Develop an automated corrosion loop development system based on k-means clustering and group technology method
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Updated
Nov 9, 2020 - JavaScript
Develop an automated corrosion loop development system based on k-means clustering and group technology method
This repository enables an engineer to generate predictions for the mechanical bending performance of corroded beams, using a database of 725 corroded beams tested under monotonic bending. Outputs include the maximum bending moment, residual capacity percentage, yield load, yield displacement, and ultimate displacement.
PCB track measurement test for perchloride corrosion
A web proxy that allows users to bypass firewalls on the local network.
Basic example of how to train and detect rust corrosion with yolo v7.
Matlab model of the tribocorrosion current from an AFM tip interacting with a stainless steel oxide.
Corrosion Detection Using SPA Methodology and Bayesian Modeling
Example machine learning applications for the determination of the residual yield force of corroded steel bars tested under monotonic tensile loading. Data is collected from 26 experimental programs avaialbe in the literature.
For GMU's Multidisciplinary Senior Design Project focused around the Corrosion Robot
Size of Oxidation Feature from Image Analysis. Developed by Pádraigín Stack for Oak Ridge National Lab. Allows the user to load a micrograph and measure the thickness of oxidation or other features on an image. Originally built for SiO2 formers, but should work with any image that has high enough contrast.
Example machine learning implementation to predict the residual bending moment capacity of corroded reinforced concrete beams tested under monotonic three or four-point bending. Data is collected from 54 experimental programs available in the literature.
A simple frontend design for Corrosion you can deploy
Corrosion Detection Using Faster RCNN.
Collection of MATLAB and C# applications for modeling and analyzing corrosion data.
Research project on Detection and analysis of pitting corrosion in metals exposed to alkaline medium of varying concentration using a Fast RCNN model in collaboration with CSIR - CECRI.
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