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CONTENTS
Volume 5, Number 3, July 2020
 

Abstract
In order to evaluate the performance of three heuristic optimization algorithms, namely, simulated annealing (SA), genetic algorithm (GA) and particle swarm optimization (PSO) for optimal stacking sequence of laminated composite plates with respect to critical buckling load and non-dimensional natural frequencies, a multi-objective optimization procedure is developed using the weighted summation method. Classical lamination theory and first order shear deformation theory are employed for critical buckling load and natural frequency computations respectively. The analytical critical buckling load and finite element calculation schemes for natural frequencies are validated through the results obtained from literature. The comparative study takes into consideration solution and computational time parameters of the three algorithms in the statistical evaluation scheme. The results indicate that particle swarm optimization (PSO) considerably outperforms the remaining two methods for the special problem considered in the study.

Key Words
Benchmarking; Heuristic optimization algorithms; structural optimization; laminated composites; buckling load; fundamental frequencies

Address
Mustafa Akbulut: TUBITAK Marmara Research Center, Kocaeli 41400, Turkey
Abdulhamit Sarac: TUBITAK National Metrology Institute, Kocaeli 41400, Turkey
Ahmet H. Ertas: Department of Mechanical Engineering, Faculty of Engineering & Natural Sciences, Bursa Technical University, Bursa 16330, Turkey

Abstract
The main purpose to introduce model based controller in proposed control technique is to provide better and fast learning of the floating dynamics by means of fuzzy logic controller and also cancelling effect of nonlinear terms of the system. An iterative adaptive dynamic programming algorithm is proposed to deal with the optimal trajectory-tracking control problems for autonomous underwater vehicle (AUV). The optimal tracking control problem is converted into an optimal regulation problem by system transformation. Then the optimal regulation problem is solved by the policy iteration adaptive dynamic programming algorithm. Finally, simulation example is given to show the performance of the iterative adaptive dynamic programming algorithm.

Key Words
complex systems; fuzzy models; delay-dependent robust stability criterion; parallel distributed compensation

Address
Tim Chen: AI Lab, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Safiullahand Khurram:Department of Computer Science, Kunduz University, Kunduz, Afghanistan
Joelli Zoungrana:School of Intelligent Science, Colinas University of Boé, Avenida 14 de Novembro Entrada do Bairro de Hafia Boe C.P. 1340 Bissau Guinea-Bissau
Lallit Pandey and J.C.Y. Chen: Department of Soil Science, Patuakhali Science and Technology University,
Dumki 8602, Patuakhali, Bangladesh

Abstract
The reasonable layout of vacuum cleaner can effectively improve the collection efficiency of iron filings generated in the process of steel production. Therefore, in this study, the CFD-DEM coupling model and two-fluid model are used to calculate the iron filings collection efficiency of vacuum cleaner with different inclination/cross-sectional area, pressure drop and inlet angle. The results are as follows: The CFD-DEM coupling method can truly reflect the motion mode of iron filings in pneumatic conveying. Considering the instability and the decline of the growth rate of iron filings collection efficiency caused by high pressure drop, the layout of 75° inclination is suggested, and the optimal pressure drop is 100Pa. The optimal simulation results based on two-fluid model show that when the inlet angle and pressure drop are in the range of 45°~65° and 70Pa~100Pa, larger mass flow rate of iron filings can be obtained. It is hoped that the simulation results can offer some suggestion to the layout of vacuum cleaner in the rolling mill.

Key Words
CFD-DEM; iron filings collection efficiency; optimization analysis; two-fluid model; mass flow rate

Address
School of Civil Engineering, Wuhan University, Wuhan, 430072, Hubei, China

Abstract
This article describes the technology for constructing of a multiply-connected three-dimensional area's finite element representation. Representation of finite-element configuration of an area is described by a discrete set that consist of the number of nodes and elements of the finite-element grid, that are orderly set of nodes' coordinates and numbers of finite elements. Corresponding theorems are given, to prove the correctness of the solution method. The adequacy of multiply-connected area topology's finite element model is shown. The merging of subareas is based on the criterion of boundary nodes' coincidence by establishing a simple hierarchy of volumes, surfaces, lines and points. Renumbering nodes is carried out by the frontal method, where nodes located on the outer edges of the structure are used as the initial front.

Key Words
modeling; finite element; grid; numbering; ordering; node; vertex; face; front; algorithm; connect; area

Address
Askhad M. Polatov, Akhmat M. Ikramov: Department of Mathematics, National University of Uzbekistan,4, University Street,
Tashkent 100174, Uzbekistan
Daniyarbek D. Razmukhamedov: Turin Polytechnic University in Tashkent, 17, Kichik halqa yo'li Street, Tashkent 100000, Uzbekistan

Abstract
In this paper, we develop models to design the airfoil using Multilayer Feed-forward Artificial Neural Network (MFANN) and Support Vector Regression model (SVR). The aerodynamic coefficients corresponding to series of airfoil are stored in a database along with the airfoil coordinates. A neural network is created with aerodynamic coefficient as input to produce the airfoil coordinates as output. The performance of the models have been evaluated. The results show that the SVR model yields the lowest prediction error.

Key Words
support vector regression model; neural networks; airfoil design; inverse design; backpropagation

Address
K. Thinakaran: Computer Science Engeneering., Saveetha School of Engineering, SIMATS, Chennai 600 077 TN, India
R. Rajasekar: Aeronautical Engineering, MVJ Engineering College, Bangalore, India
K. Santhi: Sreenivasa Institute of Technology and Management Studies, Chittoor, India
M. Nalini: Computer Science Engeneering., Saveetha School of Engineering, SIMATS, Chennai 600 077 TN, India

Abstract
In this paper is presented the solution method for three-dimensional problem of transversely isotropic body's elastoplastic deformation by the finite element method (FEM). The process of problem solution consists of: determining the effective parameters of a transversely isotropic medium; construction of the finite element mesh of the body configuration, including the determination of the local minimum value of the tape width of non-zero coefficients of equation systems by using of front method; constructing of the stiffness matrix coefficients and load vector node components of the equation for an individual finite element's state according to the theory of small elastoplastic deformations for a transversely isotropic medium; the formation of a resolving symmetric-tape system of equations by summing of all state equations coefficients summing of all finite elements; solution of the system of symmetric-tape equations systems by means of the square root method; calculation of the body's elastoplastic stress-strain state by performing the iterative process of the initial stress method. For each problem solution stage, effective computational algorithms have been developed that reduce computational operations number by modifying existing solution methods and taking into account the matrix coefficients structure. As an example it is given, the problem solution of fibrous composite straining in the form of a rectangle with a system of circular holes.

Key Words
modeling; algorithm; grid; front; FEM; transversal isotropy; fiber; composite; hole; elastoplastic; strain, stress

Address
Askhad M. Polatov, and Akhmat M. Ikramov: Department of Mathematics, National University of Uzbekistan, 4, University Street,Tashkent 100174, Uzbekistan
Abduvali A. Khaldjigitov : Samarkand branch of Tashkent University of Information Technologies, 47A,
Shohruh Mirzo Str., Samarkand, 140100, Uzbekistan

Abstract
The enhancements of bioenergy production effectiveness require the comprehensively experimental study of several parameters affecting these bioprocesses. The interpretation of the obtained experimental results and the estimation of optimum yield are extremely complicated such as misinterpreting the results of an experiment. The use of mathematical modeling and statistical experimental designs can consistently supply the predictions of the potential yield and the identification of defining parameters and also the understanding of key relationships between factors and responses. This paper summarizes several mathematical models used to achieve an adequate overall and maximal production yield and rate, to screen, to optimize, to identify, to describe and to provide useful information for the effect of several factors on bioenergy production processes. The usefulness, the validity and, the feasibility of each strategy for studying and optimizing the bioenergy-producing processes were discussed and confirmed by the good correlation between predicted and measured values.

Key Words
system modeling; experimental design methods; neural network design, identification, optimization, bioenergy

Address
Hamza Akroum, and Abderrezak Aibeche: Laboratoire d'Automatique Appliquée, Université M'Hamed Bougara de Boumerdès, 1 Av. de l'indépendance 35000 Boumerdés, Algeria
Dahbia Akroum-Amrouche : Département de chimie, faculté des sciences,Université M'Hamed Bougara de Boumerdes Av. de l'independance 35000 Boumerdes, Algeria


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