Scientific computing of thermally radiative Casson blood-based tri-hybrid nanofluid flow past an exponentially expanding surface with gyrotactic microorganisms: A machine learning approach

Key Points

• The analysis shows unique flow characteristics due to the presence of gyrotactic microorganisms and tri-hybrid nanofluids, presenting new insights into fluid dynamics.
• Key metrics include the effects of thermal radiation on the fluid flow, significantly impacting the heat transfer rate.
• Assessment using machine learning techniques helps to predict the flow behavior of thermally radiative Casson fluids under varying conditions.
• This study highlights the potential for enhanced fluid performance in biomedical applications; further validation in real-world scenarios is needed.