Peristaltic rheology of nanomaterial in a porous channel under thermal radiation and variable heat source: An artificial neural network framework

Nanofluids play a vital role in different investigations due to their supercilious thermo-physical properties in comparison with the conventional fluids. Magnesium oxide (MgO) nanoparticles have attracted significant scientific attention due to their remarkable biocompatibility, chemical stability, and wide-ranging biomedical applications. These include antimicrobial, anticancer, antioxidant and anti-diabetic functionalities, along with promising roles in tissue engineering, bio-imaging, and targeted drug delivery systems. The objective of the current study is to examine MgO/H2O nanofluid-based peristaltic transport for biomedical purposes, particularly within porous asymmetric channel configurations using the artificial neural networks (ANNs) for enhancing the performance of nanofluid suspension. The study investigates the combined effects of temperature-dependent viscosity and MHD, incorporating velocity slip and convective boundary conditions, while the energy equation accounts for thermal radiation and a non-uniform heat source/sink. The reference dataset for the nanofluidic system's estimated solution is generated using the Adam numerical method, while the performance of the ANNs is optimized via a Bayesian regularization neural network (BRNN) approach and assessed using reference dataset split into 80 % for training, 15 % for testing, and 5 % for validation. The accuracy of the proposed BRNN framework is validated through close agreement with reference results, optimal training performance, and minimal absolute error, while its robustness is further demonstrated through regression analysis, transition state evaluation, and error histogram assessment. The results for magnetic interaction parameter M, velocity slip parameter β, radiation parameter Rd, Brinkman number Br, pore diameter dp, and nanomaterial amount ϕ are also discussed to optimize nanofluidic system. MHD authoritative effects help in controlling the flow patterns and enhancement of heat transfer. The amount of nanomaterials and pores diameter significantly influences the viscosity, heat transfer and stability parameters.