Rough Terrain Rovers Dynamics Analysis and Optimization

2005 ◽  
Author(s):  
Hadi Tavakoli Nia ◽  
Seyed Hamidreza Alemohammad ◽  
Saeed Bagheri ◽  
Reza Hajiaghaee Khiabani ◽  
Ali Meghdari
Keyword(s):  
Genetic Algorithm ◽  
Software Package ◽  
Random Search ◽  
Nonlinear Problems ◽  
Directional Derivatives ◽  
Rough Terrain ◽  
Dynamics Analysis ◽  
Search Technique ◽  
Dynamical Equations ◽  
New Approach

In this paper a new approach to dynamics optimization of rough terrain rovers is introduced. Since rover wheels traction has a significant role in rover mobility, optimization is based on the minimization of traction at rover wheel-ground interfaces. The method of optimization chosen is Genetic Algorithm (GA) which is a directed random search technique along with the usual optimization based on directional derivatives. GA is a suitable and efficient method of optimization for nonlinear problems. The procedure is applied on a specific rough terrain rover called CEDRA-I Shrimp Rover. Dynamical equations are obtained using Kane’s method. Finally, the results are verified by modeling of the rover in ADAMS® software package.

scholarly journals Performance of Enhanced Multiple-Searching Genetic Algorithm for Test Case Generation in Software Testing

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1779
Author(s):  
Wanida Khamprapai ◽  
Cheng-Fa Tsai ◽  
Paohsi Wang ◽  
Chi-En Tsai
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Random Search ◽  
Automatic Generation ◽  
Superior Performance ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Network Systems ◽  
Routing Problem

Test case generation is an important process in software testing. However, manual generation of test cases is a time-consuming process. Automation can considerably reduce the time required to create adequate test cases for software testing. Genetic algorithms (GAs) are considered to be effective in this regard. The multiple-searching genetic algorithm (MSGA) uses a modified version of the GA to solve the multicast routing problem in network systems. MSGA can be improved to make it suitable for generating test cases. In this paper, a new algorithm called the enhanced multiple-searching genetic algorithm (EMSGA), which involves a few additional processes for selecting the best chromosomes in the GA process, is proposed. The performance of EMSGA was evaluated through comparison with seven different search-based techniques, including random search. All algorithms were implemented in EvoSuite, which is a tool for automatic generation of test cases. The experimental results showed that EMSGA increased the efficiency of testing when compared with conventional algorithms and could detect more faults. Because of its superior performance compared with that of existing algorithms, EMSGA can enable seamless automation of software testing, thereby facilitating the development of different software packages.

Recent and Planned Developments of the Program OxCal

Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 720-730 ◽  
Author(s):  
Christopher Bronk Ramsey ◽  
Sharen Lee
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Software Package ◽  
Model Averaging ◽  
Data Sets ◽  
Radiocarbon Dates ◽  
New Approach ◽  
New Models ◽  
Multiphase Models ◽  
Deposition Models

OxCal is a widely used software package for the calibration of radiocarbon dates and the statistical analysis of 14C and other chronological information. The program aims to make statistical methods easily available to researchers and students working in a range of different disciplines. This paper will look at the recent and planned developments of the package. The recent additions to the statistical methods are primarily aimed at providing more robust models, in particular through model averaging for deposition models and through different multiphase models. The paper will look at how these new models have been implemented and explore the implications for researchers who might benefit from their use. In addition, a new approach to the evaluation of marine reservoir offsets will be presented. As the quantity and complexity of chronological data increase, it is also important to have efficient methods for the visualization of such extensive data sets and methods for the presentation of spatial and geographical data embedded within planned future versions of OxCal will also be discussed.

Optimization of the Closure-Weld Region of Cylindrical Containers for Long-Term Corrosion Resistance Using the Successive Heuristic Quadratic Approximation Technique*

2003 ◽  
Vol 125 (3) ◽  
pp. 533-539 ◽  
Author(s):  
Zekai Ceylan ◽  
Mohamed B. Trabia
Keyword(s):  
Finite Element ◽  
Random Search ◽  
Nonlinear Problems ◽  
Search Space ◽  
Induction Coil ◽  
Quadratic Approximation ◽  
Approximation Technique ◽  
General Corrosion ◽  
Highly Nonlinear

Welded cylindrical containers are susceptible to stress corrosion cracking (SCC) in the closure-weld area. An induction coil heating technique may be used to relieve the residual stresses in the closure-weld. This technique involves localized heating of the material by the surrounding coils. The material is then cooled to room temperature by quenching. A two-dimensional axisymmetric finite element model is developed to study the effects of induction coil heating and subsequent quenching. The finite element results are validated through an experimental test. The container design is tuned to maximize the compressive stress from the outer surface to a depth that is equal to the long-term general corrosion rate of the container material multiplied by the desired container lifetime. The problem is subject to several geometrical and stress constraints. Two different solution methods are implemented for this purpose. First, an off-the-shelf optimization software is used. The results however were unsatisfactory because of the highly nonlinear nature of the problem. The paper proposes a novel alternative: the Successive Heuristic Quadratic Approximation (SHQA) technique. This algorithm combines successive quadratic approximation with an adaptive random search within varying search space. SHQA promises to be a suitable search method for computationally intensive, highly nonlinear problems.

scholarly journals Some Studies on Forming Optimization with Genetic Algorithm

2012 ◽  
Vol 2 (2) ◽  
pp. 105-112
Author(s):  
Ganesh Marotrao KAKANDIKAR ◽  
Vilas M. NANDEDKAR
Keyword(s):  
Genetic Algorithm ◽  
Process Parameters ◽  
Wide Spectrum ◽  
Simulation Software ◽  
Flow Conditions ◽  
Element Analysis ◽  
Blank Holder ◽  
New Approach ◽  
Finite Element Analysis Simulation ◽  
Selection Of

Forming is a compression-tension process involving wide spectrum of operations and flow conditions. The result of the process depends on the large number of parameters and their interdependence. The selection of various parameters is still based on trial and error methods. In this paper the authors presents a new approach to optimize the geometry parameters of circular components, process parameters such as blank holder pressure and coefficient of friction etc. The optimization problem has been formulated with the objective of optimizing the maximum forming load required in Forming. Genetic algorithm is used for the optimization purpose to minimize the drawing load and to optimize the process parameters. A finite element analysis simulation software Fast Form Advanced is used for the validations of the results after optimization.

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