Characteristics of dissipative forces on thermal and solutal transport in boger fluid with thermophoretic particle deposition: An intelligent neuro-computing paradigm
Munawar Abbas, Abdulbasit A. Darem, Asma A. Alhashmi, Nashwan Adnan Othman, Dilsora Abduvalieva, Youssef El‐Khatib, Ali Akgül, Muhammad Shafique
Abstract
The goal of this examination is to evaluate the Marangoni convection influences on gyrotactic microbes in Boger fluid flow across a sheet with porous medium and thermophoretic particle deposition. The thermophoretic particle deposition is a basic method in electrical and aero-solution engineering for transporting small particles across a temperature gradient. Our model combines the Levenberg–Marquardt method with AI-based neural networks for higher accuracy than traditional methods. It supports industrial fluid dynamics, biomedical engineering, and environmental research. AI-based forecasts also enhance nanofluid heat transfer and advanced biotechnology applications. The proposed paradigm has significant applications in bioengineering, environmental sciences, and industrial operations. Enhancing microbial mobility in bioreactors can enhance the production of biofuel and wastewater treatment. In the medical sciences, targeted medication delivery is aided by an understanding of microbe dynamics in non-Newtonian fluids. The model also advances nanotechnology by improving particle deposition techniques in microfluidic devices. By assessing how microorganisms react to external stimuli, it promotes ecological balance and water quality regulation in marine environments. In a range of engineering and scientific domains, the intelligent neuro-computing approach enhances prediction accuracy even more, making it a practical instrument for real-time monitoring and optimization.