Investigation on the Optimal Design and Flow Mechanism of High Pressure Ratio Impeller with Machine Learning Method
المؤلفون المشاركون
المصدر
International Journal of Aerospace Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-11-29
دولة النشر
مصر
عدد الصفحات
11
الملخص EN
The optimization of high-pressure ratio impeller with splitter blades is difficult because of large-scale design parameters, high time cost, and complex flow field.
So few relative works are published.
In this paper, an engineering-applied centrifugal impeller with ultrahigh pressure ratio 9 was selected as datum geometry.
One kind of advanced optimization strategy including the parameterization of impeller with 41 parameters, high-quality CFD simulation, deep machine learning model based on SVR (Support Vector Machine), random forest, and multipoint genetic algorithm (MPGA) were set up based on the combination of commercial software and in-house python code.
The optimization objective is to maximize the peak efficiency with the constraints of pressure-ratio at near stall point and choked mass flow.
Results show that the peak efficiency increases by 1.24% and the overall performance is improved simultaneously.
By comparing the details of the flow field, it is found that the weakening of the strength of shock wave, reduction of tip leakage flow rate near the leading edge, separation region near the root of leading edge, and more homogenous outlet flow distributions are the main reasons for performance improvement.
It verified the reliability of the SVR-MPGA model for multiparameter optimization of high aerodynamic loading impeller and revealed the probable performance improvement pattern.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yi, Weilin& Cheng, Hongliang. 2020. Investigation on the Optimal Design and Flow Mechanism of High Pressure Ratio Impeller with Machine Learning Method. International Journal of Aerospace Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1168384
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yi, Weilin& Cheng, Hongliang. Investigation on the Optimal Design and Flow Mechanism of High Pressure Ratio Impeller with Machine Learning Method. International Journal of Aerospace Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1168384
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yi, Weilin& Cheng, Hongliang. Investigation on the Optimal Design and Flow Mechanism of High Pressure Ratio Impeller with Machine Learning Method. International Journal of Aerospace Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1168384
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1168384
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر