Prediction of Concrete Fragments Amount and Travel Distance under Impact Loading Using Deep Neural Network and Gradient Boosting Method

Prediction of Concrete Fragments Amount and Travel Distance under Impact Loading Using Deep Neural Network and Gradient Boosting Method

In the present study, the amount of fragments generated and their travel distances due to vehicle collision with concrete median barrier (CMB) was analyzed and predicted. In this regard, machine learning was applied to the results of numerical analysis, which were developed by comparing with field t...

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Bibliographic Details
Main Authors: Kyeongjin Kim, WooSeok Kim, Junwon Seo, Yoseok Jeong, Meeju Lee, Jaeha Lee
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Materials
Subjects:
concrete median barrier
gradient boosting machine
smoothed particle hydrodynamics
deep neural network
artificial neural network
fragments
Online Access:https://www.mdpi.com/1996-1944/15/3/1045

Internet

https://www.mdpi.com/1996-1944/15/3/1045

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