Digital twinning of infrastructures using statistical finite element method (statFEM)

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• Eky Febrianto, University of Glasgow
• Friday 13 May 2022, 15:00-16:00
• CivEng Seminar Room (1-33) (Civil Engineering Building).

If you have a question about this talk, please contact Mishael Nuh.

The monitoring of infrastructure assets using sensor networks is becoming increasingly prevalent. A digital twin in the form of a finite element (FE) model can help make sense of the copious amount of collected sensor data. This talk reviews the statistical finite element method (statFEM) that provides the means of synthesising measurement data and FE models. In statFEM, the data and FE model are random variables with uncertainties associated with measurement error, random inputs, and modelling assumptions. A physics-informed prior density distribution of the system response, e.g., strain or displacement, is given by a conventional stochastic forward problem. The posterior density of the system response is obtained through the Bayes rule from the postulated prior density and a data-dependent likelihood function. This talk also presents the application of statFEM to predict the structural response of an instrumented steel railway bridge and nonlinear continuous welded rail system. 

This talk is part of the Engineering Department Structures Research Seminars series.

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