Multi-objective optimization of bladed cylindrical solar tower receivers using random forest surrogates and NSGA-II

Bladed cylindrical receivers have the potential to reduce external heat-losses in solar tower concentrated solar power systems, but their added blades also increase surface area and aerodynamic loading. These competing effects create a coupled thermal–aerodynamic–geometric design problem that has not been fully addressed in previous optimization studies. This work develops a surrogate-assisted multi-objective optimization framework to identify receiver geometries that balance heat-loss reduction, aerodynamic performance, and geometric compactness. Machine-learning surrogate models were trained using a CFD database spanning multiple receiver temperatures, wind conditions, blade lengths, and blade numbers, achieving high predictive accuracy with cross-validated coefficients of determination of about 0.98 for both thermal and aerodynamic responses. The optimization results reveal a consistent trade-off structure across all operating conditions. Very compact designs exhibit both higher drag coefficients and higher total heat-loss coefficients, while highly extended designs reduce the total heat-loss coefficient but introduce excessive surface area and geometric complexity. Between these extremes, a stable intermediate design region provides the best balanced compromise. The surrogate predictions indicate that the knee-point candidates have approximately 43%–52% lower drag coefficients and 33%–40% lower total heat-loss coefficients than the compact design extreme. The proposed framework offers practical design envelopes for early-stage screening of bladed receiver concepts, while indicating that intermediate geometries should be further assessed using high-fidelity simulations before final design selection.

International Journal of Heat and Fluid Flow

International Journal of Heat and Fluid Flow

122

0142-727X

N/A

N/A

14