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S. M.

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Open access 2026

Deep Learning-Based Numerical Solutions for Nonlinear Partial Differential Equations in Fluid Dynamics

This paper presents a comprehensive study of deep learning-based numerical solutions for nonlinear PDEs in fluid dynamics, and proposes a proposed framework that integrates neural network architectures with physics informed constraints to accurately approximate fluid behavior while reducing computational complexity.

S. M. · International Journal of Mat... · 0 citations