Knock is a major impediment to achieving higher efficiency in Spark-Ignition (SI) engines. The recent trends of boosting, downsizing and downspeeding have exacerbated this issue by driving engines toward higher power density and higher load duty cycles. Apart from the engine operating conditions, fuel anti-knock quality is a major determinant of the knocking tendency in engines, as quantified by its octane number (ON). The ON of a fuel is based on an octane scale which is defined according to the standard octane rating methods for Research Octane Number (RON) and Motor Octane Number (MON). These tests are performed in a single cylinder Cooperative Fuel Research (CFR) engine. In the present work, a numerical approach was developed based on multidimensional computational fluid dynamics (CFD) to predict knocking combustion in a CFR engine. The G-equation model was employed to track the propagation of the turbulent flame front and a multi-zone model based on temperature and equivalence ratio was used to capture auto-ignition in the endgas ahead of the flame front. Furthermore, a novel methodology was developed wherein a lookup table generated from a chemical kinetic mechanism could be employed to provide laminar flame speed as an input to the G-equation model, instead of using empirical correlations. To account for fuel chemistry effects accurately and lower the computational cost, a compact 121-species primary reference fuel (PRF) skeletal mechanism was developed from a more detailed gasoline surrogate mechanism using the directed relation graph assisted sensitivity analysis (DRGASA) reduction technique. Extensive validation of the skeletal mechanism was performed against experimental data available in the literature for both homogeneous ignition delay and laminar flame speed. The skeletal mechanism was used to generate the lookup tables for laminar flame speed as a function of pressure, temperature and equivalence ratio. The engine CFD model incorporating the skeletal mechanism was employed to perform numerical simulations under RON and MON conditions for different PRFs. Parametric tests were conducted at different compression ratios and the predicted values of critical compression ratio (at knock onset), delineating the boundary between “no knock” and “knock”, were found to be in good agreement with the available experimental data. The virtual CFR engine model was, therefore, demonstrated to be capable of adequately capturing the sensitivity of knock propensity to fuel chemistry.

This review article examines the last decade of studies investigating solid, molten and liquid particle interactions with one another and with walls in heterogeneous multiphase flows. Such flows are experienced in state-of-the-art and future-concept gas turbine engines, where particles from the environment, including volcanic ash, runway debris, dust clouds, and sand, are transported by a fluid carrier phase and undergo high-speed collisions with high-temperature engine components. Sand or volcanic ash ingestion in gas turbine engines is known to lead to power-loss and/or complete engine failure. The particle-wall interactions that occur in high temperature sections of an engine involve physics and intrinsic conditions that are sufficiently complex that they result in highly disparate and transient outcomes. These particles, which often times are made up of glassy constituents called CMAS (calcium-magnesium-alumino-silicate), are susceptible to phase change at combustor temperatures (1650?), and can deposit on surfaces, undergo elastic and plastic deformation, rebound, and undergo breakup. Considerable research has been put into developing empirical and physics-based models and numerical strategies to address phase interactions. This article provides a detailed account of the conceptual foundation of physics-based models employed to understand the behavior of particle-wall interaction, the evolution of numerical methods utilized for modeling these interactions, and challenges associated with improving models of particle-particle and particle-wall interactions needed to better characterize multiphase flows. It also includes description of a testbed for acquiring canonical data for model validation studies.

A numerical approach was developed based on multidimensional computational fluid dynamics (CFD) to predict knocking combustion in a cooperative fuel research (CFR) engine. G-equation model was employed to track the turbulent flame front and a multizone model was used to capture auto-ignition in the end-gas. Furthermore, a novel methodology was developed wherein a lookup table generated from a chemical kinetic mechanism could be employed to provide laminar flame speed as an input to the G-equation model, instead of using empirical correlations. To account for fuel chemistry effects accurately and lower the computational cost, a compact 121-species primary reference fuel (PRF) skeletal mechanism was developed from a detailed gasoline surrogate mechanism using the directed relation graph (DRG) assisted sensitivity analysis (DRGASA) reduction technique. Extensive validation of the skeletal mechanism was performed against experimental data available from the literature on both homogeneous ignition delay and laminar flame speed. The skeletal mechanism was used to generate lookup tables for laminar flame speed as a function of pressure, temperature, and equivalence ratio. The numerical model incorporating the skeletal mechanism was employed to perform simulations under research octane number (RON) and motor octane number (MON) conditions for two different PRFs. Parametric tests were conducted at different compression ratios (CR) and the predicted values of critical CR, delineating the boundary between “no knock” and “knock,” were found to be in good agreement with available experimental data. The virtual CFR engine model was, therefore, demonstrated to be capable of adequately capturing the sensitivity of knock propensity to fuel chemistry.