Computational analysis of graphene oxide nanofluid flow in an unsteady permeable channel for heat transfer applications with experimental validation

Purpose This study aims to investigate the role of nanoparticle radius and inter-particle spacing on the thermal and flow characteristics within an unsteady permeable channel under the impact of thermal radiation. Design/methodology/approach Different volume ratios are used to prepare the ionic nanofluids (INF) that are based on mixtures of ionic liquids (IL), water (H2O) and graphene oxide (GO): Findings Results revealed that increasing (Fr) and (Kr) values reduced fluid velocity by up to 20%, whereas higher (Rd) and (Ec) led to a temperature rise exceeding 40% near the upper plate. The IL-H2O (25–75%)/GO nanofluid exhibited the highest Nusselt number, showing an improvement of (30–40%) in heat transfer relative to other mixtures. These findings offer valuable insight into the advancement of high efficiency nanofluid systems applied in solar energy absorption, porous media flows and compact thermal storage technologies. Originality/value Real-time experimental data thereby bridges the gap between computational predictions and physical validations. Variable nanoparticle sizing provides a comprehensive understanding of radiative heat transfer mechanisms in nanofluid systems. The inclusion of permeability further adds a degree of complexity by mimicking realistic porous structures, which are relevant in energy harvesting and thermal management applications.