Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Havacılık ve Uzay Mühendisliği Bölümü, Türkiye
Tezin Onay Tarihi: 2015
Öğrenci: BERKAN ALANBAY
Danışman: MELİN ŞAHİN
Özet:In this study, a multi-objective aero-structural multidisciplinary design optimization (MDO) of a joined-wing kit which is installed on a transonic free fall munition is performed. The main purpose of the joined-wing kit is to enable the munitions to extend their range and gain standoff attack capability. In order to fulfill these aims joined-wing kit configurations are generally investigated through various analyses. Each joined-wing configurations are determined through two geometric key parameters namely; the aft wing sweep angle and the location of the joint. In the first part of the thesis, dynamic characteristics of the joined-wing configurations are investigated through series of finite element modelling and analyses. Thereafter, experimental validations of these finite element models are performed by classical modal analyses techniques comprising both impact hammer and shaker tests. The second part of the thesis focuses on the high-fidelity multi-point aero-structural optimizations of the joined-wing configurations. In addition to the geometric design parameters, the effects of two aerodynamic design variables; namely speed and the angle of attack of the munition are also explored. The objectives of the optimization can be listed as maximizing lift-to-drag ratio, minimizing weight of the joined-wing vi kit and increasing wing stiffness. For these purposes, loosely coupled MDO analyses are elucidated with a hybrid genetic algorithm and response surface methodology (RSM). In consideration of the 3D aerodynamic analyses, RANS (Reynold Averaged Navier Stokes) simulations with Spalart-Allmaras model are used for turbulence closure. Then, the structural analyses are performed under various the aerodynamic loads. In order to construct accurate response surfaces, both aerodynamic and structural analyses are repeated for required number of experimental design points which are chosen through design of experiments. Finally, candidate design points for the best design are extracted from the response surface models by using multi-objective genetic algorithms.