A flexible numerical model of a multistage active magnetocaloric regenerator

• An active magnetocaloric regenerator model is described with specific correlations.
• Time step is set for each time increment based on three criteria to ensure stability.
• Magnetocaloric effect data are scaled by field strength.
• Entropy is forcibly conserved in the recreated magnetocaloric effect data.
• Convergence acceleration is applied, yielding 50% reduction in convergence time.

A flexible one-dimensional model was created in Python to determine the periodic steady state cooling power of an active magnetocaloric regenerator. Several features of the model provide advantages when performing large parametric studies. Geometry, material properties, and operation parameters are read in as input. Fluid flow and magnetization profiles are parameterized, and thermodynamic consistency is forced in magnetocaloric material properties. A dynamic time step is used, and three associated model constants are set to work over a wide range of input parameter combinations. Derivative gain is adjusted to minimize convergence time resulting in an average convergence time reduction of approximately 50%.