AI-assisted prediction of particle impact deformation simulated by Material Point Method

Authors

Mojtaba Ghadiri (ORCID: https://orcid.org/0000-0003-0479-2845)
Saba Saifoori
Saeid Nezamabadi (ORCID: https://orcid.org/0000-0001-8234-332X)
Carsten Schilde (ORCID: https://orcid.org/0000-0003-0851-8042)
Somayeh Hosseinhashemi
Mohammad Alasossi

Publication Details

Journal: Powder Technology
Published: 2025-04-09
DOI: https://doi.org/10.1016/j.powtec.2025.121018
Citations: 1
Primary Topic: Fluid Dynamics Simulations and Interactions
Type: article
Field-Weighted Citation Impact: 1.33

Funders

Deutsche Forschungsgemeinschaft
Agence Nationale de la Recherche
Bundesministerium für Bildung und Forschung
Engineering and Physical Sciences Research Council

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article

AI-assisted prediction of particle impact deformation simulated by Material Point Method

Mojtaba Ghadiri, Saba Saifoori, Saeid Nezamabadi, Carsten Schilde et al.

Apr 9, 2025

1 citations

Powder Technology

Fluid Dynamics Simulations and Interactions

1.33

article

AI-assisted prediction of particle impact deformation simulated by Material Point Method

Mojtaba Ghadiri, Saba Saifoori, Saeid Nezamabadi, Carsten Schilde, Somayeh Hosseinhashemi, Mohammad Alasossi

April 9, 2025article en

1 citations

Abstract

No abstract available for this paper.

Powder TechnologyVol. 459

Deutsche Forschungsgemeinschaft, Agence Nationale de la Recherche, Bundesministerium für Bildung und Forschung, Engineering and Physical Sciences Research Council

Climate action

Openalex Percentile: Top 25%

Fluid Dynamics Simulations and Interactions

1.33

DOI Open Access PDF OpenAlex

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