Kinetic-Monte-Carlo-Based Parallel Evolution Simulation Algorithm of Dust Particles

被引：1

作者：

Hu, Xiaomei ^{[1
]}

Xu, Zhifeng ^{[1
]}

Cai, Hongxia ^{[1
]}

Hu, Junjun ^{[1
]}

机构：

[1] Shanghai Univ, Sch Mech Engn & Automat, Shanghai Key Lab Mech Automat & Robot, Shanghai 200072, Peoples R China

来源：

JOURNAL OF APPLIED MATHEMATICS | 2014年

关键词：

MODEL; DEPOSITION; AIR;

D O I：

10.1155/2014/839726

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The evolution simulation of dust particles provides an important way to analyze the impact of dust on the environment. KMC-based parallel algorithm is proposed to simulate the evolution of dust particles. In the parallel evolution simulation algorithm of dust particles, data distribution way and communication optimizing strategy are raised to balance the load of every process and reduce the communication expense among processes. The experimental results show that the simulation of diffusion, sediment, and resuspension of dust particles in virtual campus is realized and the simulation time is shortened by parallel algorithm, which makes up for the shortage of serial computing and makes the simulation of large-scale virtual environment possible.

引用

下载

页数：11

共 50 条

[41] Estimation of kinetic parameters for chemical reactions based on Monte Carlo simulation
Zhan, XL
Luo, ZH
Chen, FQ
Yang, YR
CHEMICAL JOURNAL OF CHINESE UNIVERSITIES-CHINESE, 2003, 24 (08): : 1511 - 1514
[42] RELIABLE KINETIC MONTE CARLO SIMULATION BASED ON RANDOM SET SAMPLING
Wang, Yan
PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2011, VOL 5, PTS A AND B, 2012, : 1189 - 1199
[43] Reliable kinetic Monte Carlo simulation based on random set sampling
Yan Wang
Soft Computing, 2013, 17 : 1439 - 1451
[44] Molecular dynamics based kinetic Monte Carlo simulation for accelerated diffusion
Tavenner, Jacob P.
Mendelev, Mikhail I.
Lawson, John W.
COMPUTATIONAL MATERIALS SCIENCE, 2023, 218
[45] Reliable kinetic Monte Carlo simulation based on random set sampling
Wang, Yan
SOFT COMPUTING, 2013, 17 (08) : 1439 - 1451
[46] Spark-Based Monte Carlo Parallel Simulation Approach for FTA
Liu, Yan
Ren, Yi
Liu, Linlin
Li, Zhifeng
PROCEEDINGS OF THE 2015 FIRST INTERNATIONAL CONFERENCE ON RELIABILITY SYSTEMS ENGINEERING 2015 ICRSE, 2015,
[47] A parallel approach for Monte Carlo-based photon propagation simulation
Rusu, Ionela
Pentiuc, Stefan-Gheorghe
Ungurean, Ioan
Craciun, Elena-Gina
2012 5TH ROMANIA TIER 2 FEDERATION GRID, CLOUD & HIGH PERFORMANCE COMPUTING SCIENCE (RO-LCG), 2012, : 78 - 81
[48] Capacity Evaluation Method for Parallel Runway Based on Monte Carlo Simulation
Wang, Fei
Zhao, LiGang
PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 5411 - 5415
[49] Monte Carlo Simulation of Dust Particles in a Protoplanetary Disk: Crystalline to Amorphous Silicate Ratio in Comets
Okamoto, Tamami
Ida, Shigeru
ASTROPHYSICAL JOURNAL, 2022, 928 (02):
[50] Monte Carlo simulation of the systems with many particles
Bren, D.
Kulhanek, P.
Skandera, D.
Computer Physics Communications, 1999, 121

← 1 2 3 4 5 →