2014
DOI: 10.1177/1464419314549875
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Molecular dynamics simulation of simple polymer chain formation using divide and conquer algorithm based on the augmented Lagrangian method

Abstract: This paper presents an efficient multibody methodology for the simulation of molecular dynamics of simple polymer chains. The algorithm is formulated in terms of absolute coordinates. The augmented Lagrangian method is incorporated into the divide and conquer framework giving new parallel, logarithmic order algorithm suitable for the simulation of general multibody system topologies. The approach is robust in case of potential rank deficiencies of the Jacobian matrices that embrace the group of systems involvi… Show more

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Cited by 15 publications
(6 citation statements)
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“…Multibody dynamics has been used in various research branches from microscale (Malczyk andFrączek 2014, Haghshenas-Jaryani andBowling 2015)to macroscale systems (Featherstone 2014). In some cases, the traditional joints, e.g., prismatic, spherical, and revolute joints cannot simulate the system's actual behavior.…”
Section: Introductionmentioning
confidence: 99%
“…Multibody dynamics has been used in various research branches from microscale (Malczyk andFrączek 2014, Haghshenas-Jaryani andBowling 2015)to macroscale systems (Featherstone 2014). In some cases, the traditional joints, e.g., prismatic, spherical, and revolute joints cannot simulate the system's actual behavior.…”
Section: Introductionmentioning
confidence: 99%
“…Computational improvements to the initial algorithm have been published as well such as techniques to keep constraint drift under control [24,31] and optimized variants of the algorithm for computer architectures with reduced computational resources [10]. The practical applications of the DCA are multiple and range from the simulation of simple linkages and multibody chains to molecular dynamics [29,38].…”
Section: Related Workmentioning
confidence: 99%
“…In Gunzburger and Lee (2000), Bresch and Koko (2006), Koko and Sassi (2016), Qiang 2001, various domain decomposition algorithms are obtained for partial differential equations with different energy functionals and solution strategies. Kong et al (2009) only restrict the interest to the velocity vector for the domain decomposition method and construct the optimization problems by using the sensitivity derivatives method and the Lagrange multiplier rule (Malczyk and Czek 2015), the constrained optimization problems are transformed into unconstrained problems, then, a gradient method-based approach to the solution of domain decomposition problem is proposed to solve the unconstrained optimality system.…”
Section: Introductionmentioning
confidence: 99%