Fluid dynamic simulations and genetic-based algorithms for parametric analysis and performance optimization of air-solid jet pumps used in pneumatic transportation of high-density particles - Orozco-Murillo, William; Patiño Arcila, Iván D.; Palacio-Fernández, José A. (Powder technology, 2025)
This study employs genetic algorithms for parametric analysis and optimization of three performance parameters of air-solid jet pumps, namely, mass flow rate ratio (ψ), pressure recovery ratio (PR) and energetic efficiency (η), in terms of five non-dimensional parameters involving measurements of nozzle, mixing chamber and diffuser. The Dense Discrete Phase Model (DDPM) is used in the computational simulations, and experiments are undergone for validation of numerical results, yielding suitable accuracy for the mass flow rate ratio (ψ). Jet pump geometries corresponding to single-objective and multi-objective optimizations are compared in terms of fields of pressure, Mach number, granular temperature, solids volume fraction, air and particle velocity, and particles' residence time. In general, jet pump performance is highly influenced by the suction generation capacity, the particle-particle and particle-wall collisions, changes of particle velocities and trajectories by shock waves formation and drag uniformity of particles. Optimal values obtained for the performance parameters are ψ = 1.576, PR = 0.298 and η = 0.389. [Display omitted] •Jet pump performance depends on non-dimensional parameters of nozzle, mixing chamber and diffuser.•Particle collisions in suction chamber and drag uniformity at diffuser impact the mass flow rate ratio.•Suction capacity of nozzle and pressure rise at diffuser influence the pressure recovery ratio.•Energetic efficiency is influenced by particle collisions, shock wave formation and air recirculation.•Performance depends on pressure, Mach number, granular temperature, velocity, and particles' residence times.