Neural Network Model Predicts Hybrid Nanofluid Behavior for Enhanced Heat Transfer Systems
Scientists have developed an advanced neural network approach to model hybrid nanofluid behavior over cylinders and plates. The AI-powered system demonstrates exceptional accuracy in predicting heat and mass transfer dynamics, potentially revolutionizing thermal management in industrial applications.
Breakthrough in Thermal Management Prediction
Researchers have developed an innovative artificial intelligence approach to predict the complex dynamics of hybrid nanofluids flowing over cylinders and inclined plates, according to reports in Scientific Reports. The study integrates numerical solvers with optimized feed-forward artificial neural networks (FF-ANN) based on the Levenberg-Marquardt algorithm (LMA), creating a powerful predictive tool for thermal management applications.