Speaker
Description
High-temperature volumetric solar absorbers operating above 1000 K are key components for next-generation concentrating solar power systems. However, their deployment is still limited by the occurrence of severe thermal gradients, reaching up to 200 K·cm⁻¹, which lead to mechanical cracking, material degradation, and a reduction of overall thermal efficiency due to radiative losses. Addressing these challenges requires advanced design strategies capable of controlling heat transfer mechanisms within porous structures.
This work focuses on the development of a topology optimization framework for silicon carbide (SiC) volumetric solar absorbers, based on a homogenized porous medium approach. The objective is to enhance thermal performance while mitigating temperature gradients by optimally tailoring the internal porosity distribution. Recent studies have investigated spatially varying absorber geometries by introducing gradients in parameters such as porosity or pore diameter. However, these approaches remain limited to one-dimensional variations or a restricted number of predefined configurations.
In this work, a fully coupled conductive–convective–radiative optimization tool is developed using an adjoint-state method to efficiently compute sensitivities and determine optimal porosity fields that minimize a chosen cost function. Several optimization objectives are considered, including maximizing absorber efficiency, minimizing temperature gradients, or achieving a compromise between multiple performance criteria. Fluid flow within the porous absorber is modeled using the compressible Darcy–Forchheimer formulation, while heat transfer between the solid matrix and the fluid is described using a Local Thermal Non-Equilibrium (LTNE) approach. Solar radiation absorption is modeled using the Beer–Lambert law, and infrared re-emission is treated with the P1 radiation model, whose validity is assessed through comparison with reference Monte Carlo simulations.
A critical aspect of this study concerns the selection of thermo-physical correlations for effective porous-medium properties. While the literature offers a wide range of empirical correlations, their applicability to highly porous SiC absorbers remains uncertain. In this context, a new correlation for the extinction coefficient is proposed and implemented within the optimization framework, providing improved consistency between optical absorption and homogenized parameters.
Optimized porosity distributions are obtained by exploring different combinations of efficiency maximization and temperature-gradient constraints. In practice, the optimization is performed by maximizing thermal efficiency while imposing various admissible upper bounds on the maximum temperature gradient. This approach makes it possible to identify a wide range of optimal solutions, spanning from nearly isothermal temperature fields with maximum gradients below 50 K·cm⁻¹, to configurations achieving very high efficiency, as well as intermediate compromise designs that balance thermal performance and structural integrity.
Finally, a dedicated de-homogenization tool developed in Python is presented. This tool reconstructs discrete-scale geometries from optimized porosity and pore diameter fields while explicitly accounting for industrial manufacturing constraints. The ultimate goal is to fabricate optimized absorber samples in collaboration with the MEMTI SUSPIP laboratory and to experimentally validate their performance through solar furnace testing at the PROMES facility.
| Country | France |
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| Student Awards | I would like to submit this presentation into the Earth Energy Science (EES) and Capillarity Student Poster Awards. |
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