Publication: Kanat Modellerinin Yüksek Doğruluklu Çözücülerle Güvenilirlik Tabanlı Yapısal Ve Aeroelastik Eniyileştirmesi
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Hesaplamalı Bilim Ve Mühendislik
Computational Science and Engineering
Computational Science and Engineering
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Bilişim Ensititüsü
Institute of Informatics
Institute of Informatics
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Mühendislik tasarımında, geometriye, malzeme özelliklerine, üretim süreçlerine ve işletim koşullarına bağlı belirsizlikler kaçınılmazdır. Bu belirsizlikler doğru olarak değerlendirilmeli ve sistemler tasarlanırken ve eniyilenirken hesaba katılmalıdırlar. Bu çalışmada, güvenilirlik tabanlı tasarım eniyileme (GTTE) metodolojisi oluşturulmuştur. Burada hem ticari mühendislik yazılımları hem de kendimizin geliştirilmiş güvenilirlik kodu ilk uygulama olarak, literatürden alınan ankastre kiriş örneğiyle doğrulanmıştır. Daha sonra genel kanat yapısının eniyilemesi ve en son olarak AGARD 445.6 kanadının aeroelastik eniyilemesi problemine uygulanmıştır. Ele alınan en son problemde, eniyileme kriterleri arasında akma mukavemeti, Mach sayısı ve hücum açısı gibi yapısal ve aerodinamik parametrelere ait belirsizlikler, olasılıksal kısıtlamalarda kullanılmıştır, ayrıca deterministik kısıtlamalarda mevcuttur. Olasılıksal kısıtların hata olasılığını hesaplamak için, birinci dereceden güvenilirlik analiz metodlarından olan Hasofer-Lind iterasyon metodu ve geliştirilmiş ortalama değer (GOD) metodu Matlab'da uygulanmıştır. Böylece en olası hasar noktası (EON) çözümü hesap edilmiştir.
In engineering design, uncertainties related to geometries, material properties, manufacturing processes and operating conditions are inevitable factors which should be accurately quantified and included while designing and optimizing a realistic system for a required level of reliability and efficiency. In this thesis, reliability based design optimization (RBDO) methodology is constructed by coupling high-fidelity commercial solvers for aeroelastic analysis and an in-house code developed for reliability analysis. A RBDO benchmark problem (from the literature) and the developed methodology is validated. An in-house code is integrated to commercial software for aircraft wing applications. Finally the methodology is applied to a fluid-structure interaction (FSI) problem where reliability based structural optimization of a simple aircraft wing and reliability based aeroelastic optimization of AGARD 445.6 wing are performed. In the final application, the optimization criteria include both deterministic and probabilistic constraints with both structural and aerodynamic uncertainties such as in yield strength, Mach number and angle of attack. To evaluate the probability of failure for the probabilistic constraints, first order reliability analysis methods, Hasofer-Lind (HL) iteration method and advanced mean value (AMV) method are implemented in Matlab to compute most probable failure point (MPP) solution.
In engineering design, uncertainties related to geometries, material properties, manufacturing processes and operating conditions are inevitable factors which should be accurately quantified and included while designing and optimizing a realistic system for a required level of reliability and efficiency. In this thesis, reliability based design optimization (RBDO) methodology is constructed by coupling high-fidelity commercial solvers for aeroelastic analysis and an in-house code developed for reliability analysis. A RBDO benchmark problem (from the literature) and the developed methodology is validated. An in-house code is integrated to commercial software for aircraft wing applications. Finally the methodology is applied to a fluid-structure interaction (FSI) problem where reliability based structural optimization of a simple aircraft wing and reliability based aeroelastic optimization of AGARD 445.6 wing are performed. In the final application, the optimization criteria include both deterministic and probabilistic constraints with both structural and aerodynamic uncertainties such as in yield strength, Mach number and angle of attack. To evaluate the probability of failure for the probabilistic constraints, first order reliability analysis methods, Hasofer-Lind (HL) iteration method and advanced mean value (AMV) method are implemented in Matlab to compute most probable failure point (MPP) solution.
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Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Bilişim Enstitüsü, 2011
Thesis (M.Sc.) -- İstanbul Technical University, Institute of Informatics, 2011
Thesis (M.Sc.) -- İstanbul Technical University, Institute of Informatics, 2011
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İTÜ theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
İTÜ theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
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Uçak Mühendisliği, İstatistik, Yapısal analiz, Aircraft Engineering, Statistics, Structural analysis
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