Parallel Computing in Multibody System Dynamics: Why, When, and
                    How

Negrut, Dan; Serban, Radu; Mazhar, Hammad; Heyn, Toby

doi:10.1115/1.4027313

Cited by 49 publications

(31 citation statements)

References 58 publications

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“…It is worth mentioning that the order of the coefficient matrix U all is very low, which will not cost too much time in computation of determinant det U all . From equation (4), it can also be found that the characteristic equation is a nonlinear or even transcendental function w.r.t. the eigenvalue.…”

Section: Basic Idea Of Linear Mstmmmentioning

confidence: 98%

“…Then the eigenvalue v of the system can be acquired by solving equation (4). For a multibody system in a more generic topology, the overall transfer equation and the overall transfer matrix can be obtained by simply following the automatic deduction theorem of the overall transfer equation for multibody systems 11 taking a general form…”

Section: Basic Idea Of Linear Mstmmmentioning

confidence: 99%

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Distributed parallel computing of the recursive eigenvalue search in the context of transfer matrix method for multibody systems

Rui

Chen

et al. 2016

Advances in Mechanical Engineering

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The modeling and solving a transcendental eigenvalue problem are important issues in the transfer matrix method for linear multibody systems. Based on the recursive eigenvalue search algorithm for transfer matrix method for linear multibody system, the distributed parallel approach for assembling overall transfer matrix and searching eigenvalues is proposed. This is achieved based on Message Parallel Interface. The influence of the CPU core number as well as the distributed network environment on the final computational time is analyzed through numerical examples of both a nonuniform beam and a multiple launch rocket system. The results indicate that the computational time is significantly reduced by the proposed parallel computing method, so that the computational efficiency on optimization and design of complex multibody systems can be improved.

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Section: Basic Idea Of Linear Mstmmmentioning

confidence: 98%

Section: Basic Idea Of Linear Mstmmmentioning

confidence: 99%

Distributed parallel computing of the recursive eigenvalue search in the context of transfer matrix method for multibody systems

Rui

Chen

et al. 2016

Advances in Mechanical Engineering

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“…By using the augmented Lagrangian technique to avoid numerical ill-conditioning, accurate solutions were obtained. Other approaches for the improvement of computational efficiency are based on the advances of parallelization technology [1,2,5,17,18]. García de Jalón et al [10,12,20] developed an alternative formulation of the equations of motion in terms of independent coordinates.…”

Section: Introductionmentioning

confidence: 99%

Efficient and accurate modeling of rigid rods

et al. 2016

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Ten years ago, an original semi-recursive formulation for the dynamic simulation of large-scale multibody systems was presented by García de Jalón et al. (Advances in Computational Multibody Systems, pp. 1-23, 2005). By taking advantage of the cut-joint and rod-removal techniques through a double-step velocity transformation, this formulation proved to be remarkably efficient. The rod-removal technique was employed, primarily, to reduce the number of differential and constraint equations. As a result, inertia and external forces were applied to neighboring bodies. Those inertia forces depended on unknown accelerations, a fact that contributed to the complexity of the system inertia matrix. In search of performance improvement, this paper presents an approximation of rod-related inertia forces by using accelerations from previous time-steps. Additionally, a mass matrix partition is carried out to preserve the accuracy of the original formulation. Three extrapolation methods, namely, point, linear Lagrange and quadratic Lagrange extrapolation methods, are introduced to evaluate the unknown rod-related inertia forces. In order to assess the computational efficiency and solution accuracy of the presented approach, a general-purpose MATLAB/C/C++ simulation code is implemented. A 15-DOF, 12-rod sedan vehicle model with MacPherson strut and multi-link suspension systems is modeled, simulated and analyzed.

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“…One can encounter applications like that in such areas as robotics, biomechanics, and automotive industry. The other places where one needs efficient MBS simulations can be found in various interdisciplinary applications like, e.g., molecular dynamics simulations [1,2] or granular media physics [3]. The applications are more complex and demanding.…”

Section: Introductionmentioning

confidence: 99%

“…In [19], Critchley and Anderson explored the notion of recursive coordinate reduction. There are other works associated with parallel multibody dynamics simulations as well [3,20,21]. Recently, the divide-and-conquer based schemes [17] have attracted significant attention to the development of efficient parallel algorithms for large MBS, partially due to the fact that computationally powerful multicore processors or graphics processor units are cheaply available on the market.…”

Section: Introductionmentioning

confidence: 99%

A parallel Hamiltonian formulation for forward dynamics of closed-loop multibody systems

2016

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This paper presents a novel recursive divide-and-conquer formulation for the simulation of complex constrained multibody system dynamics based on Hamilton's canonical equations (HDCA). The systems under consideration are subjected to holonomic, independent constraints and may include serial chains, tree chains, or closed-loop topologies. Although Hamilton's canonical equations exhibit many advantageous features compared to their acceleration based counterparts, it appears that there is a lack of dedicated parallel algorithms for multi-rigid-body system dynamics based on the Hamiltonian formulation. The developed HDCA formulation leads to a two-stage procedure. In the first phase, the approach utilizes the divide and conquer scheme, i.e., a hierarchic assembly-disassembly process to traverse the multibody system topology in a binary tree manner. The purpose of this step is to evaluate the joint velocities and constraint force impulses. The process exhibits linear O(n) (n -number of bodies) and logarithmic O(log 2 n) numerical cost, in serial and parallel implementations, respectively. The time derivatives of the total momenta are directly evaluated in the second parallelizable step of the algorithm. Sample closed-loop test cases indicate very small constraint violation errors at the position and velocity level as well as marginal energy drift without any additional form of constraint stabilization techniques involved in the solution process. The results are comparatively set against more standard acceleration based Featherstone's DCA approach to indicate the performance of the HDCA algorithm.

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Parallel Computing in Multibody System Dynamics: Why, When, and How

Cited by 49 publications

References 58 publications

Distributed parallel computing of the recursive eigenvalue search in the context of transfer matrix method for multibody systems

Distributed parallel computing of the recursive eigenvalue search in the context of transfer matrix method for multibody systems

Efficient and accurate modeling of rigid rods

A parallel Hamiltonian formulation for forward dynamics of closed-loop multibody systems

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