Automated multidisciplinary design of aircraft requires the optimization of complex performance objectives with respect to a number of design parameters and constraints. The effect of these independent design variables on the system performance criteria can be quantified in terms of sensitivity derivatives for the individual discipline simulation codes. Typical advanced CFD codes do not provide such derivatives as part of a flow solution. These derivatives are expensive to obtain by divided differences from perturbed solutions, and may be unreliable, particularly for noisy functions. In this paper, automatic differentiation has been investigated as a means of extending iterative CFD codes with sensitivity derivatives. In particular, the ADIFOR automatic differentiator has been applied to the 3--D, thin--layer Navier--Stokes, multigrid flow solver called TLNS3D coupled with the WTCO wing grid generator. Results of a sequence of efforts in which TLNS3D has been successfully augmented to ...

This paper describes an integrated aerodynamic/dynamic/structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general purpose optimizer using multilevel decomposition techniques. At the upper level, the blade structure and response are represented in terms of global quantities (stiffnesses, mass, and average strains). At the lower level, the blade structure and response are represented in terms of local quantities (detailed dimensions and stresses). The upper level objective function is a linear combination of performance and dynamic measures. Upper level design variables include pretwist, point of taper initiation, taper ratio, root chord, blade stiffnesses, tuning masses,

Astute choices made early in the design process provide the best opportunity for reducing the life cycle cost of a new product. Optimal decisions require reasonably detailed disciplinary analyses, which pose coordination challenges. These types of complex multidisciplinary problems are best addressed through the use of decomposition-based methods, several of which have recently been developed. Two of these methods are collaborative optimization (CO) and analytical target cascading (ATC). CO was conceived in 1994 in response to multidisciplinary design needs in the aerospace industry. Recent progress has led to an updated version, enhanced collaborative optimization (ECO), that is introduced in this paper. ECO addresses many of the computational challenges inherent in CO, yielding significant computational savings and more robust solutions. ATC was formalized in 2000 to address needs in the automotive industry. While ATC was originally developed for object-based decomposition, it is also applicable to multidisciplinary design problems. In this paper, both methods are applied to a set of test cases. The goal is to introduce the ECO methodology by comparing and contrasting it with ATC, a method familiar within the mechanical engineering design community. Comparison of ECO and ATC is not intended to establish the computational superiority of either method. Rather, these two methods are compared as a means of highlighting several promising approaches to the coordination of distributed design problems.