With increasing concerns about the harmful effects of conventional liquid fossil fuel emissions, natural gas has become a very attractive alternative fuel to power prime movers and stationary energy conversion devices. This research studies the injection and ignition numerically for natural gas (mainly methane) as a fuel applied to diesel engine.
Natural gas injector and glow plug ignition enhancement are two of the most technical difficulties for direct injection natural gas engine design. This thesis models the natural gas injector, and studies the characteristics of the internal flow in the injector and natural gas jet in the combustion chamber during the injection process. The poppet valve model and pintle valve model are the first reported models to simulate the natural gas injector to improve the traditional velocity and pressure boundary conditions.
This thesis also successfully models the glow plug assisted natural gas ignition and combustion processes by developing a glow plug discretized model and a novel virtual gas sub-layer model. Glow plug discretized model can describe the transient heat transfer, and adequately represents the thin layers of heat penetration and the local temperature difference due to the cold gas jet impingement. The virtual gas sub-layer model considers complicated physical processes, such as chemical reaction, heat conduction, and mass diffusion within the virtual sub-layers without significantly increasing computational time and load.
KIVA-3V CFD code was chosen to simulate the fluid flow. Since the KIVA-3V is designed specifically for engine research application with conventional liquid fuels, many modifications have been implemented to facilitate this research.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OTU.1807/11188 |
| Date | 30 July 2008 |
| Creators | Cheng, Xu Jr. |
| Contributors | Wallace, James S. |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
| Format | 6615493 bytes, application/pdf |
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