Composite Materials
Hiral Parikh; Piyush Gohil
Abstract
As the fiber-reinforced polymer matrix composites give good strength and can work in rigorous environmental conditions, nowadays, more focus is given to study the behavior of these materials under different operating conditions. Due to the environmental concern, the focus on the natural fiber reinforced ...
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As the fiber-reinforced polymer matrix composites give good strength and can work in rigorous environmental conditions, nowadays, more focus is given to study the behavior of these materials under different operating conditions. Due to the environmental concern, the focus on the natural fiber reinforced polymer matrix composite is enhancing both in research and industrial sectors. Currently, the focus has been given to unifying solid fillers with the polymer matrix composite to improve their mechanical and tribo properties. Aligned to this, the present work discusses the effect of various weight fractions of fillers (Flyash, SiC, and graphite) on the frictional behavior of natural fiber (cotton) polyester matrix composites. The specimen prepared with a hand lay-up process followed by compression molding. A plan of experiments, response surface technique, was used to obtain a response in an organized way by varying load, speed, and sliding distance. The test results reveal that different weight concentration of fillers has a considerable result on the output. The frictional behavior of materials evaluated by general regression and artificial neural network. The validation experiment effects show the estimated friction by using the artificial neural network was closer to experimental values compare to the regression models.
Vibration
B. Asmar; M. Karimi; F. Nazari; A. Bolandgerami
Abstract
Crack identification is a very important issue in mechanical systems, because it is a damage that if develops may cause catastrophic failure. In the first part of this research, modal analysis of a multi-cracked variable cross-section beam is done using finite element method. Then, the obtained results ...
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Crack identification is a very important issue in mechanical systems, because it is a damage that if develops may cause catastrophic failure. In the first part of this research, modal analysis of a multi-cracked variable cross-section beam is done using finite element method. Then, the obtained results are validated usingthe results of experimental modal analysis tests. In the next part, a novel procedure is considered to identify the locations and depths of cracks in the multi-cracked variable cross-section beam using natural frequency variations of the beam based on artificial neural network and particle swarm optimization algorithm. In the proposed crack identification algorithm, four distinct neural networks are employed for the identification of locations and depths of both cracks. Back error propagation and particle swarm optimization algorithms are used to train the networks. Finally, the results of these two methods are evaluated.
Vibration
Mahdi Karimi; Alireza Shooshtari; Soheil Razavi
Abstract
In this paper, nonlinear equations of motion for laminated composite rectangular plates based on the first order shear deformation theory were derived. Using a perturbation method, the nonlinear equation of motion was solved and analytical relations were obtained for natural and nonlinear frequencies. ...
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In this paper, nonlinear equations of motion for laminated composite rectangular plates based on the first order shear deformation theory were derived. Using a perturbation method, the nonlinear equation of motion was solved and analytical relations were obtained for natural and nonlinear frequencies. After proving the validity of the obtained analytical relations, as an alternative and simple modeling technique, ANN was also employed to model the laminated rectangular plates and predict effects of different parameters on the natural and nonlinear frequencies of the plates. In this respect, an optimal ANN was selected and trained by training data sets obtained from analytical method and also tested by testing data sets. The obtained results were in good agreement with the analytical and published results.
Manufacturing Processes
Mahdi Ghamami; Masoud Shariat Panahi; Maryam Rezaei
Abstract
In today's design, system complexity and increasing demand for safer, more efficient and less costly systems have created new challenges in science and engineering. Locomotives are products which are designed according to market order and technical needs of customers. Accordingly, targets of companies, ...
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In today's design, system complexity and increasing demand for safer, more efficient and less costly systems have created new challenges in science and engineering. Locomotives are products which are designed according to market order and technical needs of customers. Accordingly, targets of companies, especially designers and manufacturers of locomotives, have always been on the path of progress and seek to offer products with higher technology than other competitors. Quality of body structures is based on indicators such as natural frequency, displacement, fatigue life and maximum stress. Natural frequency of various components of the system and their adaption to each other are important for avoiding the phenomenon of resonance. In this study, body structures of ER24 locomotive (Iran Safir Locomotive) was studied. A combination of imperialist competitive algorithm (ICA) and artificial neural network was proposed to find optimal weight of structures while natural frequencies were in the determined range. Optimization of locomotive's structure was performed with an emphasis on maintaining locomotive abilities in static and dynamic fields. The results indicated that use of optimization techniques in the design process was a powerful and effective tool for identifying and improving main dynamic characteristics of structures and also optimizing performance in stress, noise and vibration fields.
