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Anil K. Chopra - One of the best experts on this subject based on the ideXlab platform.

  • earthquake analysis of Arch Dams factors to be considered
    Journal of Structural Engineering-asce, 2012
    Co-Authors: Anil K. Chopra
    Abstract:

    The factors that significantly influence the three-dimensional analysis of Arch Dams are identified: the semiunbounded size of the reservoir and foundation-rock domains, dam-water interaction, wave absorption at the reservoir boundary, water compressibility, dam–foundation rock interaction, and spatial variations in ground motion at the dam-rock interface. Through a series of example analyses of actual Dams, it is demonstrated that (1) by neglecting water compressibility, the stresses may be significantly underestimated for some Dams or overestimated for others; (2) by neglecting foundation-rock mass and damping, the stresses may be overestimated by a factor of 2 to 3; and (3) spatial variations in ground motion, typically ignored in dam engineering practice, can have profound influence on the earthquake-induced stresses in the dam. This influence obviously depends on the degree to which ground motion varies spatially along the dam-rock interface. For the same dam, this influence would differ from one ear...

  • linear analysis of concrete Arch Dams including dam water foundation rock interaction considering spatially varying ground motions
    Earthquake Engineering & Structural Dynamics, 2010
    Co-Authors: Jin-ting Wang, Anil K. Chopra
    Abstract:

    The available substructure method and computer program for earthquake response analysis of Arch Dams, including the effects of dam–water–foundation rock interaction and recognizing the semi-unbounded size of the foundation rock and fluid domains, are extended to consider spatial variations in ground motions around the canyon. The response of Mauvoisin Dam in Switzerland to spatially varying ground motion recorded during a small earthquake is analyzed to illustrate the results from this analysis procedure. Copyright © 2009 John Wiley & Sons, Ltd.

  • earthquake response of Arch Dams to spatially varying ground motion
    Earthquake Engineering & Structural Dynamics, 2009
    Co-Authors: Anil K. Chopra, Jin-ting Wang
    Abstract:

    The response of two Arch Dams to spatially varying ground motions recorded during earthquakes is computed by a recently developed linear analysis procedure, which includes dam-water-foundation rock interaction effects and recognizes the semi-unbounded extent of the rock and impounded water domains. By comparing the computed and recorded responses, several issues that arise in analysis of Arch Dams are investigated. It is also demonstrated that spatial variations in ground motion, typically ignored in engineering practice, can have profound influence on the earthquake-induced stresses in the dam. This influence obviously depends on the degree to which ground motion varies spatially along the dam-rock interface. Thus, for the same dam, this influence could differ from one earthquake to the next, depending on the epicenter location and the focal depth of the earthquake relative to the dam site.

  • earthquake analysis of Arch Dams including dam water foundation rock interaction
    Earthquake Engineering & Structural Dynamics, 1995
    Co-Authors: Hanchen Tan, Anil K. Chopra
    Abstract:

    The available substructure method and computer program for the earthquake response analysis of Arch Dams, including the effects of dam-water interaction, reservoir boundary absorption, and foundation rock flexibility, is extended to include the effects of dam-foundation rock interaction with inertia and damping of the foundation rock considered. Efficient techniques are developed for evaluating the foundation impedance terms, computationally the most demanding part of the procedure.

  • dam foundation rock interaction effects in frequency response functions of Arch Dams
    Earthquake Engineering & Structural Dynamics, 1995
    Co-Authors: Hanchen Tan, Anil K. Chopra
    Abstract:

    The linear response of a selected Arch dam to harmonic upstream, vertical or cross-stream ground motion is presented for a wide range of the important system parameters characterizing the properties of the dam, foundation rock, impounded water and reservoir boundary materials. Based on these frequency-response functions, the dam-foundation rock interaction effects in the dynamic response of Arch Dams are investigated.

S M Seyedpoor - One of the best experts on this subject based on the ideXlab platform.

  • Shape optimal design of materially nonlinear Arch Dams including dam-water-foundation rock interaction using an improved PSO algorithm
    Optimization and Engineering, 2012
    Co-Authors: S M Seyedpoor, J Salajegheh, Eysa Salajegheh
    Abstract:

    An efficient optimization procedure is proposed to find the optimal shape of Arch Dams including dam-water-foundation rock interaction subject to earthquake. The Arch dam is treated as a three-dimensional structure involving the material nonlinearity effects. For this purpose, the nonlinear behavior of the dam concrete is idealized as an elasto-plastic material using the Drucker-Prager model. In order to reduce the computational cost of optimization process, a wavelet back propagation (WBP) neural network is designed to approximate the dam response instead of directly evaluating it by a time-consuming finite element analysis (FEA). An improved particle swarm optimization (IPSO) is also presented. In test example, the computational merits of the proposed methodology for optimizing an existing Arch dam are demonstrated.

  • shape optimization of Arch Dams by metaheuristics and neural networks for frequency constraints
    Scientia Iranica, 2011
    Co-Authors: Saeed Gholizadeh, S M Seyedpoor
    Abstract:

    Abstract The main aim of this paper is to propose an efficient soft computing based methodology to achieve optimal shape design of Arch Dams subjected to natural frequency constraints. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as two popular metaheuristics are employed to perform optimization task. As in the present paper fluid–structure interaction is considered, computing the natural frequencies by Finite Element Analysis (FEA) during the optimization process is time consuming. In order to reduce the computational burden, Back Propagation (BP) and Radial Basis Function (RBF) neural networks are used to predict the Arch dam natural frequencies. The numerical results show that PSO incorporating BP provides the best results.

  • optimum design of Arch Dams for frequency limitations
    Iran University of Science & Technology, 2011
    Co-Authors: Saeed Gholizadeh, S M Seyedpoor
    Abstract:

    An efficient methodology is proposed to find optimal shape of Arch Dams on the basis of constrained natural frequencies. The optimization is carried out by virtual sub population (VSP) evolutionary algorithm employing real values of design variables. In order to reduce the computational cost of the optimization process, the Arch dam natural frequencies are predicted by properly trained back propagation (BP) and wavelet back propagation (WBP) neural networks. The WBP network provides better generalization compared with the standard BP network. The numerical results demonstrate the computational merits of the proposed methodology for optimum design of Arch Dams.

  • optimal design of Arch Dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms
    Applied Soft Computing, 2011
    Co-Authors: S M Seyedpoor, J Salajegheh, E Salajegheh, Shima Gholizadeh
    Abstract:

    An efficient optimization procedure is introduced to find the optimal shapes of Arch Dams considering fluid-structure interaction subject to earthquake loading. The optimization is performed by a combination of simultaneous perturbation stochastic approximation (SPSA) and particle swarm optimization (PSO) algorithms. This serial integration of the two single methods is termed as SPSA-PSO. The operation of SPSA-PSO includes three phases. In the first phase, a preliminary optimization is accomplished using the SPSA. In the second phase, an optimal initial swarm is produced using the first phase results. In the last phase, the PSO is employed to find the optimum design using the optimal initial swarm. The numerical results demonstrate the high performance of the proposed strategy for optimal design of Arch Dams. The solutions obtained by the SPSA-PSO are compared with those of SPSA and PSO. It is revealed that the SPSA-PSO converges to a superior solution compared to the SPSA and PSO having a lower computation cost.

  • shape optimal design of Arch Dams using an adaptive neuro fuzzy inference system and improved particle swarm optimization
    Applied Mathematical Modelling, 2010
    Co-Authors: D Hamidian, S M Seyedpoor
    Abstract:

    Abstract An efficient methodology is proposed to find the optimal shape of Arch Dams including fluid–structure interaction subject to earthquake ground motion. In order to reduce the computational cost of optimization process, an adaptive neuro-fuzzy inference system (ANFIS) is built to predict the dam effective response instead of directly evaluating it by a time-consuming finite element analysis (FEA). The presented ANFIS is compared with a widespread neural network termed back propagation neural network (BPNN) and it appears a better performance generality for estimating the dam response. The optimization task is implemented using an improved version of particle swarm optimization (PSO) named here as IPSO. In order to assess the effectiveness of the proposed methodology, the optimization of a real world Arch dam is performed via both IPSO–ANFIS and PSO–BPNN approaches. The numerical results demonstrate the computational advantages of the proposed IPSO–ANFIS for optimal design of Arch Dams when compared with the PSO–BPNN approach.

Jin-ting Wang - One of the best experts on this subject based on the ideXlab platform.

  • automatic modal parameter identification of high Arch Dams feasibility verification
    Earthquake Engineering and Engineering Vibration, 2020
    Co-Authors: Jianwen Pan, Guangheng Luo, Jin-ting Wang
    Abstract:

    Modal parameters, including fundamental frequencies, damping ratios, and mode shapes, could be used to evaluate the health condition of structures. Automatic modal parameter identification, which plays an essential role in realtime structural health monitoring, has become a popular topic in recent years. In this study, an automatic modal parameter identification procedure for high Arch Dams is proposed. The proposed procedure is implemented by combining the density-based spatial clustering of applications with noise (DBSCAN) algorithm and the stochastic subspace identification (SSI). The 210-m-high Dagangshan Dam is investigated as an example to verify the feasibility of the procedure. The results show that the DBSCAN algorithm is robust enough to interpret the stabilization diagram from SSI and may avoid outline modes. This leads to the proposed procedure obtaining a better performance than the partitioned clustering and hierArchical clustering algorithms. In addition, the errors of the identified frequencies of the Arch dam are within 4%, and the identified mode shapes are in agreement with those obtained from the finite element model, which implies that the proposed procedure is accurate enough to use in modal parameter identification. The procedure is feasible for online modal parameter identification and modal tracking of Arch Dams.

  • a spectrum based earthquake record truncation method for nonlinear dynamic analysis of Arch Dams
    Soil Dynamics and Earthquake Engineering, 2020
    Co-Authors: Aiyun Jin, Jianwen Pan, Jin-ting Wang
    Abstract:

    Abstract Due to the complexity of the model and the long duration of earthquake records, the nonlinear dynamic analysis of Arch Dams consumes a lot of calculation time. In this paper, an earthquake record truncation method based on the acceleration response spectrum (ARS) is proposed to save the calculation time of nonlinear dynamic analysis of Arch Dams. The nonlinear dynamic responses of the 210m-high Dagangshan dam of China are performed as a numerical example. Firstly, the statistical relationship between the Arias intensity (AI) and ARS is investigated using a large number of actual ground motion records. Secondly, the spectrum-based earthquake record truncation method is proposed. Finally, the accuracy of the proposed method is verified using the actual earthquake records, and the efficiency of the proposed method is compared with the AI-based method. Analysis results show that the proposed method, considering the structural characteristics of the Arch dam, can save more calculation time than the AI-based method, while ensuring a sufficiently accurate calculation result.

  • parametric analysis of ssi algorithm in modal identification of high Arch Dams
    Soil Dynamics and Earthquake Engineering, 2020
    Co-Authors: Jin-ting Wang, Aiyun Jin, Guangheng Luo
    Abstract:

    Abstract The covariance-driven stochastic subspace identification (SSI–COV) is widely used in the operational modal analysis of structures. However, the appropriate selection of user-defined parameters in the SSI–COV algorithm remains a challenging issue, especially for the modal tracking. This study aims to analyze the effect of the four user-defined parameters in SSI–COV for the modal identification of high Arch Dams. Two finite element (FE) models of the Dagangshan dam are investigated by the SSI–COV to identify the modal parameters. The FE model with the massless foundation is analyzed to investigate the effect of four user-defined parameters on the identification of dynamic properties, and the selection suggestions are proposed for each parameter. The FE model recognizing the semi-unbounded size of foundation rock is further analyzed to investigate the radiation damping effect based on the proposed suggestions of user-defined parameters. The results show that the radiation damping effect of the semi-unbounded foundation rock is approximately 0.6%–2.0% for the first four modes. Moreover, the modal parameters of the Xiluodu dam (285 m) are identified using ambient vibration test, which illustrates that the proposed suggestions for selecting user-defined parameters are effective and reasonable. This study is very beneficial for the modal tracking and structural health monitoring of Arch Dams in the future.

  • effect of foundation models on seismic response of Arch Dams
    Engineering Structures, 2019
    Co-Authors: Aiyun Jin, Jin-ting Wang, Jianwen Pan, Chong Zhang
    Abstract:

    Abstract Simulation of the infinite foundation is a key issue in the seismic response analysis of high Dams. This paper studies how the major characteristics of foundation models influence the nonlinear dynamic response of Arch Dams when the radiation damping effect is taken into account. The nonlinear dynamic responses of the 217 m high Yebatan Arch dam under construction in China is performed as a numerical example. Several key factors, including truncated size, material damping and non-uniformity of the foundation, are analyzed comprehensively. The results show that the material damping and the size of the foundation affect the dynamic response of the dam when the incident wave method is used. Neglect of the material damping of the foundation is proposed to solve this problem, and its rationality is verified. In addition, the results show that the realistic non-uniformity of the foundation should be considered in the earthquake response of Arch Dams.

  • nonlinear seismic response analysis of high Arch Dams to spatially varying ground motions
    International Journal of Civil Engineering, 2019
    Co-Authors: Jin-ting Wang, Feng Jin, Chuhan Zhang
    Abstract:

    The failure of a large dam can be catastrophic to human life and property downstream. Therefore, the seismic safety is of particular concern for high Dams in seismically active regions. This paper addresses the nonlinear seismic response analysis of high Arch Dams due to spatially-varying ground motions. Firstly, a comprehensive analysis model developed at Tsinghua University is presented, which takes into account radiation damping effect of semi-unbounded canyon, dynamic interaction of dam-water, opening of contraction joints, seismic damage cracking and strengthening of dam concrete, and nonlinearity of foundation rock. Subsequently, the seismic damage of Pacoima dam during the 1994 Northridge earthquake is qualitatively analyzed by the developed analysis model. The results agree with the actual damage observed after the earthquake. Most of the contraction joints opened and closed during the earthquake, and a larger residual opening occurred at the thrust block joint after the earthquake. The cracks continue from the bottom of the thrust block joint in three directions: diagonal, horizontal, and vertical. Finally, a large-scale numerical simulation of seismic ground motion from source rupture to dam canyon is introduced, which can simulate the characteristics of near-field ground motions at dam sites by considering the effect of source mechanism, propagation media, and local site.

E Salajegheh - One of the best experts on this subject based on the ideXlab platform.

  • optimal design of Arch Dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms
    Applied Soft Computing, 2011
    Co-Authors: S M Seyedpoor, J Salajegheh, E Salajegheh, Shima Gholizadeh
    Abstract:

    An efficient optimization procedure is introduced to find the optimal shapes of Arch Dams considering fluid-structure interaction subject to earthquake loading. The optimization is performed by a combination of simultaneous perturbation stochastic approximation (SPSA) and particle swarm optimization (PSO) algorithms. This serial integration of the two single methods is termed as SPSA-PSO. The operation of SPSA-PSO includes three phases. In the first phase, a preliminary optimization is accomplished using the SPSA. In the second phase, an optimal initial swarm is produced using the first phase results. In the last phase, the PSO is employed to find the optimum design using the optimal initial swarm. The numerical results demonstrate the high performance of the proposed strategy for optimal design of Arch Dams. The solutions obtained by the SPSA-PSO are compared with those of SPSA and PSO. It is revealed that the SPSA-PSO converges to a superior solution compared to the SPSA and PSO having a lower computation cost.

  • shape optimal design of Arch Dams including dam water foundation rock interaction using a grading strategy and approximation concepts
    Applied Mathematical Modelling, 2010
    Co-Authors: S M Seyedpoor, J Salajegheh, E Salajegheh
    Abstract:

    Abstract Optimal design of Arch Dams including dam-water–foundation rock interaction is achieved using the soft computing techniques. For this, linear dynamic behavior of Arch dam-water–foundation rock system subjected to earthquake ground motion is simulated using the finite element method at first and then, to reduce the computational cost of optimization process, a wavelet back propagation neural network (WBPNN) is designed to predict the Arch dam response instead of directly evaluating it by a time-consuming finite-element analysis (FEA). In order to enhance the performance generality of the neural network, a dam grading technique (DGT) is also introduced. To assess the computational efficiency of the proposed methodology for Arch dam optimization, an actual Arch dam is considered. The optimization is implemented via the simultaneous perturbation stochastic approximation (SPSA) algorithm for the various conditions of the interaction problem. Numerical results show the merits of the suggested techniques for Arch dam optimization. It is also found that considering the dam-water–foundation rock interaction has an important role for safely designing an Arch dam.

  • optimum shape design of Arch Dams for earthquake loading using a fuzzy inference system and wavelet neural networks
    Engineering Optimization, 2009
    Co-Authors: S M Seyedpoor, J Salajegheh, E Salajegheh, Shima Gholizadeh
    Abstract:

    An efficient methodology is proposed to find the optimum shape of Arch Dams considering fluid-structure interaction subject to earthquake loading. The earthquake load is considered by time variant ground acceleration applied in the upstream–downstream direction of the Arch dam. The optimization is carried out by particle swarm optimization, employing real values of design variables. To reduce the computational cost of the optimization process, two strategies are adopted. In the first strategy, the most influential design variables on Arch-dam response from original variables are selected using an adaptive neuro-fuzzy inference system. In the second, Arch-dam response is predicted by a properly trained wavelet radial basis function neural network employing the influential design variables as the inputs. In order to assess the effectiveness of the suggested methodology, a real Arch dam is considered as a test example. The numerical results demonstrate the computational advantages of the proposed methodology...

J Salajegheh - One of the best experts on this subject based on the ideXlab platform.

  • Shape optimal design of materially nonlinear Arch Dams including dam-water-foundation rock interaction using an improved PSO algorithm
    Optimization and Engineering, 2012
    Co-Authors: S M Seyedpoor, J Salajegheh, Eysa Salajegheh
    Abstract:

    An efficient optimization procedure is proposed to find the optimal shape of Arch Dams including dam-water-foundation rock interaction subject to earthquake. The Arch dam is treated as a three-dimensional structure involving the material nonlinearity effects. For this purpose, the nonlinear behavior of the dam concrete is idealized as an elasto-plastic material using the Drucker-Prager model. In order to reduce the computational cost of optimization process, a wavelet back propagation (WBP) neural network is designed to approximate the dam response instead of directly evaluating it by a time-consuming finite element analysis (FEA). An improved particle swarm optimization (IPSO) is also presented. In test example, the computational merits of the proposed methodology for optimizing an existing Arch dam are demonstrated.

  • optimal design of Arch Dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms
    Applied Soft Computing, 2011
    Co-Authors: S M Seyedpoor, J Salajegheh, E Salajegheh, Shima Gholizadeh
    Abstract:

    An efficient optimization procedure is introduced to find the optimal shapes of Arch Dams considering fluid-structure interaction subject to earthquake loading. The optimization is performed by a combination of simultaneous perturbation stochastic approximation (SPSA) and particle swarm optimization (PSO) algorithms. This serial integration of the two single methods is termed as SPSA-PSO. The operation of SPSA-PSO includes three phases. In the first phase, a preliminary optimization is accomplished using the SPSA. In the second phase, an optimal initial swarm is produced using the first phase results. In the last phase, the PSO is employed to find the optimum design using the optimal initial swarm. The numerical results demonstrate the high performance of the proposed strategy for optimal design of Arch Dams. The solutions obtained by the SPSA-PSO are compared with those of SPSA and PSO. It is revealed that the SPSA-PSO converges to a superior solution compared to the SPSA and PSO having a lower computation cost.

  • shape optimal design of Arch Dams including dam water foundation rock interaction using a grading strategy and approximation concepts
    Applied Mathematical Modelling, 2010
    Co-Authors: S M Seyedpoor, J Salajegheh, E Salajegheh
    Abstract:

    Abstract Optimal design of Arch Dams including dam-water–foundation rock interaction is achieved using the soft computing techniques. For this, linear dynamic behavior of Arch dam-water–foundation rock system subjected to earthquake ground motion is simulated using the finite element method at first and then, to reduce the computational cost of optimization process, a wavelet back propagation neural network (WBPNN) is designed to predict the Arch dam response instead of directly evaluating it by a time-consuming finite-element analysis (FEA). In order to enhance the performance generality of the neural network, a dam grading technique (DGT) is also introduced. To assess the computational efficiency of the proposed methodology for Arch dam optimization, an actual Arch dam is considered. The optimization is implemented via the simultaneous perturbation stochastic approximation (SPSA) algorithm for the various conditions of the interaction problem. Numerical results show the merits of the suggested techniques for Arch dam optimization. It is also found that considering the dam-water–foundation rock interaction has an important role for safely designing an Arch dam.

  • optimum shape design of Arch Dams for earthquake loading using a fuzzy inference system and wavelet neural networks
    Engineering Optimization, 2009
    Co-Authors: S M Seyedpoor, J Salajegheh, E Salajegheh, Shima Gholizadeh
    Abstract:

    An efficient methodology is proposed to find the optimum shape of Arch Dams considering fluid-structure interaction subject to earthquake loading. The earthquake load is considered by time variant ground acceleration applied in the upstream–downstream direction of the Arch dam. The optimization is carried out by particle swarm optimization, employing real values of design variables. To reduce the computational cost of the optimization process, two strategies are adopted. In the first strategy, the most influential design variables on Arch-dam response from original variables are selected using an adaptive neuro-fuzzy inference system. In the second, Arch-dam response is predicted by a properly trained wavelet radial basis function neural network employing the influential design variables as the inputs. In order to assess the effectiveness of the suggested methodology, a real Arch dam is considered as a test example. The numerical results demonstrate the computational advantages of the proposed methodology...

  • adaptive neuro fuzzy inference system for high speed computing in optimal shape design of Arch Dams subjected to earthquake loading
    Mechanics Based Design of Structures and Machines, 2009
    Co-Authors: S M Seyedpoor, J Salajegheh
    Abstract:

    An efficient methodology is proposed to find optimal shapes of Arch Dams, including fluid-structure interaction for earthquake loading. The optimization is implemented using a particle swarm optimization (PSO). In order to reduce the computational cost of the optimization process, an adaptive neuro-fuzzy inference system (ANFIS) is utilized to predict the Arch dam response instead of directly evaluating it by a time-consuming finite element analysis (FEA). The presented ANFIS is compared with a back-propagation neural network (BPNN) and appears to have better performance. Test example results demonstrate the computational advantages of the proposed method for the optimal design of Arch Dams when compared with those of obtained through FEA.