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Abstract
The paper presents a study regarding rubber compressibility behavior. The objective is to analyze the effect of compression degree of rubber on its mechanical properties and propose a new methodology based on reverse engineering to predict compressibility degree based on uniaxial stretching test and Finite Element Analysis (FEA). In general, rubbers are considered to be almost incompressible and Poisson

Key Words
experimental investigation; finite element method (FEM); hyperelasticity; optimization; rubber

Address
Debora Francisco Lalo, Marcelo Greco: Graduate Program in Structural Engineering, Department of Structural Engineering, School of Engineering, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil Matias Meroniuc: Fluid Mechanics Laboratory, Railway Engineering, National Technological University, Paris 532, Haedo, Buenos Aires, Argentina

Abstract
In recent years, there is an increasing interest to optimize the fuzzy logic controller with different methods. This paper focuses on the optimization of a fuzzy logic controller applied to a seismically excited nonlinear building. In most cases, this problem is formulated based on the linear behavior of the structure, however in this paper, four sets of objective functions are considered with respect to the nonlinear responses of the structure as the peak interstory drift ratio, the peak level acceleration, the ductility factor and the maximum control force. The Improved Charged System Search is used to optimize the membership functions and the rule base of the fuzzy controller. The obtained results of the optimized and the non-optimized fuzzy controllers are compared to the uncontrolled responses of the structure. Also, the performance of the utilized method is compared with various classical and advanced optimization algorithms.

Key Words
fuzzy logic controller; benchmark building; nonlinear response; optimization; metaheuristic algorithm; charged system search

Address
Mahdi Azizi, Siamak Talatahari: Department of Civil Engineering, University of Tabriz, Tabriz, Iran Seyyed Arash Mousavi Ghasemi, Reza Goli Ejlali: Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran Siamak Talatahari: Engineering Faculty, Near East University, North Cyprus, Mersin 10, Turkey

Abstract
The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

Key Words
consistent approximation; shape optimization; size optimization; truss structures

Address
Hosein Ahmadvand: Department of Civil Engineering, University of Kurdistan, Sanandaj, Iran Alireza Habibi: Department of Civil Engineering, Shahed University, Tehran, Iran

Abstract
The geometric nonlinearity has been successfully integrated with the design of steel structural system. Thus, the tubular lattice girder, one application of steel structural systems have already been optimized to obtain an economic design following the completion of computationally expensive design procedure. In order to decrease its computing cost, this study proposes to employ five multi-objective metaheuristics for the design optimization of geometrically nonlinear tubular lattice girder. Then, the employed multi-objective optimization algorithms (MOAs), NSGAII, PESAII, SPEAII, AbYSS and MoCell are evaluated considering their computing performances. For an unbiased evaluation of their computing performance, a tubular lattice girder with varying size-shape-topology and a benchmark truss design with 17 members are not only optimized considering the geometrically nonlinear behavior, but three benchmark mathematical functions along with the four benchmark linear design problems are also included for the comparison purpose. The proposed experimental study is carried out by use of an intelligent optimization tool named JMetal v5.10. According to the quantitative results of employed quality indicators with respect to a statistical analysis test, MoCell is resulted with an achievement of showing better computing performance compared to other four MOAs. Consequently, MoCell is suggested as an optimization tool for the design of geometrically nonlinear tubular lattice girder than the other employed MOAs.

Key Words
multi-objective optimization; evolutionary metaheuristics; geometric nonlinearity; tubular lattice girder

Address
Tugrul Talaslioglu: Department of Civil Engineering, Osmaniye Korkut Ata University, 80000, Osmaniye, Turkey

Abstract
In this paper, an enhanced Violation-based Sensitivity analysis and Border-Line Adaptive Sliding Technique (ViS-BLAST) will be utilized for optimization of some well-known structural and mechanical engineering problems. ViS-BLAST has already been introduced by the authors for solving truss optimization problems. For those problems, this method showed a satisfactory enactment both in speed and efficiency. The Enriched ViS-BLAST or EVB is introduced to be vastly applicable to any solvable constrained optimization problem without any specific initialization. It uses one-directional step-wise searching technique and mostly limits exploration to the vicinity of FNF border and does not explore the entire design space. It first enters the feasible region very quickly and keeps the feasibility of solutions. For doing this important, EVB groups variables for specifying the desired searching directions in order to moving toward best solutions out or inside feasible domains. EVB was employed for solving seven numerical engineering design problems. Results show that for problems with tiny or even complex feasible regions with a larger number of highly non-linear constraints, EVB has a better performance compared to some records in the literature. This dominance was evaluated in terms of the feasibility of solutions, the quality of optimum objective values found and the total number of function evaluations performed.

Key Words
constrained optimization; sensitivity analysis; mechanical engineering design; highly non-linear

Address
Babak Dizangian: Department of Civil Engineering, Velayat University, Iranshahr, Iran Mohammad Reza Ghasemi: Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran

Abstract
In the recent decades, various optimization algorithms have been considered for the optimization of structures. In this research, a new enhanced algorithm is used for the size and topology optimization of truss structures. This algorithm, which is obtained from the combination of Crow Search Algorithm (CSA) and the Cellular Automata (CA) method, is called CA-CSA method. In the first iteration of the CA-CSA method, some of the best designs of the crow's memory are first selected and then located in the cells of CA. Then, a random cell is selected from CA, and the best design is chosen from the selected cell and its neighborhood; it is considered as a "local superior design" (LSD). In the optimization process, the LSD design is used to modify the CSA method. Numerical examples show that the CA-CSA method is more effective than CSA in the size and topology optimization of the truss structures.

Key Words
truss structures; size optimization; topology optimization; crow search algorithm; cellular automata method

Address
Mostafa Mashayekhi and Roghayeh Yousefi: Department of Civil Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

Abstract
This work studies the behaviour of a steel portal frame selection under fire exposure, considering both span lengths and fire exposure times as variables. Such structures combine carbon steel (S275), fireproof micro-alloyed steel (FR), and coatings of intumescent paint with variable thicknesses, improving thereby the flame retardant behaviour of the steel structure. Thus, the main contribution of this study is the optimization of the portal frames by combining both steels, analysing the resulting costs influence on the final dimensions. Besides, the topological optimization of each steel component within the structure is also defined, in accordance with the following variables: weather conditions, span, paint thickness, and cost of steel. The results mainly confirmed that using both FR and S275 grades with intumescent painting is the Pareto optimum when considering performance, feasibility and costs of such portal frames widely used for industrial facilities.

Key Words
fire resistance steel; FR; metallic structure; intumescent paint; dimensioning method; structural optimization

Address
Harkaitz Garcia: Department of Mechanical Engineering, University of the Basque Country (UPV/EHU), 48940 Leioa Vizcaya, Spain Jesus Cuadrado: Department of Mechanical Engineering, University of the Basque Country (UPV/EHU), 48940 Leioa Vizcaya, Spain Maria V. Biezma: Department of Earth and Materials Science and Engineering, University of Cantabria, 39004 Santander, Spain Inigo Calderon: Sustainable Construction Division, Tecnalia Research and Innovation, 20009 San Sebastian, Guipuzcoa, Spain

Abstract
Local school buildings are critical facilities that can provide shelter in disasters such as earthquakes, so they must be more resistant to seismic forces than other structures. In this study, a sensitivity analysis was conducted to determine which columns-as the most critical members in a reinforced concrete building-most urgently require seismic retrofitting. The sensitivity analysis was conducted using an optimization technique with the location of each column as a parameter. A numerical model was developed to simulate a realistic collapse mode through a three-dimensional dynamic analysis. Based on numerical analysis results, it was found that the columns positioned in the lower floors, such as the first floor and in the outer part of a building, urgently require retrofitting. For reinforcement of the RC columns, which has been proven for its performance in previous research, was applied. Through this study, the importance of appropriate retrofitting is demonstrated. Further, a method for determining the appropriate location for retrofitting-when retrofitting is not possible on the entire structure-is presented.

Key Words
sensitivity analysis; optimization; school building; RC column; seismic retrofitting

Address
Hyunsu Seo: Institute of Technology Team, Daon Co., LTD, 20, Nodae-gil, Hwasun-eup, Hwasun-gun, 58125, South Korea Kyoungsub Park: Department of Civil Engineering, University fo Texas at Arlington, Arlington, TX76013, USA Minho Kwon: Department of Civil Engineering, Gyeongsang National University, Jinju, 52828, South Korea Jinsup Kim: Department of Civil Engineering, Gyeongsang National University, Jinju, 52828, South Korea

Abstract
Dynamic compaction of Aluminum powder using gas detonation forming technique was investigated. The experiments were carried out on four different conditions of total pre-detonation pressure. The effects of the initial powder mass and grain particle size on the green density and strength of compacted specimens were investigated. The relationships between the mentioned powder design parameters and the final features of specimens were characterized using Response Surface Methodology (RSM). Artificial Neural Network (ANN) models using the Group Method of Data Handling (GMDH) algorithm were also developed to predict the green density and green strength of compacted specimens. Furthermore, the desirability function was employed for multi-objective optimization purposes. The obtained optimal solutions were verified with three new experiments and ANN models. The obtained experimental results corresponding to the best optimal setting with the desirability of 1 are 2714 kg m3 and 21.5 MPa for the green density and green strength, respectively, which are very close to the predicted values.

Key Words
aluminum powder; artificial neural network; high-velocity compaction; modelling; optimization; response surface methodology

Address
Tohid Mirzababaie Mostofi: Faculty of Mechanical Engineering, University of Eyvanekey, Eyvanekey, Iran Mostafa Sayah-Badkhor: Faculty of Mechanical Engineering, University of Eyvanekey, Eyvanekey, Iran Mohammad Rezasefat: Faculty of Mechanical Engineering, University of Eyvanekey, Eyvanekey, Iran Hashem Babaei: Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran Togay Ozbakkaloglu: Ingram School of Engineering, Texas State University, San Marcos, TX 78666, USA

Abstract
Composite material-due to low density-causes weight savings, which results in lower fuel consumption of transport vehicles. The aim of the research was to change the existing base-plate of the aluminum airplane container with the composite sandwich plate in order to reduce the weight of the containers of cargo aircrafts. The newly constructed sandwich plate consists of aluminum honeycomb core and composite face-sheets. The face-sheets consist of glass or carbon or hybrid fiber layers. The orientations of the fibers in the face-sheets were 0o, 90o and +-45o. Multi-objective optimization method was elaborated for the newly constructed sandwich plates. Based on the design aim, the importance of the objective functions (weight and cost of sandwich plates) was the same (50%). During the optimization nine design constraints were considered: stiffness, deflection, facing stress, core shear stress, skin stress, plate buckling, shear crimping, skin wrinkling, intracell buckling. The design variables were core thickness and number of layers of the face-sheets. During the optimization both the Weighted Normalized Method of the Excel Solver and the Genetic Algorithm Solver of Matlab software were applied. The mechanical properties of composite face-sheets were calculated by Laminator software according to the Classical Lamination Plate Theory and Tsai-Hill failure criteria. The main added-value of the study is that the multi-objective optimization method was elaborated for the newly constructed sandwich structures. It was confirmed that the optimal new composite sandwich construction-due to weight savings and lower fuel consumption of cargo aircrafts - is more advantageous than conventional all-aluminum container.

Key Words
composite sandwich plates; weight and cost optimization; airplane container; weighted normalized method; genetic algorithm

Address
Alaa Al-Fatlawi: Faculty of Mechanical Engineering and Informatics, University of Miskolc, H-3515 Miskolc, Egyetemváros, Hungary; Faculty of Mechanical Engineering, University of Kufa, 54001 Al-Najaf, Iraq Karoly Jarmai, Gyorgy Kovacs: Faculty of Mechanical Engineering and Informatics, University of Miskolc, H-3515 Miskolc, Egyetemváros, Hungary

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