Enhancements of the Thermal Uniformity Inside a Gas Turbine Dilution Section Using Dimensional Optmization
| Autor: | Tarek ElGammal, Ryoichi S. Amano, Osama M. Selim |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Gas turbines
0303 health sciences Materials science Renewable Energy Sustainability and the Environment Mechanical Engineering Energy Engineering and Power Technology Mechanics Dilution 03 medical and health sciences 0302 clinical medicine Fuel Technology Geochemistry and Petrology Section (archaeology) 030220 oncology & carcinogenesis Thermal 030304 developmental biology |
| Zdroj: | Journal of Energy Resources Technology. 143 |
| ISSN: | 1528-8994 0195-0738 |
| DOI: | 10.1115/1.4049284 |
| Popis: | In the dilution section of the gas turbine, the flow and thermal mixing between the cold radial jets and hot mainstream is always a matter of interest to generate a consistent thermal profile, extending the longevity of the turbine blades. Multiple researches explored the topic experimentally and numerically, and new designs have been evaluated, including a central streamlined body with swirlers inside the dilution zone. Moreover, the dimensional aspects (diameter, length, and position) of the streamlined body can help in generating more uniform thermal profiles, but with the cost of increased pressure drop. Various design iterations are needed to be tested and assessed based on minimizing the contradicting uniformity number and pressure drop. Such a process is time and resources consuming if not wisely managed. The paper proposes a solution for the current problem by the integration of the “Design of Experiment/Optimization Algorithms” generator with the computational fluid dynamics solver. The outcomes from three different algorithms (ULH, MOGA-II, and HYBRID) are statistically analyzed to understand inputs-outputs correlations, develop response surface methodology, and help in finding the optimal designs. The suggested HYBRID optimization provided a better optimal curve with improvements of 69% and 15% in the thermal uniformity and pressure drop, respectively. The correlation coefficients stressed on the importance of the diameter as the highest influencer with inverse and direct correlations with uniformity and pressure drop, respectively. Finally, the Kriging response surface model enabled more optimal designs and a better understanding of the effective ranges of the three inputs. |
| Databáze: | OpenAIRE |
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