Ignition delay and chemical–kinetic modeling of undiluted mixtures in a high‐pressure shock tube: Nonideal effects and comparative uncertainty analysis

Abstract

AbstractHigh‐pressure shock tube ignition delay data are essential for fuel characterization and for the validation and optimization of chemical–kinetic models. Therefore, it is crucial that realistic measurement conditions are considered in modeling. Furthermore, an accurate uncertainty quantification for experimental data is the basis for evaluation of the predictive reliability of chemical–kinetic models. Several measurement aspects are investigated to improve the interpretation of measurement results: (1) A new approach for integrating the nonideal pressure rise into chemical–kinetic modeling based on a correlation to measurement data is introduced, which enables the determination at each condition and fuel–air mixture individually with minimal effort. (2) A semiempirical model for available test times of reactive mixtures is introduced, which is based on measurement data of nonreactive mixtures. It allows for a priori prediction of test times and provides experimental limits to support the measurement. (3) A literature review shows that different uncertainty sources are considered in ignition delay time uncertainty analysis. A comparative analysis is conducted to investigate the significance of different uncertainty sources for test temperature and ignition delay time. The analysis of ignition delay time uncertainty indicates that for fuels with negative temperature coefficient behavior a comprehensive uncertainty analysis has to be conducted to accurately estimate measurement uncertainty in the intermediate temperature range. Additionally, ignition delay times of dimethyl ether–air mixtures are measured at pressures of 8, 12, and 35 bar and at equivalence ratios of 0.5, 1.0, and 2.0. Furthermore, the data on first‐stage ignition delay are rather scarce and have therefore been recorded additionally. The new approach of integrating the nonideal pressure rise into modeling and the comprehensive uncertainty analysis supports the interpretation of measurement data, such that the prediction capabilities of chemical–kinetic models can be evaluated thoroughly.