We present a solution method that, compared to the traditional Gauss-Seidel approach, reduces the time required to simulate the dynamics of large systems of rigid bodies interacting through frictional contact by one to two orders of magnitude. Unlike Gauss-Seidel, it can be easily parallelized, which allows for the physics-based simulation of systems with millions of bodies. The proposed accelerated projected gradient descent (APGD) method relies on an approach by Nesterov in which a quadratic optimization problem with conic constraints is solved at each simulation time step to recover the normal and friction forces present in the system. The APGD method is validated against experimental data, compared in terms of speed of convergence and solution time with the Gauss-Seidel and Jacobi methods, and demonstrated in conjunction with snow modeling, bulldozer dynamics, and several benchmark tests that highlight the interplay between the friction and cohesion forces. . 2015.Using Nesterov's method to accelerate multibody dynamics with friction and contact.
Abstract. The last decade witnessed a manifest shift in the microprocessor industry towards chip designs that promote parallel computing. Until recently the privilege of a select group of large research centers, Teraflop computing is becoming a commodity owing to inexpensive GPU cards and multi to many-core x86 processors. This paradigm shift towards large scale parallel computing has been leveraged in Chrono, a freely available C++ multi-physics simulation package. Chrono is made up of a collection of loosely coupled components that facilitate different aspects of multi-physics modeling, simulation, and visualization. This contribution provides an overview of Chrono::Engine, Chrono::Flex, Chrono::Fluid, and Chrono::Render, which are modules that can capitalize on the processing power of hundreds of parallel processors. Problems that can be tackled in Chrono include but are not limited to granular material dynamics, tangled large flexible structures with self contact, particulate flows, and tracked vehicle mobility. The paper presents an overview of each of these modules and illustrates through several examples the potential of this multi-physics library.
This paper describes an approach for the dynamic simulation of complex computer-aided engineering models where large collections of rigid bodies interact mutually through millions of frictional contacts and bilateral mechanical constraints. Thanks to the massive parallelism available on today's GPU boards, we are able to simulate sand, granular materials, and other complex physical scenarios with one order of magnitude speedup when compared to a sequential CPU-based implementation of the discussed algorithms.
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