Researchers from the University of Ghent, the RWTH Aachen University and BASF released a research paper introducing a hybrid model for reliably forecasting the thermal performance of direct contact counter current cooling towers.
Traditional computational fluid dynamics methods are often time-consuming and computationally intensive. However, this study pioneers a simpler methodology, incorporating a mechanistic component and an artificial neural network. With an impressive R² exceeding 0.94, the model accurately predicts mass transfer coefficients, achieving an overall prediction accuracy of 0.99. This breakthrough promises real-time monitoring and operational optimization, revolutionizing the cooling cycle in chemical plants.
You can have a look at the full paper at this link.