Studies of Non-equilibrium Phenomena of Colloidal Dispersions Using a New Simulation Method
| Project/Area Number |
18540405
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Biophysics/Chemical physics
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| Research Institution | Kyoto University |
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Principal Investigator |
YAMAMOTO Ryoichi Kyoto University, Department of Chemical Engineering, Associate Professor (10263401)
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| Co-Investigator(Kenkyū-buntansha) |
SHINTO Hiroyuki Kyoto University, Department of Chemical Engineering, Assistant Professor (80324656)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,890,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥390,000)
Fiscal Year 2007: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2006: ¥2,200,000 (Direct Cost: ¥2,200,000)
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| Keywords | Computational Physics / Chemical Physics / Modeling / Fluid / Colloid / Parallel Computation / Rheology / Thermal Fluctuation |
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| Research Abstract |
We have developed a unique method for direct numerical simulations (DNS) of dense colloidal dispersions This method enables us to compute the time evolutions of colloidal particles, ions, and host fluids simultaneously by solving Newton, advection-diffusion, and Navier-Stokes equations, so that the electro-hydrodynamic couplings can be fully taken into amount We have released a colloidal simulator named KAPSEL with implementing SPM and applied it for colloidal dispersions in several situations including under shear flow Modification for introducing the thermal fluctuations was also done recently to extend this method to Brownian systems.
A significant achievement was obtained in the fiscal year 2007 on large scale simulation and its application. We have succeeded to parallelize KAPSEL so that it can run on modern multi-core type CPUs with OpenMP coding. Several efforts have been made to realize better performance such as linked List method and usual thread optimizations. As a result, over 95% of the initial axle was parallelized and 5.4 times better performance has been obtained with using a Xeon 8-core CPU.
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Report
(3 results)
Research Products
(61 results)
