Physics-Informed Neural Network for modeling steady laminar flow in a circular pipe (Hagen-Poiseuille flow). Built with PyTorch.
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Updated
Sep 20, 2026 - Python
Physics-Informed Neural Network for modeling steady laminar flow in a circular pipe (Hagen-Poiseuille flow). Built with PyTorch.
MATLAB code for order-of-magnitude analysis (OMA) and physics-informed symbolic regression (GPTIPS-2) to model turbulent pipe-flow friction/pressure drop using Nikuradse & Superpipe data, including custom constraints, fitness functions, and figure reproduction scripts.
Moody diagram svg generator
Transparent, validation-backed workflow for preliminary pipe headloss and circular gravity-flow checks.
MATLAB scripts for generating asymmetric Reynolds-number cycles and post-processing Nusselt number and skin-friction data from turbulent pipe-flow DNS.
CFD simulation of laminar pipe flow development length using ANSYS Fluent and CFX.
Hybrid neural-numerical warm-start correction framework for Colebrook-White pipe-flow equations with Newton refinement.
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