Simulation of Fluid Structure Inte actions by using High Order FEM and SPH

The investigation of fluid structure interactions is crucial in many areas of science and technology. This study presents a robust methodology for studying fluid structure interactions, which is characterized by high convergence behavior and is insensitive to distortion and stiffening effects. Therefore, the Smoothed Particle Hydodynamicy is coupled with the high order FEM. After various coupling methods for linear and quadratic elements from the literature have been described, a variant with higher-value approach functions is implemented. The two methods can be meshed independend without loss of accuracy. After successful validation, it is shown that only a few finite elements are necessary to obtain a convergent solution. The presented method is promising especially for thin-walled structures where significantly fewer degrees of freedom are required than for linear elements

A study on harmonic excitation based experimental characterization of damping materials for acoustic simulations

The presented study deals with the experimental characterization of damping materials for acoustic simulations with respect to the stiffness and damping in dependence of the excitation frequency, i.e.~frequency-dependent elasticity modulus.The test rigs under consideration utilize a shaker, acceleration sensors and a laser Doppler vibrometer (LDV) to measure oscillating behaviour at frequencies ranging from 20 to 2000 Hz.Suitable mounting properties of the test rigs are examined experimentally and by finite element analysis. The applicability of the gained results for acoustic simulations is investigated with results from a window test setup

Auslegung und Multi-fidelity Optimierung von spant- und stringerversteiften Schalen aus kohlenstofffaserverstärktem Kunststoff (CFK)

In dieser Arbeit wird eine automatisierte Optimierung spant- und stringerversteifter Teilschalen erarbeitet, die die Minimierung der Masse unter Gewährleistung definierter Stabilitätskriterien zum Ziel hat. Möglichkeiten zur Steigerung der Geschwindigkeit und Genauigkeit von Optimierungsprozessen werden vorgestellt und erprobt. Die notwendige Ermittlung der Beullasten wird mit linearen Eigenwertanalysen, Metamodellen und nichtlinearen Nachbeulanalysen durchgeführt. Ein FEM-Programm zur schnellen Beulanalyse wird hinsichtlich Modellierung, Diskretisierung und Parametersensitivität untersucht. Verschiedene Metamodelle werden bezüglich Approximationsgenauigkeit und erforderlichen Aufwandes studiert

Rechen- und laufzeitoptimierte Implementierung von adaptiven Steuerungen durch digitale Signalverarbeitung mit Multi-rate Algorithmen

This work is an attempt to find suitable multi-rate (MR) algorithms for an adaptive control by means of an active structural acoustic control (ASAC). For a practical application these MR algorithms are implemented as single-input-single-output (SISO) systems. The systems are compared to traditional adaptive controls taking into account run time and control success. Furthermore, alternative structures of MR systems are presented and compared with respect to delay, control performance and computational efficiency. Effects produced by MR components are discussed in detail and questions regarding causality and filter selection are investigated thoroughly

Autoregressive neural networks for predicting the behavior of viscoelastic materials

In the present work, the capabilities of neural networks to describe viscoelastic material behavior are investigated. Using real one-dimensional test data from a tensile test, autoregressive neural networks were trained. The best networks were then used to calculate the stress and the stiffness in displacement- and force-driven simulations. The results were compared with both experimental data and simulation results of a classical material model.The viscoelasticity discussed here plays a special role in the description of complex rubber materials, in addition to long-term effects, failure or heat-induced mechanisms. Classical material models simplify the real behavior, which is the reason for the occurrence of simulation errors. To overcome these limitations, this paper presents a different way of material modeling by describing the strain-stress correlation using a neural network. Previous stress states from the time history are used in the calculation to account for the path-dependent behavior of viscoelastic materials. Other effects, such as the influence of different temperatures, are not addressed in this work, but can be included with an appropriately large training data set

NOISE CONTROL OF VEHICLE DRIVE SYSTEMS

The paper presents an overall simulation approach to control the noise emission of car engines at a very early stage of the design process where no real prototypes are available. The suggested approach combines different physical models and couples different software tools such as multi-body analysis, fluid dynamics, structural mechanics, magneto-electrodynamics, thermodynamics, acoustics and control as well. The general overall simulation methodology is presented first. Then, this methodology is applied to a combustion engine in order to improve its acoustical behavior by passive means, such as changing the stiffness and the use of damping materials to build acoustic and thermal encapsulations. The active control by applying piezoelectric patch actuators at the oil sump as the noisiest part of the engine is discussed as well. The sound emission is evaluated by hearing tests and a mathematical prediction model of the human perception. Finally, it is shown that the presented approach can be extended to electric engines, which is demonstrated at a newly developed electric wheel hub motor

Simulation of Fluid Structure Inte actions by using High Order FEM and SPH

The investigation of fluid structure interactions is crucial in many areas of science and technology. This study presents a robust methodology for studying fluid structure interactions, which is characterized by high convergence behavior and is insensitive to distortion and stiffening effects. Therefore, the Smoothed Particle Hydodynamicy is coupled with the high order FEM. After various coupling methods for linear and quadratic elements from the literature have been described, a variant with higher-value approach functions is implemented. The two methods can be meshed independend without loss of accuracy. After successful validation, it is shown that only a few finite elements are necessary to obtain a convergent solution. The presented method is promising especially for thin-walled structures where significantly fewer degrees of freedom are required than for linear elements

Application of Particle Dampers on a Scaled Wind Turbine Generator to Improve Low-Frequency Vibro-Acoustic Behavior

The purpose of this paper is to introduce a honeycomb damping plate (HCDP) concept based on the particle damping technique to reduce the low-frequency vibration response of wind turbine generators. The HCDP cells contain granular materials and are mounted at different positions on the generator to reduce the transmission of vibrations from stator ring to stator arm. To investigate the efficiency of the HCDP concept in the laboratory, a small-scale replica inspired by the original wind turbine generator is used as reference geometry. The efficiency of the vibration attenuation by using the HCDP concept is experimentally investigated with the help of a laser scanning vibrometer device. In this contribution, the influence of four different granular materials on the vibration attenuation is experimentally investigated. Furthermore, the influence of HCDP positioning on the transmission path damping is analyzed. Apart from this, the effect of single-unit (SU) and multi-unit (MU) HCDP on the frequency response of the generator is also studied. The experimental approach in this paper shows good damping properties of the HCDP concept for reducing the vibration amplitude

Suppression of the Coffee Ring Effect in a Single Solvent-Based Silicon Nanoparticle Ink

Silicon (Si) is made printable by dispersing Si nanoparticles in a single organic solvent. Viscoelastic properties of the prepared inks as well as the uniformity of inkjet-printed thin films are investigated in dependence on the Si volume fraction. It has been demonstrated that no ink additives are needed to completely suppress the occurrence of the coffee ring effect. This is obtained by increasing the ink’s volume fraction to induce gelation in order to generate elasticity. The printability of our inks is investigated in terms of Weber, Reynolds, and Ohnesorge numbers and found to be maintained even at high particle loads due to shear-thinning viscosity behavior. When printed onto tungsten (W) substrates, Si inks with ϕ(Si) = 0.4% and ϕ(Si) = 2.1% leave a ring stain after drying, whereas coffee rings are absent for inks with ϕ(Si) = 3.0% and above. The reason for this is a significant ink elasticity achieved by the buildup of a gel network for higher particle loads, which leads to thixotropy-like properties. These are low viscosity for printability and elevated elasticity during ink drying, made possible by a breakup of the gel network during drop formation in conjunction with a rapid network reformation after deposition