Skeletal mechanism generation for surrogate fuels using directed relation graph with error propagation and sensitivity analysis
Kyle E. Niemeyer, Chih-Jen Sung, and Mandhapati P. Raju

TL;DR
This paper introduces DRGEPSA, a new method combining existing techniques to efficiently generate minimal skeletal reaction mechanisms for surrogate fuels, validated on hydrocarbons like n-decane.
Contribution
The paper presents DRGEPSA, an improved skeletal reduction method that overcomes limitations of previous techniques, producing smaller, accurate mechanisms for surrogate fuels.
Findings
DRGEPSA produces smaller skeletal mechanisms than previous methods.
Validated mechanisms accurately reproduce detailed mechanism results.
Effective across a wide range of conditions for surrogate fuels.
Abstract
A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with examples for three hydrocarbon components, n-heptane, iso-octane, and n-decane, relevant to surrogate fuel development. DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit. It is illustrated that the combination of the DRGEP and DRGASA methods allows the DRGEPSA approach to overcome the weaknesses of each, specifically that DRGEP cannot identify all…
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