Application of Multidisciplinary Systems‐of‐Systems Optimization to an Aircraft Design Problem

Abstract

A generic mathematical formulation for Systems‐of‐Systems (SoS) optimization problems is presented. SoS optimization problems resemble the structure of a tree of Multidisciplinary Design Optimization (MDO) problems with additional unique features. The framework for solving such problems involves features from evolutionary computing, platform‐based design, and evolving design spaces. One important aspect of SoS Engineering, often overlooked, is the role it plays in improving the design of individual systems. In this vein, this work has sought to exemplify such a synergistic approach for aircraft design. A large‐scale SoS optimization problem for designing noise‐optimal aircraft and improved procedures for the approach phase is studied. Modules involving Computational Fluid Dynamics (CFD), noise modeling, multifidelity analysis, topology optimization, and autotuned control systems are used to obtain optimal solutions.

Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements

“…The environmental impact is an aspect which is increasingly being considered in the development of aerial vehicle applications, and as a result, it can be observed that some MDO frameworks have included a model in order to be able to capture its effect on the design. In total, there are two possible ways of measuring the environmental performance, and those are the estimation of the harmful emissions that are generated from fuel burn [38,53,54,56,70] and the noise that the engine as well as the airframe generates on the ground [35,41,55,58,[70][71][72][73]. Overall, the advantages of considering such a model become clear if specific requirements like airport and community regulations must be taken into account [17,38,[71][72][73][74], while to this date, the common approach is to use empirical equations for the emission calculations [38,70] and advanced finite element solvers [35,41,55,58] or analytical expressions [26,70] for the phenomenon of noise propagation.…”

“…The ultimate objective in all the aforementioned applications is the reduction of the structural weight, and in theory, this is achieved by increasing the structural strength in the critical loading points and decreasing it in the noncritical sections. In topology optimization, the idea is that there should be a more efficient use of material, and this is determined by identifying the critical loads and in turn adjusting the use of material thickness and density [48,71,97]. Similarly, in the use of composites, the goal is to use the most effective elements, and hence, the challenge here is to find the load directions and subsequently develop composite skins that have the best ply thickness and orientation [14,49].…”

Optimized synthesis of cost‐effective, controllable oil system architectures for turbofan engines

“…Ref. . presents another multilevel optimization framework for systems‐of‐systems (SoS) architectures.…”

“…Improved project performance can be gained even through less formal approaches whereby the majority of systems architecture decisions are carried out using the knowledge and expertise of engineers, but in a well‐defined task‐flow . More formal approaches attempt to automate some of these tasks and use optimization to produce optimal architectures that maximize satisfaction of some objective function and ensure system requirements or constraints are met . Use of optimization also ensures a fuller exploration of the search space and limits the effects of cognitive biases.…”

“…2018;21:417-431. c 2018 Wiley Periodicals, Inc. 417 wileyonlinelibrary.com/journal/sys met. [9][10][11][12][13][14][15][16] Use of optimization also ensures a fuller exploration of the search space and limits the effects of cognitive biases. This paper follows a more formal approach, presenting a framework for optimization of controlled flow network architectures.…”