فهرست مطالب

International Journal of Optimization in Civil Engineering
Volume:10 Issue: 2, Spring 2020

  • تاریخ انتشار: 1399/01/19
  • تعداد عناوین: 10
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  • B. Eftekhar, O. Rezaifar*, A. Kheyroddin Pages 181-200

    Among the different lateral force resisting systems, shear walls are of appropriate stiffness and hence are extensively employed in the design of high-rise structures. The architectural concerns regarding the safety of these structures have further widened the application of coupled shear walls. The present study investigated the optimal dimensional design of coupled shear walls based on the improved Big Bang-Big Crunch algorithm. This optimization method achieves unique solutions in a short period according to the defined objective function, design variables, and constraints. Moreover, the results of the present study indicated that the dimensions of the coupling beam in the shear wall significantly affect the wall behavior by maximizing its efficiency which implies on its practical application by considering the wall in the flexural model.

    Keywords: Optimization, Coupled shear wall, Big Bang-Big Crunch Algorithm, Design
  • D. Pourrostam, S. Y. Mousavi*, T. Bakhshpoori, K. Shabrang Pages 201-215

    In recent years, soft computing and artificial intelligence techniques such as artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have been effectively used in various civil engineering applications. This study aims to examine the potential of ANN and ANFIS for modeling the compressive strength of concrete containing expanded perlite powder (EPP). For doing this, a total of forty-five EPP incorporated concrete mixtures were produced and tested for compressive strength at different curing ages of 3, 7, 28, 42 and 90 days. Two different ANN models were developed and the suitable and stable ANN architecture for each model was considered by calculating various statistical parameters. For comparative purposes, two ANFIS models with different membership functions were also trained. According to the results, it can be concluded that the proposed ANN models relatively give a good degree of accuracy in predicting the compressive strength of concrete made with EPP, higher than that of observed from ANFIS models.

    Keywords: Concrete, Expanded Perlite Powder, Compressive Strength, Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System
  • S. G. Morkhade*, F. P. Kumthekar, C. B. Nayak Pages 217-229

    This paper presents a parametric study of steel I- beam with stepped flanges by using finite element analysis. Stepped flange beam is used in structures to decrease the negative bending moments near interior supports that causes failure due to buckling. Steps in the cross section can be achieved by adding cover plates to the beam flanges, changing the size of the hot rolled section, or changing the flange thickness and/or width for built-up section. The stress concentration with variation in stepped beam configuration such as doubly and singly stepped I-beams has been examined thoroughly. The loadings are limited to those having an inflection point of zero under point load at mid span. Beams with degree of symmetry, ρ of 0.2 are investigated for the present study. Unbraced length to height ratio of the beam to be analyzed is considered as 15. In addition, to check the effect of steps, stepped parameters α, β and γ are varied. The results shows that, a change of flange thickness is more significant than a change of flange width on the lateral torsional buckling capacity of a singly stepped beam.

    Keywords: Parametric Study, Stepped I-Beam, Stepped Parameters, Negative Bending Moment, Non Linear Buckling
  • A. Kaveh*, K. Biabani Hamedani, F. Barzinpour Pages 231-260

    Meta-heuristic algorithms are applied in optimization problems in a variety of fields, including engineering, economics, and computer science. In this paper, seven population-based meta-heuristic algorithms are employed for size and geometry optimization of truss structures. These algorithms consist of the Artificial Bee Colony algorithm, Cyclical Parthenogenesis Algorithm, Cuckoo Search algorithm, Teaching-Learning-Based Optimization algorithm, Vibrating Particles System algorithm, Water Evaporation Optimization, and a hybridized ABC-TLBO algorithm. The Taguchi method is employed to tune the parameters of the meta-heuristics. Optimization aims to minimize the weight of truss structures while satisfying some constraints on their natural frequencies. The capability and robustness of the algorithms is investigated through four well-known benchmark truss structure examples.

    Keywords: structural optimization, optimal design, meta-heuristic algorithms, truss structures, natural frequency, Taguchi method
  • H. Fattahi* Pages 261-275

    The evaluation of seismic slope performance during earthquakes is important, because the failure of slope (such as an earth dam, natural slope, or constructed earth embankment) can result in significant financial losses and human. It is important, therefore, to be able to forecast such displacements induced by earthquake. However, the traditional forecasting methods, such as empirical formulae, are inaccurate because most of them do not take into consideration all the relevant factors. In this paper, new intelligence method, namely relevance vector regression (RVR) optimized by dolphin echolocation (DE) and grey wolf optimizer (GWO) algorithms is introduced to forecast the earthquake induced displacements (EID) of slopes. The DE and GWO algorithms is combined with the RVR for determining the optimal value of its user-defined paramee RVR. The performances of the proposed predictive models were examined according to two performance indices, i.e., coefficient of determination (R2) and mean square error (MSE). The obtained results of this study indicated that the RVR-GWO model is a reliable method to forecast EID with a higher degree of accuracy (MSE= 0.0160 and R2= 0.9955).

    Keywords: Seismic Slope Performance, Relevance Vector Regression, Dolphin Echolocation Algorithm, Grey Wolf Optimizer Algorithm
  • M. Shahrouzi*, N. Khavaninzadeh, A. Jahanbakhsh Pages 277-294

    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.

    Keywords: Tall Building, Lateral Resisting System, Jaya, Passive Congregation, Sizing Optimization
  • E. Pouriyanezhad, H. Rahami*, S. M. Mirhosseini Pages 295-313

    In this paper, the discrete method of eigenvectors of covariance matrix has been used to weight minimization of steel frame structures. Eigenvectors of Covariance Matrix (ECM) algorithm is a robust and iterative method for solving optimization problems and is inspired by the CMA-ES method. Both of these methods use covariance matrix in the optimization process, but the covariance matrix calculation and new population generation in these two methods are completely different. At each stage of the ECM algorithm, successful distributions are identified and the covariance matrix of the successful distributions is formed. Subsequently, by the help of the principal component analysis (PCA), the scattering directions of these distributions will be achieved. The new population is generated by the combination of weighted directions that have a successful distribution and using random normal distribution. In the discrete ECM method, in case of succeeding in a certain number of cycles the step size is increased, otherwise the step size is reduced. In order to determine the efficiency of this method, three benchmark steel frames were optimized due to the resistance and displacement criteria specifications of the AISC-LRFD, and the results were compared to other optimization methods. Considerable outputs of this algorithm show that this method can handle the complex problems of optimizing discrete steel frames.

    Keywords: Frame Design Optimization, Discrete Optimization, Meta-Heuristic Algorithms, Eigenvectors Of Covariance Matrix
  • F. Rahmani, R. Kamgar*, R. Rahgozar Pages 315-331

    The purpose of this study is to evaluate the long-term vertical deformations of segmented pre-tensioned concrete bridges by a new approach. It provides a practical and reliable method for calculating the amount of long-term deformation based on creep and shrinkage in segmented prestress bridges. There are various relationships for estimating the creep and shrinkage of concrete. The analytical results of existing models can be very different, and the results are not reliable. In this paper, the different existing relationships are written in MATLAB software. After calculation, the values of the creep and shrinkage are stored. Then a sample bridge is simulated in the CSI-Bridge software, and different values of creep and shrinkage are allocated separately. Therefore, the data are analyzed, and its maximum deformation value is extracted at a critical span (Dv-max). Assigning different amount of creep and shrinkage to the model results in different values  of Dv-max. In the next step, all Dv-max values  resulting from the change in creep and shrinkage contents should be re-introduced to MATLAB code to perform the calculation of the failure curve, and extract the corresponding Dv-max values at 95% probability. In a new approach, fragility curves are used to obtain the corresponding creep and shrinkage values corresponding to the desired probability percentage. Thus, instead of simulating several models, only one model is simulated. The results of the analysis of a bridge sample in this study indicate acceptable accuracy of the proposed solution for the 95% probability.

    Keywords: Segmented Prestress Bridges, Creep, Shrinkage, Long-Term Deformation, Concrete
  • H. Abd El, Wahed Khalifa* Pages 333-344

    Quadratic programming (QP) is an optimization problem wherein one minimizes (or maximizes) a quadratic function of a finite number of decision variable subject to a finite number of linear inequality and/ or equality constraints. In this paper, a quadratic programming problem (FFQP) is considered in which all cost coefficients, constraints coefficients, and right hand side are characterized by L-R fuzzy numbers. The FFQP problem is converted into the fully fuzzy linear programming using the Taylor series and hence into a linear programming problem which may be solved by applying GAMS Software. Finally, an example is given to illustrate the practically and the efficiency of the method.

    Keywords: Fully Fuzzy Quadratic, L-R Fuzzy Numbers, Taylor Series, Fully Fuzzy Linear Programming, Ranking Function, Linear Programming, Fuzzy Optimal Solution
  • M. Sheikhi Azqandi*, M. Arjmand Pages 345-363

    This research presents a novel design approach to achieve an optimal structure established upon multiple objective functions by simultaneous utilization of the Enhanced Time Evolutionary Optimization method and Fuzzy Logic (FLETEO). For this purpose, at first, modeling of the structure design problem in this space is performed using fuzzy logic concepts. Thus, a new problem creates with functions and constraints regarding the design in fuzzy space as well as membership functions corresponded to every single of them. Then, the problem is solved by means of the Enhanced Time Evolutionary Optimization method (ETEO), eventually, based on the acquired results, the values of optimal design variables are obtained in the main problem. In the current paper, to validate the proposed approach and evaluate its performance, the optimal design of several standard structures has been carried out. Comparing the acquired results and previous ones is an indication of the high power of the proposed method in finding the best possible design with high convergence speed and deprived of contravening the constraints governing the problems.

    Keywords: Multi-Objective Optimization, Truss, Enhanced Time Evolutionary Optimization, Fuzzy Logic