Structural Optimization of the Aircraft NACA Inlet Based on BP Neural Networks and Genetic Algorithms
المؤلفون المشاركون
Li, Zhimao
Chen, Changdong
Pei, Houju
Kong, Benben
المصدر
International Journal of Aerospace Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-01
دولة النشر
مصر
عدد الصفحات
9
الملخص EN
With the development of the increasing demand for cooling air in cabin and electronic components on aircraft, it urges to present an energy-efficient optimum method for the ram air inlet system.
A ram air performance evaluation method is proposed, and the main structural parameters can be extended to a certain type of aircraft.
The influence of structural parameters on the ram air performance is studied, and a database for the performance is generated.
A new method of integrating the BP neural networks and genetic algorithm is used for structure optimization and is proven effective.
Moreover, the optimum result of the structure of the NACA ram air inlet system is deduced.
Results show that (1) the optimization algorithm is efficient with less prediction error of the mass flow rate and fuel penalty.
The average relative error of the mass flow rate is 1.37%, and the average relative error of the fuel penalty is 1.41% in the full samples.
(2) Predicted deviation analysis shows very little difference between optimized and unoptimized design.
The relative error of the mass flow rate is 0.080% while that of the fuel penalty is 0.083%.
The accuracy of the proposed optimization method is proven.
(3) The mass flow rate after optimization is increased to 2.506 kg/s, and the fuel penalty is decreased by 74.595 Et kg.
The BP neural networks and genetic algorithms are studied to optimize the design of the ram air inlet system.
It is proven to be a novel approach, and the efficiency can be highly improved.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Zhimao& Chen, Changdong& Pei, Houju& Kong, Benben. 2020. Structural Optimization of the Aircraft NACA Inlet Based on BP Neural Networks and Genetic Algorithms. International Journal of Aerospace Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1168408
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Zhimao…[et al.]. Structural Optimization of the Aircraft NACA Inlet Based on BP Neural Networks and Genetic Algorithms. International Journal of Aerospace Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1168408
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Zhimao& Chen, Changdong& Pei, Houju& Kong, Benben. Structural Optimization of the Aircraft NACA Inlet Based on BP Neural Networks and Genetic Algorithms. International Journal of Aerospace Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1168408
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1168408
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