Date of Award
5-2024
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Mechanical and Civil Engineering
First Advisor
Hamidreza Najafi
Second Advisor
Darshan G. Pahinkar
Third Advisor
Jian Du
Fourth Advisor
Ashok Pandit
Abstract
Thermal protection system (TPS) plays a pivotal role in safeguarding space vehicles from extreme aerothermal heating during atmospheric entry. To ensure effective thermal management, Hybrid Thermal Protection seamlessly integrating both active and passive TPS is an innovative solution. The passive TPS consists of an insulative layer on vehicle skin to counteract the aerothermal heat. Although a thicker layer enhances insulation, a trade-off arises between the thickness of the passive layer and the spacecraft’s weight. Beneath the passive TPS layer lies the active TPS functioning as a heat exchanger where the vehicle fuel liquid is considered as coolant. The effectiveness of the active TPS is influenced by parameters such as the coolant flowrate and the design of the flow channel. In this paper, two potential designs for the active TPS are considered and the resulting hybrid systems are studied through parametric analysis and optimization using multi-objective optimization through genetic algorithm. Two objective functions including the total weight of the system as well as the required pumping power are considered and parameters including coolant velocity, thickness of passive TPS layer and thickness of gyroid are used as the optimization variables. The methodology used and results produced from this study provide insights regarding the design and optimization of hybrid TPS and the potentials for using triply iv periodic minimal surfaces to achieve enhanced heat transfer performance. The gyroid configuration demonstrated enhanced performance for both temperature and heat flux within the range of design parameters that were used for this study. The measurement of incoming heat flux is an important parameter of TPS but this is not directly possible. This study also includes a solution to inverse heat transfer problem using a deep learning model that can predict the incoming heat flux on top of a hybrid TPS layer based on the bottom surface temperature.
Recommended Citation
Nabi, Syed Arafun, "Methodologies for Optimization and Surface Heat Flux Estimation for Hybrid Thermal Protection Systems" (2024). Theses and Dissertations. 1423.
https://repository.fit.edu/etd/1423