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Title: Efficient modelling of failure envelopes and load patterns in aircraft structures
Author: Dharmasaroja, Atipong
ISNI:       0000 0004 5995 0158
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2015
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Due to the dynamically-varying nature of aircraft loading scenarios, a large number of global load cases are generated which must be analysed in a Global Finite Element Model (GFEM) to obtain the internal load paths going into each substructure. Analysing all load cases is often not possible due to computational constraints, so that substantial engineering judgement in load case down-selection is required. One innovation developed by QUB to reduce the number of load cases is to use Singular Value Decomposition (SVD) to derive a smaller set of characteristic loads which represent all the global load distributions. This research focuses on developing the SVD based load development process by studying factors that could affect the accuracy and proposes some robust error quantification methods suitable for different scenarios. The major downstream benefit of the process is that the analysis results for this set of characteristic loads can be superimposed to create the internal load distributions resulting from all the original load cases. The method is also used in sensitivity analysis for gradient based optimisation and shows a very large reduction in computational effort. When the SVD is performed at the local structure level, a few internal load characteristic patterns, which represent all internal loads, can also be identified. Another major development in this work is that the failure envelope can be constructed in this reduced dimensional load space. The resulting surface defines critical failure constraints under any loading. The novel parameterisatlon and adaptive mesh refinement techniques have been employed to efficiently construct the failure surface of the industry standard structural assessment tools, which are treated as a black box. The failure envelope therefore provides valuable insights into the structures, failures and loads. Moreover, the down-selection process or constraint filtering can be performed very quickly using the information from this envelope.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available