Optimum Design of a Single Circumferential Groove to Improve the Compressor Performance with CFD, Neural Networks and Multi-Objective Genetic Algorithm

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

BAZAZZADEH M.; Agha Seyed Mirzabozorg M.; Hamzezade M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF MECHANICAL ENGINEERING Year:2019 | Volume:48 | Issue:4 (85) Page(s): 57-66

Download Full-Text

Persian Verion

View:

339

Download:

Cites:

Information Journal Paper

Title

Optimum Design of a Single Circumferential Groove to Improve the Compressor Performance with CFD, Neural Networks and Multi-Objective Genetic Algorithm

Author(s)

BAZAZZADEH M. | Agha Seyed Mirzabozorg M. | Hamzezade M. | Issue Writer Certificate

Keywords

Circumferential groove

Optimization

Multi-objective genetic algorithm

Neural networks

Stall margin

CFD

Abstract

The aim of this paper is the optimum design of a single Circumferential groove for NASA Rotor 37, a transonic compressor. The design variables are the width, the depth and the position of the groove. Also the objective functions are the Stall margin and the peak efficiency. The total pressure ratio at the near stall condition is used as a criterion to choose the optimum design. Neural networks are used to model the relation between design variables and objective functions. 123 various design points are simulated by CFD and the results are used to train the networks. Afterwards, a Multi-objective genetic algorithm is used to optimize the design based on the maximum Stall margin and the minimum reduction of the peak efficiency. After sorting the Pareto front according to the Stall margin value, the first design point whose total pressure ratio is larger than the smooth wall condition, is selected as the optimum design. Simulation of the compressor with optimum groove shows the increase of the Stall margin by 6. 2 percent with negligible effect on the efficiency.

Cites

No record.

References

No record.

Cite

APA: Copy

BAZAZZADEH, M., Agha Seyed Mirzabozorg, M., & Hamzezade, M.. (2019). Optimum Design of a Single Circumferential Groove to Improve the Compressor Performance with CFD, Neural Networks and Multi-Objective Genetic Algorithm. JOURNAL OF MECHANICAL ENGINEERING, 48(4 (85) ), 57-66. SID. https://sid.ir/paper/269935/en

Vancouver: Copy

BAZAZZADEH M., Agha Seyed Mirzabozorg M., Hamzezade M.. Optimum Design of a Single Circumferential Groove to Improve the Compressor Performance with CFD, Neural Networks and Multi-Objective Genetic Algorithm. JOURNAL OF MECHANICAL ENGINEERING[Internet]. 2019;48(4 (85) ):57-66. Available from: https://sid.ir/paper/269935/en

IEEE: Copy

M. BAZAZZADEH, M. Agha Seyed Mirzabozorg, and M. Hamzezade, “Optimum Design of a Single Circumferential Groove to Improve the Compressor Performance with CFD, Neural Networks and Multi-Objective Genetic Algorithm,” JOURNAL OF MECHANICAL ENGINEERING, vol. 48, no. 4 (85) , pp. 57–66, 2019, [Online]. Available: https://sid.ir/paper/269935/en

Related Journal Papers