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Machine learning prediction of combined blast and fragments loading using a hybrid data-driven algorithm
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inferredcites →https://doi.org/10.1016/j.dt.2014.06.003openalex-snapshot
Numerical simulation of the natural fragmentation of explosively loaded thick walled cylinders
inferredcites →https://doi.org/10.1016/j.dt.2019.01.007openalex-snapshot
Real-time calculation of fragment velocity for cylindrical warheads
inferredcites →https://doi.org/10.1016/j.dt.2020.02.004openalex-snapshot
Reaction degree of composition B explosive with multi-layered compound structure protection subjected to detonation loading
inferredcites →https://doi.org/10.1016/j.dt.2024.07.007openalex-snapshot
Data driven prediction of fragment velocity distribution under explosive loading conditions
inferredcites →https://doi.org/10.1016/j.dt.2025.07.003openalex-snapshot
Experimental and numerical analysis of near-field detonation products and shock wave characteristics for cylindrical charge
inferredcites →https://doi.org/10.1016/j.engstruct.2024.118271openalex-snapshot
Use of explainable machine learning models in blast load prediction
inferredcites →https://doi.org/10.1016/j.ijimpeng.2017.10.003openalex-snapshot
Spatial mass distribution of fragments striking a protective structure
inferredcites →https://doi.org/10.1016/j.ijimpeng.2017.11.006openalex-snapshot
General formula to calculate the fragment velocity of warheads with hollow core
inferredcites →https://doi.org/10.1016/j.ijimpeng.2018.03.011openalex-snapshot
Velocity axial distribution of fragments from non-cylindrical symmetry explosive-filled casing
inferredcites →https://doi.org/10.1016/j.ijimpeng.2019.04.027openalex-snapshot
Fragment velocity distribution of D-shaped casing with multiple fragment layers
inferredcites →https://doi.org/10.1016/j.ijimpeng.2022.104183openalex-snapshot
Confined blast loading of steel plates with and without pre-formed holes
inferredcites →https://doi.org/10.1016/j.ijimpeng.2025.105288openalex-snapshot
Development of a machine learning-driven formula for calculating fragment velocity
inferredcites →https://doi.org/10.1016/j.jmps.2011.03.004openalex-snapshot
A discrete particle approach to simulate the combined effect of blast and sand impact loading of steel plates
inferredcites →https://doi.org/10.1016/j.matdes.2013.04.041openalex-snapshot
A numerical investigation on explosive fragmentation of metal casing using Smoothed Particle Hydrodynamic method
inferredcites →https://doi.org/10.1016/j.neucom.2026.132641openalex-snapshot
evTransFER: A transfer learning framework for event-based facial expression recognition
inferredcites →https://doi.org/10.1016/j.oceaneng.2025.121735openalex-snapshot
ML-based prediction of scour depth around a cylindrical bridge pier: A comparative analysis of ANN, SVM, and Ensemble Trees
inferredcites →https://doi.org/10.1016/j.petrol.2020.108182openalex-snapshot
Application of supervised machine learning paradigms in the prediction of petroleum reservoir properties: Comparative analysis of ANN and SVM models
inferredcites →https://doi.org/10.1016/j.psep.2018.11.014openalex-snapshot
Comparative study on vulnerability assessment for urban buried gas pipeline network based on SVM and ANN methods
inferredcites →https://doi.org/10.1016/j.psep.2023.02.008openalex-snapshot
Prediction of BLEVE loads on structures using machine learning and CFD
inferredcites →https://doi.org/10.1016/j.tws.2021.107914openalex-snapshot
Influence of standoff distance on the deformation of square steel plates subjected to internal blast loadings
inferredcites →https://doi.org/10.1177/2041419620970570openalex-snapshot
Prediction of blast loading in an internal environment using artificial neural networks
inferredcites →https://doi.org/10.1177/20414196231177364openalex-snapshot
The Direction-encoded Neural Network: A machine learning approach to rapidly predict blast loading in obstructed environments
inferredcites →https://doi.org/10.3390/app12031133openalex-snapshot
Influence of Ball Bearing Size on the Flight and Damage Characteristics of Blast-Driven Ball Bearings
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