SCAP-1D : A Spatial Correlation Assessment Procedure from unidimensional discrete data
| Autor: | Franck Schoefs, Romain Clerc, Mestapha Oumouni |
|---|---|
| Přispěvatelé: | Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Spatial correlation
Iterative method media_common.quotation_subject Ergodicity Bilinear interpolation 020101 civil engineering 02 engineering and technology 01 natural sciences Industrial and Manufacturing Engineering 0201 civil engineering Correlation 010104 statistics & probability [SPI]Engineering Sciences [physics] Spatial variability 0101 mathematics Safety Risk Reliability and Quality Constant (mathematics) Algorithm Normality media_common Mathematics |
| Zdroj: | Reliability Engineering and System Safety Reliability Engineering and System Safety, Elsevier, 2019, 191, pp.106498-. ⟨10.1016/j.ress.2019.106498⟩ |
| ISSN: | 0951-8320 1879-0836 |
| DOI: | 10.1016/j.ress.2019.106498⟩ |
| Popis: | Optimal placement of Non-destructive Testing sensors is essential for structure diagnosis as it allows to get maximum information about degradation at minimum cost. Latest optimization methods consider spatial variability of quantities of interest and thus strongly rely on correlation lengths assessment. However, this assessment is usually done with straightforward techniques on raw data, which may not satisfy the required hypotheses of stationarity and ergodicity and induce important mis-estimations. In this paper, we propose a Spatial Correlation Assessment Procedure (SCAP-1D) which allows to rigorously assess correlation length of a quantity of interest modeled as a piecewise-trend-stationary Gaussian-Random-Field (GRF). The procedure is applicable to unidimensional limited data and comprises two steps. First, the correlation length is assessed through an iterative algorithm including mean changepoints detection. Then, stationarity, ergodicity, and normality are tested to validate both the model and estimations. In numerical studies, we demonstrate the ability of our procedure to accurately estimate correlation length of a GRF in the cases of constant, stepped and bilinear mean, with performance ranges assessment. Applications to experimental Half-Cell Potential measurements with effective mean and slope steps validate the capacity of our method to precisely determine mean changepoints and correlation length on real data. |
| Databáze: | OpenAIRE |
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