamics to determine states that are robust against perturbations during the operation. Linear stability concepts, such as the complex eigenvalue analysis, constitute the core of analysis approaches in engineering reality. However, most stability concepts are limited to local perturbations, i.e. they can only measure a state&rsquo;s stability against small perturbations. Recently, the concept of basin stability has been proposed as a global stability concept for multi-stable systems. As multi-stability is a well-known property of a range of nonlinear dynamical systems, this work studies the basin stability of bi-stable mechanical oscillators that are affected and self-excited by dry friction. The results indicate how the basin stability complements the classical binary stability concepts for quantifying how stable a state is given a set of permissible perturbations.</jats:p>
Tonazzi D, Passafiume M, Papangelo A, et al., 2020, Numerical and experimental analysis of the bi-stable state for frictional continuous system, NONLINEAR DYNAMICS, Vol: 102, Pages: 1361-1374, ISSN: 0924-090X
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- Citations: 6
Papangelo A, Putignano C, Hoffmann N, 2020, Self-excited vibrations due to viscoelastic interactions, MECHANICAL SYSTEMS AND SIGNAL PROCESSING, Vol: 144, ISSN: 0888-3270
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- Citations: 24
Stender M, Jahn M, Hoffmann N, et al., 2020, Hyperchaos co-existing with periodic orbits in a frictional oscillator, JOURNAL OF SOUND AND VIBRATION, Vol: 472, ISSN: 0022-460X
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- Citations: 11
Hartmann MCN, Polach FVBU, Ehlers S, et al., 2020, Investigation of Nonlinear Wave-Ice Interaction Using Parameter Study and Numerical Simulation, JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING-TRANSACTIONS OF THE ASME, Vol: 142, ISSN: 0892-7219
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- Citations: 3
Klein M, Dudek M, Clauss GF, et al., 2020, On the Deterministic Prediction of Water Waves, FLUIDS, Vol: 5
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- Citations: 26
Jahn M, Stender M, Tatzko S, et al., 2020, The extended periodic motion concept for fast limit cycle detection of self-excited systems, COMPUTERS & STRUCTURES, Vol: 227, ISSN: 0045-7949
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- Citations: 6
Wollmann T, Dannemann M, Langkamp A, et al., 2020, Combined experimental-numerical approach for the 3D vibration analysis of rotating composite compressor blades: An introduction
As compressor blades are subjected to highly dynamic loads, there is a particular interest in determining their modal properties under operating condition. Furthermore, intensive research is conducted for the development of fibre-reinforced epoxy blades due to the high specific stiffness and strength as well as the high damping of composite materials. Traditional modal analysis techniques are state of the art to determine the vibration behaviour of non-rotating/stationary blades, where some new approaches show the vibration analysis of rotating blades. These approaches for rotating structures have the disadvantage, that either the excitation or the measurement method are influencing the dynamic behaviour of the investigated structure or the method itself cannot be applied for composite materials. Other techniques do not allow a continuous or full-field measurement of the rotating structure. To determine the vibration behaviour of rotating composite compressor blades, a combined experimental-numerical approach is introduced. Therefore, an experimental system for the vibration excitation and a 3-dimensional determination of the vibration behaviour of rotating components are presented. An overview of the main addressed research topics is given.
Wollmann T, Dannemann M, Langkamp A, et al., 2020, Combined experimental-numerical approach for the 3D vibration analysis of rotating composite compressor blades: An introduction
© CCM 2020 - 18th European Conference on Composite Materials. All rights reserved. As compressor blades are subjected to highly dynamic loads, there is a particular interest in determining their modal properties under operating condition. Furthermore, intensive research is conducted for the development of fibre-reinforced epoxy blades due to the high specific stiffness and strength as well as the high damping of composite materials. Traditional modal analysis techniques are state of the art to determine the vibration behaviour of non-rotating/stationary blades, where some new approaches show the vibration analysis of rotating blades. These approaches for rotating structures have the disadvantage, that either the excitation or the measurement method are influencing the dynamic behaviour of the investigated structure or the method itself cannot be applied for composite materials. Other techniques do not allow a continuous or full-field measurement of the rotating structure. To determine the vibration behaviour of rotating composite compressor blades, a combined experimental-numerical approach is introduced. Therefore, an experimental system for the vibration excitation and a 3-dimensional determination of the vibration behaviour of rotating components are presented. An overview of the main addressed research topics is given.
Wollmann T, Dannemann M, Langkamp A, et al., 2020, Combined experimental-numerical approach for the 3D vibration analysis of rotating composite compressor blades: An introduction
© CCM 2020 - 18th European Conference on Composite Materials. All rights reserved. As compressor blades are subjected to highly dynamic loads, there is a particular interest in determining their modal properties under operating condition. Furthermore, intensive research is conducted for the development of fibre-reinforced epoxy blades due to the high specific stiffness and strength as well as the high damping of composite materials. Traditional modal analysis techniques are state of the art to determine the vibration behaviour of non-rotating/stationary blades, where some new approaches show the vibration analysis of rotating blades. These approaches for rotating structures have the disadvantage, that either the excitation or the measurement method are influencing the dynamic behaviour of the investigated structure or the method itself cannot be applied for composite materials. Other techniques do not allow a continuous or full-field measurement of the rotating structure. To determine the vibration behaviour of rotating composite compressor blades, a combined experimental-numerical approach is introduced. Therefore, an experimental system for the vibration excitation and a 3-dimensional determination of the vibration behaviour of rotating components are presented. An overview of the main addressed research topics is given.
Shiroky IB, Papangelo A, Hoffmann N, et al., 2020, Nucleation and propagation of excitation fronts in self-excited systems, PHYSICA D-NONLINEAR PHENOMENA, Vol: 401, ISSN: 0167-2789
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- Citations: 6
Stender M, Hoffmann N, 2020, Deep learning for predicting brake squeal, International Conference on Noise and Vibration Engineering (ISMA) / International Conference on Uncertainty in Structural Dynamics (USD), Publisher: KATHOLIEKE UNIV LEUVEN, DEPT WERKTUIGKUNDE, Pages: 3327-3337
Stender M, Di Bartolomeo M, Massi F, et al., 2019, Revealing transitions in friction-excited vibrations by nonlinear time-series analysis, NONLINEAR DYNAMICS, Vol: 98, Pages: 2613-2630, ISSN: 0924-090X
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- Citations: 20
Stender M, Tiedemann M, Hoffmann N, 2019, Energy harvesting below the onset of flutter, JOURNAL OF SOUND AND VIBRATION, Vol: 458, Pages: 17-21, ISSN: 0022-460X
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- Citations: 8
Stender M, Oberst S, Tiedemann M, et al., 2019, Complex machine dynamics: systematic recurrence quantification analysis of disk brake vibration data, NONLINEAR DYNAMICS, Vol: 97, Pages: 2483-2497, ISSN: 0924-090X
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- Citations: 21
Gnanasambandham C, Stender M, Hoffmann N, et al., 2019, Multi-scale dynamics of particle dampers using wavelets: Extracting particle activity metrics from ring down experiments, JOURNAL OF SOUND AND VIBRATION, Vol: 454, Pages: 1-13, ISSN: 0022-460X
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- Citations: 7
Stender M, Tiedemann M, Hoffmann L, et al., 2019, Determining growth rates of instabilities from time-series vibration data: Methods and applications for brake squeal, MECHANICAL SYSTEMS AND SIGNAL PROCESSING, Vol: 129, Pages: 250-264, ISSN: 0888-3270
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- Citations: 16
Didonna M, Stender M, Papangelo A, et al., 2019, Reconstruction of Governing Equations from Vibration Measurements for Geometrically Nonlinear Systems, LUBRICANTS, Vol: 7
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- Citations: 11
Chabchoub A, Hoffmann N, Tobisch E, et al., 2019, Drifting breathers and Fermi-Pasta-Ulam paradox for water waves, WAVE MOTION, Vol: 90, Pages: 168-174, ISSN: 0165-2125
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- Citations: 14
Kellner L, Stender M, Von Bock Und Polach RUF, et al., 2019, Establishing a common database of ice experiments and using machine learning to understand and predict ice behavior, Cold Regions Science and Technology, Vol: 162, Pages: 56-73, ISSN: 0165-232X
Ice material models often limit the accuracy of ice related simulations. The reasons for this are manifold, e.g. complex ice properties. One issue is linking experimental data to ice material modeling, where the aim is to identify patterns in the data that can be used by the models. However, numerous parameters that influence ice behavior lead to large, high dimensional data sets which are often fragmented. Handling the data manually becomes impractical. Machine learning and statistical tools are applied to identify how parameters, such as temperature, influence peak stress and ice behavior. To enable the analysis, a common and small scale experimental database is established.
Chabchoub A, Mozumi K, Hoffmann N, et al., 2019, Directional soliton and breather beams, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 116, Pages: 9759-9763, ISSN: 0027-8424
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- Citations: 16
Fontanela F, Grolet A, Salles L, et al., 2019, Dissipative solitons in forced cyclic and symmetric structures, MECHANICAL SYSTEMS AND SIGNAL PROCESSING, Vol: 117, Pages: 280-292, ISSN: 0888-3270
Papangelo A, Fontanela F, Grolet A, et al., 2019, Multistability and localization in forced cyclic symmetric structures modelled by weakly-coupled Duffing oscillators, Publisher: Elsevier
Stender M, Oberst S, Hoffmann N, 2019, Recovery of differential equations from impulse response time series data for model identification and feature extraction, Vibration, Vol: 2, Pages: 25-46, ISSN: 2571-631X
Time recordings of impulse-type oscillation responses are short and highly transient. These characteristics may complicate the usage of classical spectral signal processing techniques for (a) describing the dynamics and (b) deriving discriminative features from the data. However, common model identification and validation techniques mostly rely on steady-state recordings, characteristic spectral properties and non-transient behavior. In this work, a recent method, which allows reconstructing differential equations from time series data, is extended for higher degrees of automation. With special focus on short and strongly damped oscillations, an optimization procedure is proposed that fine-tunes the reconstructed dynamical models with respect to model simplicity and error reduction. This framework is analyzed with particular focus on the amount of information available to the reconstruction, noise contamination and nonlinearities contained in the time series input. Using the example of a mechanical oscillator, we illustrate how the optimized reconstruction method can be used to identify a suitable model and how to extract features from uni-variate and multivariate time series recordings in an engineering-compliant environment. Moreover, the determined minimal models allow for identifying the qualitative nature of the underlying dynamical systems as well as testing for the degree and strength of nonlinearity. The reconstructed differential equations would then be potentially available for classical numerical studies, such as bifurcation analysis. These results represent a physically interpretable enhancement of data-driven modeling approaches in structural dynamics.
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