14 research outputs found
Reduced-order hybrid multiscale method combining the molecular dynamics and the discontinuous-galerkin method
We present a new reduced-order hybrid multiscale method to simulate com-
plex fluids. continuum and molecular descriptions.
We follow the framework of the heterogeneous multi-scale method (HMM) that makes use of
the scale separation into macro- and micro-levels. On the macro-level, the governing equations of
the incompressible flow are the continuity and momentum equations. The equations are
solved using a high-order accurate discontinuous Galerkin Finite Element Method (dG) and
implemented in the BoSSS code. The missing information on the macro-level is represented
by the unknown stress tensor evaluated by means of the molecular dynam- ics (MD) simulations on
the micro-level. We shear the microscopic system by applying Lees-Edwards boundary
conditions and either an isokinetic or Lowe-Andersen thermostat. The data obtained from the MD
simulations underlie large stochastic errors that can be controlled by means of the least-square
approximation. In order to reduce a large number of computationally expensive MD runs, we apply
the reduced order approach. Nume al
experiments confirm the robustness of our newly developed hybrid MD-dG method
Accelerated GPU simulation of compressible flow by the discontinuous evolution Galerkin method
The aim of the present paper is to report on our recent results for GPU accelerated simulations of compressible flows. For numerical simulation the adaptive discontinuous Galerkin method with the multidimensional bicharacteristic based evolution Galerkin operator has been used. For time discretization we have applied the explicit third order Runge-Kutta method. Evaluation of the genuinely multidimensional evolution operator has been accelerated using the GPU implementation. We have obtained a speedup up to 30 (in comparison to a single CPU core) for the calculation of the evolution Galerkin operator on a typical discretization mesh consisting of 16384 mesh cells
Accelerated GPU simulation of compressible flow by the discontinuous evolution Galerkin method
The aim of the present paper is to report on our recent results for GPU accelerated simulations of compressible flows. For numerical simulation the adaptive discontinuous Galerkin method with the multidimensional bicharacteristic based evolution Galerkin operator has been used. For time discretization we have applied the explicit third order Runge-Kutta method. Evaluation of the genuinely multidimensional evolution operator has been accelerated using the GPU implementation. We have obtained a speedup up to 30 (in comparison to a single CPU core) for the calculation of the evolution Galerkin operator on a typical discretization mesh consisting of 16384 mesh cells
Accelerated GPU simulation of compressible flow by the discontinuous evolution Galerkin method
Reduced-order hybrid multiscale method combining the molecular dynamics and the discontinuous-galerkin method
We present a new reduced-order hybrid multiscale method to simulate com-
plex fluids. continuum and molecular descriptions.
We follow the framework of the heterogeneous multi-scale method (HMM) that makes use of
the scale separation into macro- and micro-levels. On the macro-level, the governing equations of
the incompressible flow are the continuity and momentum equations. The equations are
solved using a high-order accurate discontinuous Galerkin Finite Element Method (dG) and
implemented in the BoSSS code. The missing information on the macro-level is represented
by the unknown stress tensor evaluated by means of the molecular dynam- ics (MD) simulations on
the micro-level. We shear the microscopic system by applying Lees-Edwards boundary
conditions and either an isokinetic or Lowe-Andersen thermostat. The data obtained from the MD
simulations underlie large stochastic errors that can be controlled by means of the least-square
approximation. In order to reduce a large number of computationally expensive MD runs, we apply
the reduced order approach. Nume al
experiments confirm the robustness of our newly developed hybrid MD-dG method