dc.contributor.advisor | Tian Tian. | en_US |
dc.contributor.author | Zhang, Qin,Ph.D.Massachusetts Institute of Technology. | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Mechanical Engineering. | en_US |
dc.date.accessioned | 2021-01-05T23:14:40Z | |
dc.date.available | 2021-01-05T23:14:40Z | |
dc.date.copyright | 2020 | en_US |
dc.date.issued | 2020 | en_US |
dc.identifier.uri | https://hdl.handle.net/1721.1/129038 | |
dc.description | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2020 | en_US |
dc.description | Cataloged from student-submitted PDF of thesis. | en_US |
dc.description | Includes bibliographical references (pages 177-183). | en_US |
dc.description.abstract | As a continued effort to advance the understanding of the power cylinder system and design capacities, we develop a modeling framework for multi-phase macro mixture transport that integrates all length scales, time scales and flow regimes using a hybrid approach combining deterministic modeling and machine learning. This framework considers various mechanical and physical processes including ring dynamics, gas flow, oil redistribution and multi-phase transport to paint a detailed picture of the global lubrication environment in the piston/ring/liner system. The main contributions of this thesis can be summarized as the following: 1) designed a modular architecture that decouples various processes to manage complex dependencies, 2) achieved fast inference of flow separation and vortices near ring gaps by a physics-informed Generative Adversarial Network, and 3) established a lower bound estimation of oil consumption based on the "healthy system" oil distribution pattern. This thesis provides a powerful modeling methodology that can achieve fast modeling and monitoring of oil consumption and PM emissions from IC engines, which is of immediate economic, environmental and health concern. | en_US |
dc.description.statementofresponsibility | by Qin Zhang. | en_US |
dc.format.extent | 183 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Mechanical Engineering. | en_US |
dc.title | Fast modeling of multi-phase mixture transport in piston/ring/liner system via GAN-augmented progressive modeling | en_US |
dc.type | Thesis | en_US |
dc.description.degree | Ph. D. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | en_US |
dc.identifier.oclc | 1227042792 | en_US |
dc.description.collection | Ph.D. Massachusetts Institute of Technology, Department of Mechanical Engineering | en_US |
dspace.imported | 2021-01-05T23:14:38Z | en_US |
mit.thesis.degree | Doctoral | en_US |
mit.thesis.department | MechE | en_US |