An improved Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model with wide fuel applicability based on data-driven techniques

Haoran Li, Ming Jia, Rui Ding, Xinyi Li, Zonghan Zhang and Yanzhi Zhang

Energy, 2025, vol. 334, issue C

Abstract: The Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) model, widely used for spray breakup simulations, relies on some idealized assumptions (e.g., neglect fuel viscosity and surface tension), necessitating case-specific manual tuning that introduces substantial prediction uncertainties in spray simulations. This is critical because spray simulation accuracy directly impacts the in-cylinder mixture formation, combustion, and ultimately the performance predictions of power equipment. To address this issue, this study establishes a data-driven correlation between the breakup length constant Cb and two key parameters (i.e., ambient density ρg and fuel kinematic viscosity νl) through Non-dominated Sorting Genetic Algorithm II (NSGA-II), which can be expressed as Cb = 0.075⋅νl3⋅ln(ρg)+4.74. The proposed correlation is first verified by the analytical solution of Cb, demonstrating good agreement in both magnitude and trend. Furthermore, large-scale validation using 563 cases was conducted, confirming that spray features of the eight fuels (i.e., diesel, gasoline, biodiesel, DME, methanol, PODE, ammonia, and n-butanol) under various conditions can be accurately captured by the improved KH-RT model without manual parameter tuning. The impacts of fuel properties and ambient conditions on breakup length, along with their influences on spray development, were finally investigated. The improved KH-RT model eliminates empirical parameter tuning, significantly reducing both computational time and spray prediction uncertainties, thereby improving power equipment performance predictions.

Keywords: E-fuel; Spray simulation; KH-RT breakup model; Breakup length; Genetic algorithm; Fuel adaptability (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:334:y:2025:i:c:s0360544225033031

DOI: 10.1016/j.energy.2025.137661

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