In this paper a Multi-Disciplinary and Multi-Objective Optimization (MDO-MOO) of a baseline Over-Wing-Nacelle (OWN) concept design is presented. The present study extends previous works, which considered only aerodynamic optimization, to include structural and mission design parameters. The competing objectives of minimum empty weight and minimum fuel weight for a design mission are considered in the multi-objective formulation as well as the single objective problem of minimizing takeoff gross weight, one of many compromises possible for the multi-objective problem. An integrated computational environment has been implemented. High-fidelity analyses for the structural and aeroelastic assessment, together with middle-fidelity analyses for aerodynamic, mission, and performance analyses are performed. A complex multi-disciplinary analysis framework is proposed, in order to account for the interdisciplinary interaction and to provide a consistent computational framework. Optimization results with a Multi Objective Genetic Algorithm (MOGA) show Pareto frontiers accounting for structural, aeroelastic, and mission design constraints. The disciplines coupling is quantified, in terms of constraints, design variables influences, and possible trade-offs among the objectives.
Multi‑disciplinary and multi‑objective optimization of an over‑wing‑nacelle aircraft concept / Gemma, S.; Mastroddi, F.. - In: CEAS AERONAUTICAL JOURNAL. - ISSN 1869-5582. - 10:3(2019), pp. 771-793. [10.1007/s13272-018-0347-7]
Multi‑disciplinary and multi‑objective optimization of an over‑wing‑nacelle aircraft concept
Mastroddi F.
2019
Abstract
In this paper a Multi-Disciplinary and Multi-Objective Optimization (MDO-MOO) of a baseline Over-Wing-Nacelle (OWN) concept design is presented. The present study extends previous works, which considered only aerodynamic optimization, to include structural and mission design parameters. The competing objectives of minimum empty weight and minimum fuel weight for a design mission are considered in the multi-objective formulation as well as the single objective problem of minimizing takeoff gross weight, one of many compromises possible for the multi-objective problem. An integrated computational environment has been implemented. High-fidelity analyses for the structural and aeroelastic assessment, together with middle-fidelity analyses for aerodynamic, mission, and performance analyses are performed. A complex multi-disciplinary analysis framework is proposed, in order to account for the interdisciplinary interaction and to provide a consistent computational framework. Optimization results with a Multi Objective Genetic Algorithm (MOGA) show Pareto frontiers accounting for structural, aeroelastic, and mission design constraints. The disciplines coupling is quantified, in terms of constraints, design variables influences, and possible trade-offs among the objectives.File | Dimensione | Formato | |
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