Hierarchical Bayesian modelling of quasi-region-specific soil porosity

Wang, Mingyuan; Pan, Sunjuexu; Tao, Yuanqin; Sun, Honglei

doi:10.1016/j.oceaneng.2022.113052

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…Figure 3B shows the results of C u estimated based on SPTN, according to Decourt (1990). Number of cohesion values used at various depths vary, for example at depths of (1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,22,23,24,25) The collected data were presented in histograms to be more reliable and to provide a means to reduce the high uncertainty. It is noted in Figure 4 that 95% of the cohesion rate in most projects ranges from (50-150) kPa, which was estimated through the equations of the corrected values for SPT N according to Decourt [17].…”

Section: Previous Knowledgementioning

confidence: 99%

“…In geotechnical engineering, the evaluations of in situ geotechnical parameters are typically limited and sparse due to terrain limitations and high testing expenses [3]. It is urgent to find a solution for this lack of region-specific data to create accurate regional models [4]. Results of uncertainty quantification, such as statistics and probability distributions of geotechnical characteristics, heavily rely on the accuracy of the information gathered during the site investigation [5].…”

Section: Introductionmentioning

confidence: 99%

“…Figure3Bshows the results of C u estimated based on SPTN, according toDecourt (1990). Number of cohesion values used at various depths vary, for example at depths of(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,22,23,24,25) m the number of calculated values of cohesion were respectively (2, 5, 9, 4, 7, 7, 7, 4, 11, 1, 5, 7, 5, 1, 10, 5, 3, 4, 4, 4, 2, 4, 2, 3).…”

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confidence: 99%

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Uncertainty Characterization for Soil Cohesion in a Project Site in Nasiriyah Using Bayesian Methods

Abd Al-Haleem,

Shakir

2023

E3S Web Conf.

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High uncertainties arias through the characterization of soil parameters because of the lack of data obtained from geotechnical reports. Reducing these uncertainties may improve the characteristic values of soil parameters. This research aims to probabilistically characterize a soil's cohesion parameter in Nasiriyah. The Bayesian approach has been applied to soil data obtained through a project in Nasiriyah. The soil at the site is classified as lean clay, and the soil cohesion has been evaluated using two Bayesian methods: the ordinary, normal distribution method (OND) and the Marcove Chain Monte Carlo-based Bayesian approach (MCMC) method. The previous knowledge utilized in the Bayesian approach was based on 20 boreholes, and the subjective probability approach has functioned in the prior probability distribution. The OND method deduced a mean value of cohesion of (195.9 kPa) and a standard deviation of (14.68 kPa), (COV) 7.49%. It was noted that the probability distribution has a more significant effect than the previous distribution on the posterior distribution. The MCMC method summarized the probabilistic description of the soil characteristic, through which it reached the mean and the subsequent standard deviation (167.49) kPa (109.8) kPa, respectively, and the coefficient of Variation (COV) was 65.6%. It is considered the most appropriate and common method, especially in high-dimensional data when the results are not well known because it can provide a probabilistic value for the not well-known data.

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Section: Previous Knowledgementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Figure3Bshows the results of C u estimated based on SPTN, according toDecourt (1990). Number of cohesion values used at various depths vary, for example at depths of(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,22,23,24,25) m the number of calculated values of cohesion were respectively (2, 5, 9, 4, 7, 7, 7, 4, 11, 1, 5, 7, 5, 1, 10, 5, 3, 4, 4, 4, 2, 4, 2, 3).…”

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confidence: 99%

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