Dynamic modeling and prediction of post launch rebound mechanism of tethered space net

This study presents a mathematical model to analyze the complex dynamics and rebound mechanism of the Tethered Space Net (TSN). Using the lumped mass method, a dynamic model of the TSN is developed and validated through ground swing testing. Building on this foundation, a novel predictive model is introduced to reveal the rebound mechanism of the TSN. This model incorporates TSN's momentum and energy, utilizing a rebound index and a characterization function to forecast potential rebounds and quantitatively describe the rebound state. The primary cause of the TSN rebound is the uneven speed distribution across the net surface, which results from the local stretching of tethers after launch. This phenomenon leads to a rebound in TSN. The proposed model effectively elucidates this mechanism and proves adaptable to various types of rebound scenarios. A subsequent parametric analysis provides a comprehensive understanding of the rebound behavior described by the model. Furthermore, Fuzzy logic is integrated into the predictive model to enhance the precision of the rebound timing forecasts. Results from 1,000 random tests demonstrate the model's accuracy, with a maximum error of <4 % in predicting rebound time.