Data assimilation for combustion ignition delay time simulation using schlieren image velocimetry

This study sought to improve the accuracy of simulating spray penetration and combustion ignition delay by means of data assimilation (DA). The simulations were conducted using the Reynolds-averaged Navier–Stokes (RANS) equations and assimilating the schlieren image data. In DA, an ensemble square root filter (EnSRF) was used to build the statistical model, making the simulation results more accurate without any change in the governing equations. Recognizing that the spray-cone injection angle has a large effect on penetration, we created ensemble members with different injection angles. And we applied the two-component velocity distribution calculated via SIV and updated both velocity and temperature by using a DA statistical model derived from RANS ensemble simulations. The ignition delay time is generally known to vary even under the same experimental conditions because it is influenced by many factors. In this study, we attempted the transient DA-assisted RANS simulation to predict the ignition delay time even when the temporal resolution and accuracy of the observation data ware insufficient. Our trials offer an example of how a combination of techniques can be effectively used to assimilate experimental data obtained under restricted conditions. •The flame characteristics in diesel engine combustion are heavily influenced by the mixture of fuel and air upstream of the flame, which is determined by the complex processes of droplet break-up and spray development.•We attempt to improve the performance of a conventional Reynolds-averaged Navier–Stokes (RANS) solver to simulate the spray penetration and combustion ignition delay phenomena with physical consistency by performing data assimilation (DA) to integrate schlieren images of a spray field into a numerical simulation.•The prediction accuracy for the ignition delay time in the combustion field was improved when we used the velocity data by SIV and updated both the velocity and the temperature in DA, even when the time resolution of the original schlieren image data was not enough.•Experiments are often limited to obtain the necessary statistics, but it was shown that data assimilation can be effectively applied by using such techniques as schlieren image velocimetry (SIV) for velocity and statistical modeling for temperature in the data assimilation.