Nitrogen driver for low-enthalpy testing in free-piston-driven shock tunnels

Nitrogen is proposed as a suitable driver gas candidate for the operation of free-piston-driven shock tunnels at low total enthalpies. When compressed adiabatically, nitrogen has a lower speed of sound than the commonly used driver gases, e.g., argon and helium, thus providing the ability to achieve tailored conditions and longer test durations at lower enthalpies. This paper describes the methodology used to design operating conditions using nitrogen as the driver gas and presents an experimental and numerical demonstration of its use to achieve tailored conditions in a free-piston-driven shock tunnel. In this demonstration, the useful test flow duration was extended from less than 0.5 ms to 4 ms based on a constant-nozzle-supply-pressure criterion for tests at total enthalpies of 1.6 MJ/kg. The same design methodology was then used to develop different nitrogen–argon driver conditions for tailored operation in the free-piston-driven shock tunnel T4 for enthalpies spanning from 1.6 to 3.2 MJ/kg. With a nitrogen driver gas, T4, which was originally designed for operation up to Mach 25 flight conditions, can now operate at conditions as low as an equivalent flight Mach number of 5.5. This is significant because the experimental results, supported by numerical simulations, clearly demonstrate that nitrogen can be used as a driver gas in free-piston-driven shock tunnels to maximise the duration at which test conditions are held constant when testing at low total enthalpies

Development of an Uncertainty Quantification Predictive Chemical Reaction Model for Syngas Combustion

An automated data-centric infrastructure, Process Informatics Model (PrIMe), was applied to validation and optimization of a syngas combustion model. The Bound-to-Bound Data Collaboration (B2BDC) module of PrIMe was employed to discover the limits of parameter modifications based on uncertainty quantification (UQ) and consistency analysis of the model–data system and experimental data, including shock-tube ignition delay times and laminar flame speeds. Existing syngas reaction models are reviewed, and the selected kinetic data are described in detail. Empirical rules were developed and applied to evaluate the uncertainty bounds of the literature experimental data. The initial H₂/CO reaction model, assembled from 73 reactions and 17 species, was subjected to a B2BDC analysis. For this purpose, a dataset was constructed that included a total of 167 experimental targets and 55 active model parameters. Consistency analysis of the composed dataset revealed disagreement between models and data. Further analysis suggested that removing 45 experimental targets, 8 of which were self-inconsistent, would lead to a consistent dataset. This dataset was subjected to a correlation analysis, which highlights possible directions for parameter modification and model improvement. Additionally, several methods of parameter optimization were applied, some of them unique to the B2BDC framework. The optimized models demonstrated improved agreement with experiments compared to the initially assembled model, and their predictions for experiments not included in the initial dataset (i.e., a blind prediction) were investigated. The results demonstrate benefits of applying the B2BDC methodology for developing predictive kinetic models