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Abstract: System identification is an emerging field of structural engineering which plays a key role in structures of great importance such as concrete gravity dams. In this study, an artificial neural network (ANN) procedure is proposed for the identification of concrete gravity dams, in conjunction with a hybrid finite element–boundary element (FE–BE) analysis for the prediction of dynamic characteristics of an existing concrete gravity dam with an empty reservoir. First, a dam–reservoir interaction analysis is carried out by the hybrid FE–BE approach in the frequency domain. A two-dimensional (2D) FE model (FEM) is used for linear-elastic analysis of the gravity dam on a rigid foundation, while the unbounded reservoir with inviscid, compressible, and frictionless fluid is discretized by BEs. Various analyses are performed for different height to base width ratios of dams in terms of different wave reflection coefficient of the reservoir bottom. The use of ANNs is motivated by the approximate concepts inherent in system identification approaches, and the time-consuming repeated analyses required for dam–reservoir interacting systems. The conjugate gradient algorithm (CGA) and the Levenberg–Marquardt algorithm (LMA) are implemented for training the ANNs, using available data generated from the results of coupled dam–reservoir system analyses. The trained ANNs are then employed to compute the dynamic amplification of dam crest displacement and natural frequencies of existing concrete gravity dams through forced vibration tests. The results obtained by solving the present inverse problem are compared with existing FEM solutions to demonstrate the accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: The finite element method is a computationally intensive method. Effective use of the method requires setting up the computational framework in an appropriate manner, which typically requires expertise. The computational cost of generating the mesh may be much lower, comparable, or in some cases higher than the cost associated with the numeric solver of the partial differential equations, depending on the application and the specific numeric scheme at hand. The aim of this paper is to present a mesh generation approach using the application of self-organizing artificial neural networks through adaptive finite element computations. The problem domain is initially constructed using the self-organizing neural networks. This domain is used as the background mesh which forms the input for finite element analysis and from which adaptive parameters are calculated through adaptivity analysis. Subsequently, self-organizing neural network is used again to adjust the location of randomly selected mesh nodes as is the coordinates of all nodes within a certain neighborhood of the chosen node. The adjustment is a movement of the selected nodes toward a specific input point on the mesh. Thus, based on the results obtained from the adaptivity analysis, the movement of nodal points adjusts the element sizes in a way that the concentration of elements will occur in the regions of high stresses. The methods and experiments developed here are for two-dimensional triangular elements but seem naturally extendible to quadrilateral elements. [Copyright &y& Elsevier]

• A numerical solution using the XFEM and time integration by α-method are coupled to study the 2D dynamic fracture of dam-foundation-reservoir problem. • The proposed method can improve the computation efficiency and avoid numerical instability. • Obtained results show by increasing the value of α in time integration, the shock waves after crack growth are decreased. • The effect of dynamic term is small and only increases at crack propagation times, but cracking profile with dynamic term oscillates around the static path. Extended finite element method (XFEM) and time integration by α-method are coupled in the direct integration scheme to study the 2D dynamic fracture of concrete gravity dam-foundation-reservoir interaction. The advantages of XFEM for the strong displacement discontinuity description of a crack and α-method for the time integration in dynamic analysis to dissipate the shockwaves after crack growth are combined together. The proposed method can improve the computation efficiency and can avoid numerical instability to judge the crack propagation orientation of XFEM. Obtained results show by increasing the value of α in time integration, the shock waves after crack growth are decreased and the stability of numerical solution is increased. In addition the accuracy of the dynamic fracture simulation using the proposed method is investigated in comparison with other reported in the literature. To apply the interaction in finite element model, zero thickness six-nodal contact elements are used in which the dam, foundation and reservoir are formulated with Lagrangian approach. Also, to predict dynamic fracture behavior of a cracked dam, dynamic stress intensity factors (DSIFs) are used. The interaction integral (conservation integral) originally proposed to evaluate SIFs to incorporate dynamic effects is utilized to evaluate DSIFs. Effective parameters in problem-solving such as the contribution of each distinct term in the interaction integral, crack tip element, length of crack growth, integration radius, location of initial crack, angle of initial crack, internal damping ratio of the dam, and fracture energy based on proposed method are discussed. [ABSTRACT FROM AUTHOR]