A simulation-based optimization approach for poultry axial exhaust fans to fulfill aerodynamic and mechanical service constraints

Abstract

Ventilation plays a crucial role in controlling temperature, humidity, and air contamination in poultry houses. This work presents a simulation-based optimization approach that combines stochastic particle–swarm optimization (PSO) with numerical aerodynamic and structural analysis in a staggered mode to design a new propeller that reduces the number of blades and improves the performance curve and efficiency of an actual fixed-speed axial exhaust fan. The fitness–function is to maximize the aerodynamic performance of the exhaust fan, subject to a serie of aerodynamic and structural constraints, which include power, noise, stress, blade tip displacement, and vibrations, and allow the direct retrofit of the optimized blades into the actual rotor assembly. The blades are represented with four parameters: airfoil family, width fraction, chord, and twist distribution. A polynomial parametrization of the chord and twist distribution of the blades is proposed, and appropriate bounds of these parameters are determined with an analytical design theory for axial fans. An 18% increase in efficiency was obtained with regards to a prescribed propeller while all design constraints were fulfilled.