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An Adaptive Multiscaling Approach for Reducing Computation Time in Simulations of Articulated Biopolymers

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Microscale dynamic simulations can require significant computational resources to generate desired time evolutions. Microscale phenomena are often driven by even smaller scale dynamics, requiring multiscale system definitions to combine these… Click to show full abstract

Microscale dynamic simulations can require significant computational resources to generate desired time evolutions. Microscale phenomena are often driven by even smaller scale dynamics, requiring multiscale system definitions to combine these effects. At the smallest scale, large active forces lead to large resultant accelerations, requiring small integration time steps to fully capture the motion and dictating the integration time for the entire model. Multiscale modeling techniques aim to reduce this computational cost, often by separating the system into subsystems or coarse graining to simplify calculations. A multiscale method has been previously shown to greatly reduce the time required to simulate systems in the continuum regime while generating equivalent time histories. This method identifies a portion of the active and dissipative forces that cancel and contribute little to the overall motion. The forces are then scaled to eliminate these noncontributing portions. This work extends that method to include an adaptive scaling method for forces that have large changes in magnitude across the time history. Results show that the adaptive formulation generates time histories similar to those of the unscaled truth model. Computation time reduction is consistent with the existing method.

Keywords: adaptive multiscaling; multiscaling approach; time; approach reducing; computation time

Journal Title: Journal of Computational and Nonlinear Dynamics
Year Published: 2019

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