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- W2151833328 abstract "The paper presents an approach to formulate and solve multi-disciplinary optimization (MDO) problems wherein the system parameters (e.g., material properties, boundary conditions, loads, model prediction errors, etc.) are not necessarily deterministic and are described by probability distributions. The approach uses an adaptive response surface method, based on the fractional central composite experimental design technique and the most probable failure point (MPP) concept. Monte Carlo Simulation is applied to evaluate the objective and constraints once their response surfaces are generated. In this approach the objective is performance-based while the constraints are reliability-based. Consequently, random variables are separated into operational and single-occurrence random variables to properly model the reliabilitybased MD0 problems. Comparisons are made between the deterministic MD0 and RBMDO for the wing shape examples, where we optimize the shape of a transport aircraft wing for maximum cruise range; involving fully coupled aero~-structural analysis and uncertain design variables. Design variables include the shape of the wing characterized as chord, sweep, twist, and airfoil cross section shape. The aero-structural analysis of the wing uses an in-house driver, coupled with aerodynamics and finite element codes. The results show that the RBMDO approach is able to obtain the solution that best balances performance and reliability, considering the range of operating conditions." @default.
- W2151833328 created "2016-06-24" @default.
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- W2151833328 date "1999-04-12" @default.
- W2151833328 modified "2023-10-14" @default.
- W2151833328 title "Multi-disciplinary wing shape optimization with uncertain parameters" @default.
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- W2151833328 doi "https://doi.org/10.2514/6.1999-1601" @default.
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