A collaborative benchmarking framework for multibody system dynamics

[Abstract] Despite the importance given to the computational efficiency of multibody system (MBS) simulation tools, there is a lack of standard benchmarks to measure the performance of these kinds of numerical simulations. This works proposes a collaborative benchmarking framework to measure and compare the performance of different MBS simulation methods. The framework is made up of two main components: (a) an on-line repository of test problems with reference solutions and standardized procedures to measure computational efficiency and (b) a prototype implementation of a collaborative web-based application to collect, organize and share information about performance results in an intuitive and graphical form. The proposed benchmarking framework has been tested to evaluate the performance of a commercial MBS simulation software, and it proved to be an effective tool to collect and analyze information about the numerous factors which affect the computational efficiency of dynamic simulations of multibody systems

EFFICIENT PARALLEL COMPUTER SIMULATION OF THE MOTION BEHAVIORS OF CLOSED-LOOP MULTIBODY SYSTEMS

ABSTRACT This paper presents an efficient parallelizable algorithm for the computer-aided simulation and numerical analysis of motion behaviors of multibody systems with closed-loops. The method is based on cutting certain user-defined system interbody joints so that a system of independent multibody subchains is formed. These subchains interact with one another through associated unknown constraint forces c f at the cut joints. The increased parallelism is obtainable through cutting joints and the explicit determination of associated constraint forces combined with a sequential O(n) method. Consequently, the sequential O(n) procedure is carried out within each subchain to form and solve the equations of motion while parallel strategies are performed between the subchains to form and solve constraint equations concurrently. For multibody systems with closed-loops, joint separations play both a role of creation of parallelism for computing load distribution and a role of opening a closed-loop for use of the O(n) algorithm. Joint separation strategies provide the flexibility for use of the algorithm so that it can easily accommodate the available number of processors while maintaining high efficiency. The algorithm gives the best performance for the application scenarios for n>>1 and n>>m, where n and m are number of degree of freedom and number of constraints of a multibody system with closed-loops respectively. The algorithm can be applied to both distributed-memory parallel computing systems and shared-memory parallel computing systems. INTRODUCTION In practice, dynamical systems can be modeled as multibody systems. Examples of such systems include, but are not limited to, spacecraft, robotic systems, mechanisms in machinery, automotive applications, land vehicles, underwater vehicles, ships, aircraft, the human body, molecular chain in biotechnology fields, and even quantum dynamical system at nano scale

A Gluing Algorithm for Distributed Simulation of Multibody Systems

A new gluing algorithm is presented that can be used tocouple distributed subsystem models fordynamics simulation of mechanical systems. Using this gluingalgorithm, subsystem models can be analyzed attheir distributed locations, using their own independent solvers,and on their own platforms. The gluing algorithmdeveloped relies only on information available at the subsysteminterfaces. This not only enables efficientintegration of subsystem models, but also engenders modelsecurity by limiting model access only to the exposedinterface information. These features make the algorithm suitablefor a real and practical distributed simulationenvironment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43325/1/11071_2004_Article_5252593.pd

Integration of Heterogeneous Simulation Models for Network-Distributed Simulation.

Distributed simulation is close to reaching its potential to fulfill the demands of industrial CAE by harnessing nearly unlimited computing power across network environments and by efficiently reusing and integrating already constructed simulation models. A distributed simulation platform, denoted as D-Sim, has been under development in our research group since 2001. The present work focuses on the integration of heterogeneous subsystem models, including multibody dynamics (MBD) and finite element (FEM) subsystem models, and conducting seamlessly integrated simulation for design tasks in a distributed computing environment. Under the guise of a gluing algorithm, the Partitioned Iteration Method (PIM) was developed, which can be used to integrate distributed deformable bodies while allowing large rigid body motions among the bodies or subsystems. The PIM is based upon a floating frame of reference, in which the global motion of the flexible body can be expressed with linearized elastic deformations by assumption of infinitesimal strains and reference frame as large overall motion. When embedded in D-Sim, it also enables using independent simulation servers, in which each server can run commercially available or research-based MBD and/or FEM codes to minimize the information exchange across the different platforms yet still obtain results within engineering accuracy. Examples are provided which integrate FEM and MBD models and which demonstrate the performance of the PIM. The examples also highlight how to decouple and integrate rigid body motion and elastic deformation using the enhanced gluing algorithm. A gluing algorithm plays a critical role in integrating the distributed subsystems and components. It is one of the research objectives to apply the gluing algorithm to general simulation models, which may be assembled by diverse connecting methods, including spot welds, bolts, bushings, and other physical connections. The gluing algorithm concept has been extended by creating flexible gluing joints, which can deal with various connections between subsystems, and can account for linear and non-linear flexibility at these connections. This not only improves the accuracy of the simulation to represent the real physical system, but also can improve the convergence of multibody dynamics simulation.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64747/1/gsryu_1.pd