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Volume 19, Issue 3
Automated Parallel and Body-Fitted Mesh Generation in Finite Element Simulation of Macromolecular Systems

Yan Xie, Tiantian Liu, Bin Tu, Benzhuo Lu & Linbo Zhang

Commun. Comput. Phys., 19 (2016), pp. 582-602.

Published online: 2018-04

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  • Abstract

Mesh generation is a bottleneck for finite element simulations of biomolecules. A robust and efficient approach, based on the immersed boundary method proposed in [8], has been developed and implemented to generate large-scale mesh body-fitted to molecular shape for general parallel finite element simulations. The molecular Gaussian surface is adopted to represent the molecular surface, and is finally approximated by piecewise planes via the tool phgSurfaceCut in PHG [43], which is improved and can reliably handle complicated molecular surfaces, through mesh refinement steps. A coarse background mesh is imported first and then is distributed into each process using a mesh partitioning algorithm such as space filling curve [5] or METIS [22]. A bisection method is used for the mesh refinements according to the molecular PDB or PQR file which describes the biomolecular region. After mesh refinements, the mesh is optionally repartitioned and redistributed for load balancing. For finite element simulations, the modification of region mark and boundary types is done in parallel. Our parallel mesh generation method has been successfully applied to a sphere cavity model, a DNA fragment, a gramicidin A channel and a huge Dengue virus system. The results of numerical experiments show good parallel efficiency. Computations of electrostatic potential and solvation energy also validate the method. Moreover, the meshing process and adaptive finite element computation can be integrated as one PHG project to avoid the mesh importing and exporting costs, and improve the convenience of application as well.

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@Article{CiCP-19-582, author = {Yan Xie, Tiantian Liu, Bin Tu, Benzhuo Lu and Linbo Zhang}, title = {Automated Parallel and Body-Fitted Mesh Generation in Finite Element Simulation of Macromolecular Systems}, journal = {Communications in Computational Physics}, year = {2018}, volume = {19}, number = {3}, pages = {582--602}, abstract = {

Mesh generation is a bottleneck for finite element simulations of biomolecules. A robust and efficient approach, based on the immersed boundary method proposed in [8], has been developed and implemented to generate large-scale mesh body-fitted to molecular shape for general parallel finite element simulations. The molecular Gaussian surface is adopted to represent the molecular surface, and is finally approximated by piecewise planes via the tool phgSurfaceCut in PHG [43], which is improved and can reliably handle complicated molecular surfaces, through mesh refinement steps. A coarse background mesh is imported first and then is distributed into each process using a mesh partitioning algorithm such as space filling curve [5] or METIS [22]. A bisection method is used for the mesh refinements according to the molecular PDB or PQR file which describes the biomolecular region. After mesh refinements, the mesh is optionally repartitioned and redistributed for load balancing. For finite element simulations, the modification of region mark and boundary types is done in parallel. Our parallel mesh generation method has been successfully applied to a sphere cavity model, a DNA fragment, a gramicidin A channel and a huge Dengue virus system. The results of numerical experiments show good parallel efficiency. Computations of electrostatic potential and solvation energy also validate the method. Moreover, the meshing process and adaptive finite element computation can be integrated as one PHG project to avoid the mesh importing and exporting costs, and improve the convenience of application as well.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.161114.021015a}, url = {http://global-sci.org/intro/article_detail/cicp/11101.html} }
TY - JOUR T1 - Automated Parallel and Body-Fitted Mesh Generation in Finite Element Simulation of Macromolecular Systems AU - Yan Xie, Tiantian Liu, Bin Tu, Benzhuo Lu & Linbo Zhang JO - Communications in Computational Physics VL - 3 SP - 582 EP - 602 PY - 2018 DA - 2018/04 SN - 19 DO - http://doi.org/10.4208/cicp.161114.021015a UR - https://global-sci.org/intro/article_detail/cicp/11101.html KW - AB -

Mesh generation is a bottleneck for finite element simulations of biomolecules. A robust and efficient approach, based on the immersed boundary method proposed in [8], has been developed and implemented to generate large-scale mesh body-fitted to molecular shape for general parallel finite element simulations. The molecular Gaussian surface is adopted to represent the molecular surface, and is finally approximated by piecewise planes via the tool phgSurfaceCut in PHG [43], which is improved and can reliably handle complicated molecular surfaces, through mesh refinement steps. A coarse background mesh is imported first and then is distributed into each process using a mesh partitioning algorithm such as space filling curve [5] or METIS [22]. A bisection method is used for the mesh refinements according to the molecular PDB or PQR file which describes the biomolecular region. After mesh refinements, the mesh is optionally repartitioned and redistributed for load balancing. For finite element simulations, the modification of region mark and boundary types is done in parallel. Our parallel mesh generation method has been successfully applied to a sphere cavity model, a DNA fragment, a gramicidin A channel and a huge Dengue virus system. The results of numerical experiments show good parallel efficiency. Computations of electrostatic potential and solvation energy also validate the method. Moreover, the meshing process and adaptive finite element computation can be integrated as one PHG project to avoid the mesh importing and exporting costs, and improve the convenience of application as well.

Yan Xie, Tiantian Liu, Bin Tu, Benzhuo Lu and Linbo Zhang. (2018). Automated Parallel and Body-Fitted Mesh Generation in Finite Element Simulation of Macromolecular Systems. Communications in Computational Physics. 19 (3). 582-602. doi:10.4208/cicp.161114.021015a
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