The increasing complexity of engineering systems has sparked increasing interest in multidisciplinary optimization (MDO). This paper presents a survey of recent publications in the field of aerospace where interest in MDO has been particularly intense. The two main challenges of MDO are computational expense and organizational complexity. Accordingly the survey is focused on various ways different researchers use to deal with these challenges. The survey is organized by a breakdown of MDO into its conceptual components. Accordingly, the survey includes sections on Mathematical Modeling, Design- oriented Analysis, Approximation Concepts, Optimization Procedures, System Sensitivity, and Human Interface. With the authors'' main expertise being in the structures area, the bulk of the references focus on the interaction of the structures discipline with other disciplines. In particular, two sections at the end focus on two such interactions that have recently been pursued with a particular vigor: Simultaneous Optimization of Structures and Aerodynamics, and Simultaneous Optimization of Structures Combined With Active Control.

/pdf/multidisciplinary-aerospace-design-optimization-survey-of-3xuwvr970l.pdf

Multidisciplinary Aerospace Design Optimization: Survey of Recent Developments

The increasing complexity of engineering systems has sparked increasing interest in multidisciplinary optimization (MDO). This paper presents a survey of recent publications in the field of aerospace where interest in MDO has been particularly intense. The two main challenges of MDO are computational expense and organizational complexity. Accordingly the survey is focussed on various ways different researchers use to deal with these challenges. The survey is organized by a breakdown of MDO into its conceptual components. Accordingly, the survey includes sections on Mathematical Modeling, Design-oriented Analysis, Approximation Concepts, Optimization Procedures, System Sensitivity, and Human Interface. With the authors' main expertise being in the structures area, the bulk of the references focus on the interaction of the structures discipline with other disciplines. In particular, two sections at the end focus on two such interactions that have recently been pursued with a particular vigor: Simultaneous Optimization of Structures and Aerodynamics, and Simultaneous Optimization of Structures Combined With Active Control.

/pdf/multidisciplinary-aerospace-design-optimization-survey-of-ghzjxaiur6.pdf

Multidisciplinary aerospace design optimization: Survey of recent developments

This paper attempts to define the Multidisciplinary Design Optimization (MDO) as a new field of research endeavor and as an aid in the design of engineering systems. It examines the MDO conceptual components in relation to each other and defines their functions.

/pdf/multidisciplinary-design-optimization-an-emerging-new-12tppl4ybp.pdf

Multidisciplinary Design Optimization: An Emerging New Engineering Discipline

Collaborative optimization is a recently developed method for solving multidisciplinary design problems. It preserves a degree of disciplinary autonomy and allows parallel optimization. In this paper collaborative optimization is applied to two aircraft design problems to illustrate its implementation and performance characteristics. The first example, a relatively simple wing design problem, is solved using both collaborative and sequential optimization. The results are compared with those obtained using a direct, single-level optimization strategy. Collaborative optimization is shown to converge to the correct solution, while sequential disciplinary suboptimization converges to a nonoptimal result. The second example, an aircraft sizing problem, involves static aeroelastic feedback between disciplines and more complex analysis codes within the subproblems. The complete problem, in forty-five design variables and twenty-six constraints, was solved using both collaborative and single-level optimization. Both methods converge to the correct solution. The performance of the optimization strategy and the effect of increasing problem dimensionality is discussed.

Aircraft design using collaborative optimization

The investigation focuses on development of a rapid multidisciplinary analysis and optimization capability for launch-vehicle design. Two multidisciplinary optimization strategies in which the analyses are integrated in different manners are implemented and evaluated for solution of a single-stage-to-orbit launch-vehicle design problem. Weights and sizing, propulsion, and trajectory issues are directly addressed in each optimization process. Additionally, the need to maintain a consistent vehicle model across the disciplines is discussed. Both solution strategies were shown to obtain similar solutions from two different starting points. These solutions suggests that a dual-fuel, single-stage-to-orbit vehicle with a dry weight of approximately 1.927 x 10(exp 5)lb, gross liftoff weight of 2.165 x 10(exp 6)lb, and length of 181 ft is attainable. A comparison of the two approaches demonstrates that treatment or disciplinary coupling has a direct effect on optimization convergence and the required computational effort. In comparison with the first solution strategy, which is of the general form typically used within the launch vehicle design community at present, the second optimization approach is shown to he 3-4 times more computationally efficient.

/pdf/comparison-of-two-multidisciplinary-optimization-strategies-226256j0is.pdf

Comparison of two multidisciplinary optimization strategies for launch-vehicle design

The performance of the quasi-procedural analysis system in optimization tasks is investigated. In particular, the quasi-procedural method is applied to the complete mission optimization of a medium-sized transport aircraft using a vortex-lattice aerodynamic model and finite element structural analysis of the wing and the tail. Some modifications and improvements to the system, required in order to complete this task, are described. The performance of the system is compared with that of the standard procedural system, and it is shown that the quasi-procedural approach reduces the analysis required to reach the optimum. The overall cost is shown to be strongly dependent on the analysis architecture and data structure.

Development of the quasi-procedural method for use in aircraft configuration optimization

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Development of the quasi-procedural method for use in aircraft configuration optimization