• Smart Structures and Systems
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• 제26권3호
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• pp.319-329
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• 2020

Structural damage to an arch dam is often of major concern and must be evaluated for probable rehabilitation to ensure safe, regular, normal operation. This evaluation is crucial to prevent any catastrophic or failure consequences for the life time of the dam. If specific major damage such as a large crack occurs to the dam body, the assessments will be necessary to determine the current level of safety and predict the resistance of the structure to various future loading such as earthquakes, etc. This study investigates the behavior of an arch dam cracked due to water pressure. Safety factors (SFs), of shear and compressive tractions were calculated at the surfaces of the contraction joints and the cracks. The results indicated that for cracking with an extension depth of half the thickness of the dam body, for both cases of penetration and non-penetration of water load into the cracks, SFs only slightly reduces. However, in case of increasing the depth of crack extension into the entire thickness of the dam body, the friction angle of the cracked surface is crucial; however, if it reduces, the normal loading SFs of stresses and joints tractions reduce significantly.

• Smart Structures and Systems
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• 제32권5호
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Structural Monitoring and Maintenance
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• 제3권2호
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• pp.129-144
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• 2016

We present a methodology to validate with monitoring data finite element models of existing concrete dams: numerical analyses are performed to assess the structural response under the effects of seasonal loading conditions, represented by hydrostatic pressure on the upstream-downstream dam surfaces and thermal variations as recorded by a thermometers network. We show that the stiffness effect of the rock foundation and the surface degradation of concrete due to aging are crucial aspects to be accounted for a correct interpretation of the real behavior. This work summarizes some general procedures developed by this research group at Politecnico di Milano on traditional static monitoring systems and two significant case studies: a buttress gravity and an arch-gravity dam.

• Computers and Concrete
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• 제15권1호
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• pp.103-126
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• 2015

Thermal effects are significant loads for assessing concrete dam behaviour during operation. A new methodology to estimate thermal loads on concrete dams taking into account processes which were previously unconsidered, such as: the evaporative cooling, the night radiating cooling or the shades, has been recently reported. The application of this novel approach in combination with a three-dimensional finite element method to solve the heat diffusion equation led to a precise characterization of the thermal field inside the dam. However, that approach may be computationally expensive. This paper proposes the use of a new one-dimensional model based on an explicit finite difference scheme which is improved by means of the reported methodology for computing the heat fluxes through the dam faces. The improved model has been applied to a case study where observations from 21 concrete thermometers and data of climatic variables were available. The results are compared with those from: (a) the original one-dimensional finite difference model, (b) the Stucky-Derron classical one-dimensional analytical solution, and (c) a three-dimensional finite element method. The results of the improved model match well with the observed temperatures, in addition they are similar to those obtained with (c) except in the vicinity of the abutments, although this later is a considerably more complex methodology. The improved model have a better performance than the models (a) and (b), whose results present larger error and bias when compared with the recorded data.