zsulsw/mlsa
Machine Learning-based Second-order Analysis of Beam-columns through Physics-Informed Neural Networks
This project helps structural engineers and researchers accurately analyze the second-order behavior of slender steel beam-columns, even when large deflections occur. It takes design parameters for a beam-column as input and provides precise predictions of its structural response, overcoming limitations of traditional analytical or finite-element methods. This tool is ideal for structural engineers, civil engineering researchers, and academics working on advanced structural analysis.
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Use this if you need a more accurate and robust method for second-order analysis of slender steel beam-columns, especially when traditional methods struggle with large deflections or when data for training models is scarce.
Not ideal if you are looking for a simple, off-the-shelf software package without engaging with Python code or if you are dealing with very basic structural analysis problems that don't involve complex second-order effects.
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15
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1
Language
Python
License
GPL-3.0
Category
Last pushed
Feb 18, 2025
Commits (30d)
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