Parallel Computations and Co-Simulation in Universal Mechanism Software. Part I: Algorithms and Implementation

Abstract

Parallel computations speed up simulation of multibody system dynamics, in particular, dynamics of railway vehicles and trains. It is important for reduction of required time at the stage of new railway vehicle design, for increase of complexity of studied problems and for real-time applications. We consider realization of parallel computations in Universal Mechanism software in three different areas: simulation of rail vehicle and train dynamics, evaluation of wheel profile wear and multi-variant computations. The use of clusters for parallel running of multi-variant computations is illustrated. Co-simulation based on the interface between Universal Mechanism and Matlab/Simulink and other software tools is discussed.

Parallel Computations and Co-Simulation in Universal Mechanism Software. Part Ii: Examples

“…Frictional wedges are modeled by rigid bodies with six DOF each. The model has no joints, and its simulation with the parallel algorithm described in [1] is faster using even one thread in comparison with other solvers available in UM. Simulation in our case corresponds to the vehicle motion in a tangent section of 300 m length with a constant speed of 20 m/s.…”

“…As discussed in the first part of this paper [1], there are several possible strategies to compute a series of numerical experiments: (1) to run one solver sequentially with allowed maximum of computing threads in it, (2) to run allowed maximum of solvers with the only computing thread in it, or (3) to run several solvers with several threads in each. In UM software, the maximum number of simultaneously running processes (solvers) and threads in one solver is limited by the number of logical processors of the operating system.…”

“…The table includes the average values of the following variables: h -integration step size; Th -CPU costs for one step size; the value does not include an overhead related to computation of simulation results, animation, plots, etc. Other variables correspond to the CPU time for each of the parallel sections [1]: Tkin -PS1 (prediction, computation of kinematics, mass matrices, internal elastic and damping forces, inertia and gravity forces); Tfrc -PS2 (evaluation of forces and Jacobians); Taddf -PS3 (evaluation and factorization of the preconditioning matrices, computation of total forces in equations); Tcg_s, Tcg_d, Tcg_c, Tcg_t, Tcg_f -PS4-8 (solving linear equations by the conjugate gradient method); Tfin -PS9 (computation of new values of coordinates, velocities, and accelerations).…”

“…In Section 2, we consider a practical application of parallel algorithms, described in the first part of this paper [1], and implemented in Universal Mechanism software [2].…”