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Active Learning Enhanced Neural Networks for Aerodynamics Design in Military and Civil Aviation Nasir, Sheharyar; Hussain, Hafiz Khawar; Ibrar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5036

Abstract

The use of adaptive neural networks in aerodynamics design has become one of the most promising recent invention in both military and civil aircraft design, providing new approaches to the solution of a number of problematic issues connected with optimization of aircraft performance. Herein, this review provides a synthesis of neural networks and aerodynamics by emphasizing their ability to facilitate advanced design engineering, expedite the design process, as well as promote the usability and effectiveness of higher performing systems. Neural networks are involved in shape optimization, drag cutting, real time aircraft modifications and other key issue areas attesting to their capability in handling aerodynamics. Employing methods like supervised learning, reinforcement learning, and physics aware neural networks these networks can simulate non-linear multidimensional systems and arrive at solutions that are impossible through ordinary methods. The usage of these tools has been pushed even more over time, due to new advancements such as High-Performance Computing and specialized hardware. The review also considers effective application of systematic adaptive neural networks in the military and civil aviation hypersonic vehicle design, stealth aircraft design and optimization, the new fuel-efficient wings, and flight efficiency systems for real time control. The results put into evidence benefits of neural networks for cutting down design cycles, boosting MPG, increasing safety, and encouraging environmentally friendly solutions. The future for aerospace engineering will be in the hands of adaptive neural networks as part of the development of the aviation industry, dictating new advancements in both military and commercial aviation.
Active Learning Enhanced Neural Networks for Aerodynamics Design in Military and Civil Aviation Nasir, Sheharyar; Hussain, Hafiz Khawar; Ibrar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5036

Abstract

The use of adaptive neural networks in aerodynamics design has become one of the most promising recent invention in both military and civil aircraft design, providing new approaches to the solution of a number of problematic issues connected with optimization of aircraft performance. Herein, this review provides a synthesis of neural networks and aerodynamics by emphasizing their ability to facilitate advanced design engineering, expedite the design process, as well as promote the usability and effectiveness of higher performing systems. Neural networks are involved in shape optimization, drag cutting, real time aircraft modifications and other key issue areas attesting to their capability in handling aerodynamics. Employing methods like supervised learning, reinforcement learning, and physics aware neural networks these networks can simulate non-linear multidimensional systems and arrive at solutions that are impossible through ordinary methods. The usage of these tools has been pushed even more over time, due to new advancements such as High-Performance Computing and specialized hardware. The review also considers effective application of systematic adaptive neural networks in the military and civil aviation hypersonic vehicle design, stealth aircraft design and optimization, the new fuel-efficient wings, and flight efficiency systems for real time control. The results put into evidence benefits of neural networks for cutting down design cycles, boosting MPG, increasing safety, and encouraging environmentally friendly solutions. The future for aerospace engineering will be in the hands of adaptive neural networks as part of the development of the aviation industry, dictating new advancements in both military and commercial aviation.
3D Printing Techniques: Transforming Manufacturing with Precision and Sustainability Shahrukh Khan Lodhi; Ahmad Yousaf Gill; Ibrar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 3 (2024): International Journal of Multidisciplinary Sciences and Arts, Article July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i3.4568

Abstract

Additive manufacturing, sometimes known as 3D printing, has advanced quickly and has the potential to revolutionize a number of industries. This analysis examines the noteworthy developments and upcoming trends in 3D printing, emphasizing the effects on accuracy, eco-friendliness, and industrial uses. The first section of the book explores how advances in materials have affected 3D printing, with a focus on the creation of thermoplastics, photopolymers, metal powders, ceramics, and bio-printable materials. These developments have increased 3D printing's potential and made it possible to produce components that are biocompatible, customizable, and high-performing. The topic of sustainability is then brought up, with particular emphasis on how 3D printing helps to cut down on energy and material waste. The key components of the technology's environmental benefits are its on-demand part production capability and its utilization of environmentally benign resources like recycled and biodegradable polymers. The essay also discusses the difficulties associated with material disposal and energy use in the perspective of sustainability. Examining industrial applications, the paper emphasizes how 3D printing is revolutionizing industries like consumer products, construction, healthcare, automotive, and aerospace. The technology's versatility and effect across multiple fields are demonstrated by highlighting its role in enabling rapid prototyping, customized production, and novel design solutions. The assessment highlights major developments in 3D printing for the future, such as advances in materials science, technological advancements, and integration with other cutting-edge fields like artificial intelligence, the Internet of things, and robotics. Highlighted are the possibilities for increased customization, on-demand production, and sustainability, demonstrating how these advancements will continue to influence the market? The assessment highlights the significant effects that 3D printing will have on manufacturing and design, emphasizing how technology may spur innovation, lessen its negative effects on the environment, and adapt to changing needs in a variety of industries. Technology will play an ever-more-important role in improving sustainability and revolutionizing sectors as it develops.