Open Access
Analysis and relief method of reentry aerodynamic load based on matched asymptotic expansions method
Author(s) -
Xiaoxu Du,
Haiyang Li
Publication year - 2014
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.63.200401
Subject(s) - reentry , aerodynamics , ordinary differential equation , monte carlo method , differential equation , computation , aerodynamic force , closed form expression , control theory (sociology) , computer science , mathematics , mechanics , physics , mathematical analysis , algorithm , statistics , medicine , cardiology , control (management) , artificial intelligence
Reentry velocity of lunar module reaches the second cosmic velocity, which could make the aerodynamic environment insupportable. So it is essential to analysis the reentry aerodynamic load. The equation of motion for reentry vehicle is a group of ordinary differential equations, and numerical methods are inadequate for online mission because their computation amount is too large. An analytical method of solving the reentry equation of motion is proposed in this paper to analyze the reentry aerodynamic load. First, matched asymptotic method is used to obtain solutions of longitudinal equation of motion in outer and inner region independently and combine them to obtain a unified closed-form solution. Reentry aerodynamic load has been analyzed in three fragments using the closed-form solution, and approximate solution of load is compared with the exact solution. Second, suppositional initial conditions are obtained by solving the closed-form solution using current state, then an analytical method of predicting the first load peak is proposed, and the relative prediction error is analyzed for different bank angles. Third, the load relief method based on load peak prediction is proposed, which can redistribute the total dissipated energy in the whole reentry process, and the validity of the method is verified by Monte Carlo simulation.