MDO Architectures for Coupled Aerodynamic and Structural Optimization of a Flexible Wing

Abstract

This paper deals with the formulation and testing of different variants of some existing single level generic architectures, specifically for coupled aerodynamic and structural optimization of wing, focused on static aeroelasticity. The design problem involves simultaneous optimization of the wing aerodynamic plan-form and section variables along with its structural sizing variables for minimum load carrying structural weight subjected to structural, aerodynamic, performance and geometric constraints. The associated Multi-Disciplinary Analysis (MDA) problem essentially involves coupled solution of the state equations of the aerodynamic and the structural disciplines by nested iterations. The Multidisciplinary Design Optimization (MDO) problem is posed as a three discipline coupled problem, with the trim (maneuver) process required to define structural design loads considered as a separate discipline. This leads to a number of interesting reformulations of the MDO problem based on (i) the reordering of the nested iterations and (ii) decoupling the nested iterations at different levels through the introduction of pseudo design variables and pseudo constraints. Formulation of six variants of the MDO problem and their implementation is presented along with computational issues related to convergence of the iterative processes. A special constraint based on a divergence control parameter has been formulated to handle instability. Optimization results from the different formulations are compared to study their computational performance and bring out the impact of aeroelasticity on the design of the flexible wing.

DFSS of a diagonal impeller

“…The emphasis is on a systematic methodology and on exploiting interdisciplinary interactions to achieve a better overall system than can be achieved by ignoring the interactions. Since 1980's, a large amount of researches have been done in MDO techniques [26][27], such as approximation concepts, MDO architectures, sensitivity analysis, optimization algorithms and theory, software infrastructure, analysis methodology.…”

Reduced-Order Techniques for Sensitivity Analysis and Design Optimization of Aerospace Systems

“…[70][71][72][73] MDO strategies such as multiple discipline feasible, 52 all-at-once, individual discipline feasible, collaborative optimization, 74 collaborative subspace optimization, 75 bi-level integrated system synthesis, 76 the collaboration pursuing method, [77][78][79][80] analytical target cascading, and others 50,81,82 are examples of common MDO schemes into which this work may be integrated in the future. 61 There have been several studies comparing various frameworks 40,53,[83][84][85][86][87] and presenting general descriptive schemes for the various techniques. 40,88,89 Process modeling frameworks are closely related to these schemes, being the practical implementations that ultimately determine how useful the techniques are to end users.…”

“…43 Some examples of MDO applications include aeroelastic optimization, [44][45][46] multilevel wing box optimization, 47 aerostructural optimization, 25,48 space structures, 49 and others. [50][51][52][53][54] There have been several attempts at providing multidisciplinary problem test suites, which are also useful as examples; these include efforts by the Hulme and Bloebaum 55-58 and Padula. 59 Bandwidth reduction is a common issue with MDO applications, and several techniques have been suggested for addressing it; this includes intermediate models, 1,60 reduced order data sets, 61,62 and other approaches.…”