The Gravitational Search Algorithm in Antiresonance Layer Optimization of Laminated Composite Plates

In the present study, Gravitational Search Algorithm (GSA) is combined with Finite Element Method (FEM) for optimizing laminated composites vibration behavior. The fiber orientation angle of layers is considered as design variable. The 8-layerd and 12-layerd plates with both of square and rectangular shapes are investigated. Twenty distinct boundary conditions and [Formula: see text] of fiber angle increment are considered. The results of the proposed method are in good agreement with reference methods, and in some cases the GSA-FEM is more efficient. Moreover, the simple structure of GSA and its exploration and exploitation features avoids trapping in a local optimum.

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Minimize the Deflection of Laminated Composite Plates under the External Load Using Fiber Orientation Angle

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.709.144 ◽

2014 ◽

Vol 709 ◽

pp. 144-147

Author(s):

Ying Tao Chen ◽

Song Xiang ◽

Wei Ping Zhao

Keyword(s):

Fiber Orientation ◽

External Load ◽

Optimization Problem ◽

Orientation Angle ◽

Laminated Composite ◽

Composite Plates ◽

Laminated Composite Plates ◽

Load Optimization ◽

Fiber Orientation Angle ◽

Optimization Parameters

Optimization of fiber orientation angle is studied to minimize the deflection of the laminated composite plates by the genetic algorithm. The objective function of optimization problem is the minimum deflection of laminated composite plates under the external load; optimization parameters are fiber orientation angle of laminated composite plates. The results for the optimal fiber orientation angle and the minimum deflection of the 4-layer plates are presented to demonstrate the validity of present method.

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Optimization of Laminated Composite Plates for Maximum Biaxial Buckling Load

VNU Journal of Science Mathematics - Physics ◽

10.25073/2588-1124/vnumap.4509 ◽

2020 ◽

Vol 36 (2) ◽

Author(s):

Pham Dinh Nguyen ◽

Quang-Viet Vu ◽

George Papazafeiropoulos ◽

Hoang Thi Thiem ◽

Pham Minh Vuong ◽

...

Keyword(s):

Fiber Orientation ◽

Orientation Angle ◽

Laminated Composite ◽

Optimization Procedure ◽

Composite Plates ◽

Buckling Load ◽

Biaxial Compression ◽

Laminated Composite Plates ◽

Design Variables ◽

Fiber Orientation Angle

This paper proposes an optimization procedure for maximization of the biaxial buckling load of laminated composite plates using the gradient-based interior-point optimization algorithm. The fiber orientation angle and the thickness of each lamina are considered as continuous design variables of the problem. The effect of the number of layers, fiber orientation angles, thickness and length to thickness ratios on the buckling load of the laminated composite plates under biaxial compression is investigated. The effectiveness of the optimization procedure in this study is compared with previous works.

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Optimization for the Maximum Buckling Loads of Laminated Composite Plates – Comparison of Various Design Methods

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.334-335.89 ◽

2007 ◽

Vol 334-335 ◽

pp. 89-92 ◽

Cited By ~ 9

Author(s):

Shinya Honda ◽

Yoshihiro Narita ◽

Katsuhiko Sasaki

Keyword(s):

Composite Structures ◽

Orientation Angle ◽

Laminated Composite ◽

Composite Plates ◽

Laminated Composite Plates ◽

Advantages And Disadvantages ◽

Optimum Parameters ◽

Plate Elements ◽

Buckling Optimization ◽

Fiber Orientation Angle

Structural plate elements in composite structures are typically fabricated by stacking orthotropic layers, each of which is composed of reinforcing fibers and matrix materials. In this work, three optimum design approaches are compared to clarify the advantages and disadvantages for optimizing the buckling performance of laminated composite plates. The first approach is developed recently by the authors, where the buckling load is maximized with respect to the lamination parameters by a gradient method and then the optimum lay-up design is determined by minimizing the errors between the optimum parameters and parameters for all possible discrete lay-ups. The second approach is the layerwise optimization (LO) approach where the fiber orientation angle in each layer is optimized step-by-step by repeating one dimensional search. The third one is a direct application of a simple genetic algorithm (SGA). In numerical examples, three sets of results are compared to discuss on the methodology for buckling optimization.

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A “Tuned” Mask Learnt Approach Based on Gravitational Search Algorithm

Computational Intelligence and Neuroscience ◽

10.1155/2016/8179670 ◽

2016 ◽

Vol 2016 ◽

pp. 1-16 ◽

Cited By ~ 4

Author(s):

Youchuan Wan ◽

Mingwei Wang ◽

Zhiwei Ye ◽

Xudong Lai

Keyword(s):

Image Classification ◽

Search Algorithm ◽

Gravitational Search Algorithm ◽

Gabor Wavelet ◽

Hill Climbing ◽

Local Optimum ◽

Texture Image ◽

Fitness Value ◽

Gravitational Search ◽

Texture Image Classification

Texture image classification is an important topic in many applications in machine vision and image analysis. Texture feature extracted from the original texture image by using “Tuned” mask is one of the simplest and most effective methods. However, hill climbing based training methods could not acquire the satisfying mask at a time; on the other hand, some commonly used evolutionary algorithms like genetic algorithm (GA) and particle swarm optimization (PSO) easily fall into the local optimum. A novel approach for texture image classification exemplified with recognition of residential area is detailed in the paper. In the proposed approach, “Tuned” mask is viewed as a constrained optimization problem and the optimal “Tuned” mask is acquired by maximizing the texture energy via a newly proposed gravitational search algorithm (GSA). The optimal “Tuned” mask is achieved through the convergence of GSA. The proposed approach has been, respectively, tested on some public texture and remote sensing images. The results are then compared with that of GA, PSO, honey-bee mating optimization (HBMO), and artificial immune algorithm (AIA). Moreover, feature extracted by Gabor wavelet is also utilized to make a further comparison. Experimental results show that the proposed method is robust and adaptive and exhibits better performance than other methods involved in the paper in terms of fitness value and classification accuracy.

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Optimal Design of Laminated Composite Plates Under Axial Compression

Transactions of the Canadian Society for Mechanical Engineering ◽

10.1139/tcsme-1985-0007 ◽

1985 ◽

Vol 9 (1) ◽

pp. 45-50 ◽

Cited By ~ 13

Author(s):

S.P. Joshi ◽

N.G.R. Iyengar

Keyword(s):

Optimum Design ◽

Optimization Problems ◽

Orientation Angle ◽

Laminated Composite ◽

Composite Plates ◽

Aspect Ratios ◽

Unconstrained Optimization Problems ◽

Reinforced Composite ◽

Design Variables ◽

Fiber Orientation Angle

The study is carried out for the optimum design of laminated fiber reinforced composite plates, subjected to multiple in-plane loadings. Angle-ply laminates with orthotropic laminae are considered. Thickness of plies and corresponding fiber orientations are incorporated as design variables. The constrained optimization problem is transformed into a series of unconstrained optimization problems, using an interior penalty function approach. The results have been obtained for different aspect ratios and uniform biaxial in-plane loading ratios. This study shows that the fiber orientations of the plies near mid-plane have little effect on the optimum design. There exists a particular fiber orientation angle for the over all thickness of laminate, which results in the optimum design for a plate of a given aspect ratio under a given set of loadings.

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Intelligent gravitational search random forest algorithm for fake news detection

International Journal of Modern Physics C ◽

10.1142/s012918312250084x ◽

2021 ◽

Author(s):

Rathika Natarajan ◽

Abolfazl Mehbodniya ◽

Kantilal Pitambar Rane ◽

Sonika Jindal ◽

Mohammed Faez Hasan ◽

...

Keyword(s):

Social Media ◽

Random Forest ◽

Search Algorithm ◽

Gravitational Search Algorithm ◽

Solution Space ◽

Automated System ◽

Local Optimum ◽

Fake News ◽

Online Social Media ◽

Gravitational Search

Online social media has made the process of disseminating news so quick that people have shifted their way of accessing news from traditional journalism and press to online social media sources. The rapid rotation of news on social media makes it challenging to evaluate its reliability. Fake news not only erodes public trust but also subverts their opinions. An intelligent automated system is required to detect fake news as there is a tenuous difference between fake and real news. This paper proposes an intelligent gravitational search random forest (IGSRF) algorithm to be employed to detect fake news. The IGSRF algorithm amalgamates the Intelligent Gravitational Search Algorithm (IGSA) and the Random Forest (RF) algorithm. The IGSA is an improved intelligent variant of the classical gravitational search algorithm (GSA) that adds information about the best and worst gravitational mass agents in order to retain the exploitation ability of agents at later iterations and thus avoid the trapping of the classical GSA in local optimum. In the proposed IGSRF algorithm, all the intelligent mass agents determine the solution by generating decision trees (DT) with a random subset of attributes following the hypothesis of random forest. The mass agents generate the collection of solutions from solution space using random proportional rules. The comprehensive prediction to decide the class of news (fake or real) is determined by all the agents following the attributes of random forest. The performance of the proposed algorithm is determined for the FakeNewsNet dataset, which has sub-categories of BuzzFeed and PolitiFact news categories. To analyze the effectiveness of the proposed algorithm, the results are also evaluated with decision tree and random forest algorithms. The proposed IGSRF algorithm has attained superlative results compared to the DT, RF and state-of-the-art techniques.

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Fiber Orientation Angle Optimization for Minimum Stress of Laminated Composite Plates

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.709.135 ◽

2014 ◽

Vol 709 ◽

pp. 135-138

Author(s):

Ying Tao Chen ◽

Song Xiang ◽

Wei Ping Zhao

Keyword(s):

Genetic Algorithm ◽

Fiber Orientation ◽

Optimization Problem ◽

Orientation Angle ◽

Laminated Composite ◽

Composite Plates ◽

Laminated Composite Plates ◽

Load Optimization ◽

Fiber Orientation Angle ◽

Minimum Stress

The genetic algorithm is used to minimize the stress of the laminated composite plates by optimizing the fiber orientation angle. The objective function of optimization problem is the minimum stress in center of laminated composite plates under the external load; optimization variables are fiber orientation angle. The results for the optimal fiber orientation angle and the minimum stress of the 2-layer plates and 3-layer plates are presented.

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