It is common practice to validate diesel spray models against experimental diesel-spray images based on elastic light scattering, but the metric used to define the liquid boundary in a modeled spray can be physically inconsistent with the liquid boundary detected by light scattering measurements. In particular, spray models typically define liquid penetration based on a liquid mass threshold, while light scattering signal intensities are based on droplet size and volume fraction. These metrics have different response characteristics to changes in ambient conditions and fuel properties. Thus, when spray models are “tuned” or calibrated to match these types of measurements, the predictive capabilities of these models can be compromised.
In this work, we compare two different liquid length metrics of an evaporating, non-reacting n-dodecane spray under diesel-like conditions using KIVA-3V. The first computational liquid length definition is mass-based, where the liquid length is defined as the downstream axial location where a selected percentage of the total injected mass has been encompassed (typically 95-99%). This definition is closely linked to liquid length scaling laws found in the literature that define the liquid length based on the axial location where vaporization is complete. The second employed definition is based on the radial path-averaged liquid volume fraction and is more closely related to the Mie-scatter imaging technique. The liquid length is defined as the furthest axial location where the radial path-averaged liquid volume fraction exceeds a threshold value. We assess the ability of each metric to capture experimentally measured liquid penetration trends under operating conditions with varying ambient density and temperature. We also discuss the implications of these results on liquid penetration scaling laws developed from elastic light scattering liquid penetration measurements in the literature. Finally, we offer guidance for selecting a physically-based liquid penetration metric for robust spray model validation against spray imaging data.