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Showing 46 results for Earthquake

M. Shahrouzi,
Volume 1, Issue 1 (3-2011)
Abstract

Earthquake time history records are required to perform dynamic nonlinear analyses. In order to provide a suitable set of such records, they are scaled to match a target spectrum as introduced in the well-known design codes. Corresponding scaling factors are taken similar in practice however, optimizing them reduces extra-ordinary economic charge for the seismic design. In the present work a new hybrid meta-heuristic is developed combining key features from genotypic search and particle swarm optimization. The method is applied to an illustrative example via a parametric study to evaluate its effectiveness and less probability of premature convergence compared with the standard particle swarm optimization.
Y. Arfiadi, M.n.s. Hadi,
Volume 1, Issue 1 (3-2011)
Abstract

Tuned mass dampers (TMDs) systems are one of the vibration controlled devices used to reduce the response of buildings subject to lateral loadings such as wind and earthquake loadings. Although TMDs system has received much attention from researchers due to their simplicity, the optimization of properties and placement of TMDs is a challenging task. Most research studies consider optimization of TMDs properties. However, the placement of TMDs in a building is also important. This paper considers optimum placement as well as properties of TMDs. Genetic algorithms (GAs) is used to optimize the location and properties of TMDs. Because the location of TMDs at a particular floor of a building is a discrete number, it is represented by binary coded genetic algorithm (BCGA), whereas the properties of TMDS are best suited to be represented by using real coded genetic algorithm (RCGA). The combination of these optimization tools represents a hybrid coded genetic algorithm (HCGA) that optimizes discrete and real values of design variables in one arrangement. It is shown that the optimization tool presented in this paper is stable and has the ability to explore an unknown domain of interest of the design variables, especially in the case of real coding parts. The simulation of the optimized TMDs subject to earthquake ground accelerations shows that the present approaches are comparable and/or outperform the available methods.
M. Mashayekhi, M.j. Fadaee, J. Salajegheh , E. Salajegheh,
Volume 1, Issue 2 (6-2011)
Abstract

A two-stage optimization method is presented by employing the evolutionary structural optimization (ESO) and ant colony optimization (ACO), which is called ESO-ACO method. To implement ESO-ACO, size optimization is performed using ESO, first. Then, the outcomes of ESO are employed to enhance ACO. In optimization process, the weight of double layer grid is minimized under various constraints which artificial ground motion is used to calculate the structural responses. The presence or absence of elements in bottom and web grids and also cross-sectional areas are selected as design variables. The numerical results reveal the computational advantages and effectiveness of the proposed method.
A. Nozari , H.e. Estekanchi,
Volume 1, Issue 2 (6-2011)
Abstract

Numerical simulation of structural response is a challenging issue in earthquake engineering and there has been remarkable progress in this area in the last decade. Endurance Time (ET) method is a new response history based analysis procedure for seismic assessment and structural design in which structures are subjected to a gradually intensifying dynamic excitation and their seismic performance is evaluated based on their responses at different excitation levels. Generating appropriate artificial dynamic excitation is essential in this type of analysis. In this paper, an optimization procedure is presented for computation of the intensifying acceleration functions utilized in the ET method and the results of this procedure are discussed. A set of the ET acceleration functions (ETAFs) is considered which has been produced utilizing numerical optimization considering 2048 acceleration points as optimization variables by an unconstrained optimization procedure. The ET formulation is then modified from the continuous time condition into the discrete time state thus the optimization problem is reformulated as a nonlinear least squares problem. In this way, a second set of the ETAFs is generated which better satisfies the proposed objective function. Subsequently, acceleration points are increased to 4096, for 40 seconds duration, and the third set of the ETAFs is produced using a multi level optimization procedure. Improvement of the ETAFs is demonstrated by analyzing several SDOF systems.
R. Kamyab, E. Salajegheh,
Volume 1, Issue 3 (9-2011)
Abstract

This study deals with predicting nonlinear time history deflection of scallop domes subject to earthquake loading employing neural network technique. Scallop domes have alternate ridged and grooves that radiate from the centre. There are two main types of scallop domes, lattice and continuous, which the latticed type of scallop domes is considered in the present paper. Due to the large number of the structural nodes and elements of scallop domes, nonlinear time history analysis of such structures is time consuming. In this study to reduce the computational burden radial basis function (RBF) neural network is utilized. The type of inputs of neural network models seriously affects the computational performance and accuracy of the network. Two types of input vectors: cross-sectional properties and natural periods of the structures can be employed for neural network training. In this paper the most influential natural periods of the structure are determined by adaptive neuro-fuzzy inference system (ANFIS) and then are used as the input vector of the RBF network. Results of illustrative example demonstrate high performance and computational accuracy of RBF network.
F.r. Rofooei, A. Kaveh, F.m. Farahani,
Volume 1, Issue 3 (9-2011)
Abstract

Heavy economic losses and human casualties caused by destructive earthquakes around the world clearly show the need for a systematic approach for large scale damage detection of various types of existing structures. That could provide the proper means for the decision makers for any rehabilitation plans. The aim of this study is to present an innovative method for investigating the seismic vulnerability of the existing concrete structures with moment resisting frames (MRF). For this purpose, a number of 2-D structural models with varying number of bays and stories are designed based on the previous Iranian seismic design code, Standard 2800 (First Edition). The seismically–induced damages to these structural models are determined by performing extensive nonlinear dynamic analyses under a number of earthquake records. Using the IDARC program for dynamic analyses, the Park and Ang damage index is considered for damage evaluation of the structural models. A database is generated using the level of induced damages versus different parameters such as PGA, the ratio of number of stories to number of bays, the dynamic properties of the structures models such as natural frequencies and earthquakes. Finally, in order to estimate the vulnerability of any typical reinforced MRF concrete structures, a number of artificial neural networks are trained for estimation of the probable seismic damage index.
A. Bagheria, G. Ghodrati Amirib, M. Khorasanib , J. Haghdoust,
Volume 1, Issue 4 (12-2011)
Abstract

The main objective of this study is to present new method on the basis of genetic algorithms for attenuation relationship determination of horizontal peak ground acceleration and spectral acceleration. The proposed method employs the optimization capabilities of genetic algorithm to determine the coefficients of attenuation relationships of peak ground and spectral accelerations. This method has been applied to 361 Iranian earthquake records with magnitudes between 4.5 and 7.4 obtained from two seismic zones, namely Zagros and Alborz-Central Iran. The obtained results indicated that the proposed method can be characterized as a powerful tool for prediction horizontal peak ground and spectral accelerations.
J. Salajegheh, S. Khosravi,
Volume 1, Issue 4 (12-2011)
Abstract

A hybrid meta-heuristic optimization method is introduced to efficiently find the optimal shape of concrete gravity dams including dam-water-foundation rock interaction subjected to earthquake loading. The hybrid meta-heuristic optimization method is based on a hybrid of gravitational search algorithm (GSA) and particle swarm optimization (PSO), which is called GSA-PSO. The operation of GSA-PSO includes three phases. In the first phase, a preliminary optimization is accomplished using GSA as local search. In the second phase, an optimal initial swarm is produced using the optimum result of GSA. Finally, PSO is employed to find the optimum design using the optimal initial swarm. In order to reduce the computational cost of dam analysis subject to earthquake loading, weighted least squares support vector machine (WLS-SVM) is employed to accurately predict dynamic responses of gravity dams. Numerical results demonstrate the high performance of the hybrid meta-heuristic optimization for optimal shape design of concrete gravity dams. The solutions obtained by GSA-PSO are compared with those of GSA and PSO. It is revealed that GSA-PSO converges to a superior solution compared to GSA and PSO, and has a lower computation cost.
S. Gholizadeh, M.r. Sheidaii , S. Farajzadeh,
Volume 2, Issue 1 (3-2012)
Abstract

The main contribution of the present paper is to train efficient neural networks for seismic design of double layer grids subject to multiple-earthquake loading. As the seismic analysis and design of such large scale structures require high computational efforts, employing neural network techniques substantially decreases the computational burden. Square-on-square double layer grids with the variable length of span and height are considered. Back-propagation (BP), radial basis function (RBF) and generalized regression (GR) neural networks are trained for efficiently prediction of the seismic design of the structures. The numerical results demonstrate the superiority of the GR over the BP and RBF neural networks.
A. Farshidianfar, S. Soheili,
Volume 2, Issue 2 (6-2012)
Abstract

This paper investigates the optimized parameters for the tuned liquid column dampers to decrease the earthquake vibrations of high-rise buildings. Considering soil effects, the soilstructure interaction (SSI) is involved in this model. The Tuned Liquid Column Damper (TLCD) is also utilized on the roof of the building. Since the TLCD is a nonlinear device, the time domain analysis based on nonlinear Newmark method is employed to obtain the displacement, velocity and acceleration of different stories and TLCD. To illustrate the results, Kobe earthquake data is applied to the model. In order to obtain the best settings for TLCD, different parameters of TLCD are examined with constant mass quantity. The effective length, head loss coefficient, cross sectional ratio and length ratio of TLCD are assumed as the design variables. The objective is to reduce the maximum absolute and Root Mean Square (RMS) values of displacement and acceleration during earthquake vibration. The results show that the TLCDs are very effective and beneficial devices for decreasing the oscillations of high-rise buildings. It is indicated that the soil type highly affects the suitable parameters of TLCD subjected to the earthquake oscillations. This study helps the researchers to the better understanding of earthquake vibration of the structures including soil effects, and leads the designers to achieve the optimized TLCD for the high-rise buildings.
S. Gharehbaghi, M. J. Fadaee,
Volume 2, Issue 4 (10-2012)
Abstract

This paper deals with the optimization of reinforced concrete (RC) structures under earthquake loads by introducing a simple methodology. One of the most important problems in the design of RC structures is the existing of various design scenarios that all of them satisfy design constraints. Despite of the steel structures, a large number of design candidates due to a large number of design variables can be utilized. Doubtless, the economical and practical aspects are two effective parameters on accepting a design candidate. As such, in this paper the conventional design process that uses a trial and error process is replaced with an automated process using optimization technique. Also, the cost of construction is selected as an objective function in the automated process. A real valued model of particle swarm optimization (PSO) algorithm is utilized to perform the optimization process. Design constraints conform to the ACI318-08 code and standard 2800-code recommendations. Three ground motion records modified based on Iranian Design Spectrum is considered as earthquake excitations. Moreover, to reveal the effectiveness and robustness of the presented methodology, for example, a three-bay eighteen-story RC frame is optimized against the combination of gravity and earthquake loads. The entire process is summarized in a computer programming using a link between MATLAB platform and OpenSEES as open source object-oriented software.
S. Gholizadeh, P. Torkzadeh, S. Jabarzadeh,
Volume 3, Issue 1 (3-2013)
Abstract

In this paper, a methodology is presented for optimum shape design of double-layer grids subject to gravity and earthquake loadings. The design variables are the number of divisions in two directions, the height between two layers and the cross-sectional areas of the structural elements. The objective function is the weight of the structure and the design constraints are some limitations on stress and slenderness of the elements besides the vertical displacements of the joints. To achieve the optimization task a variant of particle swarm optimization (PSO) entitled as quantum-behaved particle swarm optimization (QPSO) algorithm is employed. The computational burden of the optimization process due to performing time history analysis is very high. In order to decrease the optimization time, the radial basis function (RBF) neural networks are employed to predict the desired responses of the structures during the optimization process. The numerical results demonstrate the effectiveness of the presented methodology
G. Ghodrati Amiri, P. Namiranian,
Volume 3, Issue 1 (3-2013)
Abstract

The main objective of this paper is to use ant optimized neural networks to generate artificial earthquake records. In this regard, training accelerograms selected according to the site geology of recorder station and Wavelet Packet Transform (WPT) used to decompose these records. Then Artificial Neural Networks (ANN) optimized with Ant Colony Optimization and resilient Backpropagation algorithm and learn to relate the dimension reduced response spectrum of records to their wavelet packet coefficients. Trained ANNs are capable to produce wavelet packet coefficients for a specified spectrum, so by using inverse WPT artificial accelerograms obtained. By using these tools, the learning time of ANNs reduced salient and generated accelerograms had more spectrum-compatibility and save their essence as earthquake accelerograms.
M. Mohebbi,
Volume 3, Issue 2 (6-2013)
Abstract

Tuned mass damper (TMD) have been studied and installed in structures extensively to protect the structures against lateral loads. Multiple tuned mass dampers (MTMDs) which include a number of TMDs with different parameters have been proposed for improving the performance of single TMDs. When the structural system is considered as multiple degrees of freedom (MDOF) and implemented with MTMDs, there is no effective closed-form solution to determine the optimal parameters of MTMDs. On the other hand designing optimal MTMDs include a large number of variables. For optimal design of MTMDs, in this research an effective method has been proposed in which the parameters of TMDs are determined based on minimizing the Hankel’s norm of structure. Since the optimization procedure includes a large number of variables, hence it has been decided to use Genetic Algorithms (GAs) for determining the variables. For numerical simulation, the method has been utilized on an eight-storey shear frame modeled as MDOF, and optimal MTMDs have been designed. The results show that using the Hankel’s norm of structure as objective function has led to design effective MTMDs which could be effective in reducing the response of structure, especially the average value, under different far-field and near-field earthquakes. Also it has been found that the method is effective regarding its simplicity and convergence in solving complex optimization problem. Through extensive numerical analysis the effect of MTMDs mass ratio and TMDs number in MTMDs has been studied.
A. Farshidianfar, S. Soheili,
Volume 3, Issue 3 (9-2013)
Abstract

This paper investigates the optimized parameters of Tuned Mass Dampers (TMDs) for high-rise structures considering Soil Structure Interaction (SSI) effects. Three optimization methods, namely the ant colony optimization (ACO) technique together with artificial bee colony (ABC) and shuffled complex evolution (SCE) methods are utilized for the optimization of TMD Mass, damping coefficient and spring stiffness as the design variables. The objective is to decrease the maximum displacement of structure. The 40 story structure with three soil types is employed to design TMD for six types of far field earthquakes. The results are then utilized to obtain relations for the optimized TMD parameters with SSI effects. The relations are then applied to design TMD for the same structure with another five types of far field oscillations, and reasonable results are achieved. For further investigations, the obtained relations are utilized to design TMD for a new structure, and the reduction values are obtained for five types of earthquakes, which show acceptable results. This study improves the understanding of earthquake oscillations, and helps the designers to achieve the optimized TMD for high-rise buildings.
G. Ghodrati Amiri, K. Iraji , P. Namiranian,
Volume 4, Issue 1 (3-2014)
Abstract

The Hartley transform, a real-valued alternative to the complex Fourier transform, is presented as an efficient tool for the analysis and simulation of earthquake accelerograms. This paper is introduced a novel method based on discrete Hartley transform (DHT) and radial basis function (RBF) neural network for generation of artificial earthquake accelerograms from specific target spectrums. Acceleration time histories of horizontal earthquake ground motion are obtained by the capability of learning of RBF neural network to expand the knowledge of the inverse mapping from the response spectrum to earthquake accelerogram. In the first step, Hartley transform is used to decompose earthquake accelerograms, then a RBF neural network is trained to learn to relate the response spectrum to Hartley spectrum. Finally, the generated accelerogram using inverse discrete Hartley transform is obtained from target spectrum. Approximately 200 uniformly scaled horizontal ground motion records from recent Iran’s earthquakes are used to decompose with real Hartley transform and train networks.
A. Gholizad , S. D. Ojaghzadeh Mohammadi,
Volume 4, Issue 1 (3-2014)
Abstract

Structural vibration control is one of the most important features in structural engineering. Real-time information about seismic resultant forces is required for deciding module of intelligent control systems. Evaluation of lateral forces during an earthquake is a complicated problem considering uncertainties of gravity loads amount and distribution and earthquake characteristics. An artificial neural network (ANN) has been trained in this article to estimate these forces. This ANN was trained on the results of time history analysis of a three-story building under 702 different loadings. Results of numerical examples verify that the trained ANN can predict the expected forces with negligible deviations.
M. Mohebbi, S. Moradpour , Y. Ghanbarpour,
Volume 4, Issue 1 (3-2014)
Abstract

In this research, optimal design and assessment of multiple tuned mass dampers (MTMDs) capability in mitigating the damage of nonlinear steel structures subjected to earthquake excitation has been studied. Optimal parameters of TMDs on nonlinear multi-degree-of-freedom (MDOF) structures have been determined based on minimizing the maximum relative displacement (drift) of structure where for solving the optimization problem the genetic algorithm (GA) has been used successfully. For numerical analysis, three and nine storey 2-D moment resisting nonlinear steel frames subjected to far-field and near-field earthquakes and optimal MTMDs has been designed for different values of mass ratio and TMDs number. According to the results of numerical simulations, it can be said that MTMDs mechanism could reduce the damage of nonlinear steel structures where the effectiveness increases by increasing TMDs mass ratio. Also the performance of MTMDs depends on earthquake characteristics, mass ratio and TMDs configuration where in this research the effective case has been locating TMDs on top floor in parallel configuration.
R. Kamyab , E. Salajegheh,
Volume 4, Issue 2 (6-2014)
Abstract

This paper presents an efficient meta-heuristic algorithm for optimization of double-layer scallop domes subjected to earthquake loading. The optimization is performed by a combination of harmony search (HS) and firefly algorithm (FA). This new algorithm is called harmony search firefly algorithm (HSFA). The optimization task is achieved by taking into account geometrical and material nonlinearities. Operation of HSFA includes three phases. In the first phase, a preliminary optimization is accomplished using HS. In the second phase, an optimal initial population is produced using the first phase results. In the last phase, FA is employed to find optimum design using the produced optimal initial population. The optimum design obtained by HSFA is compared with those of HS and FA. It is demonstrated that the HSFA converges to better solution compared to the other algorithms.
B. Mohebi, Gh. Ghodrati Amiri, M. Taheri,
Volume 4, Issue 4 (11-2014)
Abstract

This paper presents a suitable and quick way to choose earthquake records in non-linear dynamic analysis using optimization methods. In addition, these earthquake records are scaled. Therefore, structural responses of three different soil-frame models were examined, the change in maximum displacement of roof was analyzed and the damage index of whole structures was measured. The soil classification of project location was divided into 4 different types according to the velocity of shear waves in the Iranian Code for Seismic Design. As a result, 8 frame models were considered. The selection and scaling were carried out in 2 stages. In the first stage, the matching with design spectrum was carried out using genetic algorithm in order to achieve the mean of structural response. In the second stage, the matching with average of structural responses were carried out using PSO to achieve 1 or 3 accelerograms with related factors in order to be used in structural analysis.

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