Evolutionary numerical simulation approach for design optimization of gas turbine blade cooling channels

Nagaiah, Narasimha; Geiger, Christopher D.

doi:10.1051/smdo/2014001

Cited by 12 publications

(7 citation statements)

References 12 publications

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“…Furthermore or more detailed description for the turbine cooling system and its significance, the selection of periodic segment from cooling channel, selection of design variables and genetic algorithm control parameters, refer to author's previous publications [1,14].…”

Section: Design Problem Selectionmentioning

confidence: 99%

“…To address above shortcomings of the conventional simulation and experimental design methods, the author first proposed multi-objective optimization framework integrated with commercial numerical simulation tool and nature-inspired evolutionary based genetic algorithm (GA) to solve for two conflicting objective functions [1]. In this research article, the author introduced the third conflicting objective function, iteratively selected suitable genetic algorithm operators values (i.e., crossover and mutation probability) and shown the effect of introducing more design variables while optimizing the design of the complex mechanical component.…”

Section: Introductionmentioning

confidence: 99%

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Application of evolutionary algorithms to optimize cooling channels

Nagaiah

Geiger²

2019

Int. J. Simul. Multidisci. Des. Optim.

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The design and development is a complex, repetitive, and more often difficult task, as design tasks comprising of restraining and conflicting relationships among design variables with more than one design objectives. Conventional methods for solving more than one objective optimization problems is to build one composite function by scalarizing the multiple objective functions into a single objective function with one solution. But, the disadvantages of conventional methods inspired scientists and engineers to look for different methods that result in more than one design solutions, also known as Pareto optimal solutions instead of one single solution. Furthermore, these methods not only involved in the optimization of more than one objectives concurrently but also optimize the objectives which are conflicting in nature, where optimizing one or more objective affects the outcome of other objectives negatively. This study demonstrates a nature-based and bio-inspired evolutionary simulation method that addresses the disadvantages of current methods in the application of design optimization. As an example, in this research, we chose to optimize the periodic segment of the cooling passage of an industrial gas turbine blade comprising of ribs (also known as turbulators) to enhance the cooling effectiveness. The outlined design optimization method provides a set of tradeoff designs to pick from depending on designer requirements.

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Section: Design Problem Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of evolutionary algorithms to optimize cooling channels

Nagaiah

Geiger²

2019

Int. J. Simul. Multidisci. Des. Optim.

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“…Gas turbine, also referred to as a combustion turbine, is commonly used for multiple applications, such as electricity generation, aircraft propulsion and other industrial applications [1]. The gas turbine runs at exceptionally high temperatures between 1600 K and 1900 K in order to improve the efficiency of the turbine [2].…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of the Effectiveness of Jet Impingement Cooling System on the Pressure Side of the Turbine Blade

Kamalulzaman

Azman

Musa

et al. 2021

ARFMTS

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The effectiveness of the jet impingement system on the turbine blade pressure side has been experimentally investigated. The effects of height-to-diameter ratio and air velocity on the effectiveness of jet impingement were studied. Experiments was performed under varying height-to-diameter ratios (H/D = 5, 10, 15, 20) where the distance from the nozzle to the pressure side surface ranged from 20, 40, 60 and 80 mm with a constant nozzle diameter of 4 mm. The Nusselt number is calculated to determine the cooling effect of the pressure side model surface. Experiments were also performed at varying air velocity at 6.4 m/s and 12.6 m/s. The findings revealed that there was no direct relationship between Nusselt number and H/D ratio where the optimum cooling impact at a velocity of 6.4 m/s was found to be at H/D=15, whereas at a velocity of 12.6 m/s it was found to be at H/D=5. The findings also reveal that the amount of Nusselts rises as the air velocity increases.

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“…cooling [1] Over the last 5 decades, there are many research works concerned on gas turbine blade cooling techniques. Analytical, computational and experimental methods are applied to study and improve various cooling approaches in gas turbines [2].…”

Section: Introductionmentioning

confidence: 99%

Rhomboid Concave and Convex Dimples Applied for Cooling in Gas Turbines

2016

IJSR

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The scope of this work is to contribute towards a more efficient cooling design platforms for gas turbines. Concave and convex schemes of rhomboid dimples, arranged irregularly in a cooling channel, are numerically modeled and studied for their effects on heat transfer and cooling of turbine blades. Research is fulfilled in Gambit and Fluent based on a mathematical model and specified boundary conditions for modeling of aero-and thermodynamic characteristics of flow in cooling ducts. The proposed design shape and arrangement of dimples is found to be very promising and effective for intensive heat transfer and cooling in gas turbines and other industrial applications.

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Evolutionary numerical simulation approach for design optimization of gas turbine blade cooling channels

Cited by 12 publications

References 12 publications

Application of evolutionary algorithms to optimize cooling channels

Application of evolutionary algorithms to optimize cooling channels

Experimental Investigation of the Effectiveness of Jet Impingement Cooling System on the Pressure Side of the Turbine Blade

Rhomboid Concave and Convex Dimples Applied for Cooling in Gas Turbines

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