Abstract
Recently, probabilistic simulations became an inseparable part of risk analysis. Managers and stakeholders prefer to make their decision knowing the existing uncertainties in the system. Nonlinear dynamic analysis and design of infrastructures are affected by two main uncertainty sources, i.e., epistemic and aleatory. In the present paper, the epistemic uncertainty is addressed in the context of material randomness. An old ultra‐high arch dam is selected as a vehicle for numerical analyses. Four material properties are selected as random variables in the coupled dam‐reservoir‐foundation system, i.e., concrete elasticity, mass density, compressive (and tensile) strength, and the rock modulus of elasticity. The efficient Box‐Behnken experimental design is adopted to minimize the required simulations. A response surface metamodel is developed for the system based on different outputs, i.e., displacement and damage index. The polynomial‐based response surface model is subsequently validated with a large number of simulations based on Latin Hypercube sampling. Results confirm the high accuracy of proposed technique in material uncertainty quantification.
Highlights
With the recent advances in computational tools, the probabilistic numerical simulations became an important aspect in risk analysis and risk management
This ground motion is scaled to maximum design level (MDL) for the dam site Hariri-Ardebili and Kianoush [6]
Pilot dam is referred to the one with all the material properties at their mean value, Table 1
Summary
With the recent advances in computational tools, the probabilistic numerical simulations became an important aspect in risk analysis and risk management. Nowadays, decisionmaking is based on the uncertainties in the system and not a deterministic simulation. Nonlinear dynamic response of concrete dams can be affected by two main uncertainty sources: epistemic and aleatory [1]. Uncertainty in material characteristics (e.g., modulus of elasticity and strength) is the main source in this category. Both these uncertainties can be incorporated in the numerical simulations, which results in the uncertainty propagation though the model, Figure 1. A comprehensive state-of-the-art review on the fragility analysis of concrete dam can be found in [2]. Material uncertainties were studied in few cases [3,4,5]
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