Reducing greenhouse gas emissions in Sandia methane-air flame by using a biofuel Seyed Moein Rassoulinejad-Mousavi a , Yijin Mao b , Yuwen Zhang a, * a Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia, MO, 65211, USA b Convergent Science, 6400 Enterprise Ln, Madison, WI, 53719, USA article info Article history: Received 3 December 2017 Received in revised form 20 May 2018 Accepted 21 May 2018 Available online 23 May 2018 Keywords: Renewable energy Sustainability Biofuel Reduced reaction mechanism Sandia flame D Greenhouse gas emissions abstract This article aims to study suitability and merits of employing a biofuel in methane-air jet flames for energy security and environmental sustainability purposes. A special biofuel (methyl decanoate, methyl 9-decenoate, and n-heptane) oxidation with 118 species reduced/skeletal mechanism and 837 reactions is combusted instead of methane. The biofuel was fed in the main jet inlet of the well-known Sandia flame D (SFD) while the hot pilot jet is still responsible for ignition. The open-source software OpenFOAM was used for simulating turbulent biofuel-air combustion. To check the accuracy of computational re- sults, the system was initially validated with SFD experimental results and good agreements were found. After ignition, mean temperature distribution and species mean mass fraction at different distances in axial and radial directions were investigated. Results showed that the biofuel can be effectively used as an alternative to SFD not only for generating a reasonable temperature as methane does, but also for significantly reduction in principal greenhouse gas emissions. © 2018 Elsevier Ltd. All rights reserved. 1. Introduction Key drivers for future energy policy are climate change and energy security that sparkled so much debates and concerns in many organizations including International Energy Agency (IEA) [1]. High demand and dependency of industries on fossil fuel supply, along with the fact of scarcity or disruptions of the fuel, jeopardize the energy security. Furthermore, increasing global greenhouse gases (GHGs) emissions from fossil fuels combustion and industrial processes are contributing a lot to global warming and subsequently climate change. Hence, switching from fossil fuels to biofuels in transportation by automobiles, trains, ships, and aircraft, as well as most of the industries has promising implica- tions for energy security and mitigation of climate change. Eco- nomic developments are also expected since investment in biofuels could lead to creation of new jobs as well as new sources of income [2]. High temperature methane combustion in diffusion flames leads to the emission of major GHGs. Methane-Air Sandia flame series are turbulent piloted methane diffusion flames which are being used widely for combustion studies. Sandia Flame D (SND) experiment [3] provides a standard and high quality reference data set for validation of turbulent flame calculations. This type of tur- bulent piloted methane/air diffusion flame has been investigated many times since it is an important and widely used flame for various studies. For instances, recently Renzo et al. [4] carried out a comparative study among large eddy simulations performed with various grid resolutions, a Reynolds averaged Navier-Stokes simu- lation, and experimental data concerning the well-known Sandia D flame test case. Cai et al. [5] implemented a new non-gray radiation modeling library for combustion gases in OpenFOAM for compar- isons of radiative heat transfer calculations in a jet diffusion flame using spherical harmonics and k-Distributions. Kadar [6] modeled the turbulent non-premixed combustion in industrial furnaces using an open source toolbox. Schneider et al. [7] measured the flow field of stable and locally extinguishing hydrocarbon-fueled jet flames. There are a huge number of other attractions on multiple aspect studies of the Sandia flame such as rate-controlled con- strained equilibrium [8], premixed and non-premixed flamelet- generated manifolds [9], thermal radiation influence [10], Sparse- Lagrangian multiple mapping conditioning simulation [11], Large Eddy Simulation the Eulerian stochastic field method [12], multi- environment probability density function models [13], modeling of evolution equation for the sub-grid joint probability density * Corresponding author. E-mail address: zhangyu@missouri.edu (Y. Zhang). Contents lists available at ScienceDirect Renewable Energy journal homepage: www.elsevier.com/locate/renene https://doi.org/10.1016/j.renene.2018.05.079 0960-1481/© 2018 Elsevier Ltd. All rights reserved. Renewable Energy 128 (2018) 313e323