Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Experimental and Numerical Investigation of Metal Type and Thickness Effects on the Impact Resistance of Fiber Metal Laminates

Abstract: The impact response of fiber metal laminates (FMLs), has been investigated with experiments and numerical simulations, which is reported in this article. Low-velocity impacts were carried out to study the effects of metal type and thickness within FMLs. Glare5-3/2 laminates with two aluminum layer thicknesses and a similar FML containing magnesium sheets were impacted by drop weight tests. Also, a major part of this study was to accomplish a dynamic non-linear transient analysis to study the impact response of FMLs using the commercial finite element (FE) analysis code ABAQUS. By reviewing different approaches of modeling constituents of an FML, it is shown that the appropriate selection of elements hasmore significant role than failure criterion to predict acceptable results for this type of laminate and loading. The good agreement obtained between experimental and numerical results verifies the possibility of relatively simpler simulation by FE-analysis to predict overall response of FMLs under impact loading.

Rock strength estimation: a PSO-based BP approach

Abstract: Application of back-propagation (BP) artificial neural network (ANN) as an accurate, practical and quick tool in indirect estimation of uniaxial compressive strength (UCS) of rocks has recently been highlighted in the literature. This is mainly due to difficulty in direct determination of UCS in laboratory as preparing the core samples for this test is troublesome and time-consuming. However, ANN technique has some limitations such as getting trapped in local minima. These limitations can be minimized by combining the ANNs with robust optimization algorithms like particle swarm optimization (PSO). This paper gives insight into development of a hybrid PSO–BP predictive model of UCS. For this reason, dataset comprising the results of 228 laboratory tests including dry density, moisture content, P wave velocity, point load index test, slake durability index and UCS was prepared. These tests were conducted on 38 sandstone samples which were taken from two excavation sites in Malaysia. Findings showed that PSO–BP model performs well in predicting UCS. Nevertheless, to compare the prediction performance of the PSO–BP model, the UCS is predicted using ANN-based PSO and BP models. The correlation coefficient, R, values equal to 0.988 and 0.999 for training and testing datasets, respectively, suggest that the PSO–BP model outperforms the other predictive models.

Hot working behavior of 2205 austenite–ferrite duplex stainless steel characterized by constitutive equations and processing maps

Abstract: The hot deformation characteristics of the 2205 duplex stainless steel were analyzed using constitutive equations and processing maps. The hot compression tests were performed at temperature range of 950–1200 °C and strain rate of 0.001–1 s−1. Flow stress was modeled by the constitutive equation of hyperbolic sine function. However, the stress exponent and strain rate sensitivity were different at low and high deformation temperatures where austenite and ferrite are dominant, respectively. It was recognized that strain at the peak point of flow curve increases with the Zener–Hollomon parameter, Z, at low temperature deformation while at high temperature deformation it actually decreases with Z. The power dissipation map, instability map and processing map were developed for the typical strain of 0.3. It was realized that dynamic restoration mechanisms could efficiently hinder the occurrence of flow instability at low and medium strain rates. Otherwise, the increase in strain rate at low and high temperatures could increase the risk of flow instability.

Deriving preference order of open pit mines equipment through MADM methods: Application of modified VIKOR method

Abstract: In multiple attribute decision making (MADM) problem, a decision maker (DM) has to choose the best alternative that satisfies the evaluation criteria among a set of candidate solutions. It is generally hard to find an alternative that meets all the criteria simultaneously, so a good compromise solution is preferred. The VIKOR method was developed for multi-criteria optimization of complex systems. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. It introduces the multi-criteria ranking index based on the particular measure of ''closeness'' to the ''ideal'' solution. To deal with the uncertainty and vagueness from humans' subjective perception and experience in decision process, this paper presents an evaluation model based on deterministic data, fuzzy numbers, interval numbers and linguistic terms. Combination of analytic hierarchy process (AHP) and entropy method was applied for attribute weighting in this proposed MADM method. To demonstrate the potential of the methodology, the proposed method is used for surface mine equipment selection problems.