Combustion modelling in spark-ignition engines using conditional source-term estimation

• Main Author: Nivarti, Girish Venkata
• Language: English
• Published: University of British Columbia 2013
• Online Access: http://hdl.handle.net/2429/44838

Conditional Source-term Estimation (CSE) is a chemical closure model for the simulation of turbulent combustion. In this work, CSE has been explored for modelling combustion phenomena in a spark-ignition (SI) engine. In the arbitrarily complex geometries imposed by industrial design, estimation of conditionally averaged scalars is challenging. The key underlying requirement of CSE is that conditionally averaged scalars be calculated within spatially localized sub-domains. A domain partitioning algorithm based on space-filling curves has been developed to construct localized ensembles of points necessary to retain the validity of CSE. Algorithms have been developed to evenly distribute points to the maximum extent possible while maintaining spatial locality. A metric has been defined to estimate relative inter-partition contact as an indicator of communication in parallel computing architectures. Domain partitioning tests conducted on relevant geometries highlight the performance of the method as an unsupervised and computationally inexpensive domain partitioning tool. In addition to involving complex geometries, SI engines pose the challenge of accurately modelling the transient ignition process. Combustion in a homogeneous-charge natural gas fuelled SI engine with a relatively simple chamber geometry has been simulated using an empirical model for ignition. An oxygen based reaction progress variable is employed as the conditioning variable and its stochastic behaviour is approximated by a presumed probability density function (PDF). A trajectory generated low-dimensional manifold has been used to tabulate chemistry in a hyper-dimensional space described by the reaction progress variable, temperature and pressure. The estimates of pressure trace and pollutant emission trends obtained using CSE accurately match experimental measurements.