Reliability assessment of large hydraulic structures with spatially distributed measurements

Abstract Hydraulic structures, such as ship locks and weirs, form an essential part of waterway networks. An efficient life-cycle management is necessary to manage these large concrete structures safely and economically. Inspections and material testing form an important part of this process, as they enable an improved assessment of the condition, materials and properties of the structure. Traditionally, the limited data from tests is used to estimate probability distributions of material parameters; characteristic values for the assessment are then obtained from these distributions. Spatial correlation between measurement locations or different material layers is typically neglected. In this contribution, the spatially variable material parameters are modelled with random fields. The available data from local measurements is used to update the distribution of the random fields using Bayesian analysis. For comparison, the approach of Eurocode 0 for obtaining characteristic values is also applied. The structural reliability is then calculated applying subset simulation. It is shown that the employed random field modelling approach provides a more detailed statement about the material parameters. The results of an application to a ship lock wall demonstrate that modelling the spatial variability of concrete properties can increase the reliability estimate of large hydraulic structures when measurement information is included.

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