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The design and operation of premixers for gas turbines must deal with the possibility of relatively rare events causing dangerous autoignition (AI). Rare AI events may occur in the presence of fluctuations of operational parameters, such as temperature and fuel composition, and must be understood and predicted. This work presents a methodology based on incompletely stirred reactor (ISR) and surrogate modeling to increase efficiency and feasibility in premixer design optimization for rare events. For a representative premixer, a space-filling design is used to sample the variability of three influential operational parameters. An ISR is reconstructed and solved in a postprocessing fashion for each sample, leveraging a well-resolved computational fluid dynamics solution of the non-reacting flow inside the premixer. Via detailed chemistry and reduced computational costs, ISR tracks the evolution of AI precursors and temperature conditioned on a mixture fraction. Accurate surrogate models are then trained for selected AI metrics on all ISR samples. The final quantification of the AI probability is achieved by querying the surrogate models via Monte Carlo sampling of the random parameters. The approach is fast and reliable so that user-controllable, independent variables can be optimized to maximize system performance while observing a constraint on the allowable probability of AI. [ABSTRACT FROM AUTHOR]

A probabilistic model predicts hip fracture probability for postflight male astronauts during lateral fall scenarios from various heights. A biomechanical representation of the hip provides impact load. Correlations relate spaceflight bone mineral density (BMD) loss and postflight BMD recovery to bone strength (BS). Translations convert fracture risk index (FRI), the ratio of applied load (AL) to BS, to fracture probability. Parameter distributions capture uncertainty and Monte Carlo simulations provide probability outcomes. The fracture probability for a 1 m fall 0 days postflight is 15% greater than preflight and remains 6% greater than pre-flight at 365 days postflight. Probability quantification provides insight into how spaceflight induced BMD loss affects fracture probability. A bone loss rate reflecting improved exercise countermeasures and dietary intake further reduces the postflight fracture probability to 6% greater than preflight at 0 days postflight and 2% greater at 365 days postflight. Quantification informs assessments of countermeasure effectiveness. When preflight BMD is one standard deviation below mean astronaut preflight BMD, fracture probability at 0 days postflight is 34% greater than the preflight fracture probability calculated with mean BMD and 28% greater at 365 days postflight. Quantification aids review of astronaut BMD fitness for duty standards. Increases in postflight fracture probability are associated with an estimated 18% reduction in postflight BS. Therefore, a 0.82 deconditioning coefficient modifies force application limits for crew vehicles. [ABSTRACT FROM AUTHOR]