Chapter
Jul 11, 2012

The Effects of Simplifications on Model Predictions and Consequences for Model- Based Data Interpretation

Publication: 20th Analysis and Computation Specialty Conference

Abstract

Situations that justify structural measurements continue to increase in number and in importance. Measurement-data interpretation has become the principle scientific challenge for such activities. This paper summarizes a study of quantifying modeling uncertainties using the Grand-Mere Bridge located in Canada. This case study demonstrates that modeling errors involve systematic biases and that these biases can affects data interpretation and ultimately, the quality of infrastructure-management support. The impact of systematic errors on traditional data-interpretation approach is discussed.

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Go to 20th Analysis and Computation Specialty Conference
20th Analysis and Computation Specialty Conference
Pages: 107 - 116

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Published online: Jul 11, 2012

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J.-A. Goulet
Computing and Mechanics Laboratory (IMAC), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL) Lausanne, Switzerland
I. F. C. Smith
Computing and Mechanics Laboratory (IMAC), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL) Lausanne, Switzerland
M. Texier
Computing and Mechanics Laboratory (IMAC), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL) Lausanne, Switzerland
L. Chouinard
Department of Civil Engineering and Applied Mechanics McGill University, Montréal, Canada

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