Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Nima H. Siboni"'
Autor:
Mohammad S. Khorrami, Jaber R. Mianroodi, Nima H. Siboni, Pawan Goyal, Bob Svendsen, Peter Benner, Dierk Raabe
Publikováno v:
npj Computational Materials, Vol 9, Iss 1, Pp 1-10 (2023)
Abstract The purpose of this work is the development of a trained artificial neural network for surrogate modeling of the mechanical response of elasto-viscoplastic grain microstructures. To this end, a U-Net-based convolutional neural network (CNN)
Externí odkaz:
https://doaj.org/article/dd6344fcbb0b40e585ce83212f4777ba
Publikováno v:
npj Computational Materials, Vol 8, Iss 1, Pp 1-12 (2022)
Abstract A seamless and lossless transition of the constitutive description of the elastic response of materials between atomic and continuum scales has been so far elusive. Here we show how this problem can be overcome by using artificial intelligen
Externí odkaz:
https://doaj.org/article/1046e8e5d12a40498f6b6c3c596c9d0f
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
Abstract We propose a deep neural network (DNN) as a fast surrogate model for local stress calculations in inhomogeneous non-linear materials. We show that the DNN predicts the local stresses with 3.8% mean absolute percentage error (MAPE) for the ca
Externí odkaz:
https://doaj.org/article/7ffda2b990bd48ada3fb0971fd99c195
Publikováno v:
Physical Sciences Reviews. 7:1345-1371
Hybrid mixtures composed of magnetic nanoparticles (MNP) in liquid crystalline (LC) matrices are a fascinating class of soft materials with intriguing physical properties and a wide range of potential applications, e.g., as stimuli-responsive and ada
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f4045f3f7e82094c88474933038fbc35
https://doi.org/10.1515/psr-2019-0108
https://doi.org/10.1515/psr-2019-0108
Autor:
Mohammad S. Khorrami, Jaber R. Mianroodi, Nima H. Siboni, Pawan Goyal, Bob Svendsen, Peter Benner, Dierk Raabe
Publikováno v:
npj Computational Materials
npj computational materials 9, 37 (2023). doi:10.1038/s41524-023-00991-z
npj computational materials 9, 37 (2023). doi:10.1038/s41524-023-00991-z
npj computational materials 9, 37 (2023). doi:10.1038/s41524-023-00991-z
Published by Nature Publ. Group, London
Published by Nature Publ. Group, London
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0507f7b0420ba313055d49faff5cf1e9
Autor:
Iman Peivaste, Nima H. Siboni, Ghasem Alahyarizadeh, Reza Ghaderi, Bob Svendsen, Dierk Raabe, Jaber Rezaei Mianroodi
Publikováno v:
Computational Materials Science. 214:111750
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3c261d9c9a974a5381d8f24fc12e458
https://doi.org/10.1016/j.commatsci.2022.111750
https://doi.org/10.1016/j.commatsci.2022.111750
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
npj Computational Materials
npj Computational Materials
We propose a deep neural network (DNN) as a fast surrogate model for local stress calculations in inhomogeneous non-linear materials. We show that the DNN predicts the local stresses with 3.8% mean absolute percentage error (MAPE) for the case of het
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e809f6bef5b9343293ef6eeaa8a3610a
https://doi.org/10.1038/s41524-021-00571-z
https://doi.org/10.1038/s41524-021-00571-z
Autor:
Klaus Pierz, René Lohmann, Hans Werner Schumacher, J. Schluck, Beate Horn-Cosfeld, Thomas Heinzel, Dominique Mailly, Nima H. Siboni, Jürgen Horbach
Publikováno v:
Physical Review B
Physical Review B, American Physical Society, 2020, 102, ⟨10.1103/physrevb.102.081302⟩
Physical Review B, American Physical Society, 2020, 102, ⟨10.1103/physrevb.102.081302⟩
International audience; The magnetotransport of an electron gas in a two-dimensional, random arrangement of overlapping retrore-flective crosses is studied using a combination of experiment and classical event-driven molecular dynamics simulation. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8246a060fa1c3ee6524fdcbba5232f3
https://hal.archives-ouvertes.fr/hal-03010567/document
https://hal.archives-ouvertes.fr/hal-03010567/document
Publikováno v:
The European Physical Journal Special Topics. 226:3113-3128
The diffusion dynamics of particles in heterogeneous media is studied using particle-based simulation techniques. A special focus is placed on systems where the transport of particles at long times exhibits anomalies such as subdiffusive or superdiff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffe2c6aba80c5096615331fd19febc41
https://doi.org/10.1140/epjst/e2017-70081-3
https://doi.org/10.1140/epjst/e2017-70081-3