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An optimal semi-active Cuckoo- Fuzzy algorithm is developed to drive the hydraulic semi-active damper for effective control of the dynamic deformation of building structures under earthquake loadings, in this paper. Hydraulic semi-active dampers (MR dampers) are semi active control devices that are managed by sending external voltage supply. A new adaptive fuzzy logic controller (FLC) is introduced to manage MR damper intelligently. Furthermore, a novel evolutionary algorithm of cuckoo search (CS) was employed to optimize the placement and the number of MR dampers and sensors in the sense of minimum resultant vibration magnitude. Numerical efforts were accomplished to validate the efficiency of proposed FLC. In designer’s point of view, the proposed CS-FLC controller can find the optimal solutions during a reasonable number of iterations. Finally, The simulation results show that the developed semi‐active damper can significantly enhance the seismic performance of the buildings in terms of controlled story drift and roof displacement and acceleration. CS-FLC controller uses less input energy and could find the appropriate control force and attenuates the excessive responses in several buildings. The findings in this study will help engineers to design control systems for seismic risk mitigation and effectively facilitate the performance‐based seismic design.

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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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The use of supplementary cementing materials is gradually increasing due to technical, economical, and environmental benefits. Supplementary cementitious materials (SCM) are most commonly used in producing ready mixed concrete (RMC). A quantitative understanding of the efficiency of SCMs as a mineral admixture in concrete is essential for its effective utilisation. The performance and effective utilization of various SCMs can be possible to analyze, using the concept of the efficiency factor (k-value). This study describes the overview of various studies carried out on the efficiency factor of SCMs. Also, it is an effort directed towards a specific understanding of the efficiency of SCMs in concrete. Further it includes an overview of artificial neural network (ANN) for the prediction of the efficiency factor of SCMs in concrete. It is found that The model generated through ANN provided a tool to calculate efficiency factor (k) and capture the effects of different parameters such as, water-binder ratio; cement dosage; percentage replacement of SCMs; and curing age.

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Best Management Practices (BMPs) are implemented in a watershed to reduce the amount of non-point source pollutants transported to water bodies. However, an optimization algorithm is required to choose the efficient type, size, and location of BMPs for application in a watershed for improving the water quality. In this study, the Charged System Search, a well-known and powerful meta-heuristic optimization algorithm, as an optimization model and a semi-distributed hydrological model i.e. Soil and Water Assesment Tool (SWAT) were coupled to obtain cost-effective combination of different BMPs. To demonstrate the performance and applicability of the coupled model, it was utilized to Sofichai watershed upstream of the Alavian Reservoir in the northwestern part of Iran to compare four reduction levels of sediment, nitrate nitrogen and phosphate phosphorous loads at the watershed outlet.

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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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Construction industry has the highest ratio of fatality of workers in comparison with other industries. Construction safety has been always a matter of focus to control safety risks. This article presents a new flexible method of safety risk assessment by adding Hybrid Value Number (HVN) to the assessment equation. As a result of using this method, the results of assessment process will be more consistent with the project’s conditions, as well as being more trustful. It could provide a better perspective of safety risks for project managers. The most significant outcomes of this research are as follows: 1) the most influential factors which affect safety risks in building construction projects are "the proficiency and the experience of workers", "the complexity of construction technology" and "time limitation", 2) the biggest risk priority numbers belong to "Struck by falling objects" and "Falling to lower levels" hazards, 3)a necessary safety program must contain Personal Protective Equipment (PPE), safety measures and safety training, 4)Project managers can decrease 75% of total safety risks by investing less than 1.5% of construction budget on safety programs.

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This paper presents an improved multi-objective evolutionary algorithm (IMOEA) for the design of planar steel frames. By considering constraints as a new objective function, single objective optimization problems turned to multi objective optimization problems. To increase efficiency of IMOEA different Crossover and Mutation are employed. Also to avoid local optima dynamic interference of mutation and crossover are considered. Feasible particles called elites which are very helpful for better mutation and crossover considered as a tool to increase efficiency of proposed algorithm. The proposed evolutionary algorithm (IMOEA) is utilized to solve three well-known classical weight minimization problems of steel moment frames. In order to verify the suitability of the present method, the results of optimum design for planar steel frames are obtained by present study compared to other researches. Results indicate that, as far as the convergence, speed of the optimization process and quality of optimum design are concerned behavior, IMOEA is significantly superior to other meta-heuristic optimization algorithms with an acceptable global answer.

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Vulnerability assessment of structures encounter many uncertainties like seismic excitations intensity and response of structures. The most common approach adopted to deal with these uncertainties is vulnerability assessment through fragility functions. Fragility functions exhibit the probability of exceeding a state namely performance-level as a function of seismic intensity. A common approach is finding some response points of the fragility function and then fitting a typical probability distribution like lognormal through curve fitting estimation techniques. Maximum-likelihood approach is a fitting method to find the probability distribution parameters. Performing this approach for distributions like lognormal which is defined by just two parameters are straight forward while for more complicated distribution which are based on additional characterizing parameters is not feasible, since this approach is based on minimizing an error function through classic mathematical approaches like calculating partial derivations. An applicable modification is to add an efficient optimization approach to determine maximum-likelihood function. In this article, an optimization algorithm is proposed with maximum-likelihood-estimation and the results indicate the efficiency and feasibility of future developments in finding the most appropriate fragility function.

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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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This paper illustrates an optimization procedure of concrete beam-column joints subjected to shear that are strengthened with fiber reinforced polymer (FRP). For this aim, five different values have been considered for length, width and thickness of the FRP sheets which created 125 different models to strengthen of concrete beam-column joints. However, by using response surface methodology (RSM) in design expert software the number of these models is reduced to 20. Then, each of 20 models is simulated in ABAQUS finite element software and shear capacity is also determined. The relationship between different dimensions of the FRP sheets and shear capacity are specified by using RSM. Furthermore the optimum dimensions are determined by particle swarm optimization (PSO) algorithm.

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Lightweight concrete (LWC) is a kind of concrete that made of lightweight aggregates or gas bubbles. These aggregates could be natural or artificial, and expanded polystyrene (EPS) lightweight concrete is the most interesting lightweight concrete and has good mechanical properties. Bulk density of this kind of concrete is between 300-2000 kg/m³. In this paper flexural strength of EPS is modeled using four regression models, nine neural network models and four adaptive Network-based Fuzzy Interface System model (ANFIS). Among these models, ANFIS model with Bell-shaped membership function has the best results and can predict the flexural strength of EPS lightweight concrete more accurately.
 

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Despite widespread application of grillage structures in many engineering fields such as civil, architecture, mechanics, their analysis and design make them more complex than other type of skeletal structures. This intricacy becomes more laborious when the corresponding
analysis and design are based on plastic concepts.
In this paper, Finite Element Method is utilized to find the lower and the upper bounds solutions of rectangular planner grids and this method is compared with analogues Finite Difference Method to indicate the efficiency of proposed approach.
 

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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.

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Bridges constitute an expensive segment of construction projects; the optimization of their designs will affect their high cost. Segmental precast concrete bridges are one of the most commonly serviced bridges built for mid and long spans. Genetic algorithm is one of the most widely applied meta-heuristic algorithms due to its ability in optimizing cost. Next to providing cost optimization of these bridge types, the effects of each one of the main three selections, crossover and mutation operators are assessed, and the best operator is determined through the Taguchi experimental design. To validate the functionality of this algorithm, a bridge constructed in the city of Isfahan, Iran (completed in 2017) is optimized, a total of 13% reduction in cost and weight of its superstructure is evident. The efficiency of applying the Taguchi method in determining the type of operators of the genetic algorithm is proved.

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The present study addresses optimal design of reinforced concrete (RC) columns based on equivalent equations considering deformability regulations of ACI318-14 under axial force and uniaxial bending moment. This study contrary to common approaches working with trial and error approach in design, at first presents an exact solution for intensity of longitudinal reinforcement in column section by solving equivalent equation. Then, longitudinal and transverse reinforcement details are assessed regarding the previous step results and where achieving the lowest steel consumption design in the column is selected as the optimum. In addition to optimizing column cross-section dimension by implementing single-variable optimization methods, the effect of axial force, bending moment and concrete compressive strength variations on the column cross-section dimension, intensity of longitudinal reinforcement, construction costs and total weight of consumption steel have been investigated. The investigation on the validity of the proposed method was assessed and signified through comparison with the existed work in the literature. Finding an exact solution considering all regulations and constraints is the advantage of this method in determining optimized RC column.

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This research focuses on the effects of stiffeners and architectural opening on the steel shear wall topology optimization. To this aim, four relevant issues have been considered. The first issue is the optimality Pattern of the shear wall without stiffeners. The second is the Optimality Pattern of the shear wall with stiffeners in two directions. The third is the investigation on the topology optimization of the shear walls with fixed opening and the fourth is the multi-material topology optimization of the above issues. In the optimize process, the level set method based on the shape sensitivity and the finite element analysis for two-dimensional linear elastic problems has been used. The level set function implicitly indicated the boundaries of the design domain. Several numerical examples are used to demonstrate the optimal paths in the steel shear walls. The results show that optimal values have been changed by replacing stiffeners and creating openings in the wall, but the optimal topologies almost have a shape like a concentric bracing. Also, in the conventional shear walls (one material) the horizontal stiffeners have a significant effect on their performance.

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Partricular features of overpassing local optima and providing near-optimal soultion in practical time has led researchers to apply metaheuristics in several engineering problems. Optimal design of diagrids as one of the most efficient structural systems in tall buildings has been concerned here. Jaya algorithm as a recent paramter-less optimization method is employed to solve the problem using a set of available sections. Furthermore, passive congregation is embedded in Jaya without adding any extra control parameters. Applyig the method in a number of real-size structural examples including diagrids, exhibits performance improvement by the new hybrid algorithm with respect to Jaya.

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This study is devoted to discrete sizing optimization of truss structures employing an efficient discrete evolutionary meta-heuristic algorithm which uses the Newton gradient-based method as its updating scheme and it is named here as Newton Meta-heuristic Algorithm (NMA). In order to enable the NMA population-based meta-heuristic to effectively explore the discrete design space, a term containing the best solution found is added to the basic updating rule of the algorithm. The efficiency of the proposed NMA metaheuristic is illustrated by presenting five benchmark discrete truss optimization problems and comparing the results with literature. The numerical results demonstrate that the NMA is a robust and powerful meta-heuristic algorithm for dealing with the discrete sizing optimization problems of steel trusses.

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Due to the random nature of the variables affecting the analysis and design of structures, the reliability method is considered as one of the most important and widely used topics in structural engineering. Despite the simplicity of moment methods, the answer to problems with multiple design points (the point with the highest probability of failure) such as transmission line towers depends a lot on the starting point of the search; and it may converge to the local optima answer which is not desirable. Simulation methods also require a large number of evaluations of the limit state function and increase the volume and time of calculations. Also, the design point is not calculated in most of these methods. In this study, the reliability index of four transmission line towers was calculated with four metaheuristic algorithms in which the limit state function was defined based on the displacement of nodes and the results were compared with the results of Monte Carlo Simulation (MCS) method. For this purpose, the objective function was defined as the geometric distance between the point on the function of the boundary condition to the origin in the standard normal coordinate system and the constraint of the problem (the limit state function) based on the displacement of the nodes. Random variables in these problems consisting of the cross-sectional area of the members, the modulus of elasticity, and the nodal loads.

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The purpose of the present study is the damage detection in the thin plates in terms of the wide application of such structures in various branches of engineering such as structural, mechanical, aerospace, shipbuilding, etc. using gradient-based second-order numerical optimization techniques. The technique used for optimization in this study is the second-order Levenberg-Marquardt algorithm (SOLMA). Using the acceleration response in a number of structural nodes under dynamic excitation, identification of the location and extent of damage in the plate elements are obtained by the proposed algorithm over an iterative cycle and by updating the sensitivity matrix. The damage has been assumed in the form of decreased modulus of elasticity in linear mode. A numerical problem has been solved and presented in order to verify and compare the proposed damage detection method with other methods. Also several numerical problems have been solved and its results have been presented in order to evaluate different scenarios such as one or more damages, small or large damage extent, absence or presence of noise with different levels, number of measured responses (number of sensors), position of measured points and the dynamic analysis time of the damage detection problem with the proposed method. The results show the appropriate accuracy, efficiency and performance of the proposed damage detection method.