Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Alireza Tabarraei"'
Publikováno v:
Volume 9: Mechanics of Solids, Structures, and Fluids; Micro- and Nano-Systems Engineering and Packaging; Safety Engineering, Risk, and Reliability Analysis; Research Posters.
In this present work, a neural network (NN) is trained to deal with the optimization process of topology optimization and generate optimized structures. The NN’s activation functions are used to represent the popular Solid Isotropic Material with P
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0ed16eec8b8aab649c1aaf4e808a694
https://doi.org/10.1115/imece2022-94604
https://doi.org/10.1115/imece2022-94604
Autor:
Alireza Tabarraei, Mohan S. R. Elapolu
Publikováno v:
The Journal of Physical Chemistry C. 125:11147-11158
Molecular dynamics (MD) is employed to study the mechanical and fracture properties of polycrystalline graphene with hydrogenated grain boundaries. Polycrystalline graphene sheets with an average grain size of 4, 6, and 8 nm are considered. The impac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f27d4f86f125ff534b545b5934e1c44a
https://doi.org/10.1021/acs.jpcc.1c01328
https://doi.org/10.1021/acs.jpcc.1c01328
Publikováno v:
Finite Elements in Analysis and Design. 218:103919
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20fa194ac15c691189f37504efb59130
https://doi.org/10.1016/j.finel.2023.103919
https://doi.org/10.1016/j.finel.2023.103919
Autor:
Mohan S. R. Elapolu, Alireza Tabarraei
Publikováno v:
The Journal of Physical Chemistry A. 124:7060-7070
Using molecular dynamics (MD) simulations, we study the mechanism of stress corrosion cracking in graphene. Two sets of modelings are conducted. In the first one, large graphene sheets with cracks in the armchair and zigzag directions are exposed to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e34e92aea735a25445d18f75e0a96829
https://doi.org/10.1021/acs.jpca.0c04758
https://doi.org/10.1021/acs.jpca.0c04758
Autor:
Alireza Tabarraei, Mohan S. R. Elapolu
Publikováno v:
The Journal of Physical Chemistry C. 124:17308-17319
The impact of hydrogenation on the fracture toughness and strength of grain boundaries in graphene are studied. Molecular dynamics (MD) modeling are used to extract the traction–separation laws of ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d24d4f6513fb66e75fe068d645a8eda
https://doi.org/10.1021/acs.jpcc.0c04122
https://doi.org/10.1021/acs.jpcc.0c04122
Publikováno v:
Computational Materials Science. 218:111924
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee8f6d370af1c9deca3063e472132c49
https://doi.org/10.1016/j.commatsci.2022.111924
https://doi.org/10.1016/j.commatsci.2022.111924
Publikováno v:
Volume 12: Mechanics of Solids, Structures, and Fluids; Micro- and Nano- Systems Engineering and Packaging.
A machine learning model is developed to predict the crack propagation path in polycrystalline graphene sheets. The dataset used for training the machine learning (ML) model is obtained from the molecular dynamics (MD) simulations. A training set of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0779407c0a404a73d23a4a4942a9caf
https://doi.org/10.1115/imece2021-70543
https://doi.org/10.1115/imece2021-70543
Publikováno v:
Volume 12: Mechanics of Solids, Structures, and Fluids; Micro- and Nano- Systems Engineering and Packaging.
A data-driven deep convolution neural network model is used to predict the fracture properties of polycrystalline graphene from the atomic resolution image. A large dataset is prepared using molecular dynamic simulations and atomic resolution image o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54eb678556ef46b144703d671c4d046c
https://doi.org/10.1115/imece2021-70580
https://doi.org/10.1115/imece2021-70580
Publikováno v:
Engineering Fracture Mechanics. 212:1-12
Molecular dynamics modeling is used to study the mechanism of brittle fracture in multi-layer two-dimensional molybdenum disulfide ( MoS 2 ) with a center crack subjected to mode-I loading. The simulation data is used to verify the application of Gri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b031a44313d4540a371e2fe57a5e6d7
https://doi.org/10.1016/j.engfracmech.2019.02.027
https://doi.org/10.1016/j.engfracmech.2019.02.027