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Improving dike reliability estimates by incorporating construction survival
Abstract During construction of a dike, slope stability often reaches critical levels, due to the excess pore water pressures in the foundation. The loading condition during construction has similarities with the design conditions during flood loading. Not only in terms of the pore water pressures as the main driving force, but also in terms of criticality of the stability. This paper examines how the information of survival of the construction stage can be used to improve the reliability estimate for a dike in flood conditions, using Bayesian updating. The approach is exemplified for a range of typical dikes and for a case study of a full-scale test embankment. The main result is that the reliability can increase significantly by including the information of construction survival and the uncertainty reduction involved, especially for dikes on soft soil blankets. For the investigated cases, the posterior failure probability was up to several orders of magnitude lower than the prior failure probability. The main factors influencing the degree of reliability update, were the ground conditions and the degree of criticality of the slope stability during construction. In conclusion, using the information of the survived construction leads to improved reliability-based safety assessments of dikes, and consequently to more targeted and cost-effective flood protection.
Highlights Construction of dikes on soft soils is shown to be typically a loading condition more critical for slope stability than flood loading The paper demonstrates a Bayesian approach to incorporate survival of the construction phase in reliability estimates of dikes Reliability estimates of dikes on soft soil blankets can increase significantly when incorporating survival of the construction phase Safety assessments of dikes can improve significantly when construction survival is considered.
Improving dike reliability estimates by incorporating construction survival
Abstract During construction of a dike, slope stability often reaches critical levels, due to the excess pore water pressures in the foundation. The loading condition during construction has similarities with the design conditions during flood loading. Not only in terms of the pore water pressures as the main driving force, but also in terms of criticality of the stability. This paper examines how the information of survival of the construction stage can be used to improve the reliability estimate for a dike in flood conditions, using Bayesian updating. The approach is exemplified for a range of typical dikes and for a case study of a full-scale test embankment. The main result is that the reliability can increase significantly by including the information of construction survival and the uncertainty reduction involved, especially for dikes on soft soil blankets. For the investigated cases, the posterior failure probability was up to several orders of magnitude lower than the prior failure probability. The main factors influencing the degree of reliability update, were the ground conditions and the degree of criticality of the slope stability during construction. In conclusion, using the information of the survived construction leads to improved reliability-based safety assessments of dikes, and consequently to more targeted and cost-effective flood protection.
Highlights Construction of dikes on soft soils is shown to be typically a loading condition more critical for slope stability than flood loading The paper demonstrates a Bayesian approach to incorporate survival of the construction phase in reliability estimates of dikes Reliability estimates of dikes on soft soil blankets can increase significantly when incorporating survival of the construction phase Safety assessments of dikes can improve significantly when construction survival is considered.
Improving dike reliability estimates by incorporating construction survival
van der Krogt, Mark G. (author) / Schweckendiek, Timo (author) / Kok, Matthijs (author)
Engineering Geology ; 280
2020-11-29
Article (Journal)
Electronic Resource
English
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