Bayesian Thinking in Geotechnics

Baecher, Gregory B.

doi:10.1061/9780784480694.001

Cited by 23 publications

(5 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The combination of the most likely scenario of failure and most representative model choices is referred to as "MLC" in the remainder of this paper. In the past, Bayesian techniques have been used to characterise the lifetime reliability of geotechnical structures (Zhang, Tang, and Zhang 2010;Schweckendiek 2014b;Baecher 2017), and have been applied to the hindcasting of different types of geotechnical related structures (Luckman, Der Kiureghian, and Sitar 1987;Gilbert, Wright, and Liedtke 1998;Zhang, Tang, and Zhang 2010;Gilbert 2016). However, to our knowledge, Bayesian techniques have not been applied to hindcasting of specific levee failures.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian hindcasting method of levee failures applied to the Breitenhagen slope failure

Kool

Kanning

Jommi

et al. 2020

Georisk: Assessment and Management of Risk for Engineered Syste

View full text Add to dashboard Cite

Hindcasting of past levee failures enhances insights in the performance and vulnerability of levees. The scarcity of field evidence makes identifying the cause(s) of failure difficult. Under these circumstances, multiple scenarios and model choices are possible to characterise and to model the failure. This paper shows how probabilistic Bayesian techniques advance the procedure of hindcasting of levee failures. In the developed approach, a-priori levee information, and failure observations are systematically taken into account to determine the most likely scenario and the most representative model choices to characterise the failure most accurately. Observations, such as the slip surface, are taken into account in the probability estimates. The levee failure near Breitenhagen, Germany (2013) is used as a case study. The levee failed during river floods due the instability of the landside slope. The levee failure was most likely triggered by locally weak soil conditions and unexpected high water pressures due a connection between a pond on the riverside of the levee and the aquifer. These conditions were likely caused by the occurrence of a previous breach at this location. The approach developed in this paper is expected to support a more systematic and objective method of analysis of other levee failures.

show abstract

Section: Introductionmentioning

confidence: 99%

A Bayesian hindcasting method of levee failures applied to the Breitenhagen slope failure

Kool

Kanning

Jommi

et al. 2020

Georisk: Assessment and Management of Risk for Engineered Syste

View full text Add to dashboard Cite

show abstract

“…A lack of understanding in this regard can be perceived as an additional source of uncertainty, which is hard to define. As discussed by, e.g., Baecher (2017), many geotechnical engineers are intuitive in Bayesian thinking in their daily work but in regard to RBD people often adhere to the frequentist form of statistical thinking which is not useful expect in narrowly defined problems. Hence, this finally leads to the crucial aspect of how to achieve an adequate state of knowledge to apply RBM.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

A Review on the Current Use of RBD in Geotechnical Design Practice in View of the Next Eurocode 7

Ebener¹,

Lesny²

2022

8th International Symposium for Geotechnical Safety &Amp; Risk (ISGSR 2022)

View full text Add to dashboard Cite

In course of the evolution of the next Eurocode 7 CEN TC 250/SC7 Task Group C3 is developing a guideline on reliability-based methods for geotechnical design and assessment. As part of this work, a survey was prepared to identify best practices and examples that could be used for illustration in the guidelines. Beside this, information on possible benefits and limitations of using reliability-based methods in the engineering practice were requested from the participants. The survey was distributed in summer 2021 among the international geotechnical community. The results reveal that the main benefits are seen in the identification and visualization of uncertainties and risks as well as in the possibilities for design and cost optimization. However, as major limitations an often insufficient data basis but generally a lack of acceptance on the side of the clients and an insufficient knowledge on the side of possible practitioners were identified. Consequently, clear guidance on how to use reliability-based methods and how to implement them in decision processes are needed. The TG C3 guideline therefore is a step in the right direction. On the other hand, integrating methods of reliability analysis in the engineering education already at an early stage is also considered to be important.

show abstract

“…Bayesian thinking pertains to the processes of judgment and belief. This phenomenon results in highly significant deductions even when the available data is limited [19,20]. Whereas in this research, the approach used Bayesian methods that can handle complex models and hierarchical structures more efficiently than frequentist methods, and there are limited studies on the single-particle strength of pumice in various locations, particularly in the Kyushu area.…”

Section: Introductionmentioning

confidence: 99%

The Physical and Mechanical Properties of Single Pumice Sand Particle

Ariyana Basoka

2024

GEOMATE

View full text Add to dashboard Cite

Pumice sand is a volcanic material widely distributed in volcanic areas such as Japan, Indonesia, and countries traversed by volcanic mountains. Geotechnical problems regarding pumice sand often occur in these areas, such as landslides because of the pumice crushable structure. Based on previous research, some failure phenomena are caused by the existing pumice layer, and not so many studies describe the behavior of pumice single particle located at Kyushu Island, Japan. This study conducted a series of tests to clarify pumice material's microscopic and mechanical properties. Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) tests were carried out on pumice materials to determine the microscopic and chemical compounds in the pumice material. Then, single-particle crushability tests were carried out as representative of the mechanical behavior of pumice sand particles. The approach using linear regression fitting is carried out using conventional frequentist and Bayesian hierarchical approaches to obtain the strength behavior of the pumice sand. An overview of pumice microscopy conditions and minerals can be helpful when ground improvement and soil stabilization are discussed for this pumice material and the effect of particle shape on pumice strength is observed. According to this study, oxygen, silica, and alumina dominate pumice sand chemical components. The aspect ratio and the roundness coefficient of pumice sand do not significantly impact particle stress. Particle size reduces and increases particle stress in single-particle crushability tests. Single-particle crushability reduces pumice particle pore area and increases the number of pores.

show abstract

Bayesian Thinking in Geotechnics

Cited by 23 publications

References 35 publications

A Bayesian hindcasting method of levee failures applied to the Breitenhagen slope failure

A Bayesian hindcasting method of levee failures applied to the Breitenhagen slope failure

A Review on the Current Use of RBD in Geotechnical Design Practice in View of the Next Eurocode 7

The Physical and Mechanical Properties of Single Pumice Sand Particle

Contact Info

Product

Resources

About