We present a hybrid industrial cooling system model that embeds analytical solutions within a multiphysics simulation. This model is designed for reinforcement learning (RL) applications and balances simplicity with simulation fidelity and interpretability. The model’s fidelity is evaluated against real world data from a large scale cooling system. This is followed by a case study illustrating how themodel can be used for RL research. For this, we develop an industrial task suite that allows spe…