Heat transfer enhancement to transcritical hydrocarbons due to wall roughness within microtube heat exchangers

Regeneratively cooled scramjets using hydrocarbon fuels require high-performance heat exchangers to limit structural temperatures and manage the thermodynamic complexity of supercritical coolants. Additive manufacturing can improve the manufacturability of airframe components and cooling infrastructure but also introduces increased wall roughness. The influence of wall roughness on heat transfer to supercritical hydrocarbons remains insufficiently characterised, particularly in numerical simulations. In this study, heat transfer to supercritical n-decane in rough-walled heat exchangers is investigated using computational fluid dynamics and validated against experimental measurements. Reynolds-averaged Navier–Stokes simulations are performed using the renormalisation group k – ε and shear stress transport k – ω turbulence models. Wall roughness is represented using three approaches: numerical roughness via wall-function, statistically generated roughness, and an idealised sawtooth geometry. The renormalisation group k – ε model coupled with geometrically resolved roughness provides the closest agreement with experimental data, with mean errors of 5–10% for wall temperature and 13–26% for Nusselt number. The shear stress transport k – ω model generally overpredicts wall temperature when combined with geometric roughness but shows improved accuracy when a numerical roughness treatment is employed. A parametric study examines the effects of roughness, heat flux, and pressure on heat transfer. Roughness levels typical of additive manufacturing increase the Nusselt number by up to 320% relative to a smooth tube and reduce peak wall temperature by as much as 300 K. A new Nusselt number correlation incorporating wall roughness and supercritical thermophysical property variation predicts 89% of experimental data within ±30% error, outperforming conventional correlations. • The main conclusions of the study are RNG k–ε with geometrical roughness yields the lowest heat-transfer prediction error. • SST k–ω shows improved accur acy when roughness is modelled numerically. • Maximum thermal performance occurs for roughness in the range ε r = 0.005–0.025. • Increasing reduced pressure attenuates both heat-transfer deterioration and enhancement. • The proposed Nusselt correlation outperforms classical models for rough supercritical flow.