Aliakbar Gholampour

Evaluation of peak and residual conditions of actively confined concrete using neuro-fuzzy and neural computing techniques

Abstract This paper investigates the ability of four artificial intelligence techniques, including artificial neural network (ANN), radial basis neural network (RBNN), adaptive neuro-fuzzy inference system (ANFIS) with grid partitioning, and ANFIS with fuzzy c-means clustering, to predict the peak and residual conditions of actively confined concrete. A large experimental test database that consists of 377 axial compression test results of actively confined concrete specimens was assembled from the published literature, and it was used to train, test, and validate the four models proposed in this paper using the mentioned artificial intelligence techniques. The results show that all of the neural network and ANFIS models fit well with the experimental results, and they outperform the conventional models. Among the artificial intelligence models investigated, RBNN model is found to be the most accurate to predict the peak and residual conditions of actively confined concrete. The predictions of each proposed model are subsequently used to study the interdependence of critical parameters and their influence on the behavior of actively confined concrete.

Finite-Element Modeling of Actively Confined Normal-Strength and High-Strength Concrete under Uniaxial, Biaxial, and Triaxial Compression

AbstractA concrete strength-sensitive finite element (FE) model applicable to concrete subjected to various confining pressure levels and conditions is presented. This paper focuses primarily on the failure surface and flow rule of concrete in multiaxial compression, which were experimentally observed to vary with the unconfined concrete strength and level of confining pressure. To this end, a large experimental database, which consists of more than 1,700 results of concrete specimens tested under biaxial and triaxial compression, was assembled through an extensive review of the literature. This database was augmented with another test database of concrete in uniaxial compression that consists of more than 4,000 test results. Based on the test database results, it was observed that the tangential slope of the failure surface reduces with an increase in the unconfined concrete strength and confining pressure. The concrete dilation angle considered in the flow rule was observed to be nonlinear throughout lo...

A New Unconditionally Stable Time Integration Method for Analysis of Nonlinear Structural Dynamics

A new time integration scheme is presented for solving the differential equation of motion with nonlinear stiffness. In this new implicit method, it is assumed that the acceleration varies quadratically within each time step. By increasing the order of acceleration, more terms of the Taylor series are used, which are expected to have responses with better accuracy than the classical methods. By considering this assumption and employing two parameters δ and α, a new family of unconditionally stable schemes is obtained. The order of accuracy, numerical dissipation, and numerical dispersion are used to measure the accuracy of the proposed method. Second order accuracy is achieved for all values of δ and α. The proposed method presents less dissipation at the lower modes in comparison with Newmarks average acceleration, Wilson-θ, and generalized-α methods. Moreover, this second order accurate method can control numerical damping in the higher modes. The numerical dispersion of the proposed method is compared with three unconditionally stable methods, namely, Newmarks average acceleration, Wilson-θ, and generalized-α methods. Furthermore, the overshooting effect of the proposed method is compared with these methods. By evaluating the computational time for analysis with similar time step duration, the proposed method is shown to be faster in comparison with the other methods.

Modeling the behavior of FRP-confined concrete using dynamic harmony search algorithm

The accurate prediction of ultimate conditions for fiber reinforced polymer (FRP)-confined concrete is essential for the reliable structural analysis and design of resulting structural members. Nonlinear mathematical models can be used for accurate calibration of strength and strain enhancement ratios of FRP-confined concrete. In this paper, a new procedure is proposed to calibrate the nonlinear mathematical functions, which involved the use of a dynamic harmony search (DHS) algorithm. The harmony memory is dynamically adjusted based on a novel pitch generation scheme using a dynamic bandwidth and random number with normal standard distribution in DHS. A new design-oriented confinement model is proposed based on three influential factors of FRP area ratio (

Mechanical and Durability Properties of Recycled Aggregate Concrete: Effect of Recycled Aggregate Properties and Content

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Application of Weight Functions in Nonlinear Analysis of Structural Dynamics Problems

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Short-Term Mechanical Properties of Concrete Containing Recycled Polypropylene Coarse Aggregates under Ambient and Elevated Temperature

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