Optimum Design of Vibration Absorbers Using Genetic Algorithm

1995 ◽  
Author(s):  
Ting-Yu Chen ◽  
Jun-Jei Lan
Keyword(s):  
Genetic Algorithm ◽  
Frequency Response ◽  
Optimum Design ◽  
The Other ◽  
Vibration Absorbers ◽  
Discrete Variables ◽  
Discrete Variable ◽  
Frequency Responses ◽  
Design Variables ◽  
Variable Problem

Abstract The genetic algorithm (GA) is used to design vibration absorbers. The problem is formulated as mixed continuous and discrete variable problem. The continuous design variables include the mass, the spring constant and the damping coefficient of the vibration absorbers. The discrete variables are the installing locations of the absorbers. GA fits in this problem very well. Two examples are given. The near optimum solutions show that when the number of constrained frequency responses is less than or equal to the number of vibration absorbers, the optimum locations of the absorbers are exactly the nodes where the frequency response constraints are imposed. On the other hand, if the number of constrained frequency responses is greater than the number of absorbers, the optimum locations for the absorbers tend to be at the nodes that keep near equal distances to those constrained nodes.

Shape Optimization of a Knuckle using the Design of Experiments

2007 ◽  
Vol 345-346 ◽  
pp. 905-908 ◽  
Author(s):  
Young Chul Park ◽  
Jung Ho Kang ◽  
Dong Hwa Lee ◽  
Seung Hwan Oh ◽  
Won Deg Ko ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Characteristic Function ◽  
Design Of Experiments ◽  
Structural Optimization ◽  
Shape Optimization ◽  
Orthogonal Array ◽  
The Other ◽  
Discrete Variables ◽  
Design Variables ◽  
Constraint Feasibility

DOE (design of experiments) was applied to the design of a knuckle as a part of a suspension system. Specifically, knuckle made of aluminum alloy was optimized considering the strength. On the other hand, design variables were set as shape variables. During structural optimization using DOE, an orthogonal array strategy was developed to determine the optimum design. The relevant discrete variables were treated as levels. Since the conventional orthogonal array did not consider the constraint, however, the characteristic function was defined to include the effect of constraint feasibility. The general DOE was expanded to include problems with constraints related to the new characteristic function.

Optimum design of rolling element bearings using a genetic algorithm—differential evolution (GA—DE) hybrid algorithm

2010 ◽  
Vol 225 (3) ◽  
pp. 714-721 ◽  
Author(s):  
W Y Lin
Keyword(s):  
Genetic Algorithm ◽  
Differential Evolution ◽  
Objective Function ◽  
Optimum Design ◽  
Dynamic Loads ◽  
Representative Case ◽  
De Algorithm ◽  
Design Variables ◽  
Deep Groove ◽  
Rolling Element

Binary-code genetic algorithms (BGA) have been used to obtain the optimum design for deep groove ball bearings, based on maximum fatigue life as an objective function. The problem has ten design variables and 20 constraint conditions. This method can find better basic dynamic loads rating than those listed in standard catalogues. However, the BGA algorithm requires a tremendous number of evaluations of the objective function per case to achieve convergence (e.g. about 5 200 000 for a representative case). To overcome this difficulty, a hybrid evolutionary algorithm by combining real-valued genetic algorithm (GA) with differential evolution (DE) is used together with the proper handling of constraints for this optimum design task. Findings show that the GA—DE algorithm can successfully find the better dynamic loads rating, about 1.3—11.1 per cent higher than those obtained using the traditional BGA. Moreover, the mean number of evaluations of the objective function required to achieve convergence is about 3011, using the GA—DE algorithm, as opposed to about 5 200 000 for a representative case using the BGA. Comparison shows the GA—DE algorithm to be much more effective and efficient than the BGA.

Optimum Design of a Dynamic Micro-Mixer for Multiphase Flow

2007 ◽  
Vol 353-358 ◽  
pp. 2836-2838
Author(s):  
Seok Young Han ◽  
J.Y. Park ◽  
Y.D. Kim ◽  
S.J. An ◽  
J.S. Maeng
Keyword(s):  
Optimum Design ◽  
Lattice Boltzmann ◽  
The Other ◽  
Time Dependent ◽  
Index Formula ◽  
Lattice Boltzmann Methods ◽  
Design Variables ◽  
Karman Vortex ◽  
Dependent Flow ◽  
Micro Mixer

An active micro-mixer equipped with an oscillating stirrer is considered by analyzing the mixing behaviors, i.e. the effect of the Karman vortex, the flow structure after the stirrer, etc. The mixing was calculated by the D2Q9 model of Lattice Boltzmann methods. In this study, the time– averaged mixing index formula, I D , is newly proposed for time dependent flow. Three models are tested and the mixing indices are compared. From the results, it was found that the mixing of Model III is enhanced and stabilized much more than the other models. Therefore, an optimum design for a dynamic micro-mixer with an oscillating stirrer was performed. The design variables were established as the length, the angle and frequency of the stirrer. It is found that the optimal design variables are determined by 0.66, 107.9 o and 0.49 Hz.

Application of Optimal Technique with Discrete Variables in Furnace Structure

2011 ◽  
Vol 308-310 ◽  
pp. 1187-1192
Author(s):  
Xiao Ming Yuan ◽  
Li Jie Zhang ◽  
Bing Du ◽  
Qiu Zhong Wang ◽  
Da Xing Zeng
Keyword(s):  
Total Mass ◽  
Optimization Design ◽  
Steel Structure ◽  
Element Model ◽  
Size Optimization ◽  
Discrete Variables ◽  
Discrete Variable ◽  
Design Variables ◽  
Ansys Apdl ◽  
Automatic Loading

Based on the characteristics of steel structure of the furnace, a generic finite element model, automatic loading, analysis and post-processing was achieved by ANSYS-APDL firstly. Then taking the sizes of profile as design variables and total mass as objective function, the size optimization design on steel structure was developed by means of two-level algorithm based on discrete variable.

Design Optimization of the Flexspline in Harmonic Drive

2012 ◽  
Vol 215-216 ◽  
pp. 59-63 ◽  
Author(s):  
Juan Dai ◽  
Li Zhi Chen ◽  
Xiao Bing Pang
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Design Optimization ◽  
Optimization Model ◽  
Design Solution ◽  
Harmonic Drive ◽  
Discrete Variables ◽  
Geometrical Constraint ◽  
Design Variables ◽  
Discrete Design Variables

In order to reduce the weight of harmonic drive (HD), the total volume of flexspline and circular spline was formulated and used as an objection function. Under the constraints including the condition on the strength of flexspline, the condition on averting the tooth top interference, the condition on the transmission ratio of HD and the geometrical constraint conditions of flexspline, a design optimization model with mixed discrete variables was established. For directly applying the optimal design solution of flexspline to manufacture, a manufacture-oriented method for dealing with mixed discrete design variables was used and the established model was solved by using an improved compound genetic algorithm. An optimal design example of flexspline was given and it shows that the proposed method is practical and effective.

scholarly journals The structural optimum design of laminated slender beam section with arbitrary material distribution using a genetic algorithm

2019 ◽  
Vol 11 (1) ◽  
pp. 7-20
Author(s):  
Sang Ho AHN ◽  
Jun Hwan JANG
Keyword(s):  
Genetic Algorithm ◽  
Composite Material ◽  
Optimum Design ◽  
Rotor Blade ◽  
Design Methodology ◽  
Damage Index ◽  
Skin Thickness ◽  
Design Variables ◽  
Blade Section ◽  
Section Structure

In this paper, a study on optimum design methodology of a section structure of a composite material rotor blade using genetic algorithm is conducted, in order to calculate repetitive optimum design, analysis of strength, fatigue and vibration on blade section. In the analysis, the minimum mass of the rotor blade was defined as objective function; stress damage index, center of mass on blade section and fatigue life of blade were set as constraints. By applying genetic algorithm, laminate angle and thickness of skin, thickness, location and width of torsion box were established as design variables; the optimum design methodology on section structure of the composite material rotor blade was validated. The integrated design program of the section structure of the composite material rotor blade based on this study deals with designing the optimal rotor blade section which meets the design load and constraints given by the random position of rotor blade. By using blade’s section design variables derived from this, it can be facilitated for basic information on detailed design of rotor blade.

OPTIMUM DESIGN OF GASKET PLATE HEAT EXCHANGER USING MULTIMODAL GENETIC ALGORITHM

2013 ◽  
Vol 44 (8) ◽  
pp. 761-789 ◽  
Author(s):  
Farzaneh Hajabdollahi ◽  
Zahra Hajabdollahi ◽  
Hassan Hajabdollahi
Keyword(s):  
Genetic Algorithm ◽  
Heat Exchanger ◽  
Optimum Design ◽  
Plate Heat Exchanger ◽  
Plate Heat

Shape Optimization of Hydraulic Structures: an Example of an Optimum Design of a Fish Passage

10.29007/2k64 ◽  
2018 ◽  
Author(s):  
Pat Prodanovic ◽  
Cedric Goeury ◽  
Fabrice Zaoui ◽  
Riadh Ata ◽  
Jacques Fontaine ◽  
...  
Keyword(s):  
Numerical Model ◽  
Shape Optimization ◽  
Objective Function ◽  
Optimum Design ◽  
Optimization Problem ◽  
A Priori ◽  
Coupled System ◽  
Fish Passage ◽  
Hydraulic Structures ◽  
Design Variables

This paper presents a practical methodology developed for shape optimization studies of hydraulic structures using environmental numerical modelling codes. The methodology starts by defining the optimization problem and identifying relevant problem constraints. Design variables in shape optimization studies are configuration of structures (such as length or spacing of groins, orientation and layout of breakwaters, etc.) whose optimal orientation is not known a priori. The optimization problem is solved numerically by coupling an optimization algorithm to a numerical model. The coupled system is able to define, test and evaluate a multitude of new shapes, which are internally generated and then simulated using a numerical model. The developed methodology is tested using an example of an optimum design of a fish passage, where the design variables are the length and the position of slots. In this paper an objective function is defined where a target is specified and the numerical optimizer is asked to retrieve the target solution. Such a definition of the objective function is used to validate the developed tool chain. This work uses the numerical model TELEMAC- 2Dfrom the TELEMAC-MASCARET suite of numerical solvers for the solution of shallow water equations, coupled with various numerical optimization algorithms available in the literature.

scholarly journals Hybrid Seven-bar Press Mechanism

2018 ◽  
Vol 12 (3) ◽  
pp. 181-187
Author(s):  
M. Erkan Kütük ◽  
L. Canan Dülger
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Design Optimization ◽  
Hybrid System ◽  
Degrees Of Freedom ◽  
Dimensional Synthesis ◽  
Design Variables ◽  
Optimization Study ◽  
Metal Stamping

An optimization study with kinetostatic analysis is performed on hybrid seven-bar press mechanism. This study is based on previous studies performed on planar hybrid seven-bar linkage. Dimensional synthesis is performed, and optimum link lengths for the mechanism are found. Optimization study is performed by using genetic algorithm (GA). Genetic Algorithm Toolbox is used with Optimization Toolbox in MATLAB®. The design variables and the constraints are used during design optimization. The objective function is determined and eight precision points are used. A seven-bar linkage system with two degrees of freedom is chosen as an example. Metal stamping operation with a dwell is taken as the case study. Having completed optimization, the kinetostatic analysis is performed. All forces on the links and the crank torques are calculated on the hybrid system with the optimized link lengths

scholarly journals Multi-dimensional optimization of In0.53Ga0.47As thermophotovoltaic cell using real coded genetic algorithm

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mansur Mohammed Ali Gamel ◽  
Pin Jern Ker ◽  
Hui Jing Lee ◽  
Wan Emilin Suliza Wan Abdul Rashid ◽  
M. A. Hannan ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Output Power ◽  
Waste Heat ◽  
Antireflection Coating ◽  
Base Layer ◽  
Average Percentage ◽  
Cell Efficiency ◽  
Design Variables ◽  
Real Coded Genetic Algorithm ◽  
Dimensional Optimization

AbstractThe optimization of thermophotovoltaic (TPV) cell efficiency is essential since it leads to a significant increase in the output power. Typically, the optimization of In0.53Ga0.47As TPV cell has been limited to single variable such as the emitter thickness, while the effects of the variation in other design variables are assumed to be negligible. The reported efficiencies of In0.53Ga0.47As TPV cell mostly remain < 15%. Therefore, this work develops a multi-variable or multi-dimensional optimization of In0.53Ga0.47As TPV cell using the real coded genetic algorithm (RCGA) at various radiation temperatures. RCGA was developed using Visual Basic and it was hybridized with Silvaco TCAD for the electrical characteristics simulation. Under radiation temperatures from 800 to 2000 K, the optimized In0.53Ga0.47As TPV cell efficiency increases by an average percentage of 11.86% (from 8.5 to 20.35%) as compared to the non-optimized structure. It was found that the incorporation of a thicker base layer with the back-barrier layers enhances the separation of charge carriers and increases the collection of photo-generated carriers near the band-edge, producing an optimum output power of 0.55 W/cm2 (cell efficiency of 22.06%, without antireflection coating) at 1400 K radiation spectrum. The results of this work demonstrate the great potential to generate electricity sustainably from industrial waste heat and the multi-dimensional optimization methodology can be adopted to optimize semiconductor devices, such as solar cell, TPV cell and photodetectors.

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