Flow dynamics in a vertical pipe with internal fins exposed to sunlight – A machine learning based evaluation of thermal signature

• Fins attached to the inner surface of a vertically oriented pipe effect are examined. • Nanofluid flow and thermal characteristics when exposed to sunlight-induced heating are explored. • Machine learning is applied to tackle flow problems and thermal dynamic attributes. • Understanding pipe flow dynamics via solar radiation helps understand climate changes. • HVAC systems and industrial Applications need heat transfer analysis in such a unique setting. The present work examines that how the fins attached to the inner surface of a vertically oriented pipe affect the flow as well as thermal characteristic of the nanofluid flow when exposed to sunlight-induced heating. A definite thermal boundary condition together with fully established hydrodynamics and thermal conditions is applied that confirms uniform temperature along the sun-exposed pipe walls. Finite volume method, with computational efficiency and solution accuracy, is incorporated. A magnetic damping produces significant changes in the flow patterns within the pipe. A reduction in the velocity distribution is also caused by this damping force. The intensified applied magnetic field impact also changes the velocity distribution. It leads to a flattening of the velocity surface, indicating a decrease in velocity gradient within the flow field. The larger fins work as significant obstacles by altering flow direction and increasing velocity gradients near the solid surface. However, the higher Rayleigh numbers qualitatively change the thermal characteristics within the pipe. Finally, an artificial intelligence-based analysis is presented that correlates our research methodology with a Neural Fitting app. This neural network app is leveraged to enrich the accuracy of the present numerical technique and ensures a robust evaluation of the thermal signature of nanofluid flow within the pipe exposed to sunlight-induced heating.