Fluid-Structure Impact Modeling and Risk Assessment

• Main Author: Mitchell, Kenneth Ned
• Other Authors: Sankaran Mahadevan
• Format: Others
• Language: en
• Published: VANDERBILT 2009
• Subjects: Civil Engineering
• Online Access: http://etd.library.vanderbilt.edu/available/etd-07252009-232535/

Fluid-structure impact analysis is a topic of increasing interest to engineers and designers in the shipbuilding and aerospace industries, and recent advances in the availability of computational power have allowed for risk assessments of these types of problems to be conducted. The space shuttle solid rocket booster (SRB) splashdown event is one example of a complex structural system experiencing damage as a result of water impact. NASA witnessed several instances of the damage to the forward skirt of the SRB following shuttle launches in the 1990s. However, initial risk assessments of SRB impact based upon finite element modeling produced predictions that did not agree with the observed frequency of damage. The discrepancy was attributed to model uncertainty, computational approximations in the coupled fluid and structural domains, and uncertainty regarding the structural failure definition. The research presented herein addresses these issues through a systematic model development and validation framework for fluid-structure impact analysis. The details of the finite element approach for modeling of the SRB splashdown sequence are presented, along with a systematic approach for mesh refinement in the fluid and structural analysis domains. A model validation exercise is conducted using laboratory experimental data obtained with a small-scale aluminum cylinder and water drop tank, thus lending increased confidence in the corresponding finite element model prediction. The buckling nature of the SRB forward skirt damage is investigated through nonlinear finite element analysis in order to develop an improved failure definition, and this new limit state results in a failure rate prediction that is in agreement with the observed frequency of damage. Finally, a methodology based upon Bayesian networks is presented for quantifying any increased confidence in the SRB splashdown model prediction based upon the experimental cylinder test data, using concepts of similitude and dimensional analysis.