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On the optimization of site investigation programs using centroidal Voronoi tessellation and random field theory
Abstract This work proposes a centroidal Voronoi tessellation (CVT)-based site investigation scheme, which is applicable to arbitrary site geometries and arbitrary numbers of investigation locations. A modified Lloyd algorithm is developed to generate CVT-based site investigation programs. With the data from prior site investigations, the random field statistics of a site property are estimated using a Markov chain Monte Carlo simulation-based Bayesian inference approach, and the site property at each location is estimated using Kriging interpolation. The performance of the CVT-based site investigation programs and optimization are demonstrated using two illustrative examples, namely, a square site and an irregular site.
On the optimization of site investigation programs using centroidal Voronoi tessellation and random field theory
Abstract This work proposes a centroidal Voronoi tessellation (CVT)-based site investigation scheme, which is applicable to arbitrary site geometries and arbitrary numbers of investigation locations. A modified Lloyd algorithm is developed to generate CVT-based site investigation programs. With the data from prior site investigations, the random field statistics of a site property are estimated using a Markov chain Monte Carlo simulation-based Bayesian inference approach, and the site property at each location is estimated using Kriging interpolation. The performance of the CVT-based site investigation programs and optimization are demonstrated using two illustrative examples, namely, a square site and an irregular site.
On the optimization of site investigation programs using centroidal Voronoi tessellation and random field theory
Huang, Linchong (author) / Huang, Shuai (author) / Lai, Zhengshou (author)
2019-10-31
Article (Journal)
Electronic Resource
English
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