Gilching, Germany


Gilching, Germany
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Schulze M.,SIMPACK AG | Dietz S.,SIMPACK AG | Burgermeister B.,SIMPACK AG | Tuganov A.,7 4270 Rue Saint Dominique | And 3 more authors.
Journal of Computational and Nonlinear Dynamics | Year: 2014

Current challenges in industrial multibody system simulation are often beyond the classical range of application of existing industrial simulation tools. The present paper describes an extension of a recursive order-n multibody system (MBS) formulation to nonlinear models of flexible deformation that are of particular interest in the dynamical simulation of wind turbines. The floating frame of reference representation of flexible bodies is generalized to nonlinear structural models by a straightforward transformation of the equations of motion (EoM). The approach is discussed in detail for the integration of a recently developed discrete Cosserat rod model representing beamlike flexible structures into a general purpose MBS software package. For an efficient static and dynamic simulation, the solvers of the MBS software are adapted to the resulting class of MBS models that are characterized by a large number of degrees of freedom, stiffness, and high frequency components. As a practical example, the run-up of a simplified three-bladed wind turbine is studied where the dynamic deformations of the three blades are calculated by the Cosserat rod model. © 2014 by ASME.

Burgermeister B.,SIMPACK AG | Arnold M.,Martin Luther University of Halle Wittenberg | Eichberger A.,SIMPACK AG
Multibody System Dynamics | Year: 2011

The rapidly increasing complexity of multi-body system models in applications like vehicle dynamics, robotics and bio-mechanics requires qualitative new solution methods to slash computing times for the dynamical simulation. Detailed multi-body systems are designed for accurate off-line simulation. For real-time applications or efficient long-term simulations simplified models are used (Rill, G.: J. Braz. Soc. Mech. Sci. XIX(2):192-206 (1997)). In contrast to pure numerical model reduction techniques (Antoulas, A.C.: Approximation of large-scale dynamical systems (2005) and Fehr, J., Eberhard, P.: J. Comput. Nonlinear Dyn. 5:031005 (2010)), the presented quasi-static solution method is based on analytical model reduction combined with adapted numerical methods for evaluating and solving the (reduced) equations of motion efficiently and focuses on accelerated computation of the low frequency parts of the solution of the nonlinear equations of motion by smoothing out the velocities of fast moving low-mass bodies. The high frequency parts are eliminated by neglecting some of the inertia forces and torques. This reduces numerical stiffness and allows larger step-sizes for the time integration. The efficient and real-time capable combination with existing highly efficient algorithms for multi-body dynamics (\mathcal{O}(N) multi-body formalisms) requires appropriate integration methods that are adapted to the special structure of the multi-body formalism and solve the nonlinear constraints with a small, limited number of calculation steps. © 2011 Springer Science+Business Media B.V.

Arnold M.,Martin Luther University of Halle Wittenberg | Clauss C.,SIMPACK AG | Schierz T.,Fraunhofer Institute for Integrated Circuits
Archive of Mechanical Engineering | Year: 2013

Complex multi-disciplinary models in system dynamics are typically composed of subsystems. This modular structure of the model reflects the modular structure of complex engineering systems. In industrial applications, the individual subsystems are often modelled separately in different mono-disciplinary simulation tools. The Functional Mock-Up Interface (FMI) provides an interface standard for coupling physical models from different domains and addresses problems like export and import of model components in industrial simulation tools (FMI for Model Exchange) and the standardization of co-simulation interfaces in nonlinear system dynamics (FMI for Co-Simulation), see [10]. The renewed interest in algorithmic and numerical aspects of co-simulation inspired some new investigations on error estimation and stabilization techniques in FMI for Model Exchange and Co-Simulation v2.0 compatible co-simulation environments. In the present paper, we focus on reliable error estimation for communication step size control in this framework.

Baecker M.,Fraunhofer Institute for Industrial Mathematics | Gallrein A.,Fraunhofer Institute for Industrial Mathematics | Calabrese F.,Fraunhofer Institute for Industrial Mathematics | Mansvelders R.,SIMPACK GmbH
SAE Technical Papers | Year: 2016

Sudden pressure loss can lead to vehicle instability and - without aid of systems such as e.g. Electronic Stability Control (ESC) - to an emergency situation, possibly resulting in an accident. But also with an ESC system such a situation is an unusual (unstandardized) application case, because the vehicle system (car+tires) properties change very rapidly during the sudden pressure loss, which leads to a very high dynamic response in the system and moreover to a very fuzzy and unclear description of the vehicle system. From this point of view, a proper validation and verification of an ESC system for such an application seems to have a high safety relevancy. The authors have set up a simulation case to simulate a sudden tire inflation pressure loss and its consequences to the car stability. Using this simulation setup enables a CAE engineer to pre-develop ESC systems and/or to validate and test these for a realistic and relevant use case. © 2016 SAE International.

Arnold M.,Martin Luther University of Halle Wittenberg | Burgermeister B.,SIMPACK AG | Fuhrer C.,Lund University | Hippmann G.,SIMPACK AG | Rill G.,Regensburg University of Applied Sciences
Vehicle System Dynamics | Year: 2011

Robust and efficient numerical methods are an essential prerequisite for the computer-based dynamical analysis of engineering systems. In vehicle system dynamics, the methods and software tools from multibody system dynamics provide the integration platform for the analysis, simulation and optimisation of the complex dynamical behaviour of vehicles and vehicle components and their interaction with hydraulic components, electronical devices and control structures. Based on the principles of classical mechanics, the modelling of vehicles and their components results in nonlinear systems of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs) of moderate dimension that describe the dynamical behaviour in the frequency range required and with a level of detail being characteristic of vehicle system dynamics. Most practical problems in this field may be transformed to generic problems of numerical mathematics like systems of nonlinear equations in the (quasi-)static analysis and explicit ODEs or DAEs with a typical semi-explicit structure in the dynamical analysis. This transformation to mathematical standard problems allows to use sophisticated, freely available numerical software that is based on well approved numerical methods like the Newton-Raphson iteration for nonlinear equations or Runge-Kutta and linear multistep methods for ODE/DAE time integration. Substantial speed-ups of these numerical standard methods may be achieved exploiting some specific structure of the mathematical models in vehicle system dynamics. In the present paper, we follow this framework and start with some modelling aspects being relevant from the numerical viewpoint. The focus of the paper is on numerical methods for static and dynamic problems, including software issues and a discussion which method fits best for which class of problems. Adaptive components in state-of-the-art numerical software like stepsize and order control in time integration are introduced and illustrated by a well-known benchmark problem from rail vehicle simulation. Over the last few decades, the complexity of high-end applications in vehicle system dynamics has frequently given a fresh impetus for substantial improvements of numerical methods and for the development of novel methods for new problem classes. In the present paper, we address three of these challenging problems of current interest that are today still beyond the mainstream of numerical mathematics: (i) modelling and simulation of contact problems in multibody dynamics, (ii) real-time capable numerical simulation techniques in vehicle system dynamics and (iii) modelling and time integration of multidisciplinary problems in system dynamics including co-simulation techniques. © 2011 Copyright Taylor and Francis Group, LLC.

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