Multiple Scalar Mixing
This dataset contains high-fidelity numerical simulation data of three-component passive scalar mixing in statistically isotropic turbulence. This dataset is designed to study the fundamental physics governing industrial combustion systems. The temporal evolution of the mixture is tracked using two independent mixture fractions representing the mass fractions of the inlet streams. The dataset spans 27 distinct files, each corresponding to a unique mean initial condition for the mixture fractions. In each of the file, multiple scalar fields represent diverse initial spatial configurations, including statistically isotropic randomized distributions, layered distributions, and variations of both where two scalars are allowed to partially premix before the third is introduced.
Citation Formats
TY - DATA
AB - This dataset contains high-fidelity numerical simulation data of three-component passive scalar mixing in statistically isotropic turbulence. This dataset is designed to study the fundamental physics governing industrial combustion systems. The temporal evolution of the mixture is tracked using two independent mixture fractions representing the mass fractions of the inlet streams. The dataset spans 27 distinct files, each corresponding to a unique mean initial condition for the mixture fractions. In each of the file, multiple scalar fields represent diverse initial spatial configurations, including statistically isotropic randomized distributions, layered distributions, and variations of both where two scalars are allowed to partially premix before the third is introduced.
AU - Yellapantula, Shashank
A2 - Perry, Bruce
A3 - Mueller, Michael
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Laboratory of the Rockies
DO -
KW - energy
KW - power
LA - English
DA - 2026/09/03
PY - 2026
PB - National Renewable Energy Laboratory (NREL)
T1 - Multiple Scalar Mixing
UR - https://data.openei.org/submissions/8763
ER -
Yellapantula, Shashank, et al. Multiple Scalar Mixing. National Renewable Energy Laboratory (NREL), 3 September, 2026, Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8763.
Yellapantula, S., Perry, B., & Mueller, M. (2026). Multiple Scalar Mixing. [Data set]. Open Energy Data Initiative (OEDI). National Renewable Energy Laboratory (NREL). https://data.openei.org/submissions/8763
Yellapantula, Shashank, Bruce Perry, and Michael Mueller. Multiple Scalar Mixing. National Renewable Energy Laboratory (NREL), September, 3, 2026. Distributed by Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8763
@misc{OEDI_Dataset_8763,
title = {Multiple Scalar Mixing},
author = {Yellapantula, Shashank and Perry, Bruce and Mueller, Michael},
abstractNote = {This dataset contains high-fidelity numerical simulation data of three-component passive scalar mixing in statistically isotropic turbulence. This dataset is designed to study the fundamental physics governing industrial combustion systems. The temporal evolution of the mixture is tracked using two independent mixture fractions representing the mass fractions of the inlet streams. The dataset spans 27 distinct files, each corresponding to a unique mean initial condition for the mixture fractions. In each of the file, multiple scalar fields represent diverse initial spatial configurations, including statistically isotropic randomized distributions, layered distributions, and variations of both where two scalars are allowed to partially premix before the third is introduced.},
url = {https://data.openei.org/submissions/8763},
year = {2026},
howpublished = {Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory (NREL), https://data.openei.org/submissions/8763},
note = {Accessed: 2026-09-04}
}
Details
Data from Sep 3, 2026
Last updated Sep 3, 2026
Submission in progress
Organization
National Renewable Energy Laboratory (NREL)
Contact
Shashank Yellapantula
303.264.8595
Authors
Research Areas
DOE Project Details
Project Name Expand Fuel Specifications for Non-Road Powertrains
Project Number 352404
