Bimodal particle distributions for improved heat transfer in flowing packed bed heat exchangers

Abstract

Recent studies have demonstrated that a mixture of two differently sized solid particles decreases mixture porosity while increasing thermal conductivity. This impact is limited up to temperatures of ∼400°C at which monodisperse distributions with larger particles yield higher thermal conductivities. In this work, a numerical model of the Gen3 Particle Pilot Plant (G3P3) 20kWt prototype heat exchanger constructed by Sandia National Laboratory (SNL) is validated for monodisperse particles distributions at its working temperatures (290–500°C) and both particle and sCO2 (supercritical carbon dioxide) mass flow rates (100 g/s). The validated model is then used to simulate the performance of bimodal particle distributions at working G3P3 temperatures and predicts increases in the overall heat transfer coefficient of up to 25–40% with optimal bimodal particle mixtures when compared to monodispersed particle distributions of the respective mixtures’ large particles. At these optimal particle mixtures, the average particle wall convection coefficient contributes ∼35–45% of the specific thermal resistance while the particle near-wall contact resistance contributes ∼15–25%.

Keywords

• Particle
• Thermal conductivity
• Thermal energy storage
• Packed bed
• Heat exchanger