Polymer‐surfactant synergy for high‐turbulence drag reduction in hydrocarbon media: Experimental and reduced‐order modelling approaches

Abstract Pumping power losses in pipeline transport of fuels remain a significant constraint for the oil and gas industry. Soluble drag‐reducing additives are effective, yet stability and performance at high turbulence can be limiting. Combining polymers with surfactants has recently shown promise, but predictive tools for such mixtures, especially in hydrocarbons where polymer elasticity and shear‐responsive micelles interact, are scarce. This work investigates a polymer‐surfactant complex in diesel fuel using a rotating disk apparatus and introduces a compact predictive model anchored to measurable turnover behaviour. Experimentally, the polymer alone exhibits a monotonic drag‐reduction (DR) response, reaching 67% at 250 and 2200 rpm. The surfactant alone shows a rise‐peak‐fall profile, achieving 24%–38% DR near 1400–1600 rpm, followed by decay. Remarkably, the fixed‐composition polymer‐surfactant blend displays non‐additive synergy, peaking at 84.5% DR at 2000 rpm, well beyond either component. To interpret these dynamics, we construct a reduced‐order framework incorporating a polymer baseline, an explicit surfactant turnover term scaled to experimental peaks, and a saturating blend interaction. Parameters are fitted under physical constraints, with uncertainty captured via bootstrap confidence bands. The model closely reproduces all DR curves and enables portable guidance for formulation and operating‐point selection in rotating equipment and pipeline transport.