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Statistical space-time metamodels based on multiple responses approach for time-variant dynamic response of structures

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Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations. ?? 2010 The Korean Society ot Mechanical Engineers

Topics: Dynamic response, Structural design, Computational methods, Meta model, Computer simulation, Response surface models, Regression analysis, Experiments, Statistics, Data reduction, Interpolation, Multiple response, Regression model, Dynamics, Surface properties, Kriging model, Models
Publisher: ??????????????????
Year: 2010
DOI identifier: 10.3795/KSME-A.2010.34.8.989
OAI identifier:
Provided by: HANYANG Repository
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