Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.691012
Title: Development of a method to study aircraft trajectory optimisation in the presence of icing conditions
Author: Shinkafi, A.
ISNI:       0000 0004 5916 3787
Awarding Body: Cranfield University
Current Institution: Cranfield University
Date of Award: 2015
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Abstract:
There is a growing demand for new technologies and ight procedures that will enable aircraft operators to burn less fuel and reduce the impacts of aviation on the environment. Conventional approaches to trajectory optimisation do not include aircraft systems in the optimisation set-up. However, the fuel penalty due to aircraft systems operation is signi cant. Thus, applying optimised trajectories which do not account for systems o -takes in real aircraft Flight Management System (FMS) will likely fail to achieve a true optimum. This is more important in real scenarios where the ambient conditions in uence the systems operation signi cantly. This research proposed an ice protection methodology which enables the development of a decision making process within the FMS dependent on weather conditions; thus transforming the conventional anti-icing method into a more intelligent system. A case of a medium size transport aircraft ight from London - Amsterdam under various levels of possible icing was studied. The results show that fuel burn due to anti-icing operation can increase up to 3.7% between climb and cruise altitudes. Up to 5.5% of this penalty can be saved using icing optimised trajectories. A 45% reduction in awakenings due to noise was achieved with 3% fuel penalty. The novelty of the study was extended using 3D optimisation to further improve ight operations. It was found that the simulation successfully changed the lateral position of the aircraft to minimise the time spent and distance covered in icing conditions. The work here presents a feasible methodology for future intelligent ice protection system (IPS) development, which incorporates intelligent operation.
Supervisor: Lawson, C. P. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.691012  DOI: Not available
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