scholarly journals The Optimization Research of Diesel Cylinder Gasket Parameters Based on Hybrid Neutral Network and Improved Grey Wolf Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yi Dong ◽  
Jianmin Liu ◽  
Yanbin Liu ◽  
Xinyong Qiao ◽  
Xiaoming Zhang ◽  
...  
Keyword(s):  
Finite Element ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Maximum Temperature ◽  
Grey Wolf ◽  
Neuron Network ◽  
Bee Colony ◽  
Comparison Results ◽  
Grey Wolf Algorithm ◽  
The Way

In order to improve reliability and fatigue life of cylinder gaskets in heavy duty diesel engine, several methods and algorithms are applied to optimize operating factors of gaskets. Finite element method is utilized to figure out and analyze the temperature fields, thermal-mechanical coupling stress fields, and deformations of gasket. After determining the maximum values of three state parameters, the orthogonal experimental design method is adopted to analyze the influence rules of five operating factors on three state parameters of the gaskets and four factors which most significantly affect these state parameters are determined. Then, the method which uses operating factors to predict state parameters is established on the application of hybrid neuron network based on partial least squares regression and deep neural network. The comparison results between the predicted values and real values verified the accuracy of the hybrid neuron network method. Based on artificial bee colony algorithm, improvement is attached to the way three kinds of grey wolves locate preys in grey wolf algorithm and the way how using different hierarchy wolfs in grey wolf algorithm to determine three weight coefficients and the location of prey is put forward with. The method using artificial bee colony algorithm to optimize the grey wolf algorithm is called ABC and GWO. The proposed HNN and the ABC and GWO method are applied to work out operating factors values which correspond to optimal state parameters of gasket, and the gaskets are optimized according to the optimal values. It has been demonstrated by finite element analysis results that maximum temperature, maximum coupling stress, and the maximum deformation decrease to 6 K, 12.57 MPa, and 0.0925 mm compared to the original values, respectively, which proves the accuracy of the algorithm and the validity of the improvement.

Inferring the atmospheric duct from radar sea clutter using the improved artificial bee colony algorithm

2018 ◽  
Vol 10 (4) ◽  
pp. 437-445 ◽  
Author(s):  
Chao Yang ◽  
Lixin Guo
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Orthogonal Experimental Design ◽  
Sea Clutter ◽  
Particle Swarm Optimizer ◽  
Bee Colony ◽  
Opposition Based Learning ◽  
Atmospheric Duct ◽  
Comparison Results ◽  
Better Than

AbstractIn this paper, an orthogonal crossover artificial bee colony (OCABC) algorithm based on orthogonal experimental design is presented and applied to infer the marine atmospheric duct using the refractivity from clutter technique, and the radar sea clutter power is simulated by the commonly used parabolic equation method. In order to test the accuracy of the OCABC algorithm, the measured data and the simulated clutter power with different noise levels are, respectively, utilized to estimate the evaporation duct and surface duct. The estimation results obtained by the proposed algorithm are also compared with those of the comprehensive learning particle swarm optimizer and the artificial bee colony algorithm combined with opposition-based learning and global best search equation. The comparison results demonstrate that the performance of proposed algorithm is better than those of the compared algorithms for the marine atmospheric duct estimation.

Thermal Based Optimum Design of Tapered Roller Bearing Through Evolutionary Algorithm

2013 ◽  
Author(s):  
Rajiv Tiwari ◽  
Rahul Chandran
Keyword(s):  
Evolutionary Algorithm ◽  
Optimum Design ◽  
High Speed ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Roller Bearing ◽  
Maximum Temperature ◽  
Dynamic Capacity ◽  
Bee Colony ◽  
Tapered Roller

In high-speed applications the maximum temperature in bearings are a crucial concern. In some applications the bearing is the prime source of heat, the temperature at which a bearing operates dictates the type and amount of lubricant and the material for the fabrication of the bearing components. In the present work a thermal based optimum design of tapered roller bearings has been presented. Internal geometry of the bearing has been optimized based by evolutionary algorithm. Constraints are geometrical, kinematical, strength and thermal in nature. Optimum designs have been found to have better performance parameters. Artificial bee colony algorithm has been used for the present optimization problem, for solving constrained non-linear optimization formulations. A total of nine design variables corresponding to the bearing geometry and constraint factors have been considered. A convergence study has been carried and optimum designs based on temperature is compared with the optimized values based on dynamic capacity, both using artificial bee colony algorithm. There is an excellent improvement found in the optimized bearing designs based on temperature when compared with the optimized results based on dynamic capacity in respect of the maximum temperature in the bearing with the artificial bee colony algorithm.

scholarly journals Application of Artificial Bee Colony Algorithm and Finite Element Analysis for Optimum Design of Brushless Permanent Magnet Motor

2012 ◽  
Vol 13 (1) ◽  
Author(s):  
Reza Ilka ◽  
Seyyed Asghar Gholamian
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Permanent Magnet ◽  
Power Density ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Permanent Magnet Motor ◽  
Element Analysis ◽  
Bee Colony ◽  
Brushless Motor

ABSTRACT: This paper develops a mathematical relationship for the purpose of designing and selecting the optimum dimensions of a brushless permanent magnet motor. The design is optimised by the use of artificial bee colony algorithm with the goal of maximizing the power density and efficiency of the motor. The required dimensions of the brushless motor are calculated based on the optimum power density and efficiency requirements. Finally, the predicted results of the optimisation are validated using a 2-D numerical program based on finite element analysis.ABSTRAK: Kajian ini mencadangkan persamaan yang menghubungkan rekabentuk dan dimensi magnet motor kekal tanpa berus. Rekabentuk optima berdasarkan algorisma koloni lebah tiruan dengan tujuan meningkatkan ketumpatan kuasa dan keberkesanan dibentangkan dalam kajian ini. Dimensi magnet motor kekal tanpa berus dihitung dengan ketumpatan kuasa optima dan keberkesanan. Akhirnya, keputusan telah disahkan dengan menggunakan program berangka 2-D berdasarkan analisis elemen finit.KEYWORDS: brushless; permanent magnet motor; power density; artificial bee colony; algorithm; finite element analysis

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

Artificial bee colony algorithm with modified search strategy

2013 ◽  
Vol 32 (12) ◽  
pp. 3326-3330
Author(s):  
Yin-xue ZHANG ◽  
Xue-min TIAN ◽  
Yu-ping CAO
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Search Strategy ◽  
Bee Colony
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