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37
Computer Experiments
, 1996
"... Introduction Deterministic computer simulations of physical phenomena are becoming widely used in science and engineering. Computers are used to describe the flow of air over an airplane wing, combustion of gasses in a flame, behavior of a metal structure under stress, safety of a nuclear reactor, a ..."
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Cited by 68 (5 self)
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Introduction Deterministic computer simulations of physical phenomena are becoming widely used in science and engineering. Computers are used to describe the flow of air over an airplane wing, combustion of gasses in a flame, behavior of a metal structure under stress, safety of a nuclear reactor, and so on. Some of the most widely used computer models, and the ones that lead us to work in this area, arise in the design of the semiconductors used in the computers themselves. A process simulator starts with a data structure representing an unprocessed piece of silicon and simulates the steps such as oxidation, etching and ion injection that produce a semiconductor device such as a transistor. A device simulator takes a description of such a device and simulates the flow of current through it under varying conditions to determine properties of the device such as its switching speed and the critical voltage at which it switches. A circuit simulator takes a list of devices and the
Bayesian Treed Gaussian Process Models with an Application to Computer Modeling
 Journal of the American Statistical Association
, 2007
"... This paper explores nonparametric and semiparametric nonstationary modeling methodologies that couple stationary Gaussian processes and (limiting) linear models with treed partitioning. Partitioning is a simple but effective method for dealing with nonstationarity. Mixing between full Gaussian proce ..."
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Cited by 44 (15 self)
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This paper explores nonparametric and semiparametric nonstationary modeling methodologies that couple stationary Gaussian processes and (limiting) linear models with treed partitioning. Partitioning is a simple but effective method for dealing with nonstationarity. Mixing between full Gaussian processes and simple linear models can yield a more parsimonious spatial model while significantly reducing computational effort. The methodological developments and statistical computing details which make this approach efficient are described in detail. Illustrations of our model are given for both synthetic and real datasets. Key words: recursive partitioning, nonstationary spatial model, nonparametric regression, Bayesian model averaging 1
AIRCRAFT MULTIDISCIPLINARY DESIGN OPTIMIZATION USING DESIGN OF EXPERIMENTS THEORY AND RESPONSE SURFACE MODELING METHODS
, 1997
"... Design engineers often employ numerical optimization techniques to assist in the evaluation and comparison of new aircraft configurations. While the use of numerical optimization methods is largely successful, the presence of numerical noise in realistic engineering optimization problems often inhib ..."
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Cited by 18 (2 self)
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Design engineers often employ numerical optimization techniques to assist in the evaluation and comparison of new aircraft configurations. While the use of numerical optimization methods is largely successful, the presence of numerical noise in realistic engineering optimization problems often inhibits the use of many gradientbased optimization techniques. Numerical noise causes inaccurate gradient calculations which in turn slows or prevents convergence during optimization. The problems created by numerical noise are particularly acute in aircraft design applications where a single aerodynamic or structural analysis of a realistic aircraft configuration may require tens of CPU hours on a supercomputer. The computational expense of the analyses coupled with the convergence difficulties created by numerical noise are significant obstacles to performing aircraft multidisciplinary design optimization. To address these issues, a procedure has been developed to create two types of noisefree mathematical models for use in aircraft optimization studies. These two methods use elements of statistical analysis and the overall procedure for using the methods is made computationally affordable by the application of parallel computing techniques. The first
Dependence Of Optimal Structural Weight On Aerodynamic Shape For A High Speed Civil Transport
, 1996
"... A procedure for generating a customized weight function for wing bending material weight of the High Speed Civil Transport (HSCT) is described. The weight function is based on the shape parameters. A response surface methodology is used to fit a quadratic polynomial to data gathered from a large num ..."
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Cited by 15 (9 self)
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A procedure for generating a customized weight function for wing bending material weight of the High Speed Civil Transport (HSCT) is described. The weight function is based on the shape parameters. A response surface methodology is used to fit a quadratic polynomial to data gathered from a large number of structural optimizations. The results of the structural optimization are noisy. Noise reduction in the structural optimization results is discussed. Several techniques are 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 surfaces themselves are created employing detailed analysis methods. Intervening variables and analysis of variance are used to reduce the number of polynomial terms in the response surface model functions. Minimum vari...
Constrained Optimization of Experimental Design
 Statistics
, 1995
"... This is an attempt to discuss various approaches developed in experimental design when some constraints are imposed. The constraints may be on the total cost of the experiment, the location of the supporting point, the value of the auxiliary objective functions, and so on. The basic idea of the pape ..."
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Cited by 9 (0 self)
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This is an attempt to discuss various approaches developed in experimental design when some constraints are imposed. The constraints may be on the total cost of the experiment, the location of the supporting point, the value of the auxiliary objective functions, and so on. The basic idea of the paper is that corresponding optimization problems can be imbedded in the convex theory of experimental design. Part 1 is concerned with the properties of optimal designs, while Part 2 is devoted mainly to numerical methods. We have tried to avoid detail emphasizing ideas rather than technicalities. This is not intended as a literature review. The authors subjectively, surely left many excellent papers behind. 1 Equivalence Theorems 1.1 Introduction Experimental design problems considered in this paper are basically related to the standard linear regression model: y ij = j(x i ; `) + ffl ij ; (1) i = 1; : : : ; n; j = 1; : : : ; r i ; \Sigmar i = N; j(x; `) = ` T f(x) where `fflR m are ...
Response Surface Model Building And Multidisciplinary Optimization Using DOptimal Designs
, 1998
"... This paper discusses response surface methods for approximation model building and multidisciplinary design optimization. The response surface methods discussed are central composite designs, Bayesian methods and Doptimal designs. An overdetermined Doptimal design is applied to a configuration des ..."
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Cited by 6 (2 self)
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This paper discusses response surface methods for approximation model building and multidisciplinary design optimization. The response surface methods discussed are central composite designs, Bayesian methods and Doptimal designs. An overdetermined Doptimal design is applied to a configuration design and optimization study of a wingbody, launch vehicle. Results suggest that over determined Doptimal designs may provide an efficient approach for approximation model building and for multidisciplinary design optimization. Introduction Computerized design and analysis capabilities exist in many key disciplines required for design and analysis of space transportation systems. For a given configuration, system performance characteristics can be determined by the use of these analysis codes. The next step is to determine the settings of design parameters that optimize the system performance characteristics subject to constraints. However, the complex computer programs used in aerospace de...
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.
Optimal experimental design and some related control problems
, 2008
"... This paper traces the strong relations between experimental design and control, such as the use of optimal inputs to obtain precise parameter estimation in dynamical systems and the introduction of suitably designed perturbations in adaptive control. The mathematical background of optimal experiment ..."
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Cited by 5 (0 self)
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This paper traces the strong relations between experimental design and control, such as the use of optimal inputs to obtain precise parameter estimation in dynamical systems and the introduction of suitably designed perturbations in adaptive control. The mathematical background of optimal experimental design is briefly presented, and the role of experimental design in the asymptotic properties of estimators is emphasized. Although most of the paper concerns parametric models, some results are also presented for statistical learning and prediction with nonparametric models.
Optimal Experimental Design: Spatial Sampling
, 1994
"... this paper it is assumed that an observed surface (function, field) is a realization of some random process y(x; t), where x 2 X, t 2 T , and X and T are compact. Measurement (observation, sampling) provides realizations y ij at the points x i and the times ..."
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Cited by 2 (1 self)
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this paper it is assumed that an observed surface (function, field) is a realization of some random process y(x; t), where x 2 X, t 2 T , and X and T are compact. Measurement (observation, sampling) provides realizations y ij at the points x i and the times
Chemical library subset selection algorithms: a unified derivation using spatial statistics
 JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCE
, 2002
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