Turbulent mixing of a hydrogen jet in crossflow: direct numerical simulation and model assessment

TL;DR

This study uses DNS, LES, and RANS to evaluate hydrogen jet mixing in crossflow, revealing LES's superior accuracy and identifying limitations in RANS modeling assumptions for turbulent diffusivity.

Contribution

It provides a comprehensive DNS dataset for hydrogen jet in crossflow and insights into improving RANS turbulent mixing models.

Findings

LES accurately predicts flow and mixing compared to DNS.

RANS under-predicts turbulent stresses and mixing, due to assumptions of isotropic diffusivity.

Turbulent Schmidt number and anisotropic flux components are key factors in RANS inaccuracies.

Abstract

A numerical study for a hydrogen (H2) jet in an air crossflow (JICF) was performed using direct numerical simulation (DNS), large eddy simulation (LES), and Reynolds-averaged Navier-Stokes (RANS) approaches, based on a geometry representative of key aspects of port fuel injection (PFI) in a H2-fueled heavy-duty internal combustion engine. The focus was placed on the H2 mixing process and the turbulent species flux model used in the latter two approaches. Based on the DNS data, the performance of LES and RANS on predicting the turbulent flow fields and mixing process was comprehensively evaluated. Results showed that LES performs very well in predicting both the mean velocity and the Reynolds stress. In contrast, RANS significantly under-predicts all Reynolds stress components, while predicting the mean flow field relatively well. Regarding the H2 mixing prediction, LES shows an excellent agreement with DNS, while RANS significantly under-predicts the mixing process. The underlying reasons for the poor performance of RANS were identified by extracting turbulent transport properties used in RANS approach from DNS data. It was found that the turbulent diffusivity used in RANS is much smaller than that derived from DNS, which is attributed to the over-prediction on turbulent Schmidt number (Sct), as well as the under-prediction on turbulent viscosity. By further analyzing the anisotropic components of Sct and the misalignment angle between turbulent species fluxes directly obtained from DNS and those predicted by the RANS mixing model, the commonly used assumption of isotropic turbulent diffusivity in RANS was demonstrated to be invalid for the present configuration. This study provided a unique DNS dataset for H2 jet in a crossflow relevant to H2 PFI engines and generated new insights on improved modeling of turbulent mixing.