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Quantification of Non-stationary Non-Gaussian Geotechnical Spatial Variability in a Specific Site from Sparse Measurements
Soils and rocks are natural materials, and they are affected by many spatially varying factors during their complex geological formation process. Geotechnical property therefore exhibits spatial variability, which is site-specific. The site-specific spatial variability of geotechnical property is often non-stationary (e.g., with spatial trend) and may not follow a Gaussian distribution. On the other hands, investigation data from a site is often sparse and limited in geotechnical engineering practice due to time and budget constraints. This leads to a great challenge of how to properly quantify the non-stationary and non-Gaussian geotechnical spatial variability in a specific site from sparse measurements. A novel method is presented in this paper to address this challenge. The method is based on Bayesian compressive sampling and Karhunen-Loève expansion, without assumptions of parametric trend function form, parametric auto-correlation function form and marginal probability distribution type.
Quantification of Non-stationary Non-Gaussian Geotechnical Spatial Variability in a Specific Site from Sparse Measurements
Soils and rocks are natural materials, and they are affected by many spatially varying factors during their complex geological formation process. Geotechnical property therefore exhibits spatial variability, which is site-specific. The site-specific spatial variability of geotechnical property is often non-stationary (e.g., with spatial trend) and may not follow a Gaussian distribution. On the other hands, investigation data from a site is often sparse and limited in geotechnical engineering practice due to time and budget constraints. This leads to a great challenge of how to properly quantify the non-stationary and non-Gaussian geotechnical spatial variability in a specific site from sparse measurements. A novel method is presented in this paper to address this challenge. The method is based on Bayesian compressive sampling and Karhunen-Loève expansion, without assumptions of parametric trend function form, parametric auto-correlation function form and marginal probability distribution type.
Quantification of Non-stationary Non-Gaussian Geotechnical Spatial Variability in a Specific Site from Sparse Measurements
Lecture Notes in Civil Engineering
Barla, Marco (editor) / Di Donna, Alice (editor) / Sterpi, Donatella (editor) / Hu, Yue (author) / Wang, Yu (author)
International Conference of the International Association for Computer Methods and Advances in Geomechanics ; 2021 ; Turin, Italy
2021-01-15
8 pages
Article/Chapter (Book)
Electronic Resource
English
Modelling spatial variability in geotechnical engineering
| Taylor & Francis Verlag | 2016