Tanvi Agrawal | Searcharxiv

arXiv2024

Non-Pyrotechnic Radial Deployment Mechanism for Payloads in Sounding Rockets

A novel, non-pyrotechnic payload deployment mechanism tailored for sounding rockets is introduced in this research paper. The mechanism addresses the challenge of efficiently and compactly deploying payloads radially during a single launch, featuring a cylindrical carrier structure actuated by a rack-pinion mechanism. Powered by a servo motor, the carrier structure translates to enable radial ejection of payloads. The paper presents the mechanism's design and conducts a comprehensive performance analysis, including structural stability, system dynamics and power requirements. A simulation model is developed to assess payload deployment behavior under various conditions, demonstrating the mechanism's viability and efficiency for deploying multiple payloads within a single sounding rocket launch. The mechanism's adaptability to accommodate diverse payload types, sizes and weights enhances its versatility, while its radial deployment capability allows payloads to be released at different altitudes, offering greater flexibility for scientific experiments. The paper concludes that this innovative payload radial deployment mechanism represents a significant advancement in sounding rocket technology and holds promise for a wide array of applications in both scientific and commercial missions.

eess.SY↗

arXiv2023

Optimization of a Runge-Kutta 4th Order Method-based Airbrake Control System for High-Speed Vehicles Using Neural Networks

The Runge-Kutta 4th Order (RK4) technique is extensively employed in the numerical solution of differential equations for airbrake control system design. However, its computational efficacy may encounter restrictions when dealing with high-speed vehicles that experience intricate aerodynamic forces. Using a Neural Network, a unique technique to improving the RK4-based airbrakes code is provided. The Neural Network is trained on numerous aspects of the high-speed vehicle as well as the current status of the airbrakes. This data was generated through the traditional RK4-based simulations and can predict the state of the airbrakes for any given state of the rocket in real-time. The proposed approach is demonstrated on a high-speed airbrakes control system, achieving comparable or better performance than the traditional RK4-based system while significantly reducing computational time by reducing the number of mathematical operations. The proposed method can adapt to changes in flow conditions and optimize the airbrakes system in real-time.

math.OC↗