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 21, 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
CFD simulation of laminar pipe flow development length using ANSYS Fluent and CFX.
MATLAB scripts for generating asymmetric Reynolds-number cycles and post-processing Nusselt number and skin-friction data from turbulent pipe-flow DNS.
Transparent, validation-backed workflow for preliminary pipe headloss and circular gravity-flow checks.
Hybrid neural-numerical warm-start correction framework for Colebrook-White pipe-flow equations with Newton refinement.
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