Results 1  10
of
150
Sampling and Bayes inference in scientific modeling and robustness. (with discussion
 Journal of the Royal Statistical Society, Series A
, 1980
"... t ..."
A Concept Exploration Method for Product Family Design
 in Mechanical Engineering. Atlanta, GA: Georgia Institute of Technology
, 1998
"... ii ..."
(Show Context)
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 ..."
Abstract

Cited by 26 (13 self)
 Add to MetaCart
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 ..."
Abstract

Cited by 18 (0 self)
 Add to MetaCart
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 ..."
Abstract

Cited by 12 (1 self)
 Add to MetaCart
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.
Low cost response surface methods for and from simulation optimization
 In: Proceedings of the 2000 winter simulation conference
, 2000
"... ABSTRACT 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, ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
ABSTRACT 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.
New E(s2)optimal supersaturated designs constructed from incomplete block designs
 Technometrics
, 2008
"... We present a method for constructing twolevel supersaturated designs (SSDs) from incomplete block designs. A lower bound of E(s2) that also covers the case of odd run sizes is given. This bound is attained by SSDs constructed from balanced incomplete block designs. We study SSDs that can be constr ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
(Show Context)
We present a method for constructing twolevel supersaturated designs (SSDs) from incomplete block designs. A lower bound of E(s2) that also covers the case of odd run sizes is given. This bound is attained by SSDs constructed from balanced incomplete block designs. We study SSDs that can be constructed from regular graph designs when balanced incomplete block designs do not exist. A computer search is conducted to find SSDs with 5 ≤ n ≤ 50 and n ≤ m ≤ 2n that can be constructed from regular graph designs, where m is the number of factors and n is the run size. Many SSDs derived from regular graph designs are optimal. The best E(s2)optimal SSDs with respect to additional optimality criteria are tabulated. Some notes on the construction of saturated designs also are given. KEY WORDS: Balanced incompleteblock design; Cyclic incompleteblock design; Plackett–Burman design; Regular graph design; Saturated design.
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 ..."
Abstract

Cited by 7 (1 self)
 Add to MetaCart
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.
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 ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
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