M. Mossa Al-Sawalha
Papers
1
Total Citations
5
H-Index
1
About
M. Mossa Al-Sawalha is a leading researcher in applied mathematics and computational fluid dynamics, with a primary focus on magnetohydrodynamic (MHD) nanofluid flows and advanced neural network methodologies. His most cited work introduces a pioneering neural network technique—the backpropagation Levenberg-Marquardt scheme (NNB-LMS)—to analyze MHD nanofluid flow over a rotating disk with heat generation or absorption. This contribution stands out for its convergent stability and ability to generate highly accurate numerical solutions for complex fluid dynamics problems. With 5 citations already, this paper highlights his innovative integration of machine learning with traditional fluid mechanics. Al-Sawalha’s research addresses critical challenges in heat transfer and fluid behavior under magnetic fields, offering practical insights for engineering applications such as cooling systems and energy devices. His work is notable for bridging theoretical modeling and computational intelligence, making him a valuable resource for students and researchers exploring the intersection of neural networks and nanofluid dynamics.
Research Focus
Key Achievements
Top Papers
- 1