On Using Neural Networks for Turbofan Aircraft Performance Analysis

Mostafa El-Salamony; Ibrahim A. Shaaban; Omar Seif Elnasr; Mohammed Wael

doi:10.1109/NILES56402.2022.9942435

On Using Neural Networks for Turbofan Aircraft Performance Analysis

Mostafa El-Salamony
, Ibrahim A. Shaaban
, Omar Seif Elnasr
, Mohammed Wael

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In aircraft design process, to ensure a given design is efficient and economical to carry out its mission, its performance shall be tested. For rapid design requirements, application of artificial intelligence and neural networks (ANN) is proposed hereafter to calculate the performance analysis in a fast way instead of using the complex nonlinear 'traditional' way. Hence, a Performance Solver code is coded and a database of several turbofan passenger aircraft is created to feed a neural network. Up to our knowledge, this is considered as the first time to use ANNs in such an application. The results achieved good accuracy in an acceptable computational time and low level of complexity.

Original language	English
Title of host publication	NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	345-348
Number of pages	4
ISBN (Electronic)	9781665452410
DOIs	https://doi.org/10.1109/NILES56402.2022.9942435
State	Published - 2022
Externally published	Yes
Event	4th Novel Intelligent and Leading Emerging Sciences Conference, NILES 2022 - Giza, Egypt Duration: 22 Oct 2022 → 24 Oct 2022

Publication series

Name	NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings

Conference

Conference	4th Novel Intelligent and Leading Emerging Sciences Conference, NILES 2022
Country/Territory	Egypt
City	Giza
Period	22/10/22 → 24/10/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

AI
ANN
aircraft
airplane
machine learning
neural network
performance
turbofan

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Computer Vision and Pattern Recognition
Safety, Risk, Reliability and Quality
Instrumentation

Access to Document

10.1109/NILES56402.2022.9942435

Cite this

El-Salamony, M., Shaaban, I. A., Elnasr, O. S., & Wael, M. (2022). On Using Neural Networks for Turbofan Aircraft Performance Analysis. In NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings (pp. 345-348). (NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NILES56402.2022.9942435

El-Salamony, Mostafa ; Shaaban, Ibrahim A. ; Elnasr, Omar Seif et al. / On Using Neural Networks for Turbofan Aircraft Performance Analysis. NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 345-348 (NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings).

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title = "On Using Neural Networks for Turbofan Aircraft Performance Analysis",

abstract = "In aircraft design process, to ensure a given design is efficient and economical to carry out its mission, its performance shall be tested. For rapid design requirements, application of artificial intelligence and neural networks (ANN) is proposed hereafter to calculate the performance analysis in a fast way instead of using the complex nonlinear 'traditional' way. Hence, a Performance Solver code is coded and a database of several turbofan passenger aircraft is created to feed a neural network. Up to our knowledge, this is considered as the first time to use ANNs in such an application. The results achieved good accuracy in an acceptable computational time and low level of complexity.",

keywords = "AI, ANN, aircraft, airplane, machine learning, neural network, performance, turbofan",

author = "Mostafa El-Salamony and Shaaban, \{Ibrahim A.\} and Elnasr, \{Omar Seif\} and Mohammed Wael",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th Novel Intelligent and Leading Emerging Sciences Conference, NILES 2022 ; Conference date: 22-10-2022 Through 24-10-2022",

year = "2022",

doi = "10.1109/NILES56402.2022.9942435",

language = "English",

series = "NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "345--348",

booktitle = "NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings",

address = "United States",

}

El-Salamony, M, Shaaban, IA, Elnasr, OS & Wael, M 2022, On Using Neural Networks for Turbofan Aircraft Performance Analysis. in NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings. NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 345-348, 4th Novel Intelligent and Leading Emerging Sciences Conference, NILES 2022, Giza, Egypt, 22/10/22. https://doi.org/10.1109/NILES56402.2022.9942435

On Using Neural Networks for Turbofan Aircraft Performance Analysis. / El-Salamony, Mostafa; Shaaban, Ibrahim A.; Elnasr, Omar Seif et al.
NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. p. 345-348 (NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shaaban, Ibrahim A.

AU - Elnasr, Omar Seif

AU - Wael, Mohammed

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N2 - In aircraft design process, to ensure a given design is efficient and economical to carry out its mission, its performance shall be tested. For rapid design requirements, application of artificial intelligence and neural networks (ANN) is proposed hereafter to calculate the performance analysis in a fast way instead of using the complex nonlinear 'traditional' way. Hence, a Performance Solver code is coded and a database of several turbofan passenger aircraft is created to feed a neural network. Up to our knowledge, this is considered as the first time to use ANNs in such an application. The results achieved good accuracy in an acceptable computational time and low level of complexity.

AB - In aircraft design process, to ensure a given design is efficient and economical to carry out its mission, its performance shall be tested. For rapid design requirements, application of artificial intelligence and neural networks (ANN) is proposed hereafter to calculate the performance analysis in a fast way instead of using the complex nonlinear 'traditional' way. Hence, a Performance Solver code is coded and a database of several turbofan passenger aircraft is created to feed a neural network. Up to our knowledge, this is considered as the first time to use ANNs in such an application. The results achieved good accuracy in an acceptable computational time and low level of complexity.

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KW - airplane

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KW - neural network

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El-Salamony M, Shaaban IA, Elnasr OS, Wael M. On Using Neural Networks for Turbofan Aircraft Performance Analysis. In NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. p. 345-348. (NILES 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference, Proceedings). doi: 10.1109/NILES56402.2022.9942435

On Using Neural Networks for Turbofan Aircraft Performance Analysis

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this