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Showing 4 results for Bakhshpoori

A. Kaveh, T. Bakhshpoori , E. Afshari,
Volume 1, Issue 4 (12-2011)

This paper is concerned with the economical comparison between two commonly used configurations for double layer grids and determining their optimum span-depth ratio. Two ranges of spans as small and big sizes with certain bays of equal length in two directions and various types of element grouping are considered for each type of square grids. In order to carry out a precise comparison between different systems, optimum design procedure based on the Cuckoo Search (CS) algorithm is developed. The CS is a meta-heuristic algorithm recently developed that is inspired by the behavior of some Cuckoo species in combination with the Lévy flight behavior of some birds and insects. The design algorithm obtains minimum weight grid through appropriate selection of tube sections available in AISC Load and Resistance Factor Design (LRFD). Strength constraints of AISC-LRFD specification and displacement constraints are imposed on grids. The comparison is aimed at finding the depth at which each of the different configurations shows its advantages. The results are graphically presented from which the optimum depth can easily be estimated for each type, while the influence of element grouping can also be realized at the same time.
A. Kaveh, T. Bakhshpoori, M. Ashoory,
Volume 2, Issue 1 (3-2012)

Different kinds of meta-heuristic algorithms have been recently utilized to overcome the complex nature of optimum design of structures. In this paper, an integrated optimization procedure with the objective of minimizing the self-weight of real size structures is simply performed interfacing SAP2000 and MATLAB® softwares in the form of parallel computing. The meta-heuristic algorithm chosen here is Cuckoo Search (CS) recently developed as a type of population based algorithm inspired by the behavior of some Cuckoo species in combination with the Lévy flight behavior. The CS algorithm performs suitable selection of sections from the American Institute of Steel Construction (AISC) wide-flange (W) shapes list. Strength constraints of the AISC load and resistance factor design specification, geometric limitations and displacement constraints are imposed on frames. Effective time-saving procedure using simple parallel computing, as well as utilizing reliable analysis and design tool are also some new features of the present study. The results show that the proposed method is effective in optimizing practical structures.
A. Kaveh, S. M. Hamze-Ziabari, T. Bakhshpoori,
Volume 8, Issue 1 (1-2018)

In the present study, two new hybrid approaches are proposed for predicting peak ground acceleration (PGA) parameter. The proposed approaches are based on the combinations of Adaptive Neuro-Fuzzy System (ANFIS) with Genetic Algorithm (GA), and with Particle Swarm Optimization (PSO). In these approaches, the PSO and GA algorithms are employed to enhance the accuracy of ANFIS model. To develop hybrid models, a comprehensive database from Pacific Earthquake Engineering Research Center (PEER) are used to train and test the proposed models. Earthquake magnitude, earthquake source to site distance, average shear-wave velocity, and faulting mechanisms are used as predictive parameters. The performances of developed hybrid models (PSO-ANFIS-PSO and GA-ANFIS-GA) are compared with the ANFIS model and also the most common soft computing approaches available in the literature. According to the obtained results, three developed models can be effectively used to predict the PGA parameter, but the comparison of models shows that the PSO-ANFIS–PSO model provides better results.

A. Kaveh, S. M. Hamze-Ziabari, T. Bakhshpoori,
Volume 8, Issue 2 (8-2018)

In the present study, the multivariate adaptive regression splines (MARS) technique is employed to estimate the drying shrinkage of concrete. To this purpose, a very big database (RILEM Data Bank) from different experimental studies is used. Several effective parameters such as the age of onset of shrinkage measurement, age at start of drying, the ratio of the volume of the sample on its drying surface, relative humidity, cement content, the ratio between water and cement contents, the ratio of sand on total aggregate, average compressive strength at 28 days, and modulus of elasticity at 28 days are included in the developing process of MARS model. The performance of MARS model is compared with several codes of practice including ACI, B3, CEB MC90-99, and GL2000. The results confirmed the superior capability of developed MARS model over existing design codes. Furthermore, the robustness of the developed model is also verified through sensitivity and parametric analyses.

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