Start Date
1-3-2012 8:30 AM
Description
Predicting the reliability of the heat shield for crewed space vehicles has been a topic of continuing interest within NASA for many years. The design of a thermal protection system (TPS) is subject to numerous large sources of uncertainty and reliability assessments of such TPS are rare. The proposed talk discusses both the application of Design Of Experiments (DOE) to developing a new arc jet testing campaign for a given TPS and the reliability assessment conducted for the same TPS for a crewed space capsule (similar to Apollo capsules) to withstand re-entry to earth from space.
The objectives of the study were to 1) provide recommendations for a planned arc jet testing campaign, 2) determine the design reliability of a proposed TPS, and 3) conduct a sensitivity analysis to determine the effect of input parameters and user choices on the TPS thermal design reliability. The development of a recommended arc jet test matrix employed a combination of techniques based on the analysis of variance (ANOVA) statistical methodology. The techniques employed include DOE, response surface (RS) methodology and uncertainty quantification (UQ). The recommended test matrix consisted of 30 test cases and includes four replicated condition pairs. Randomization was used to establish the test order, the testing facility, and the test sample cut pattern from three lots of material. The resulting arc jet test matrix was a compromise between one derived from statistical DOE techniques and the existing capabilities of arc jet test facilities located at NASA JSC and ARC. Statistical metrics were employed to objectively compare the assessment-derived matrix to an existing testing proposal. Five of the six metrics examined favored the new proposed test plan over the existing proposed test plan; one of the metrics (and, perhaps, the most important) strongly favored the new test plan proposal over the existing test plan.
The reliability assessment investigated the sensitivity of reliability estimates to various input parameters, which included multiple studies to examine the total bond line temperature reliability based on 7 body point locations for 2 proposed trajectories. Each body point and trajectory combination was subjected to 5 different combinations of trajectory and aerothermal environment assumptions. The reliability was assessed based on a composite material failure criterion, which associated a greater probability of system failure proportional with the exceedance of an assumed safe bond line temperature limit. The study also investigated the sensitivity of reliability predictions to various input and problem formulation parameters. A large, statistically significant difference was found in the estimated TPS reliability when considering various formulations of the reliability problem, including the use of different failure conditions. The proposed talk will summarize the work performed in these areas and highlight some of the findings and recommendations that emerged from the work.
Included in
Ablative Thermal Protection System (TPS) Margin Study
Predicting the reliability of the heat shield for crewed space vehicles has been a topic of continuing interest within NASA for many years. The design of a thermal protection system (TPS) is subject to numerous large sources of uncertainty and reliability assessments of such TPS are rare. The proposed talk discusses both the application of Design Of Experiments (DOE) to developing a new arc jet testing campaign for a given TPS and the reliability assessment conducted for the same TPS for a crewed space capsule (similar to Apollo capsules) to withstand re-entry to earth from space.
The objectives of the study were to 1) provide recommendations for a planned arc jet testing campaign, 2) determine the design reliability of a proposed TPS, and 3) conduct a sensitivity analysis to determine the effect of input parameters and user choices on the TPS thermal design reliability. The development of a recommended arc jet test matrix employed a combination of techniques based on the analysis of variance (ANOVA) statistical methodology. The techniques employed include DOE, response surface (RS) methodology and uncertainty quantification (UQ). The recommended test matrix consisted of 30 test cases and includes four replicated condition pairs. Randomization was used to establish the test order, the testing facility, and the test sample cut pattern from three lots of material. The resulting arc jet test matrix was a compromise between one derived from statistical DOE techniques and the existing capabilities of arc jet test facilities located at NASA JSC and ARC. Statistical metrics were employed to objectively compare the assessment-derived matrix to an existing testing proposal. Five of the six metrics examined favored the new proposed test plan over the existing proposed test plan; one of the metrics (and, perhaps, the most important) strongly favored the new test plan proposal over the existing test plan.
The reliability assessment investigated the sensitivity of reliability estimates to various input parameters, which included multiple studies to examine the total bond line temperature reliability based on 7 body point locations for 2 proposed trajectories. Each body point and trajectory combination was subjected to 5 different combinations of trajectory and aerothermal environment assumptions. The reliability was assessed based on a composite material failure criterion, which associated a greater probability of system failure proportional with the exceedance of an assumed safe bond line temperature limit. The study also investigated the sensitivity of reliability predictions to various input and problem formulation parameters. A large, statistically significant difference was found in the estimated TPS reliability when considering various formulations of the reliability problem, including the use of different failure conditions. The proposed talk will summarize the work performed in these areas and highlight some of the findings and recommendations that emerged from the work.