Direct Gear Design for Asymmetric Tooth Gears

2015 ◽  
pp. 117-143 ◽  
Author(s):  
A. Kapelevich
Keyword(s):  
Gear Design

Effect of design parameters on stresses occurring at the tooth root in a spur gear pressed on a shaft

2021 ◽  
pp. 095440892199529
Author(s):  
Fatih Güven
Keyword(s):  
Internal Pressure ◽  
Tangential Stress ◽  
Spur Gear ◽  
Design Parameters ◽  
Interference Fit ◽  
Gear Design ◽  
Compact Design ◽  
Fit Tolerance ◽  
Moderate Stress ◽  
Good Agreement

Gears are commonly used in transmission systems to adjust velocity and torque. An integral gear or an interference fit could be used in a gearbox. Integral gears are mostly preferred as driving gear for a compact design to reduce the weight of the system. Interference fit makes the replacement of damaged gear possible and re-use of the shaft compared to the integral shaft. However, internal pressure occurs between mating surfaces of the components mated. This internal pressure affects the stress distribution at the root and bottom land of the gear. In this case, gear parameters should be re-considered to assure gear life while reducing the size of the gear. In this study, interference fitted gear-shaft assembly was examined numerically. The effects of rim thickness, profile shifting, module and fit tolerance on bending stress occurring at the root of the gear were investigated to optimize gear design parameters. Finite element models were in good agreement with analytical solutions. Results showed that the rim thickness of the gear is the main parameter in terms of tangential stress occurring at the bottom land of the gear. Positive profile shifting reduces the tangential stress while the pitch diameter of the gear remains constant. Also, lower tolerance class could be selected to moderate stress for small rim thickness.

A Performance Study of Real Coded Genetic Algorithm on Gear Design Optimization

2012 ◽  
Vol 622-623 ◽  
pp. 64-68 ◽  
Author(s):  
S. Padmanabhan ◽  
M. Chandrasekaran ◽  
P. Asokan ◽  
V. Srinivasa Raman
Keyword(s):  
Genetic Algorithm ◽  
Power Efficiency ◽  
Mechanical Design ◽  
Design Solution ◽  
Functional Requirements ◽  
Performance Study ◽  
Gear Design ◽  
Adverse Result ◽  
Real Coded Genetic Algorithm ◽  
Comparative Results

he major problem that deals with practical engineers is the mechanical design and creativeness. Mechanical design can be defined as the choice of materials and geometry, which satisfies, specified functional requirements of that design. A good design has to minimize the most significant adverse result and to maximize the most significant desirable result. An evolutionary algorithm offers efficient ways of creating and comparing a new design solution in order to complete an optimal design. In this paper a type of Genetic Algorithm, Real Coded Genetic Algorithm (RCGA) is used to optimize the design of helical gear pair and a combined objective function with maximizes the Power, Efficiency and minimizes the overall Weight, Centre distance. The performance of the proposed algorithms is validated through LINGO Software and the comparative results are analyzed.

Face Gear Width Prediction Using the DOE Method

2008 ◽  
Vol 130 (10) ◽  
Author(s):  
Michèle Guingand ◽  
Didier Remond ◽  
Jean-Pierre de Vaujany
Keyword(s):  
Regression Model ◽  
Simple Formula ◽  
Design Parameters ◽  
Face Gear ◽  
Main Design ◽  
Gear Design ◽  
Simple Regression Model ◽  
Numerical Tool ◽  
Influential Parameters ◽  
Simple Regression

This paper deals with face gear design. The goal is to propose a simple formula for predicting the width of the wheel as a function of the main design parameters. A specific software was used to achieve this goal. This numerical tool is able to simulate the geometry and the quasistatic loaded behavior of a face gear. The statistical method used for analyzing the influence of data is described: The design of experiments leads to a simple regression model taking into account the influential parameters and their couplings. In the last part of this paper, the results of the formulas are compared to those of the software and an optimal design is proposed based on the regression model.

DIscrepancy of Gear Tooth Allowable Bending Stress Using the Extreme Value Distribution From Different Test Methods

1991 ◽  
Author(s):  
Chienann A. Hou ◽  
Shijun Ma
Keyword(s):  
Gear Tooth ◽  
Extreme Value Distribution ◽  
Test Methods ◽  
Extreme Value ◽  
Distribution Functions ◽  
Value Distribution ◽  
Test Method ◽  
Bending Stress ◽  
Gear Design ◽  
Experimental Approaches

Abstract The allowable bending stress Se of a gear tooth is one of the basic factors in gear design. It can be determined by either the pulsating test or the gear-running test. However, some differences exist between the allowable bending stress Se obtained from these different test methods. In this paper, the probability distribution functions corresponding to each test method are analyzed and the expressions for the minimum extreme value distribution are presented. By using numerical integration, Se values from the population of the same tested gear tooth are obtained. Based on this investigation it is shown that the differences in Se obtained from the different test methods are significant. A proposed correction factor associated with the different experimental approaches is also presented.

Using Constraint Management Techniques to Design Spur and Helical Gears

1992 ◽  
Author(s):  
Rajiv Agrawal ◽  
Natarajan Sridhar ◽  
Gary L. Kinzel
Keyword(s):  
Mathematical Formulation ◽  
Spur Gears ◽  
Helical Gears ◽  
General Design ◽  
Gear Design ◽  
Constraint Management ◽  
Management Techniques

Abstract This paper presents the use of constraint management techniques to design spur and helical gears. The constraints for gear design are presented in a declarative manner such that they can be incorporated in a general Design Shell environment. A declarative representation allows the designer to experiment with a number of different designs and perform “what-if” scenarios. Since spur gears form a subset of helical gears, the mathematical formulation is presented for helical gears only. The analysis of helical gears is based on the AGMA/ANSI Standard 2001-B88.

Comparative investigation of the moth-flame algorithm and whale optimization algorithm for optimal spur gear design

2021 ◽  
Vol 63 (3) ◽  
pp. 266-271
Author(s):  
Hammoudi Abderazek ◽  
Ferhat Hamza ◽  
Ali Riza Yildiz ◽  
Sadiq M. Sait
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problem ◽  
Spur Gear ◽  
Comparative Investigation ◽  
Whale Optimization Algorithm ◽  
Solution Quality ◽  
Gear Design ◽  
Geometric Conditions ◽  
Swarm Algorithms ◽  
Whale Optimization

Abstract In this study, two recent algorithms, the whale optimization algorithm and moth-flame optimization, are used to optimize spur gear design. The objective function is the minimization of the total weight of the spur gear pair. Moreover, the optimization problem is subjected to constraints on the main kinematic and geometric conditions as well as to the resistance of the material of the gear system. The comparison between moth-flame optimization (MFO), the whale optimization algorithm (WOA), and previous studies indicate that the final results obtained from both algorithms lead to a reduction in gear weight by 1.05 %. MFO and the WOA are compared with four additional swarm algorithms. The experimental results indicate that the algorithms introduced here, in particular MFO, outperform the four other methods when compared in terms of solution quality, robustness, and high success rate.

Computer-Aided Gear Product Realization

2018 ◽  
Author(s):  
Alireza Yazdanshenas ◽  
Emilli Morrison ◽  
Chung-Hyun Goh ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Computer Aided Design ◽  
Interaction Analysis ◽  
Gear Tooth ◽  
Integrated Design ◽  
System Level ◽  
Trial And Error ◽  
Stress Concentrations ◽  
Element Analysis ◽  
Gear Design ◽  
Computer Aided

To save time and resources, many are making the transition to developing their ideas virtually. Computer-aided gear production realization is becoming more and more desired in the industry. To produce gears with custom qualities, such as material, weight and shape, the trial and error approach has yielded the best results. However, trial and error is costly and time consuming. The computer-aided integrated design and manufacturing approach is intended to resolve these drawbacks. A simple one stage reduction spur gearbox is used as an example in a case study. First, the gear geometry is developed using computer aided design (CAD) modeling. Next, using MATLAB/Simulink, the gear assembly is connected virtually to other subsystems for system expectations and interaction analysis. Finally, using finite element analysis (FEA) tools such as ABAQUS, a dynamic FEA of the gear integration is completed to analyze the stress concentrations and gear tooth failures. Through this method of virtual gear design, customized dimensions and specifications of gears for satisfying system-level requirements can be developed, thereby saving time and manufacturing costs for any custom gear design request.

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