Toward Predictive Modeling of Petroleum and Biobased Fuel Stability: Kinetics of Methyl Oleate/n-Dodecane Autoxidation

Abstract

Because of the recent changes in the formulation and handling of middle-distillate fuels, oxidation stability is becoming an increasingly important issue. However, liquid-phase oxidation kinetics of middle-distillate fuels remains poorly understood. The purpose of this study was to gain an in-depth understanding of the impact of fatty acid methyl ester (FAME) addition on autoxidation kinetics. A detailed kinetic mechanism for the autoxidation of a n-dodecane/methyl oleate (MO) surrogate mixture was generated and validated against original well-controlled accelerated oxidation experiments. Results emphasize the nonlinear oxidation promoting effect of MO on n-dodecane autoxidation. Pathway analyses reveal that HO 2 and OH propagation steps as well as the duration of initiation and propagation phases strongly affected sensitivity analysis by MO addition. On the basis of these analyses and the detailed mechanism, an analytical model was derived and validated against experiments on binary surrogate mixtures as well as blends of conventional commercial fuels and FAME. These results open up the use of bottom-up liquid-phase oxidation modeling strategies for the in silico formulation of alternative fuels and the design of innovative injection fuel systems.

Structure–Reactivity Relationships in Fuel Stability: Experimental and Kinetic Modeling Study of Isoparaffin Autoxidation

“…The generated mechanisms were coupled to a previously developed reactor model to reproduce experimental results 11,12,14 . This reactor model includes a constant-concentration option for species specified in the input file.…”

Kinetic solvent effects in organic reactions

“…These models can be quite large; for example, a model for the liquid-phase oxidation of a biodiesel surrogates fuel blend contained 3 275 chemical reactions. [2] Due to the size of these models, it is desirable to generate them automatically, but using quantum chemistry and transition state theory or direct dynamics to calculate thousands of liquid-phase reaction rates on-the-fly during mechanism generation would be computationally expensive. Jalan et al [6] automated the estimation of solvation thermochemistry and diffusion limitations during automated mechanism generation and manually modified some reaction rates, on the basis of PCM calculations, to build solvent-sensitive models of tetralin oxidation.…”

Original Experimental Approach for Assessing Transport Fuel Stability

“…A second possible methodology is to calculate the induction period using the secondary derivative 4 where the IP is indicated by a maximum in the second derivative. However, this method is limited when the conductivity signal is fluctuating which frequently occurs.…”

“…Fill the reaction vessels of Block A: 1 to 4 with 7 ml of a fresh fuel sample of methyl oleate using a pipette. 4. Configure the test.…”

“…The induction period (IP) is characterized by a sudden rise of conductivity associated especially with volatile acid species. Further details about the standard method can be found elsewhere 4,5 .…”