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https://scholarbank.nus.edu.sg/handle/10635/190587
DC Field | Value | |
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dc.title | DEVELOPMENT OF INNOVATIVE METHODS FOR CHEMICAL REACTION MECHANISM REDUCTION AND ITS APPLICATION | |
dc.contributor.author | LI HAN | |
dc.date.accessioned | 2021-05-03T18:00:36Z | |
dc.date.available | 2021-05-03T18:00:36Z | |
dc.date.issued | 2021-01-19 | |
dc.identifier.citation | LI HAN (2021-01-19). DEVELOPMENT OF INNOVATIVE METHODS FOR CHEMICAL REACTION MECHANISM REDUCTION AND ITS APPLICATION. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/190587 | |
dc.description.abstract | High-fidelity yet compact chemical reaction mechanisms are of great significance in complex combustion modelling. In this dissertation, skeletal reduction of chemical reaction mechanisms was extensively explored. First, the detailed mechanism of the realistic heavy methyl esters in biodiesel, which is difficult to reduce by common reduction methods, was reduced successfully by utilizing a simplified four-part oxidation framework. Second, systematic reduction of detailed mechanisms by rigorous reduction methods was studied towards improving the reduction usability, capability and efficiency. A generalized efficient systematic reduction strategy that requires little expertise was proposed and demonstrated to be able to generate high-fidelity yet compact mechanisms. By employing this systematic reduction strategy and integrating the clustered dynamic adaptive chemistry computational acceleration technique, 3-D engine simulation with high-fidelity combustion chemistry was achieved at a satisfactory computational cost. | |
dc.language.iso | en | |
dc.subject | combustion modelling, skeletal mechanism, mechanism reduction, biodiesel, engine simulation, computational acceleration | |
dc.type | Thesis | |
dc.contributor.department | MECHANICAL ENGINEERING | |
dc.contributor.supervisor | Wenming Yang | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY (FOE) | |
Appears in Collections: | Ph.D Theses (Open) |
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LIH.pdf | 3.97 MB | Adobe PDF | OPEN | None | View/Download |
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