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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.

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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.

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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.

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In this paper nonlinear analysis of structures are performed considering material and geometric nonlinearity using force method and energy concepts. For this purpose, the complementary energy of the structure is minimized using ant colony algorithms. Considering the energy term next to the weight of the structure, optimal design of structures is performed. The first part of this paper contains the formulation of the complementary energy of truss and frame structures for the purpose of linear analysis. In the second part material and geometric nonlinearity of structure is considered using Ramberg-Osgood relationships. In the last part optimal simultaneous analysis and design of structure is studied. In each part, the efficiency of the methods is illustrated by means simple examples.

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Estimation of collapse performance is primarily conducted through Collapse Fragility Curves (CFC’s). The EDP-based approach is the main scheme for attaining such curves and employs IDA. Obtaining CFC’s from IDA results is tremendously time consuming and computationally demanding. Introduction of more efficient methods of seismic analysis, can potentially improve this issue. The Endurance Time (ET) method is a straightforward method for dynamic analysis of structures subjected to multilevel excitation intensities. In this paper, collapse analysis using ET analysis results to obtain EDP-based CFC’s, has been explained and demonstrated by a model. For verification, the resulting CFC has been compared to that obtained by IDA.

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In this article optimal design of shear walls is performed under seismic loading. For practical aims, a database of special shear walls is created. Special shear walls are used for seismic design optimization employing the charged system search algorithm as an optimizer. Constraints consist of design and performance limitations. Nonlinear behavior of the shear wall is taken into account and performance based seismic design optimization is accomplished. Capacity curves of the optimal solution are determined and compared incorporates soil–structure interaction. Also an optimization based method is proposed for bilinear approximation of capacity curve. These are a new methodology for seismic RC shear wall optimum design.

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In the present paper, nonlinear behavior of mass concrete simulated by smeared crack model is combined with Endurance Time Analysis (ETA) method for studying seismic response of arch dams. ETA is a time-history based dynamic pushover procedure in which special predesigned intensifying acceleration functions are used for analysis and estimation of structural responses in various performance levels by just a single analysis. For this purpose 203m DEZ arch dam is selected as case study and the finite element model of dam-reservoir-foundation system is excited in various performance levels. It was found that ETA provides reasonable responses in comparison with Time-History Analysis (THA) at equivalent target time. In addition, ETAleads to acceptable estimation of crack profiles within dam body and can reduce the total time of analyses, meaningfully. Generally, it was concluded that ETA can be considered as an alternative of THA in nonlinear analysis of arch dams.

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This study deals with performance-based design optimization (PBDO) of steel moment frames employing four different metaheuristics consisting of genetic algorithm (GA), ant colony optimization (ACO), harmony search (HS), and particle swarm optimization (PSO). In order to evaluate the seismic capacity of the structures, nonlinear pushover analysis is conducted (PBDO). This method is an iterative process needed to meet code requirements. In the PBDO procedure, the metaheuristics minimize the structural weight subjected to performance constraints on inter-story drift ratios at various performance levels. Two numerical examples are presented demonstrating the superiority of the PSO to the GA, ACO and HS metaheuristic algorithms.

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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.

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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.

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The present paper tackles the optimization problem of double layer grids considering nonlinear behaviour. In this paper, an efficient optimization algorithm is proposed to achieve the optimization task based on the newly developed grey wolf algorithm (GWA) termed as sequential GWA (SGWA). In the framework of SGWA, a sequence of optimization processes is implemented in which the initial population of each process is selected from the neighboring region of the best design found in the previous optimization process. This procedure is repeated until a termination criterion is met. Two illustrative examples are presented and optimization is performed by GWA and SGWA and two other meta-heuristics. The numerical results indicate that the proposed SGWA utperforms the other algorithms in finding optimal design of nonlinear double layer grids.

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This study focuses on the shape optimization of concrete gravity dams considering dam–water–foundation interaction and nonlinear effects subject to earthquake. The concrete gravity dam is considered as a two–dimensional structure involving the geometry and material nonlinearity effects. For the description of the nonlinear behavior of concrete material under earthquake loads, the Drucker–Prager model based on the associated flow rule is adopted in this study. The optimum design of concrete gravity dams is achieved by the hybrid of an improved gravitational search algorithm (IGSA) and the orthogonal crossover (OC), called IGSA–OC. In order to reduce the computational cost of optimization process, the support vector machine approach is employed to approximate the dam response instead of directly evaluating it by a time–consuming finite element analysis. To demonstrate the nonlinear behavior of concrete material in the optimum design of concrete gravity dams, the shape optimization of a real dam is presented and compared with that of dam considering linear effect.

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In this paper, the effect of angle between predictor and corrector surfaces on the structural analysis is investigated. Two objective functions are formulated based on this angle and also the load factor. Optimizing these functions, and using the structural equilibrium path’s geometry, lead to two new constraints for the nonlinear solver. Besides, one more formula is achieved, which was previously found by other researchers, via a different mathematical process. Several benchmark structures, which have geometric nonlinear behavior, are analyzed with the proposed methods. The finite element method is utilized to analyze these problems. The abilities of suggested schemes are evaluated in tracing the complex equilibrium paths. Moreover, comparison study for the required number of increments and iterations is performed. Results reflect the robustness of the authors’ formulations.

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Critical Path Method (CPM) is one of the most popular techniques used by construction practitioners for construction project scheduling since the 1950s. Despite its popularity, CPM has a major shortcoming, as it is schedule based on two impractical acceptance that the project deadline is not bounded and that resources are unlimited. The analytical competency and computing capability of CPM thus need to be enhanced by applying some additional techniques like Time-Cost Trade-off (TCT) and Constraint Resource Scheduling (CRS) separately after the initial schedule is determined. Therefore, this paper is focusing on an effective method for considering simultaneously TCT and CRS using a nonlinear integer framework, taking help of Microsoft Project Software (MSP) and Microsoft Excel Solver. Through this method, first, a start delay technique is applied to the baseline schedule to level out the resource over allocation and then the project network diagram is modified according to the resource-leveled schedule. Secondly, a time-cost optimization is used over the resource-leveled schedule network diagram, using MS Excel solver to get the optimum duration associated with the minimum total cost of the project satisfying resource constraint. The proposed framework using overtime for activity expedition, and required less time to generate the final solution compare to the available methods considering TCT+CRS simultaneously.

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The paper is concerned with a methodology of optimal design of shells of minimum weight with strength, stability and strain constraints. Stress and strain state of the shell is determined by Galerkin method in the mixed finite element formulation within the geometrically nonlinear theory. The analysis of the effectiveness of different optimization algorithms to solve the set problem is given. The results of solving test problems are presented.

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By minimizing the total potential energy function and deploying the virtual work principle, a higher-order stiffness matrix is achieved. This new tangent stiffness matrix is used to solve the frame with geometric nonlinear behavior. Since authors’ formulation takes into account the higher-order terms of the strain vector, the convergence speed of the solution process will increase. In fact, both linear and nonlinear parts of the frame axial strains are included in the presented formulation. These higher-order terms affect the resulting unbalanced force and also frame tangent stiffness. Moreover, the finite element method, updated Lagrangian description, and arc length scheme are employed in this study. To check the efficiency of the proposed strategy, several numerical examples are solved. The findings indicate that the authors’ technique can accurately trace the structural equilibrium paths having the limit points.

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In this study, the complex behavior of steel encased reinforced concrete (SRC) composite beam–columns in biaxial bending is predicted by multilayer perceptron neural network. For this purpose, the previously proposed nonlinear analysis model, mixed beam-column formulation, is verified with biaxial bending test results. Then a large set of benchmark frames is provided and P-M_x-M_y triaxial interaction curve is obtained for them. The specifications of these frames and their analytical results are defined as inputs and targets of artificial neural network and a relatively accurate estimation model of the nonlinear behavior of these beam-columns is presented. In the end, the results of neural network are compared to some analytical examples of biaxial bending to determine the accuracy of the model.

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Design of blast resistant structures is an important subject in structural engineering, attracting the attention of governments, researchers, and engineers. Thus, given the benefits of optimization in engineering, development and assessment of optimization methods for optimum design of structures against blast is of great importance. In this research, multi-objective optimization of steel moment frames subjected to blast is investigated. The considered objectives are minimization of the structural weight and minimization of the maximum inter-story drifts. The minimization of weight is related to obtain low cost designs and the minimization of inter-story drifts is related to obtain higher performance designs. By proposing a design methodology, a framework is developed for solving numerical problems. The developed framework is constructed by combining explicit finite element analysis of the structure and the NSGA-II optimization algorithm. The applicability and efficiency of the proposed method is shown through two numerical examples.

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Endurance Time method is a time history dynamic analysis in which structures are subjected to increasing excitations. These excitations are known as endurance time excitation functions (ETEF). This study proposes a new method for generating ETEFs. In the proposed method, a new basis function for representing ETEFs is introduced. This type of ETEFs representation creates an intelligent space for this ETEFs simulating optimization problem. The proposed method is then applied in order to simulate new ETEFs. To investigate the efficiency of this proposed optimization space, newly generated ETEFs are compared with those simulated by conventional approaches. Results show an improvement in the accuracy of ETEFs as well as the reduction in the required computational time.

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In this paper, the bi-directional evolutionary structural optimization (BESO) method is used to find optimal layouts of 3D prestressed concrete beams. Considering the element sensitivity number as the design variable, the mathematical formulation of topology optimization is developed based on the ABAQUS finite element software package. The surface-to-surface contact with a small sliding between concrete and prestressing steels is assumed to accurately model the prestressing effects. The concrete constitutive model used is the concrete damaged plasticity (CDP) model in ABAQUS. The integration of the optimization algorithm and finite element analysis (FEA) tools is done by using the ABAQUS scripting interface. A pretensioned prestressed simply supported beam is modeled to show capabilities of the proposed method in finding optimal topologies of prestressed concrete beams. Many issues relating to topology optimization of prestressed concrete beams such as the effects of prestressing stress, geometrical discontinuities and height constraints on optimal designs and strut-and-tie models (STMs) are studied in the example. The results show that the proposed method can efficiently be used for layout optimization of prestressed concrete beams.