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

Multidisciplinary design optimization is a field of research that studies the application of numerical optimization techniques to the design of engineering systems involving multiple disciplines or components. Since the inception of multidisciplinary design optimization, various methods (architectures) have been developed and applied to solve multidisciplinary design-optimization problems. This paper provides a survey of all the architectures that have been presented in the literature so far. All architectures are explained in detail using a unified description that includes optimization problem statements, diagrams, and detailed algorithms. The diagrams show both data and process flow through the multidisciplinary system and computational elements, which facilitate the understanding of the various architectures, and how they relate to each other. A classification of the multidisciplinary design-optimization architectures based on their problem formulations and decomposition strategies is also provided, a...

Multidisciplinary design optimization: A survey of architectures

This paper presents an analytically robust, globally convergent approach to managing the use of approximation models of various fidelity in optimization. By robust global behavior we mean the mathematical assurance that the iterates produced by the optimization algorithm, started at an arbitrary initial iterate, will converge to a stationary point or local optimizer for the original problem. The approach we present is based on the trust region idea from nonlinear programming and is shown to be provably convergent to a solution of the original high-fidelity problem. The proposed method for managing approximations in engineering optimization suggests ways to decide when the fidelity, and thus the cost, of the approximations might be fruitfully increased or decreased in the course of the optimization iterations. The approach is quite general. We make no assumptions on the structure of the original problem, in particular, no assumptions of convexity and separability, and place only mild requirements on the approximations. The approximations used in the framework can be of any nature appropriate to an application; for instance, they can be represented by analyses, simulations, or simple algebraic models. This paper introduces the approach and outlines the convergence analysis.

/pdf/a-trust-region-framework-for-managing-the-use-of-3hoedhr52f.pdf

A Trust Region Framework for Managing the Use of Approximation Models in Optimization

This paper reviews the basic approximation concepts used in structural optimization. It also discusses some of the most recent developments in that area since the introduction of approximation concepts in the mid-seventies. The paper distinguishes between local, medium-range and global approximations; it covers function approximations and problem approximations. It shows that, although the lack of comparative data established on reference test cases prevents an accurate assessment, there have been significant improvements. The largest number of developments have been in the areas of local function approximations and use of intermediate variable and response quantities. It appears also that some new methodologies emerge which could greatly benefit from the introduction of new computer architectures.

Approximation concepts for optimum structural design — a review

Methods for calculating sensitivity derivatives for discrete structural systems are surveyed, primarily covering literature published during the past two decades. Methods are described for calculating derivatives of static displacements and stresses, eigenvalues and eigenvectors, transient structural response, and derivatives of optimum structural designs with respect to problem parameters. The survey is focused on publications developed in nonstructural fields such as electronics, controls, and physical chemistry which are directly applicable to structural problems. Most notable among the nonstructural-based methods are the adjoint variable technique from control theory, and the Green's function and FAST methods from physical chemistry.

Sensitivity Analysis of Discrete Structural Systems

BLISS is a method for optimization of engineering systems by decomposition. It separates the system level optimization, having a relatively small number of design variables, from the potentially numerous subsystem optimizations that may each have a large number of local design variables. The subsystem optimizations are autonomous and may be conducted concurrently. Subsystem and system optimizations alternate, linked by sensitivity data, producing a design improvement in each iteration. Starting from a best guess initial design, the method improves that design in iterative cycles, each cycle comprised of two steps. In step one, the system level variables are frozen and the improvement is achieved by separate, concurrent, and autonomous optimizations in the local variable subdomains. In step two, further improvement is sought in the space of the system level variables. Optimum sensitivity data link the second step to the first. The method prototype was implemented using MATLAB and iSIGHT programming software and tested on a simplified, conceptural level supersonic business jet design, and a detailed design of an electronic device. Satisfactory convergence and favorable agreement with the benchmark results were observed. Modularity of the method is intended to fit the human organization and map well on the computing technology of concurrent processing.

Bi-Level Integrated System Synthesis

P2 ~ P2 + Pi 2 are the probabilities of occurrence of x^t) or x 1(t)H-x2(f) and x2(r) or xl(t)+x2(t\ respectively. Further development of this case is left to the interested reader. It is important to note, however, that setting p1>2 = 0 implies that xl (t) and x2(f) are mutually exclusive 100% of the time, and setting p1 2 = 1 implies x^t) and x2(t) act concurrently 100% of the time. The former case illustrates how to resolve x(t) into mutually exclusive components, and the latter case leads to the principle of linear superposition. Finally, it should be noted that the p and p values are discrete and can also be determined by counting occurrences.

On the Accuracy of the Taylor Approximation for Structure Resizing

A procedure for automating the design of transport aircraft fuselage structures has been developed and implemented in the form of an operational program. The structure is designed in two stages. First, an over-all distribution of structural material is obtained by means of optimality criteria to meet strength and displacement constraints. Subsequently, the detailed design of selected rings and panels consisting of skin and stringers is performed by mathematical optimization accounting for a set of realistic design constraints. As a result one obtains a procedure whose practicality and computer efficiency is demonstrated on cylindrical and area-ruled large transport fuselage.

A Mixed Optimization Method for Automated Design of Fuselage Structures

Applications of a multidisciplinary system of computer programs to selected analytical and optimization problems encountered in an aircraft design are described The depth of the analyses and optimizations permits such detailed output as individual stringer sizes and pressure distributions Data flow from one program to another is performed in a hands-off manner in the modular and open-ended system Numerical examples show how this automation permits multidisciplinary trade-off studies, typical of a preliminary design process to be based on such a level of detail in each discipline that normally would not be available at this stage of the process

Application of Computer-Aided Aircraft Design in aMultidisciplinary Environment

A progress report is given on the first phase of a research project to develop a system of Integrated Programs for Aerospace-Vehicle Design (IPAD) which is intended to automate to the largest extent possible the preliminary and detailed design of advanced aircraft. The approach used is to build a pilot system and simultaneously to carry out two major contractual studies to define a practical IPAD system preparatory to programing. The paper summarizes the specifications and goals of the IPAD system, the progress to date, and any conclusion reached regarding its feasibility and scope. Sample calculations obtained with the pilot system are given for aircraft preliminary designs optimized with respect to discipline parameters, such as weight or L/D, and these results are compared with designs optimized with respect to overall performance parameters, such as range or payload.

An integrated computer system for preliminary design of advanced aircraft.

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