I have created PowerPoint presentations related to selected publications that include both audio and animations. Below are brief abstracts of each presentation. Please click on the title to view or save the presentation.
Space vehicles traveling at hypersonic speeds through a planetary atmosphere experience severe aerodynamic heating. An integrated thermal protection system (ITPS) serves to protect the vehicle from this aerodynamic heating, while also providing some structural load bearing function. The design of an ITPS is a compromise between structural requirements of robust structural members and the need to limit the heat conducted through these members. This compromise is an exercise in risk allocation between structural and thermal failures.
In deterministic approaches, risk allocation between failure modes is implicit in the choice of safety factors and margins. Probabilistic optimization can be used to allocate risk explicitly between failure modes. Previous work has shown the differences in risk allocation between deterministic and probabilistic optimization with constraints on the maximum temperature and buckling of the ITPS web. In this study, the effect of addition of a constraint on the maximum von Mises stress in the web on the risk allocation is examined. The ABAQUS finite element program is used to generate transient thermal response under reentry heating loads, and the structural response is calculated at critical times (e.g., time at which temperature gradient is maximum) during the re-entry process. Separable Monte Carlo is used to evaluate the limit states corresponding to the three failure modes. Probabilistic optimization reduced the mass of the ITPS by 1.2% while maintaining the same level of reliability as the deterministic design. More risk was allocated to thermal and stress failures after optimization and the probability of buckling failure was greatly reduced. The presence of only a few combined thermal-stress and buckling-stress failure modes were noted in the deterministic design, and even fewer were found in the probabilistic design.
It is common practice to test components after they are designed. The uncertainty reduction that can occur after a test is usually not incorporated in reliability calculations at the design stage. The reduction in uncertainty is accomplished by the additional knowledge provided by the test and by re-design when the test reveals that the component is unsafe or overly conservative. In this paper, we develop a methodology to estimate the effect of a single future thermal test and model the effect of the resulting uncertainty reduction on the design of an integrated thermal protection system. An integrated thermal protection system protects space vehicles from the severe aerodynamic heating experienced during atmospheric reentry while also functioning as part of the load bearing structure. Using given distributions of computational and experimental errors and given re-design rules, we obtain possible outcomes of the future test through Monte Carlo sampling to determine what changes in probability of failure, design, and weight will occur. In addition, Bayesian updating is used to gain accurate estimates of the probability of failure after a test. We observe that performing a single test can reduce the probability of failure by orders of magnitude, on average, when the objective of re-design is to restore the original safety margins. We show that instead, re-design for a given reduced probability of failure allows additional weight reduction.
After components are designed, they commonly undergo various tests, which reduce uncertainty about their performance and reliability. Furthermore, when a test reveals that components are unsafe or substantially over designed, they can be redesigned to improve safety or performance. This uncertainty reduction and possible redesign is usually not incorporated in reliability calculations at the design stage. In a previous study, we developed a methodology to estimate the effect of a single future thermal test in combination with redesign. We then examined the effect of the resulting uncertainty reduction on the design of an integrated thermal protection system. Using given distributions of computational and experimental errors and given redesign rules, we observed that performing a single test can reduce the probability of failure by orders of magnitude, on average, when the objective of re-design is to restore the original safety margins. In this study, we sought to optimize the redesign rules for three possible objectives: maximum reliability, minimum mass, and minimum number of redesigns. |