Aeromechanical optimization of first row compressor test stand blades using a hybrid machine learning model of genetic algorithm, artificial neural networks and design of experiments-Reference-Cited by-同舟云学术

Aeromechanical optimization of first row compressor test stand blades using a hybrid machine learning model of genetic algorithm, artificial neural networks and design of experiments

Published:2019-01-01 Issue:1 Volume:13 Page:892-904
ISSN:1994-2060
Container-title:Engineering Applications of Computational Fluid Mechanics
language:en
Short-container-title:Engineering Applications of Computational Fluid Mechanics

Author:

Ghalandari Mohammad¹,Ziamolki Alireza¹,Mosavi Amir²³,Shamshirband Shahaboddin⁴⁵^ORCID,Chau Kwok-Wing⁶,Bornassi Saeed¹

Affiliation:

1. Research and Development Department, MAPNA Turbine Engineering and Manufacturing Company (TUGA), Karaj, Iran

2. School of the Built Environment, Oxford Brookes University, Oxford, UK

3. Kando Kalman Faculty of Electrical Engineering, Institute of Automation, Obuda University, Budapest, Hungary

4. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam

5. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

6. Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, People’s Republic of China

Publisher

Informa UK Limited

Subject

Modelling and Simulation,General Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/19942060.2019.1649196

Reference22 articles.

1. Ashihara, K., Goto, A., Guo, S. & Okamoto, H. (2004). Optimization of microturbine aerodynamics using CFD, inverse design and FEM structural analysis: 1st report – compressor design. Paper presented at the ASME Turbo eXpo 2004: Power for Land, Sea, and Air.

2. Demeulenaere, A., Ligout, A. & Hirsch, C. (2004). Application of multipoint optimization to the design of turbomachinery blades. Paper presented at the ASME Turbo Expo 2004: Power for Land, Sea, and Air.

3. An Integrated Design and Optimization Approach for Radial Inflow Turbines—Part II: Multidisciplinary Optimization Design

4. Computational intelligence approach for modeling hydrogen production: a review

5. Numerical simulation of nanofluid flow inside a root canal

Cited by 89 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction of Aerodynamic Forces at the Tip of the Compressor Blades Based on Multi-scale 1DCNN Combined with CBAM;Thin-Walled Structures;2024-10

2. Off-design performance analysis of a radial fan using experimental, computational, and artificial intelligence approaches;European Journal of Mechanics - B/Fluids;2024-03

3. BIM adoption in sustainability, energy modelling and implementing using ISO 19650: A review;Ain Shams Engineering Journal;2024-01

4. Optimization of Urban Landscape Design Based on Interactive Genetic Algorithm;2023 5th International Symposium on Smart and Healthy Cities (ISHC);2023-12-16

5. Thermal conductivity improvement in a green building with Nano insulations using machine learning methods;Energy Reports;2023-12