• Structural Engineering and Mechanics
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• v.82 no.5
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• pp.667-678
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• 2022

Moment-resisting frames (MRFs) are among the most conventional steel structures for mid-rise buildings in many earthquake-prone cities. Here, a simplified performance-based methodology is proposed for the seismic collapse capacity assessment of these buildings. This method employs a novel multi-mode pushover analysis to determine the engineering demand parameters (EDPs) of the regular steel MRFs up to the collapse prevention (CP) performance level. The modal combination coefficients used in the proposed pushover analysis, are obtained from two metaheuristic optimization algorithms and a fitting procedure. The design variables for the optimization process are the inter-story drift ratio profiles resulting from the multi-mode pushover analyses, and the objective values are the outcomes of the incremental dynamic analysis (IDA). Here, the collapse capacity of the structures is assessed in three to five steps, using a modified IDA procedure. A series of regular mid-rise steel MRFs are selected and analyzed to calculate the modal combination coefficients and to validate the proposed approach. The new methodology is verified against the current existing approaches. This comparison shows that the suggested method more accurately evaluates the EDPs and the collapse capacity of the regular MRFs in a robust and easy to implement way.

• Steel and Composite Structures
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• v.50 no.3
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• pp.337-345
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• 2024

This research proposed a particle swarm optimization (PSO) based seismic retrofit design of moment frame structures using a steel frame assembly. Two full scale specimens of the steel frame assembly with different corner details were attached to one-story RC frames for seismic retrofit, and the lateral load resisting capacities of the retrofitted frames subjected to cyclic loads were compared with those of a bare RC frame. The open source software framework Opensees was used to develop an analytical model for validating the experimental results. The developed analytical model and the optimization scheme were applied to a case study structure for economic seismic retrofit design, and its seismic performance was assessed before and after the retrofit. The results show that the developed steel frame assembly was effective in increasing seismic load resisting capability of the structure, and the PSO algorithm could be applied as convenient optimization tool for seismic retrofit design of structures.

• Structural Engineering and Mechanics
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• v.45 no.2
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• pp.211-232
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• 2013

In this study a multi-objective optimization problem is solved. The objectives used here include simultaneous minimum construction cost in term of sections weight, minimum structural damage using a damage index, and minimum non-structural damage in term of inter-story drift under the applied ground motions. A high-speed and low-error neural network is trained and employed in the process of optimization to estimate the results of non-linear time history analysis. This approach can be utilized for all steel or concrete frame structures. In this study, the optimal design of a planar eccentric braced steel frame is performed with great detail, using the presented multi-objective algorithm with a discrete population and then a moment resisting frame is solved as a supplementary example.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.351-368
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• 2014

This study presents a hunting search based optimum design algorithm for engineering optimization problems. Hunting search algorithm is an optimum design method inspired by group hunting of animals such as wolves, lions, and dolphins. Each of these hunters employs hunting in a different way. However, they are common in that all of them search for a prey in a group. Hunters encircle the prey and the ring of siege is tightened gradually until it is caught. Hunting search algorithm is employed for the automation of optimum design process, during which the design variables are selected for the minimum objective function value controlled by the design restrictions. Three different examples, namely welded beam, cellular beam and moment resisting steel frame are selected as numerical design problems and solved for the optimum solution. Each example differs in the following ways: Unlike welded beam design problem having continuous design variables, steel frame and cellular beam design problems include discrete design variables. Moreover, while the cellular beam is designed under the provisions of BS 5960, LRFD-AISC (Load and Resistant Factor Design-American Institute of Steel Construction) is considered for the formulation of moment resisting steel frame. Levy Flights is adapted to the simple hunting search algorithm for better search. For comparison, same design examples are also solved by using some other well-known search methods in the literature. Results reveal that hunting search shows good performance in finding optimum solutions for each design problem.

• Journal of Korean Society of Steel Construction
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• v.18 no.3
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• pp.361-371
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• 2006

In recent years, to overcome drawbacks related to the aplicati on of classical structural optimization algorithms, various drift design methods based on factores of member displacement participation factors have been developed to size members if they satisfy stiffness criteria. In particular, a resizing algorithm based on dynamic displacement participation factors from the response spectrum analysis has been applied in the drift design of steel structures subjec ted to seismic lateral forces. In this aproach, active members are selected for displacement control based on the displacement participation fa ve members may be taken out and added to the active members for the drift control. The resizing algorithm can be practically and effectively applied to drift design of high-rise buildings however, the inelastic behavior o f the resizing algorithm has not ben evaluated yet. To develop the resizing algorithm considering the performance of nonlinearity as well a s elastic stifness, the evaluation model of resizing algorithm s is developed and aplied to the examples of moment-resisting steel frame, which is one of the simplest structural systems. The inelastic behavior of moment-resisting steel frame designed by the resizing algorithm is also discussed.

• Structural Engineering and Mechanics
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• v.43 no.1
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• pp.31-51
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• 2012

This paper presents a computational study that explores the design of rigid steel frames by considering construction related costs. More specifically, two different aspects are investigated in this study focusing on the effects of (a) reducing the number of labor intensive rigid connections within a frame of given geometric layout, and (b) reducing the number of different member section types used in the frame. A genetic algorithm based optimization framework searches design space for these objectives. Unlike some studies that express connection cost as a factor of the entire frame weight, here connections and their associated cost factors are explicitly represented at the member level to evaluate the cost of connections associated with each beam. In addition, because variety in member section types can drive up construction related costs, its effects are evaluated implicitly by generating curves that show the trade off between cost and different numbers of section types used within the frame. Our results show that designs in which all connections are considered to be rigid can be excessively conservative: rigid connections can often be eliminated without any appreciable increase in frame weight, resulting in a reduction in overall cost. Eliminating additional rigid connections leads to further reductions in cost, even as frame weight increases, up to a certain point. These complex relationships between overall cost, rigid connections, and member section types are presented for a representative five-story steel frame.

• Steel and Composite Structures
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• v.47 no.3
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• pp.339-353
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• 2023

The primary objective of the current study is to optimize and evaluate the seismic performance of steel momentresisting frame (MRF) structures considering soil-structure interaction (SSI) effects. The structural optimization is implemented in the context of performance-based design in accordance with FEMA-350 at different confidence levels from 50% to 90% by taking into account fixed- and flexible-base conditions using an efficient metaheuristic algorithm. Nonlinear response-history analysis (NRHA) is conducted to evaluate the seismic response of structures, and the beam-on-nonlinear Winkler foundation (BNWF) model is used to simulate the soil-foundation interaction under the MRFs. The seismic performance of optimally designed fixed- and flexible-base steel MRFs are compared in terms of overall damage index, seismic collapse safety, and interstory drift ratios at different performance levels. Two illustrative examples of 6- and 12-story steel MRFs are presented. The results show that the consideration of SSI in the optimization process of 6- and 12-story steel MRFs results in an increase of 1.0 to 9.0 % and 0.5 to 5.0 % in structural weight and a slight decrease in structural seismic safety at different confidence levels.

• Structural Engineering and Mechanics
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• v.90 no.2
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• pp.189-208
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• 2024

Artificial intelligence is one of the efficient methods that can be developed to simulate nonlinear behavior and predict the response of building structures. In this regard, an adaptive method based on optimization algorithms is used to train the TSK model of the fuzzy inference system to estimate the seismic behavior of building structures based on analytical data. The optimization algorithm is implemented to determine the parameters of the TSK model based on the minimization of prediction error for the training data set. The adaptive training is designed on the feedback of the results of previous time steps, in which three training cases of 2, 5, and 10 previous time steps were used. The training data is collected from the results of nonlinear time history analysis under 100 ground motion records with different seismic properties. Also, 10 records were used to test the inference system. The performance of the proposed inference system is evaluated on two 3 and 20-story models of nonlinear steel moment frame. The results show that the inference system of the TSK model by combining the optimization method is an efficient computational method for predicting the response of nonlinear structures. Meanwhile, the multi-vers optimization (MVO) algorithm is more accurate in determining the optimal parameters of the TSK model. Also, the accuracy of the results increases significantly with increasing the number of previous steps.

• Earthquakes and Structures
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• v.14 no.3
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• pp.215-227
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• 2018

Supplemental passive control devices are widely considered as an important tool to mitigate the dynamic response of a building under seismic excitation. Nevertheless, a systematic method for strategically placing dampers in the buildings is not prescribed in building codes and guidelines. Many deterministic and stochastic methods have been proposed by previous researchers to investigate the optimum distribution of the viscous dampers in the steel frames. However, the seismic performances of the retrofitted buildings that are under large earthquake intensity levels or near collapse state have not been evaluated by any seismic research. Recent years, an increasing number of studies utilize genetic algorithms (GA) to explore the complex engineering optimization problems. GA interfaced with nonlinear response history (NRH) analysis is considered as one of the most powerful and popular stochastic methods to deal with the nonlinear optimization problem of damper distribution. In this paper, the effectiveness and the efficiency of GA on optimizing damper distribution are first evaluated by strong ground motions associated with the collapse failure. A practical optimization framework using GA and NRH analysis is proposed for optimizing the distribution of the fluid viscous dampers within the moment resisting frames (MRF) regarding the improvements of large drifts under intensive seismic context. Both a 10-storey and a 20-storey building are involved to explore higher mode effect. A far-fault and a near-fault earthquake environment are also considered for the frames under different seismic intensity levels. To evaluate the improvements obtained from the GA optimization regarding the collapse performance of the buildings, Incremental Dynamic Analysis (IDA) is conducted and comparisons are made between the GA damper distribution and stiffness proportional damping distribution on the collapse probability of the retrofitted frames.

• Steel and Composite Structures
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• v.32 no.1
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• pp.67-77
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• 2019

Pushover analysis captures the behavior of a structure from fully elastic to collapse. In this analysis, the structure is subjected to increasing lateral load with constant gravity one. Neglecting the effects of the higher modes and the changes in the vibration characteristics during the nonlinear analysis are the main obstacles of the proposed lateral load patterns. To overcome these drawbacks, whereas some methods have been presented to achieve updated lateral load distribution, these methods are not precisely capable to predict the response of structures, precisely. In this study, a new method based on optimization procedure is developed to obtain a lateral load pattern for which the difference between the floor displacements of pushover and Nonlinear Dynamic Analyses (NDA) is minimal. For this purpose, an optimization problem is considered and the genetic algorithm is applied to calculate optimal lateral load pattern. Three special moment resisting steel frames with different dynamic characteristics are simulated and their optimal load patterns are derived. The floor displacements of these frames subjected to the proposed and conventional load patterns are acquired and the accuracy of them is evaluated via comparing with NDA responses. The outcomes reveal that the proposed lateral load distribution is more accurate than the previous ones.