Data mining methods to improve MD simulations
97 p.
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2014
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sg-ntu-dr.10356-580462023-03-11T17:16:24Z Data mining methods to improve MD simulations Chan, Hau Kong Wong Chee How School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering 97 p. Data mining was investigated in this work as a possible means of improving MD simulations, which is often computationally expensive to perform. The approach used was to adopt artificial neural network as a way to model the inputs and outputs from MD simulations. A MD simulation was implemented to compute the change in positions of atoms in a palladium beam lattice structure under constant compressive load. The implementation allows a database of different configurations to be collected and used as training of a neural network. In addition, a neural network was also trained using data from different sizes of CNT under compressive load and its eventual buckling force. Master of Science (Mechanical Engineering) 2014-04-07T11:55:25Z 2014-04-07T11:55:25Z 2011 2011 Thesis http://hdl.handle.net/10356/58046 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Mechanical engineering Chan, Hau Kong Data mining methods to improve MD simulations |
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97 p. |
author2 |
Wong Chee How |
author_facet |
Wong Chee How Chan, Hau Kong |
format |
Theses and Dissertations |
author |
Chan, Hau Kong |
author_sort |
Chan, Hau Kong |
title |
Data mining methods to improve MD simulations |
title_short |
Data mining methods to improve MD simulations |
title_full |
Data mining methods to improve MD simulations |
title_fullStr |
Data mining methods to improve MD simulations |
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Data mining methods to improve MD simulations |
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data mining methods to improve md simulations |
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2014 |
url |
http://hdl.handle.net/10356/58046 |
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1761781935703588864 |