The middle matters? An uncertainty-aware diagnostic for two-endpoint emissions screening

Two-endpoint interpolation is a convenient screening approximation for fuel-blend emissions, but its sufficiency depends on the fidelity of the resolved interior response. This study evaluates a signed, species-resolved endpoint-adequacy diagnostic for CO and NOₓ using a reduced aviation-fuel descriptor and an oxygenated composition-contrast probe across 144 operating states and 41 fractions (5904 reconstructed evaluations). A k-nearest-neighbour inverse-distance-weighted reconstruction and a cross-validated cubic response surface give substantially different local residuals and unqualified threshold-exceedance rates. An explicit non-negative C/H/O descriptor projection has an analytically determined active-set transition at w = 0.44744, explaining the shared flat response below this composition and the onset of a numerical step near w = 0.45. The transition arises from the descriptor mapping; the subsequent local emissions minimum is not established as a kinetic effect. At 5 ms, the cubic-model cross-validation errors correspond to approximate multiplicative response-error scales of 11.7% for CO and 17.0% for NOₓ, both larger than the illustrative 5% screening tolerance. These error scales are not calibrated bounds on the endpoint residual. A conservative three-way uncertainty gate accordingly gives an indeterminate result with the available evidence. No interior value has been independently verified by matched direct PSR kinetics or experiment. The contribution is a reproducible descriptor-switch diagnosis and an uncertainty-qualified decision framework for identifying when additional interior evidence is required, not a claim of verified aviation-fuel emission nonlinearity.

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Publication Details

Journal
Fuel Processing Technology
Published
2026-10-29
DOI
https://doi.org/10.1016/j.fuproc.2026.108635
Primary Topic
Vehicle emissions and performance
Type
article
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article

The middle matters? An uncertainty-aware diagnostic for two-endpoint emissions screening

Odi Fawwaz Alrebei, Malek Awashreh
Fuel Processing Technology
Vehicle emissions and performance
article

The middle matters? An uncertainty-aware diagnostic for two-endpoint emissions screening

Odi Fawwaz Alrebei, Malek Awashreh
article en

Abstract

Two-endpoint interpolation is a convenient screening approximation for fuel-blend emissions, but its sufficiency depends on the fidelity of the resolved interior response. This study evaluates a signed, species-resolved endpoint-adequacy diagnostic for CO and NOₓ using a reduced aviation-fuel descriptor and an oxygenated composition-contrast probe across 144 operating states and 41 fractions (5904 reconstructed evaluations). A k-nearest-neighbour inverse-distance-weighted reconstruction and a cross-validated cubic response surface give substantially different local residuals and unqualified threshold-exceedance rates. An explicit non-negative C/H/O descriptor projection has an analytically determined active-set transition at w = 0.44744, explaining the shared flat response below this composition and the onset of a numerical step near w = 0.45. The transition arises from the descriptor mapping; the subsequent local emissions minimum is not established as a kinetic effect. At 5 ms, the cubic-model cross-validation errors correspond to approximate multiplicative response-error scales of 11.7% for CO and 17.0% for NOₓ, both larger than the illustrative 5% screening tolerance. These error scales are not calibrated bounds on the endpoint residual. A conservative three-way uncertainty gate accordingly gives an indeterminate result with the available evidence. No interior value has been independently verified by matched direct PSR kinetics or experiment. The contribution is a reproducible descriptor-switch diagnosis and an uncertainty-qualified decision framework for identifying when additional interior evidence is required, not a claim of verified aviation-fuel emission nonlinearity.

Fuel Processing TechnologyVol. 293
Hamad bin Khalifa University (QA)
Openalex Percentile: Top 23%
Vehicle emissions and performance
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