A method to determine the uncertainties of solid particle erosion measurements utilizing machine learning techniques-Reference-Cited by-同舟云学术

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A method to determine the uncertainties of solid particle erosion measurements utilizing machine learning techniques

Published:2023-06 Issue: Volume:522 Page:204688
ISSN:0043-1648
Container-title:Wear
language:en
Short-container-title:Wear

Author:

Fallah Shojaie Elham,Darihaki Farzin^ORCID,Shirazi Siamack A.

Publisher

Elsevier BV

Subject

Materials Chemistry,Surfaces, Coatings and Films,Surfaces and Interfaces,Mechanics of Materials,Condensed Matter Physics

Reference25 articles.

1. A Semi-mechanistic Model for Predicting Sand Erosion Threshold Velocities in Gas and Multiphase Flow Production;Shirazi,2016

2. A novel trajectory-based mechanistic model for predicting solid particle erosion in elbows;Darihaki;J. Energy Resour. Technol.,2022

3. Peyman Zahedi - SAND EROSION IN ANNULAR FLOW AND LOW LIQUID LOADING FLOW CONDITIONS, ((n.d.)).

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1. Development of a semi-mechanistic correlation for erosion prediction in standard elbows;Advanced Powder Technology;2024-06

2. Measuring solid particles in sand-carrying gas flow using multiscale vibration response statistics and deep learning algorithms;Mechanical Systems and Signal Processing;2024-03

3. Physical theories of solid particle erosion and abrasive jet wear;Journal of Manufacturing Processes;2023-11

4. Machine learning regression tools for erosion prediction of WC-10Co4Cr thermal spray coating;Results in Surfaces and Interfaces;2023-10

5. Study on wear analysis of Ni-20Al2O3 HVOF micron layers using artificial neural network technique;International Journal on Interactive Design and Manufacturing (IJIDeM);2023-07-10

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