Health risk assessment of soil trace elements using the Sequential Gaussian Simulation approach

Özen, Songül Akbulut; Yeşilkanat, Cafer Mert; Özen, Murat; Başsarı, Asiye; Taşkın, Halim

doi:10.1007/s11356-022-20974-9

Cited by 3 publications

(1 citation statement)

References 57 publications

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“…The results obtained with the SGS method (Figure 6) represent the sample data spatially, meaning that regions with low sample values had lower simulated values and vice versa. This behavior has been observed in other works that have employed SGS [45][46][47][48][49][50], where the simulated values follow the spatial variability of the sample values.…”

Section: Resultssupporting

confidence: 78%

SGS method applied to damage location and uncertainty modeling for sensor grid in the ISHM

Pereira,

de Rezende,

Moura Júnior

et al. 2024

Comptes Rendus. Mécanique

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Damage location estimation is a critical aspect of condition-based maintenance systems, particularly in the context of electromechanical impedance monitoring. Various approaches have been developed to estimate damage location, yet they often need more capability to assess the reliability of data collected from sensor grids. In this paper, we introduce a novel method based on Sequential Gaussian Simulation (SGS) to pinpoint damage locations on aluminum plates and create maps that illustrate the spatial uncertainty associated with damage index values throughout the structure. Our proposed approach builds upon the SGS method and encompasses the assessment of four different sensor grid configurations to investigate how sensor spacing affects spatial uncertainty. The findings demonstrate the technique's effectiveness in accurately predicting damage positions. Moreover, by leveraging the uncertainty information generated, we can identify specific areas necessitating careful attention, thus offering valuable insights for optimizing sensor grid design.Résumé. L'estimation de la localisation des dommages est un aspect critique des systèmes de maintenance basés sur l'état, en particulier dans le contexte de la surveillance de l'impédance électromécanique. Diverses approches ont été mises au point pour estimer la localisation des dommages, mais elles nécessitent souvent davantage de capacités pour évaluer la fiabilité des données collectées à partir des grilles de capteurs. Dans cet article, nous présentons une nouvelle méthode basée sur la simulation gaussienne séquentielle (SGS) pour localiser les dommages sur les plaques d'aluminium et créer des cartes qui illustrent l'incertitude spatiale associée aux valeurs de l'indice de dommage dans l'ensemble de la structure. L'approche proposée s'appuie sur la méthode SGS et englobe l'évaluation de quatre configurations différentes de la grille de capteurs afin d'étudier comment l'espacement des capteurs affecte l'incertitude spatiale. Les résultats démontrent l'efficacité de la technique pour prédire avec précision les positions des dommages. De plus, en exploitant les

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