Even though the power of supercomputers has increased extraordinarily, there is still an insatiable need for more advanced multi-disciplinary CFD simulations in the aircraft analysis and design fields. A particular current interest is in the realistic three-dimensional fully viscous turbulent flow simulation of the highly non-linear aspects of aero-icing. This highly complex simulation is still computationally too demanding in industry, especially when several runs, such as parametric studies, are needed. In order to make such compute-intensive simulations more affordable, this work presents a reduced order modeling approach, based on the "Proper Orthogonal Decomposition", (POD), method to predict a wider swath of flow fields and ice shapes based on a limited number of "snapshots" obtained from complete high-fidelity CFD computations. The procedure of the POD approach is to first decompose the fields into modes, using a limited number of full-calculations snapshots, and then to reconstruct the field and/or ice shapes using those decomposed modes for other conditions, leading to reduced order calculations. The use of the POD technique drastically reduces the computational cost and can provide a more complete map of the performance degradation of an iced aircraft over a wide range of flight and weather conditions.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.99781 |
Date | January 2007 |
Creators | Nakakita, Kunio. |
Publisher | McGill University |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Format | application/pdf |
Coverage | Master of Engineering (Department of Mechanical Engineering.) |
Rights | © Kunio Nakakita, 2007 |
Relation | alephsysno: 002612648, proquestno: AAIMR32609, Theses scanned by UMI/ProQuest. |
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