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• Variable porosity open receivers can reduce maximum receiver temperature. • Selection of the porosity distribution within the receiver can increase the receiver efficiency. • Variable porosity changes flow velocity through porous receiver sections. Hotspots caused by asymmetric solar flux distributions present a critical design challenge in cavity receivers used for concentrated solar power (CSP) systems. These thermal nonuniformities induce steep temperature gradients that compromise the thermo-mechanical integrity and operational lifetime of receivers. This study proposes and evaluates a variable porosity design methodology for porous volumetric absorbers as a passive means to mitigate the effects of nonuniform solar irradiance. Using Monte Carlo Ray Tracing (MCRT), heat flux distributions for a spherical cavity receiver were computed based on site-specific heliostat field data from a Lancaster, CA test facility. These flux maps served as inputs for a coupled finite element model (FEM) incorporating radiative transfer (via the P1 approximation), local thermal non-equilibrium (LTNE) energy balances, and flow through porous media governed by Brinkman-Forchheimer extended Darcy’s law. The receiver was discretized into angular sectors, and six porosity distribution functions, including linear, quadratic, and piecewise variants, were applied to redistribute airflow and minimize solid matrix temperature gradients. Results show that the piecewise upward distribution, which channels more flow to high-flux regions, significantly improves receiver thermal efficiency and reduces peak solid temperatures under both summer and winter operating conditions. Performance metrics such as outlet air temperature, maximum solid-phase temperature, and average fluid velocity were used to evaluate each configuration. The proposed variable porosity framework demonstrates that tailored spatial control of internal flow can mitigate hotspot effects, enhance thermal performance, and support the economic viability of high-flux solar receivers. Future work will focus on optimization of the porosity distribution function and integration with structural stress modeling to quantify reliability improvements.