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60
A new approach to the construction of optimal designs
 J. Statistical Planning and Inference
, 1993
"... By combining a modified version of Hooke and Jeeves ’ pattern search with exact or Monte Carlo moment calculations, it is possible to find I, D and Aoptimal (or nearly optimal) designs for a wide range of responsesurface problems. The algorithm routinely handles problems involving the minimizati ..."
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Cited by 31 (10 self)
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By combining a modified version of Hooke and Jeeves ’ pattern search with exact or Monte Carlo moment calculations, it is possible to find I, D and Aoptimal (or nearly optimal) designs for a wide range of responsesurface problems. The algorithm routinely handles problems involving the minimization of functions of 1000 variables, and so for example can construct designs for a full quadratic responsesurface depending on 12 continuous process variables. The algorithm handles continuous or discrete variables, linear equality or inequality constraints, and a response surface that is any low degree polynomial. The design may be required to include a specified set of points, so a sequence of designs can be obtained, each optimal given that the earlier runs have been made. The modeling region need not coincide with the measurement region. The algorithm has been implemented in a program called gosset, which has been used to compute extensive tables of designs. Many of these are more efficient than the best designs previously known.
A Concept Exploration Method for Product Family Design
 in Mechanical Engineering. Atlanta, GA: Georgia Institute of Technology
, 1998
"... ii ..."
VariableComplexity Response Surface Approximations for Wing Structural Weight in HSCT Design
 J. Computational Mechanics
, 1996
"... A procedure for generating and using a polynomial approximation to wing bending material weight of a High Speed Civil Transport (HSCT) is presented. Response surface methodology is used to fit a quadratic polynomial to data gathered from a series of structural optimizations. Several techniques are e ..."
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Cited by 18 (10 self)
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A procedure for generating and using a polynomial approximation to wing bending material weight of a High Speed Civil Transport (HSCT) is presented. Response surface methodology is used to fit a quadratic polynomial to data gathered from a series of structural optimizations. Several techniques are employed in order to minimize the number of required structural optimizations and to maintain accuracy. First, another weight function based on statistical data is used to identify a suitable model function for the response surface. In a similar manner, geometric and loading parameters that are likely to appear in the response surface model are also identified. Next, rudimentary analysis techniques are used to find regions of the design space where reasonable HSCT designs could occur. The use of intervening variables along with analysis of variance reduce the number of polynomial terms in the response surface model function. Structural optimization is then performed by the program GENESIS on a 28node Intel Paragon. Finally, optimizations of the HSCT are completed both with and without the response surface. ii Acknowledgements
Performance Analysis of Conjoined Supply Chains
"... This research is concerned with the performance behavior of conjoined supply chains, which typically arise in webbased retail. In particular, five performance measures, belonging to three performance measure classes, are used to study the performance effects of various operational factors on conjoi ..."
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Cited by 9 (0 self)
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This research is concerned with the performance behavior of conjoined supply chains, which typically arise in webbased retail. In particular, five performance measures, belonging to three performance measure classes, are used to study the performance effects of various operational factors on conjoined supply chains. The study is accomplished via experimental design and simulation analysis, and the results suggest the effects of the various factors on supply chain performance and identify the nature of the relationships among these factors and overall supply chain performance.
Uncertainty Quantification In Large Computational Engineering Models
 In Proceedings of the 42rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, number AIAA20011455
, 2001
"... While a wealth of experience in the development of uncertainty quantification methods and software tools exists at present, a cohesive software package utilizing massively parallel computing resources does not. The thrust of the work to be discussed herein is the development of such a toolkit, which ..."
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Cited by 6 (1 self)
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While a wealth of experience in the development of uncertainty quantification methods and software tools exists at present, a cohesive software package utilizing massively parallel computing resources does not. The thrust of the work to be discussed herein is the development of such a toolkit, which has leveraged existing software frameworks (e.g., DAKOTA (Design Analysis Kit for OpTimizAtion)) where possible, and has undertaken additional development efforts when necessary. The contributions of this paper are twofold. One, the design and structure of the toolkit from a software perspective will be discussed, detailing some of its distinguishing features. Second, the toolkit's capabilities will be demonstrated by applying a subset of its available uncertainty quantification techniques to an example problem involving multiple engineering disciplines, nonlinear solid mechanics and soil mechanics. This example problem will demonstrate the toolkit's suitability in quantifying uncertainty in engineering applications of interest modeled using very large computational system models.
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.
ComputerGenerated Minimal (and Larger) ResponseSurface Designs: (II) The Cube
 I) The Sphere, Statistics Research Report, AT&T Bell Laboratories
, 1991
"... Computergenerated designs in the cube are described which have the minimal (or larger) number of runs for a full quadratic responsesurface design. Examples of 2factor designs are included with 6 to 20 runs, 3factor designs with 10 to 20 runs, 4factor designs with 15 to 20 runs, 5factor designs ..."
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Cited by 5 (3 self)
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Computergenerated designs in the cube are described which have the minimal (or larger) number of runs for a full quadratic responsesurface design. Examples of 2factor designs are included with 6 to 20 runs, 3factor designs with 10 to 20 runs, 4factor designs with 15 to 20 runs, 5factor designs with 21 to 25 runs, 6factor designs with 28 to 31 runs, and 7factor designs with 36 and 39 runs. The designs were constructed by minimizing the average prediction variance, and without imposing any prior constraints  such as a central composite structure  on the locations of the points. Key Words. Minimal designs; cube designs; quadratic response surface; computergenerated designs; minimal variance designs. 1 Present address: AT&T Shannon Labs, Florham Park, NJ 079320971 1
Designoriented Translators for Automotive Joints
, 1998
"... A hierarchical approach is typically followed in design of consumer products. First, a manufacturer sets performance targets for the whole system according to customer surveys and benchmarking of competitors ’ products. Then, designers cascade these targets to the subsystems or the components using ..."
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Cited by 3 (0 self)
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A hierarchical approach is typically followed in design of consumer products. First, a manufacturer sets performance targets for the whole system according to customer surveys and benchmarking of competitors ’ products. Then, designers cascade these targets to the subsystems or the components using a very simplified model of the overall system. Then, they try to design the components so that they meet these targets. It is important to have efficient tools that check if a set of performance targets for a component corresponds to a feasible design and determine the dimensions and mass of this design. This dissertation presents a methodology for developing two tools that link performance targets for a design to design variables that specify the geometry of the design. The first tool (called translator A) predicts the stiffness and mass of an automotive joint, whose geometry is specified, almost instantaneously. The second tool (called translator B) finds the most efficient, feasible design whose performance characteristics are close to given performance targets. The development of the two translators involves the following steps. First, an
VariableComplexity Response Surface Design of an HSCT Configuration
, 1996
"... A variablecomplexity response surface methodology has been applied to the multidisciplinary design of a High Speed Civil Transport (HSCT). The term variablecomplexity refers to a design procedure in which refined, computationally expensive analysis techniques are combined with simple, computation ..."
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Cited by 3 (1 self)
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A variablecomplexity response surface methodology has been applied to the multidisciplinary design of a High Speed Civil Transport (HSCT). The term variablecomplexity refers to a design procedure in which refined, computationally expensive analysis techniques are combined with simple, computationally inexpensive techniques. We have used the simple analysis methods to define a subregion of the design space in which an optimal HSCT design is likely to exist. The refined analysis methods were then used to construct smooth response surface models of various aerodynamic and structural weight quantities. Aerodynamic response surface models were constructed for volumetric wave drag and supersonic drag due to lift based on an example problem involving four HSCT wing design variables. Optimization was then performed for the complete HSCT configuration using the aerodynamic response surface models. Preliminary research on the development of a structural response surface model for the wing ben...
Low Cost Response Surface Methods For And From Simulation Optimization
, 2000
"... We propose "low cost response surface methods" (LCRSM) that typically require half the experimental runs of standard response surface methods based on central composite and Box Behnken designs but yield comparable or lower modeling errors under realistic assumptions. In addition, the LCRSM ..."
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Cited by 2 (0 self)
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We propose "low cost response surface methods" (LCRSM) that typically require half the experimental runs of standard response surface methods based on central composite and Box Behnken designs but yield comparable or lower modeling errors under realistic assumptions. In addition, the LCRSM methods have substantially lower modeling errors and greater expected savings compared with alternatives with comparable numbers of runs, including small composite designs and computergenerated designs based on popular criteria such as Doptimality. Therefore, when simulation runs are expensive, low cost response surface methods can be used to create regression metamodels for queuing or other system optimization. The LCRSM procedures are also apparently the first experimental design methods derived as the solution to a simulation optimization problem. For these reasons, we say that LCRSM are for and from simulation optimization. We compare the proposed LCRSM methods with a large number of alternatives based on six criteria. We conclude that the proposed methods offer attractive alternative to current methods in many relevant situations.