On the optimization of a vertical twisted tape arrangement in a channel subjected to MWCNT–water nanofluid by coupling numerical simulation and genetic algorithm

2020 ◽  
Author(s):  
Farzad Pourfattah ◽  
Majid Sabzpooshani ◽  
Davood Toghraie ◽  
Amin Asadi
Keyword(s):  
Numerical Simulation ◽  
Genetic Algorithm ◽  
Twisted Tape

scholarly journals Numerical Simulation of Shipright Using Genetic Algorithm

2000 ◽  
Vol 2000 (188) ◽  
pp. 553-558 ◽  
Author(s):  
Yasuhisa Okumoto ◽  
Kouhei Murase ◽  
Asako Tanaka
Keyword(s):  
Numerical Simulation ◽  
Genetic Algorithm

Parameter Identification of Thermal Visco-Plastic Model Considering Dynamic Recrystallization

2007 ◽  
Vol 561-565 ◽  
pp. 1869-1874
Author(s):  
Quan Lin Jin ◽  
Yan Shu Zhang
Keyword(s):  
Numerical Simulation ◽  
Genetic Algorithm ◽  
Parameter Identification ◽  
Optimization Methods ◽  
Optimization Method ◽  
Special Program ◽  
Global Optimization Method ◽  
Material Parameters ◽  
Real Coded Genetic Algorithm ◽  
Deformation Test

A hybrid global optimization method combining the Real-coded genetic algorithm and some classical local optimization methods is constructed and applied to develop a special program for parameter identification. Finally, the parameter identification for both 26Cr2Ni4MoV steel and AZ31D magnesium alloy is carried out by using the program. A comparison of deformation test and numerical simulation shows that the parameter identification and the obtained two sets of material parameters are all available.

Tournament Evaluation System Applying Win-Lose Result Presumption Considering Kansei Evaluation by Multiple People

2012 ◽  
Vol 16 (3) ◽  
pp. 453-461 ◽  
Author(s):  
Hiroshi Takenouchi ◽  
◽  
Masataka Tokumaru ◽  
Noriaki Muranaka ◽  
Keyword(s):  
Numerical Simulation ◽  
Genetic Algorithm ◽  
Evaluation System ◽  
Numerical Evaluation ◽  
Previous Method ◽  
Interactive Genetic Algorithm ◽  
Basic Model ◽  
Candidate Solution ◽  
Need To Evaluate ◽  
Simulation Results

We describe an Interactive Genetic Algorithm (IGA) with tournament evaluation for applying win-lose results obtained from an evaluation using multiple people. In our previous study, we developed an IGA with tournament evaluation as a basic model for evaluating candidate solutions using votes from multiple people [13]. However, tournament evaluation requires that IGA users evaluate the same candidate solution multiple times. Therefore, our previous method can reduce a user’s motivation for evaluating the solution. In addition, the number of users participating in a vote may decrease because of the decreasedmotivation to evaluate. To overcome this difficulty, we propose the application of a win-lose result presumption based on the tournament evaluation records of multiple people. When a system-based presumption is possible, the win-lose result presumption automatically determines the preferred and non-preferred candidates in each round. This method can reduce the number of times that users need to evaluate the same candidate solution. The effectiveness of the proposed method is verified using a numerical simulation that employs multiple numerical evaluation agents instead of human evaluators. The simulation results show an initial convergent improvement with the proposed method.

scholarly journals OPTIMIZATION OF MULTISPAN RIBBED PLYWOOD PLATE MACROSTRUCTURE FOR MULTIPLE LOAD CASES

2013 ◽  
Vol 19 (5) ◽  
pp. 696-704 ◽  
Author(s):  
Jānis Šliseris ◽  
Kārlis Rocēns
Keyword(s):  
Neural Network ◽  
Numerical Simulation ◽  
Genetic Algorithm ◽  
Finite Element Method ◽  
Artificial Neural Network ◽  
Multilayer Plate ◽  
Maximal Stress ◽  
Optimization Methodology ◽  
Stress Criteria ◽  
Multiple Load

This paper discusses an optimized structural plate of plywood composite that consists of top and bottom plywood flanges and a core of plywood ribs. The objective function is structure's weight. Typical constrains – maximal stress criteria and maximal deformation criteria – are used. The optimization is done by Genetic Algorithm (GA), and optimization results are used to train Feed-Forward Artificial Neural Network. The numerical simulation of plywood structure is done by using classical linear Kirchoff–Love theory of multilayer plate and Finite Element Method. As a result, an effective optimization methodology for plywood composite material is proposed. The most rational (according to strength-stiffness criteria) plywood composite macrostructure is obtained for some typical cases.

Research on Surface Roughness Prediction Model Based on Genetic Algorithm for Optical Ultra-Precision Machining

2007 ◽  
Vol 10-12 ◽  
pp. 369-373
Author(s):  
Jian Jun Du ◽  
Chi Fai Cheung ◽  
Suet To ◽  
Z.Y. Liu
Keyword(s):  
Numerical Simulation ◽  
Genetic Algorithm ◽  
Surface Roughness ◽  
Linear Regression ◽  
Precision Machining ◽  
Mathematics Model ◽  
Simulation Test ◽  
New Model ◽  
Roughness Prediction ◽  
Ultra Precision

In this paper a dynamic non-linear mathematics model is proposed to predict the surface roughness in optical ultra-precision machining, which can be automatically built by evoling computer program of genetic algorithm. The new model can improve the fitting and predicting accuracy, compared with the traditional linear regression model. The numerical simulation test proves the effectiveness and accuracy of new model.

scholarly journals A NUMERICAL SIMULATION SYSTEM FOR MOBILE TELEPHONY BASE STATION EMF EXPOSURE USING SMARTPHONES AS PROBES AND A GENETIC ALGORITHM TO IMPROVE ACCURACY

2020 ◽  
Vol 87 ◽  
pp. 111-129
Author(s):  
Pierre Combeau ◽  
Nicolas Noé ◽  
François Gaudaire ◽  
Steve Joumessi Demeffo ◽  
Jean-Benoit Dufour
Keyword(s):  
Numerical Simulation ◽  
Genetic Algorithm ◽  
Base Station ◽  
Simulation System ◽  
Mobile Telephony ◽  
Improve Accuracy
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