Accelerating heat exchanger design by combining physics-informed deep learning and transfer learning

•Incorporating transfer learning to accelerate physics-informed learning.•Sequential decomposition of variable space makes the complex problem trainable.•Point density adjustment used to identify the appropriate size of residual points.•It enables fast discovery of the optimal geometry and operating conditions.•The training time for designing an air cooler was reduced from 27,295 to 326 hrs.