• Earthquakes and Structures
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• v.8 no.1
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• pp.77-100
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• 2015

Multiple tuned mass dampers (MTMDs) tuned to various frequencies have been shown to efficiently control the seismic response of structures where multiple modes are dominant. One example is irregular structures that are found more vulnerable than their symmetric counterparts. With the technology of MTMDs available, design and optimal design methodologies are required for application. Such a methodology, in the form of an analysis/redesign (A/R) scheme, has been previously presented by the authors while limiting responses of interest to allowable values, i.e., performance-based design (PBD). In this paper, the A/R procedure is modified based on formal optimality criteria, making it more cost efficient, as well as more computationally efficient. It is shown that by using the methodology presented herein, a desired performance level is successfully targeted by adding near-optimal amounts of mass at various locations and tuning the TMDs to dampen several of the structure's frequencies. This is done using analysis tools only.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.376-386
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• 1995

Designs for polynomial approximation to the unknown response function are considered. Optimality criteria are monotone functions of the mean squared error matrix of the least squares estimator. They correspond to the classical A-, D-, G- and Q-optimalities. Optimal first order designs are chosen from the invariant designs and then compared with optimal second order designs.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.267-280
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• 2007

Various single-valued design optimality criteria such as D-, G-, and V-optimality are used often in constructing optimal experimental designs for mixture experiments in a constrained region R where lower and upper bound constraints are imposed on the ingredients proportions. Even though they are optimal in the strict sense of particular optimality criterion used, it is known that their performance is unsatisfactory with respect to the prediction capability over a constrained region. (Vining et at., 1993; Khuri et at., 1999) We assume the quadratic polynomial model as the mixture response surface model and are interested in finding efficient designs in the constrained design space for a mixture. In this paper, we make an expanded list of candidate design points by adding interior points to the extreme vertices, edge midpoints, constrained face centroids and the overall centroid. Then, we want to propose a robust design with respect to D-optimality, G-optimality, V-optimality and distance-based U-optimality. Comparing scaled prediction variance quantile plots (SPVQP) of robust designs with that of recommended designs in Khuri et al. (1999) and Vining et al. (1993) in the well-known examples of a four-component fertilizer experiment as well as McLean and Anderson's Railroad Flare Experiment, robust designs turned out to be superior to those recommended designs.

• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.431-440
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• 2012

Purpose: In this paper we propose modified Notz designs which are useful to experimenters who want to adopt the sequential experimentation strategy and to estimate second-order regression model with as few experimental points as possible. Methods: We first present the design matrices and design points in two or three dimensional spaces for such small sized second-order designs as small composite, hybrid, and Notz designs. Modified Notz designs are proposed and compared with some response surface designs in terms of the total number of experimental points, the estimation capability criteria such as D- and A-optimality. Results: When sequential experimentation is necessary, the modified Notz designs are recommendable. Conclusion: The result of this paper will be beneficial to experimenters who need to do experiments more efficiently, especially for those who want to reduce the time of experimentation as much as possible to develop cutting-edge products.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.253-260
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• 1997

Various algorithms are investigated with respect to finding the best model-based samples according to criteria such as D-optimality and minimum mean square error. These two criteria are slightly different, but related to each other. Therefore, it is not surprising that these two are producing the almost identical samples. Some simple examples follow and critiques are provided along with directions for further research.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.407-412
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• 2000

Response surface method is employed in optimizing the acoustic performance of automotive engine-cooling axial fans. The effects of modifications in blade geometry on noise reduction are investigated. Taking the far-field noise level as the objective, a quadratic response surface is constructed utilizing D-Optimality condition as the candidate-points selection criteria. It is shown that the quadratic model exhibits an excellent fitting capability resulting in the blade design with low far-field noise level.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.156-167
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• 1996

D-optimality is used often in design augmentation of mixture experiments. Although such alphabetic criteria provide a valuable foundation for generating designs, they often fail to convey the true nature of the design's support of the fitted model in terms of prediction variance over a region of interest. Thus, a graphical method is proposed to evaluate augmented designs in mixture experiments. This method can be used to evaluate the effect of missing observation and outlier in mixture experiments.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.27-38
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• 2018

Purpose: A large number of attributes with mixed levels are often considered in the conjoint analysis. In the cases where attributes have two or three levels, we research on the efficient design of survey questionnaire to estimate all the main effect and two factor interaction effects with a reasonable size of it. Methods: To reduce the number of questions in a questionnaire, the balanced incomplete block mixed level factorial design with minimum aberration was proposed by Lim and Chung (2016). Based on the number of questions and that of the respondents in that design, D-optimality criterion is adopted to find efficient designs where the main effect and two factor interaction effects are estimated. Results: The list of the number of questions and that of the respondents in efficient designs for survey questionnaire are recommended based on the D-efficiency of each design and the proposed selection criteria for the number of both questions and the respondents. By analyzing all the respondents survey data generated by the simulation study, we find the proper model. Conclusion: The proposed methods of designing survey questionnaires seem to perform well in the sense that how often the proper model is found in a simulation study where all the respondents survey data are generated by the simulation model.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.31-45
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• 2021

Purpose: A noncentral composite design method is to be developed to explore farther region for the first factorial design. A general guideline for sequential experimentation is provided. Methods: (1) A non-overlapping noncentral composite design (NNCD) is developed, in which the second factorial design shares one design point that indicates the best response value in the first factorial design. (2) Four composite designs are compared in terms of the four design evaluation criteria, which are D-, A, G, and I-optimality. (3) A follow-up design strategy is suggested based on the interaction effect, direction of improvement, number of factors. Results: (1) NNCD and model building method are presented, which is useful for exploring farther region from first factorial design block. (2) The performances of the four composite designs are compared. (3) A follow-up design strategy is suggested. Conclusion: (1) NNCD will be useful to explore farther region for the first factorial design. (2) A follow-up design strategy can be beneficial to the experimental practitioners for product and process design and improvement.