scholarly journals Framework for the Shape Optimization of Aerodynamic Profiles Using Genetic Algorithms

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
D. López ◽  
C. Angulo ◽  
I. Fernández de Bustos ◽  
V. García
Keyword(s):  
Fluid Dynamics ◽  
Genetic Algorithm ◽  
Computational Fluid Dynamics ◽  
Genetic Algorithms ◽  
Shape Optimization ◽  
Computational Fluid Dynamics Cfd

This study developed a framework for the shape optimization of aerodynamics profiles using computational fluid dynamics (CFD) and genetic algorithms. A genetic algorithm code and a commercial CFD code were integrated to develop a CFD shape optimization tool. The results obtained demonstrated the effectiveness of the developed tool. The shape optimization of airfoils was studied using different strategies to demonstrate the capacity of this tool with different GA parameter combinations.

Effects of Volute Cross-Sectional Area Distribution on Performance of Double-Suction Volute Pump

2019 ◽  
Author(s):  
Szu Yung Chen ◽  
Lu Zhang ◽  
Yumiko Sekino ◽  
Hiroyoshi Watanabe
Keyword(s):  
Fluid Dynamics ◽  
Genetic Algorithm ◽  
Computational Fluid Dynamics ◽  
Secondary Flow ◽  
Cross Sections ◽  
Cross Sectional Area ◽  
Sectional Area ◽  
Cross Sectional ◽  
Suction Pump ◽  
Computational Fluid Dynamics Cfd

Abstract The following study describes the optimization design procedure of a double-suction pump. BASELINE pump is designed as inlet nozzle diameter 800 mm and impeller outlet diameter 740 mm. Each component of a BASELINE pump, impeller configurations, discharge volute, and the suction casing were determined by DOE (Design of Experiments) and sensitivity analysis. However, finite selected design parameters for each component are mostly restricted to the free surface design of the pump casing. In this study, the optimization method approach along with steady Computational Fluid Dynamics (CFD) is introduced to achieve the high efficiency request of a double-suction pump. To investigate the matching optimization of the impeller and discharge volute at design point, the full parametric geometry of discharge volute was developed referred to the BASELINE shape and Multi-Objective Genetic Algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm II) was used. Optimization result shows that by increasing the volute cross-sectional area from the volute tongue till the circumferential angle 180 deg. provides lower loss. This is due to the improvement achieved for the better distribution of the velocity gradient within the volute. A validated unsteady computational fluid dynamics (CFD) was also employed to investigate the performance difference between optimized volute design and the BASELINE which correlated to the pressure fluctuation and secondary flow behavior inside the cross-sections from 80% to 120% of nominal flow rate. The result shows that the flow distortion in the streamwise direction is stronger with the BASELINE and sensitively affects the operation stability. This is due to the different secondary flow pattern in the cross-sections, hence demonstrating a design direction of desired volute cross-sectional shape for high-performance can be used in a double-suction volute pump.

scholarly journals Computational Aerodynamics: Solvers and Shape Optimization

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Luigi Martinelli ◽  
Antony Jameson
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Shape Optimization ◽  
Design Process ◽  
Optimization Techniques ◽  
Personal Account ◽  
Computational Aerodynamics ◽  
Computational Fluid Dynamics Cfd

Aeronautics, and in particular aerodynamics, has been one of the main technological drivers for the development of computational fluid dynamics (CFD). This paper presents a personal account of the main advances in the development of solvers and shape optimization techniques, which have contributed to make CFD an essential part of the design process of modern aircraft.

scholarly journals Diesel Breeding

2002 ◽  
Vol 124 (09) ◽  
pp. 53-53
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Genetic Algorithms ◽  
Diesel Engines ◽  
Fuel Efficiency ◽  
Selection Method ◽  
Engine Emissions ◽  
Engine Design ◽  
Computational Fluid Dynamics Cfd ◽  
Advanced Visualization

This article discusses the various ways of improving the performance of diesel engines. A Wisconsin engineer is making use of computation methods that mimic natural selection—or, in this case, maybe eugenics—to improve the performance of diesel engines. Peter Senecal, a partner with Convergent Thinking in Madison, WI, is using computational fluid dynamics (CFD) advanced visualization, and a selection method using genetic algorithms aimed at reducing engine emissions and enhancing fuel efficiency. He has been looking ahead to 2007, when tighter vehicle emissions requirements take effect. Senecal and two of his partners, Keith Richards and Eric Pomraning, are continuing the research into cleaner and more efficient engines. Findings have helped to optimize engine design for increased efficiency and lower emissions—two areas of great importance to engine manufacturers and environmentalists.

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