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Polynomial Chaos Expansion for assessment of tunnel linings
Křížek, Michael ; Novák, Drahomír (referee) ; Novák, Lukáš (advisor)
The study presents the application of polynomial chaos expansion (PCE) methodology for the uncertainty quantification and sensitivity analysis within the realm of predictive modeling. Its principal objective is to optimize the PCE methodology for a specific dataset and subsequently assess the resultant outcomes. These outcomes will be compared with those obtained through the Monte Carlo method to ascertain the comparative precision of the PCE methodology. To execute the requisite computations essential for data analysis, modules sourced from the UQpy project were employed. The dataset comprised 86 discrete points constituting a 2D cross-section of a tunnel. Each point encapsulated 1000 input measurements, wherein each measurement involved five uncertain variables. Static moments and Sobol indices were computed for each data point. In terms of result validation, the PCE error will be ascertained via cross-validation and analytical validation error computation, and both methodologies will be juxtaposed for comparison. Result validation will be delineated through alignment with reference data, alongside cross-validation and robustness analysis.

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