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.

General Solution for Mechanical and Thermal Stresses in a Functionally Graded Hollow Cylinder due to Nonaxisymmetric Steady-State Loads

Abstract: In this paper the general theoretical analysis of two-dimensional steady-state thermal stresses for a hollow thick cylinder made of functionally graded material is developed. The temperature distribution is assumed to be a function of radial and circumferential directions with general thermal and mechanical boundary conditions on the inside and outside surfaces. The material properties, except Poisson's ratio, are assumed to depend on the variable r and they are expressed as power functions of r The separation of variables and complex Fourier series are used to solve the heat conduction and Navier equations.

Constructing a Novel No-Equilibrium Chaotic System

Abstract: This paper introduces a new no-equilibrium chaotic system that is constructed by adding a tiny perturbation to a simple chaotic flow having a line equilibrium. The dynamics of the proposed system are investigated through Lyapunov exponents, bifurcation diagram, Poincare map and period-doubling route to chaos. A circuit realization is also represented. Moreover, two other new chaotic systems without equilibria are also proposed by applying the presented methodology.

Coexistence of hidden chaotic attractors in a novel no-equilibrium system

Abstract: Hidden attractors have received considerable interest in physics, mechanics and other dynamical areas recently. This paper introduces a novel autonomous system with hidden attractor. In particular, there exists no-equilibrium point in this system. Although the new system is simple with six terms, it exhibits complex behavior such as chaos and multistability. In addition, the offset boosting of a variable is achieved by adding a single controlled constant. Dynamical properties of the no-equilibrium system have been discovered by using nonlinear dynamical tools as well as an electronic implementation.

Synthesis and characterization of nano-hydroxyapatite rods/poly(l-lactide acid) composite scaffolds for bone tissue engineering

Abstract: The aims of this work were synthesis of rod shaped nano-hydroxyapatite (nHAP) and fabrication of novel nano-hydroxyapatite/poly( l -lactide acid) (nHAP/PLLA) composite scaffold. In the first step, the identification and morphology of chemically synthesized nHAP particles were determined by XRD, EDX, FTIR and SEM analyses. The rod shaped nHAP particles with an average size of approximately 37–65 nm in width and 100–400 nm in length were found similar to natural bone apatite in terms of chemical composition and structural morphology. In the second step, nHAP and micro sized HAP (mHAP) particles were used to fabricate HAP filled PLLA (HAP/PLLA) composites scaffolds using thermally induced phase separation method. The porosity of scaffolds was up to 85.06% and their average macropore diameter was in the range of 64–175 μm. FTIR and XRD analyses showed some molecular interactions and chemical linkages between HAP particles and PLLA matrix. The compressive strength of nanocomposite scaffolds could high up to 14.9 MPa while those of pure PLLA and microcomposite scaffolds were 1.79 and 13.68 MPa, respectively. The cell affinity and biocompatibility of the nanocomposite scaffold were found to be higher than those of pure PLLA and microcomposite scaffolds. Following the results, the newly developed nHAP/PLLA composite scaffold is comparable with cancellous bone in terms of microstructure and mechanical strength, so it may be considered for bone tissue engineering applications.

Improved visibility graph fractality with application for the diagnosis of Autism Spectrum Disorder

Abstract: Recently, the visibility graph (VG) algorithm was proposed for mapping a time series to a graph to study complexity and fractality of the time series through investigation of the complexity of its graph. The visibility graph algorithm converts a fractal time series to a scale-free graph. VG has been used for the investigation of fractality in the dynamic behavior of both artificial and natural complex systems. However, robustness and performance of the power of scale-freeness of VG (PSVG) as an effective method for measuring fractality has not been investigated. Since noise is unavoidable in real life time series, the robustness of a fractality measure is of paramount importance. To improve the accuracy and robustness of PSVG to noise for measurement of fractality of time series in biological time-series, an improved PSVG is presented in this paper. The proposed method is evaluated using two examples: a synthetic benchmark time series and a complicated real life Electroencephalograms (EEG)-based diagnostic problem, that is distinguishing autistic children from non-autistic children. It is shown that the proposed improved PSVG is less sensitive to noise and therefore more robust compared with PSVG. Further, it is shown that using improved PSVG in the wavelet-chaos neural network model of Adeli and c-workers in place of the Katz fractality dimension results in a more accurate diagnosis of autism, a complicated neurological and psychiatric disorder.