Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545691
Title: Development of new methodologies for the weight estimation of aircraft structures
Author: Hannon, Christine
ISNI:       0000 0004 2709 7236
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2011
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Abstract:
The problem of weight estimation in the aerospace industry has been acquiring considerably greater importance in recent years, due to the numerous challenges frequently encountered in the preliminary phases of the design of a new aircraft. This is the stage where it is possible to make design changes without incurring into excessive cost penalties. On the other hand, the knowledge of the design, of the relationships existing between the different variables and their subsequent impact on the final weight of the structure is very limited. As a result, the designer is unable to understand the true effect that individual design decisions will produce on the weight of the structure. In addition to this, new aircraft concepts end up being too conservative, due to the high dependency of current weight estimation methods to historical data and off-the-shelf design solutions. This thesis aims at providing an alternative framework for the weight estimation of aircraft structures at preliminary design stages. By conducting a thorough assessment of current state-of-the-art approaches and tools used in the field, fuzzy logic is presented as an appropriate foundation on which to build an innovative approach to the problem. Different adaptive fuzzy approaches have been used in the development of a methodology which is able to combine an analytical base to the structural design of selected trailing edge components, with substantial knowledge acquisition capabilities for the computation of robust and reliable weight estimates. The final framework allows considerable flexibility in the level of detail of the estimate consistent with the granularity of the input data used. This, combined with an extensive uncertainty analysis through the use of Interval Type-2 fuzzy logic, will provide the designer with the capabilities to understand the impact of error propagation within the model and increase the confidence in the final estimate.
Supervisor: Querin, Osvaldo ; Toropov, Vassili Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.545691  DOI: Not available
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