Abstract The various aspects of experimental rocket engine development, utilizing different fuels, including model studies, component-level tests, and simulated flight conditions, play an essential role in the Rocket propulsion system. The experimental development of a rocket engine or propulsion system depends on the design of the experiment. The challenges faced by classical hybrid rockets, their real-world importance, and potential mitigation methods, ensuring simplicity, cost-effectiveness, and safety without compromising their advantages. It aims to establish state-of-the-art sustainable technologies based on global findings, as most current technologies are still in early stages of commercialization. The development of a rocket engine and propulsion system depends on model studies, component-level tests, and system-level tests. When rocket engines and power plants are tested on the ground, specific techniques and equipment are used to ensure safety. Advanced hybrid rockets, which combine fast-burning fuels, composite motor construction, and innovative design, offer high performance while maintaining cost-effectiveness, environmental sustainability, and simplicity. Future space missions could be revolutionized by these technologies, requiring short-term investments that are green, safe, affordable, and high-performance. The effectiveness of Machine Learning (ML) models is contingent on the availability of high-quality training data, which can be a limiting factor in their application. Incorporating ML into existing engineering workflows poses challenges, requiring interdisciplinary collaboration and expertise.
Sukanta Roga (Mon,) studied this question.