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In this paper the piecewise level set method is combined with phase field method to solve the shape and topology optimization problem. First, the optimization problem is formed based on piecewise constant level set method then is updated using the energy term of phase field equations. The resulting diffusion equation which updates the level set function and optimization problem is solved through finite element method. The proposed method enhances the convergence rate and solution efficiency. Various two-dimensional examples are solved to verify the performance of proposed method.

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In this paper, optimal design of hybrid low damping base isolation and magnetorheological (MR) damper has been studied. Optimal hybrid base isolation system has been designed to minimize the maximum base drift of low damping base isolation system where for solving the optimization problem, genetic algorithm (GA) has been used. In design procedure the maximum acceleration of the structure has been limited, too. To determine the volatge of semi-active MR damper the H2/LQG and clipped-optimal control algorithm has been applied. For numerical simulations, a three-story frame equipped with the hybrid base isolation and MR damper subjected to the scaled El Centro excitation and optimal hybrid system has been designed. Results of numerical simulations have proven the effectiveness of the optimal hybrid control system in controlling the maximum base drift of isolated structure. Also comparing the performance of hybrid, low and high damping base isolation systems has shown that adding MR damper to low damping base isolation system has improved its performance so that the hybrid system has worked better th an high damping base isolation in reducing the maximum base drift. Testing optimal hybrid control system under different excitations has shown its efficiency.

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Structural  design  optimization  usually  deals  with  multiple  conflicting  objectives  to  obtain the minimum construction cost, minimum weight, and maximum safety of the final design. Therefore, finding the optimum design is hard and time-consuming for  such problems.  In this paper, we borrow the basic concept of multi-criterion decision-making and combine it with  Particle  Swarm  Optimization  (PSO)  to  develop  an  algorithm  for  accelerating convergence  toward  the  optimum  solution  in  structural  multi-objective  optimization scenarios.  The effectiveness of the proposed algorithm was illustrated in some benchmark reinforced concrete (RC) optimization problems. The main goal was to minimize the cost or weight of structures while satisfying all design requirements imposed by design codes.  The results confirm the ability of the proposed algorithm to efficiently find optimal solutions for structural optimization problems.

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Estimating mechanical properties of concrete before designing reinforced concrete structures is among the design requirements. Steel fibers have a considerable effect on the mechanical properties of reinforced concrete, particularly its tensile strength. So far, numerous studies have been done to estimate the relationship between tensile strength of steel fiber reinforced concrete (SFRC) and other SFRC characteristics using regression analyses. But, in order to determine appropriate relations according to these methods, we need to estimate the basic structure of relations. Genetic programming (GP) method has solved this problem. In this study, the results of 367 laboratory specimens collected from the literature are used to present some relations to predict the tensile strength of SFRC using GP. The proposed relations are more accurate than the relations which have been presented thus far.

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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 present study is concerned with the simultaneous optimization of the size of components and the arrangement of connections for performance-based seismic design of low-rise SPSWs. Design variables include the size of beams and columns, the thickness of the infill panels, the type of each beam-to-column connection and the type of each infill-to-boundary frame connection. The objective function is considered to be the sum of the material cost and rigid connection fabrication cost. For comparison purposes, the SPSW model is also optimized with regard to two fixed connection arrangements. To fulfill the optimization task a new hybrid optimization algorithm called CBO-Jaya is proposed. The performance of the proposed hybrid optimization algorithm is assessed by two benchmark optimization problems. The results of the application of the proposed algorithm to the benchmark problem indicate the efficiency, robustness, and the fast convergence of the proposed algorithm compared with other meta-heuristic algorithms. The achieved results for the SPSWs demonstrate that incorporating the optimal arrangement of beam-to-column and infill-to-boundary frame connections into the optimization procedure results in considerable reduction of the overall cost.

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Semi-active base isolation system has been proposed mainly to mitigate the base drift of isolated structures while in most cases, its application causes the maximum acceleration of superstructure to be increased. In this paper, designing optimal semi-active base isolation system composed of linear base isolation system with low damping and magneto-rheological (MR) damper has been studied for controlling superstructure acceleration and base drift separately and simultaneously. A multi-objective optimization problem has been defined for optimal design of semi-active base isolation system which considers a linear combination of maximum acceleration and base drift as objective function where Genetic algorithm (GA) has been used to solve the optimization problem. H₂/Linear Quadratic Gaussian (LQG) and clipped-optimal control algorithms have been used to determine the desired control force and the voltage of MR damper in each time step. For numerical simulation, a four-story base isolated shear frame has been considered and for different values of weighting parameter in objective function, optimal semi-active base isolation system has been designed under various design earthquakes. The results show that by using base isolation system and supplemental MR damper, the superstructure acceleration and base drift can be suppressed significantly. Also, it has been concluded that by selecting proper values for maximum acceleration and base drift related weighting parameters in objective function, it is possible to mitigate the maximum acceleration and base drift simultaneously. Furthermore, semi-active control system has worked successfully under testing earthquakes regarding design criteria.

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The present study sets out to integrate the performance-based seismic design approach with the connection topology optimization method. Performance-based connection topology optimization concept aims to simultaneously optimize the size of members and the type of connections with respect to the framework of performance-based seismic design. This new optimization concept is carried out for unbraced and X-braced steel frames in order to assess its efficiency. The cross-sectional area of components and the type of beam-to-column connections are regarded as design variables. The objective function is formulated in terms of the material costs and the cost of rigid connections. The nonlinear pushover analysis is adopted to acquire the response of the structure at various performance levels. In order to cope with the optimization problem, CBO algorithm is employed. The achieved results demonstrate that incorporating the optimal arrangement of beam-to-column connections into the optimum performance-based design procedure of either unbraced or X-braced steel frame could lead to a design that significantly reduces the overall cost of the structure and offers a predictable and reliable performance for the structure subjected to hazard levels.

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In this paper the factor of safety (FS) and critical line-segments slip surface obtained by the Alternating Variable Local Gradient (AVLG) optimization method was presented as a new topic in 2D. Results revealed that the percentage of reduction in the FS obtained by switching from a circular shape to line segments was higher with the AVLG method than other methods. The 2D-AVLG optimization method is a new topic for finding critical line-segments slip surface which has been addressed in this paper. In fact, the line-segments slip surface is a flexible slip surface. Examples proves the efficiency and precision of the 2D-AVLG method for obtaining the line-segments critical slip surface compared to the circular and circular-line slip surfaces.

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Reinforced concrete (RC) slabs exhibit complexities in their structural behavior under load due to the composite nature of the material and the multitude and variety of factors that affect such behavior. Current methods for determining the load-deflection behavior of reinforced concrete slabs are limited in scope and are mostly dependable on the results of experimental tests. In this study, an alternative approach using Artificial Neural Network (ANN) model is produced to predict the load-deflection behavior of a two-way RC slab. In the study, 30 sets of RC slab specimens of sizes 700mm x 600mm x 75mm were cast, cured for 28days using the sprinkling method of curing and tested for deflection experimentally by applying loads ranging from 10kN to 155kN at intervals of 5kN. ANN model was then developed using the neural network toolbox of ANN in MATLAB version R2015a using back propagation algorithm. About 54% of the RC specimens were used for the training of the network while 23% of the sets were used for validation leaving the remaining 23 % for testing the network. The experimental test results show that the higher the applied load on the slab, the higher the deflection. The result of the ANN model shows a good correlation between the experimental test and the predicted results with training, validation and test correlation coefficients of 0.99692, 0.98921 and 0.99611 respectively. It was also found that ANN model is quite efficient in determining the deflection of 2-way RC slab. The predicted accuracy of performance value for the load-deflection set falls at 96.67% of the experimental load-deflection with a 0.31% minimum error using the Microsoft spreadsheet model. As such the comprehensive spreadsheet tool created to incorporate the optimum neural network. The spreadsheet model uses the Microsoft version 2013 excel tool software and can be used by structural engineers for instantaneous access to the prediction if any aspect of a concrete slab behavior given minimal data to describe the slab and the loading condition.

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Cumulative absolute velocity (CAV), Arias intensity (AI), and characteristic intensity (CI) are measurable characteristics to show collapse potential of structures, evaluation of earth movement magnitude, and detection of structural failure in an earthquake. In this paper, parameters which describe three characteristics of ground motion have been investigated by using wavelet transforms (WT). In fact, in this paper, a series of twenty eight earthquake records (ER) are decomposed to a pre-defined certain levels by the use of WT. The high and low frequencies are separated. Since higher frequencies do not have any significant effect on the ER, then the low frequencies of ER have been used. For this purpose, each ER is decomposed into 5 levels. Then, for low frequencies of ER, the CAV, AI, and CI are calculated for each level and the results are compared with the values of CAV, AI, and CI which have been computed for the original ER. The results indicate that the value of error is less than 1 percent in the first and second level and this value is less than 10 percent for the third level. In addition, this value is more than 15 percent for the fourth and fifth levels. If the acceptable value for error is considered to be less than 10 percent, it is recommended to use the third level of decomposition for determining these parameters, since the value of error is low and also, the required time is reduced.

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The constitutive relationships presented for concrete modeling are often associated with unknown material constants. These constants are in fact the connectors of mathematical models to experimental results. Experimental determination of these constants is always associated with some difficulties. Their values are usually determined through trial and error procedure, with regard to experimental results. In this study, in order to determine the material constants of an elastic-damage-plastic model proposed for concrete, the results of 44 uniaxial compression and tension experiments collected from literature were used. These constants were determined by investigating the consistency of experimental and modeling results using a genetic algorithm optimization tool for all the samples; then, the precision of resulted constants were investigated by simulating cyclic and biaxial loading experiments. The simulation results were compared to those of the corresponding experimental data. The results observed in comparisons indicated the accuracy of obtained material constants in concrete modeling.

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Several researchers have proved that the constitutive models of concrete based on combination of continuum damage and plasticity theories are able to reproduce the major aspects of concrete behavior. A problem of such damage-plasticity models is associated with the material constants which are needed to be determined before using the model. These constants are in fact the connectors of constitutive models to the experimental results. Experimental determination of these constants is always associated with some problems, which restricts the applicability of such models despite their accuracy and capabilities. In the present paper, the values of material constants for a damage-plasticity model determined in part I of this work were used as a database. Genetic programming was employed to discover equations which directly relate the material constants to the concrete primary variables whose values could be simply inferred from the results of uniaxial tension and compressive tests. The simulations of uniaxial tension and compressive tests performed by using the constants extracted from the proposed equations, exhibited a reasonable level of precision.  The validity of suggested equations were also assessed via simulating experiments which were not involved in the procedure of equation discovery. The comparisons revealed the satisfactory accuracy of proposed equations.

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Structural damage detection is a field that has attracted a great interest in the scientific community in recent years. Most of these studies use dynamic analysis data of the beams as a diagnostic tool for damage. In this paper, a massless rotational spring was used to represent the cracked sections of beams and the natural frequencies and mode shape were obtained. For calculation of rotational spring stiffness equivalent of uncracked and cracked sections, finite element models and experimental test were used. The damage identification problem was addressed with two optimization techniques of different philosophers: ECBO, PSO and SQP methods. The objective functions used in the optimization process are based on the dynamic analysis data such as natural frequencies and mode shapes. This data was obtained by developing a software that performs the dynamic analysis of structures using the Finite Element Method (FEM). Comparison between the detected cracks using optimization method and real beam shows an acceptable agreement.

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For application of the plastic analysis and design methods the control of the plastic behaviour of the structures is an important requirement. In this study, the complementary strain energy of the residual forces is considered as an overall measure of the plastic performance of the structure. Shakedown theorem for the analysis of the plastic behaviour of the laterally loaded piles is developed and applied to single vertical long pile. Limit curves are presented for the shakedown load multipliers. The formulations of the problems lead to mathematical programming which are solved by the use of nonlinear algorithm.

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This study focuses on using an artificial neural network (ANN) based model for predicting the performance of high strength concrete (HSC) beams strengthened with surface mounted FRP laminates. Eight input parameters such as geometrical properties of the beam and mechanical properties of FRP laminates were considered for this study. Back propagation network with Lavenberg-Marquardt algorithm has been chosen for the proposed network, which has been implemented using the programming package MATLAB. In the present study, comparison has been made between the experimental results and those predicted through neural network modeling. The amount of MAPE and RMSE were predicted and were found to be acceptable range. The statistical indicators such as correlation co-efficient (r) and co-efficient of determination (R²) were also predicted to estimate the accuracy of results obtained through ANN modeling. The results predicted through ANN modeling exhibit good correlation with the experimental results.

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The main focus of this research has been to investigate the effectiveness of optimal single and multiple Tuned Mass Dampers (TMDs) under different ground motions as well as to develop a procedure for designing TMD and MTMDs to be effective under multiple records. To determine the parameters of TMD and MTMDs under multiple records various scenarios have been suggested and their efficiency has been assessed. For numerical simulations, a ten-story linear shear building frame subjected to 12 real earthquakes as well as a filtered white noise record and optimum parameters of TMDs and MTMDs have been determined by solving an optimization problem using genetic algorithm (GA). The results show that when designing optimal TMD and MTMD under a specific ground motion, using the optimization procedure leads to achieve the best performance while the characteristics of the design earthquake strongly affects the performance of TMDs. Furthermore, it has been found that TMDs and MTMDs designed using only one earthquake as the design record have not worked successfully under multiple ground motions. For determining the parameters of TMDs to be effective under multiple records it has been suggested to use the mean of optimal TMDs parameters obtained using each of the design records.

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One of the most important factors that affects construction costs of highways is the earthwork cost. On the other hand, the earthwork cost strongly depends on the design of vertical alignment or project line. In this study, at first, the problem of vertical alignment optimization was formulated. To this end, station, elevation and vertical curve length in case of each point of vertical intersection (PVI) were considered as decision variables. The objective function was considered as earthwork cost and constraints were assumed as the maximum and minimum grade of tangents, minimum elevation of compulsory points, and the minimum length of vertical curves. For solving this optimization problem, the Colliding Bodies Optimization (CBO) algorithm was employed and results were compared with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In order to evaluate the effectiveness of formulation and CBO algorithm, three different highways were designed with respect to three different terrains including level, rolling and mountainous. After designing the preliminary vertical alignment for each highway, the optimal vertical alignments were determined by different optimization algorithms. The results of this research show that the CBO algorithm is superior to GA and PSO. Percentage of optimality (saving in earthworks cost) by CBO algorithm for level, rolling and mountainous terrains was determined as 44.14, 21.42 and 22.54%, respectively.

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Hybrid control system composed of a base isolation system and a magneto-rheological damper so-called smart base isolation is one of effective semi-active control system in controlling the seismic response of structures. In this paper, a design method is proposed for designing the smart base isolation system in order to achieve an effective performance under multiple earthquakes. The base mass, the base stiffness and the weighting parameter of H₂/linear quadratic Gaussian control algorithm, which is used to determine the desired control force, have been considered as the design variables and different earthquake records have been considered as design earthquakes. First, the optimum values of these variables under each of the considered earthquakes have been determined by using the genetic algorithm and then, an optimum control system has been designed with multiple earthquakes-based design approach. The defined design objective is minimizing the peak base drift while the peak inter-story drift has been constrained. For numerical simulation, smart base isolation system is designed for controlling a four-story shear frame. The results show that when the control system designed for a specific earthquake is subjected to another earthquake, difference between the performance of this control system and the optimal case under that earthquake is considerable. Hence, the specific earthquake-based design approach is an inappropriate design procedure for smart base isolation. Also, it has been found that control system designed based on multiple earthquakes-based design approach shows effective performance in controlling the response of structure under a wide range of earthquakes.

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During the past two decades, some industries have been moving towards project-centered systems in many modern countries. Therefore, managing simultaneous projects with considering the limitations in resources, equipment and manpower is very crucial. In the real world, project-based organizations are always facing with two main important features. First, the construction projects are decentralized and their distances are long, and second, there are several construction projects undertaken at different time periods. Therefore, appropriate selection of projects with regard to the capabilities of the organization may lead with increasing an expected profitability. This paper investigates the multi-period decentralized multi construction-project and scheduling problem subject to resource constraints, optimal resource pool location, deterioration and batch ordering of nonrenewable resources altogether, for the first time in the literature. In order to describe the problem under consideration in this paper and obtaining the optimal solutions, a mixed integer linear programming model is developed. Finally, the impact of decision integration on the profit profile of an organization is comprehensively investigated by solving numerical examples and through developing some heuristic methods.