Airfoil shape optimization using improved simple genetic algorithm (ISGA)

Paper presented at the 5th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, South Africa, 1-4 July, 2007.To study the efficiency of genetic algorithms (GAs) in the optimization of aerodynamic shapes, the shape of an airfoil was optimized by a genetic algorithm to obtain maximum lift to drag ratio and maximum lift. The flow field is assumed to be two dimensional, Invicsid, transonic and is analyzed numerically. The camber line and thickness distribution of the airfoil were modeled by a fourth order polynomial. The airfoil chord length was assumed constant. Also, proper boundary conditions were applied. A finite volume method using the first order Roe’s flux approximation and time marching (explicit) method was used for the flow analysis. The simple genetic algorithm (SGA) was used for optimization. This algorithm could find the optimum point of this problem in an acceptable time frame. Results show that the GA could find the optimum point by examining only less than 0.1% of the total possible cases. Meanwhile, effects of parameters of GA such as population size in each generation, mutation probability and crossover probability on accuracy and speed of convergence of this SGA were studied. These parameters have very small effects on the accuracy of the genetic algorithm, but they have a sensible effect on speed of convergence. The parameters of this genetic algorithm were improved to obtain the minimum run time of optimization procedure and to maximize the speed of convergence of this genetic algorithm. Robustness and efficiency of this algorithm in optimizing the shape of the airfoils were shown. Also, by finding the optimum values of its parameters, maximum speed and minimum run time was obtained. It is shown that for engineering purposes, the speed of GAs is incredibly high, and acceptable results are sought by a fairly low number of generations of computations.cs201

Numerical Wave Propagation And Steady-State Solutions

CONTENTS ACKNOWLEDGEMENTS : : : : : : : : : : : : : : : : : : : : : : : : : : ii LIST OF FIGURES : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : vi LIST OF APPENDICES : : : : : : : : : : : : : : : : : : : : : : : : : : : : xiii CHAPTER I. INTRODUCTION : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.1 Wave-like Solutions to PDE's : : : : : : : : : : : : : : : : : : 1 1.1.1 Non-dispersive Scalar Equations : : : : : : : : : : : 2 1.1.2 Dispersive Scalar Equations : : : : : : : : : : : : : 3 1.1.3 Systems of Equations : : : : : : : : : : : : : : : : : 5 1.2 Behavior of the Euler Equations : : : : : : : : : : : : : : : : 8 1.2.1 Euler Equations : : : : : : : : : : : : : : : : : : : : 8 1.3 Error Waves or Residual Waves : : : : : : : : : : : : : : : : : 14 1.3.1 Experimental study of Residual Waves&lt

Numerical Study of Pollutant Emissions in a Jet Stirred Reactor under Elevated Pressure Lean Premixed Conditions

Numerical study of pollutant emissions (NO and CO) in a Jet Stirred Reactor (JSR) combustor for methane oxidation under Elevated Pressure Lean Premixed (EPLP) conditions is presented. A Detailed Flow-field Simplified Chemistry (DFSC) method, a low computational cost method, is employed for predicting NO and CO concentrations. Reynolds Averaged Navier Stokes (RANS) equations with species transport equations are solved. Improved-coefficient five-step global mechanisms derived from a new evolutionary-based approach were taken as combustion kinetics. For modeling turbulent flow field, Reynolds Stress Model (RSM), and for turbulence chemistry interactions, finite rate-Eddy dissipation model are employed. Effects of pressure (3, 6.5 bars) and inlet temperature (408–573 K) over a range of residence time (1.49–3.97 ms) are numerically examined. A good agreement between the numerical and experimental distribution of NO and CO was found. The effect of decreasing the operating pressure on NO generation is much more than the effect of increase in the inlet temperature

Prostate Tumor Volume Measurement with Combined T2-weighted Imaging and Diffusion-weighted MR: Correlation with Pathologic Tumor Volume1

Combined T2-weighted and diffusion-weighted MR imaging performed by using an apparent diffusion coefficient cutoff value of 0.0016 mm2/sec is significantly more accurate than T2-weighted imaging alone in the measurement of tumor volume in the peripheral zone of the prostate