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37
Analytical Target Cascading in Automotive Vehicle Design
 Journal of Mechanical Design
, 2003
"... Target cascading in product development is a systematic effort to propagate the desired toplevel system design targets to appropriate specifications for subsystems and components in a consistent and efficient manner. If analysis models are available to represent the consequences of the relevant des ..."
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Cited by 25 (13 self)
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Target cascading in product development is a systematic effort to propagate the desired toplevel system design targets to appropriate specifications for subsystems and components in a consistent and efficient manner. If analysis models are available to represent the consequences of the relevant design decisions, analytical target cascading can be formalized as a hierarchical multilevel optimization problem. The article demonstrates this complex modeling and solution process in the chassis design of a sportutility vehicle. Ride quality and handling targets are cascaded down to systems and subsystems utilizing suspension, tire, and spring analysis models. Potential incompatibilities among targets and constraints throughout the entire system can be uncovered and the tradeoffs involved in achieving system targets under different design scenarios can be quantified. �DOI: 10.1115/1.1586308�
Comparative Properties Of Collaborative Optimization And Other Approaches To Mdo
, 1999
"... We discuss criteria by which one can classify, analyze, and evaluate approaches to solving multidisciplinary design optimization (MDO) problems. Central to our discussion is the often overlooked distinction between questions of formulating MDO problems and solving the resulting computational problem ..."
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Cited by 20 (2 self)
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We discuss criteria by which one can classify, analyze, and evaluate approaches to solving multidisciplinary design optimization (MDO) problems. Central to our discussion is the often overlooked distinction between questions of formulating MDO problems and solving the resulting computational problem. We illustrate our general remarks by comparing several approaches to MDO that have been proposed. INTRODUCTION There are likely as many definitions of multidisciplinary design optimization (MDO) as there are areas and phases of design. For our discussion, we shall take MDO to mean the systematic approach to optimization of complex, coupled engineering systems, where "multidisciplinary " refers to the different aspects that must be included in a design problem. For instance, the design of aircraft involves, among other disciplines, aerodynamics, structural analysis, propulsion, and control. See SobieszczanskiSobieski and Haftka (1997), Alexandrov and Hussaini (1997) for overviews of the ...
Use Of The Collaborative Optimization Architecture For Launch Vehicle Design
 6th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization
, 1996
"... Collaborative optimization is a new design architecture specifically created for largescale distributedanalysis applications. In this approach, a problem is decomposed into a userdefined number of subspace optimization problems that are driven towards interdisciplinary compatibility and the appro ..."
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Cited by 18 (1 self)
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Collaborative optimization is a new design architecture specifically created for largescale distributedanalysis applications. In this approach, a problem is decomposed into a userdefined number of subspace optimization problems that are driven towards interdisciplinary compatibility and the appropriate solution by a systemlevel coordination process. This decentralized design strategy allows domainspecific issues to be accommodated by disciplinary analysts, while requiring interdisciplinary decisions to be reached by consensus. The present investigation focuses on application of the collaborative optimization architecture to the multidisciplinary design of a singlestagetoorbit launch vehicle. Vehicle design, trajectory, and cost issues are directly modeled. Posed to suit the collaborative architecture, the design problem is characterized by 95 design variables and 16 constraints. Numerous collaborative solutions are obtained. Comparison of these solutions demonstrates the influe...
Initial Results Of An Mdo Method Evaluation Study
, 1998
"... The NASA Langley MDO method evaluation study seeks to arrive at a set of guidelines for using promising MDO methods by accumulating and analyzing computational data for such methods. The data are collected by conducting a series of reproducible experiments. In the first phase of the study, three MDO ..."
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Cited by 14 (6 self)
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The NASA Langley MDO method evaluation study seeks to arrive at a set of guidelines for using promising MDO methods by accumulating and analyzing computational data for such methods. The data are collected by conducting a series of reproducible experiments. In the first phase of the study, three MDO methods were implemented in the iSIGHT z framework and used to solve a set of ten relatively simple problems. In this paper, we comment on the general considerations for conducting method evaluation studies and report some initial results obtained to date. In particular, although the results are not conclusive because of the small initial test set, preliminary numbers suggest that the performance of the methods tends to be consistent with their predicted theoretical properties. Key Words: Multidisciplinary Design Optimization, Method Evaluation AMS Subject Classification: 65K05, 49M37 Introduction Multidisciplinary Design Optimization (MDO) problems are optimization problems that desc...
An Efficient Weighting Update Method to Achieve Acceptable Consistency Deviation in Analytical Target Cascading
 ASME J. Mech. Des
, 2005
"... Information Information in Engineering in Engineering Conference Conference ..."
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Cited by 12 (11 self)
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Information Information in Engineering in Engineering Conference Conference
Optimal partitioning and coordination decisions in decompositionbased design optimization
, 2008
"... The solution of complex system design problems using decompositionbased optimization methods requires determination of appropriate problem partitioning and coordination strategies. Previous optimal partitioning techniques have not addressed the coordination issue explicitly. This article presents a ..."
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Cited by 12 (6 self)
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The solution of complex system design problems using decompositionbased optimization methods requires determination of appropriate problem partitioning and coordination strategies. Previous optimal partitioning techniques have not addressed the coordination issue explicitly. This article presents a formal approach to simultaneous partitioning and coordination strategy decisions that can provide insights on whether a decompositionbased method will be effective for a given problem. Paretooptimal solutions are generated to quantify tradeoffs between the sizes of subproblems and coordination problems as measures of the computational costs resulting from different partitioning and coordination strategies. Promising preliminary results with small test problems are presented. The approach is illustrated on an electric water pump design problem. �DOI: 10.1115/1.3178729� 1
Analytical Target Cascading in Product Development
 Proc. 3rd ASMO UK / ISSMO Conference on Engineering Design Optimization
"... Setting and achieving appropriate product targets is the most critical element of the product development process from both a managerial and technical viewpoint. Target cascading is a systematic process that propagates the desired toplevel design targets to appropriate specifications for a product’ ..."
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Cited by 10 (7 self)
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Setting and achieving appropriate product targets is the most critical element of the product development process from both a managerial and technical viewpoint. Target cascading is a systematic process that propagates the desired toplevel design targets to appropriate specifications for a product’s subsystems and components in a consistent and efficient manner. Design of modern complex artifacts utilizes performance analyses based on computer simulations or “virtual protoyping.” If such analysis models are available to evaluate the outcomes of the relevant design decisions, analytical target cascading can be formalized as a hierarchical multilevel optimization problem. The mathematical formulation of the analytical target cascading process is reviewed along with some case studies from automotive vehicle product development. The generality of the approach is shown through an extension to the design of product families.
Analytical and Computational Properties of Distributed Approaches to MDO
, 2000
"... Historical evolution of engineering disciplines and the complexity of the MDO problem suggest that disciplinary autonomy is a desirable goal in formulating and solving MDO problems. We examine the notion of disciplinary autonomy and discuss the analytical properties of three approaches to formulatin ..."
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Cited by 7 (2 self)
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Historical evolution of engineering disciplines and the complexity of the MDO problem suggest that disciplinary autonomy is a desirable goal in formulating and solving MDO problems. We examine the notion of disciplinary autonomy and discuss the analytical properties of three approaches to formulating and solving MDO problems that achieve varying degrees of autonomy by distributing the problem along disciplinary lines. Two of the approachesOptimization by Linear Decomposition and Collaborative Optimizationare based on bilevel optimization and reflect what we call a structural perspective. The third approach, Distributed Analysis Optimization, is a singlelevel approach that arises from what we call an algorithmic perspective. The main conclusion of the paper is that disciplinary autonomy may come at a price: in the bilevel approaches, the systemlevel constraints introduced to relax the interdisciplinary coupling and enable disciplinary autonomy can cause analytical and computatio...
Algorithmic Perspectives on Problem Formulations in MDO
, 2000
"... This work is concerned with an approach to formulating the multidisciplinary optimization (MDO) problem that reflects an algorithmic perspective on MDO problem solution. The algorithmic perspective focuses on formulating the problem in light of the abilities and inabilities of optimization algorithm ..."
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Cited by 6 (2 self)
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This work is concerned with an approach to formulating the multidisciplinary optimization (MDO) problem that reflects an algorithmic perspective on MDO problem solution. The algorithmic perspective focuses on formulating the problem in light of the abilities and inabilities of optimization algorithms, so that the resulting nonlinear programming problem can be solved reliably and efficiently by conventional optimization techniques. We propose a modular approach to formulating MDO problems that takes advantage of the problem structure, maximizes the autonomy of implementation, and allows for multiple easily interchangeable problem statements to be used depending on the available resources and the characteristics of the application problem. Key Words: Autonomy, complex system design, distributed analysis optimization, multidisciplinary analysis, multidisciplinary optimization, nonlinear programming, sensitivities, system synthesis Introduction The underlying theme of this and related p...
Development of Approximations for HSCT Wing Bending Material Weight using Response Surface Methodology
, 1997
"... A procedure for generating a customized weight function for wing bending material weight of a High Speed Civil Transport (HSCT) is described. The weight function is based on HSCT configuration parameters. A response surface methodology is used to fit a quadratic polynomial to data gathered from a la ..."
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Cited by 6 (1 self)
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A procedure for generating a customized weight function for wing bending material weight of a High Speed Civil Transport (HSCT) is described. The weight function is based on HSCT configuration parameters. A response surface methodology is used to fit a quadratic polynomial to data gathered from a large number of structural optimizations. To reduce the time of performing a large number of structural optimizations, coarsegrained parallelization with a masterslave processor assignment on an Intel Paragon computer is used. The results of the structural optimization are noisy. Noise reduction in the structural optimization results is discussed. It is shown that the response surface filters out this noise. A statistical design of experiments technique is used to minimize the number of required structural optimizations and to maintain accuracy. Simple analysis techniques are used to find regions of the design space where reasonable HSCT designs could occur, thus customizing the weight function to the design requirements of the HSCT, while the response surface itself is created employing detailed analysis methods. Analysis of variance is used to reduce the number of polynomial terms in the response surface model function. Linear and constant corrections based on a small number of high fidelity results are employed to improve the accuracy of the response surface model. Configuration optimization of the HSCT employing a customized weight function is compared to the configuration optimization of the HSCT with a general weight function.