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Implementation of Dusty Gas Model Based on Fast and Implicit Particle-Mesh Approach SPH-IDIC in Open-Source Astrophysical Code GADGET-2. / Демидова, Татьяна; Савватеева, Татьяна Александровна; Аношин, Сергей Александрович et al.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer, 2023. p. 195-208 14 (Lecture Notes in Computer Science (LNCS); Vol. 14389).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Демидова, Т, Савватеева, ТА, Аношин, СА, Григорьев, В & Стояновская, ОП 2023, Implementation of Dusty Gas Model Based on Fast and Implicit Particle-Mesh Approach SPH-IDIC in Open-Source Astrophysical Code GADGET-2. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)., 14, Lecture Notes in Computer Science (LNCS), vol. 14389, Springer, pp. 195-208, 9th Russian Supercomputing Days International Conference, Москва, Russian Federation, 25.09.2023. https://doi.org/10.1007/978-3-031-49435-2_14

APA

Демидова, Т., Савватеева, Т. А., Аношин, С. А., Григорьев, В., & Стояновская, О. П. (2023). Implementation of Dusty Gas Model Based on Fast and Implicit Particle-Mesh Approach SPH-IDIC in Open-Source Astrophysical Code GADGET-2. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 195-208). [14] (Lecture Notes in Computer Science (LNCS); Vol. 14389). Springer. https://doi.org/10.1007/978-3-031-49435-2_14

Vancouver

Демидова Т, Савватеева ТА, Аношин СА, Григорьев В, Стояновская ОП. Implementation of Dusty Gas Model Based on Fast and Implicit Particle-Mesh Approach SPH-IDIC in Open-Source Astrophysical Code GADGET-2. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2023. p. 195-208. 14. (Lecture Notes in Computer Science (LNCS)). doi: 10.1007/978-3-031-49435-2_14

Author

Демидова, Татьяна ; Савватеева, Татьяна Александровна ; Аношин, Сергей Александрович et al. / Implementation of Dusty Gas Model Based on Fast and Implicit Particle-Mesh Approach SPH-IDIC in Open-Source Astrophysical Code GADGET-2. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer, 2023. pp. 195-208 (Lecture Notes in Computer Science (LNCS)).

BibTeX

@inproceedings{1be80045131e4709adf0ff22c58f7696,
title = "Implementation of Dusty Gas Model Based on Fast and Implicit Particle-Mesh Approach SPH-IDIC in Open-Source Astrophysical Code GADGET-2",
abstract = "Particle approaches considered to study the interaction of dust grains of the same size and a gas medium based on Smoothed Particle Hydrodynamics method. The paper compares two algorithms for solving this problem, described in [1, 2]. Both algorithms were implemented by in a modified version of the GADGET-2 program code. One-dimensional and three-dimensional tests were carried out in order to confirm the properties of the algorithms and to make performance measurements of the code.",
keywords = "Computational Physics, Epstein drag simulation, Hydrodynamics",
author = "Татьяна Демидова and Савватеева, {Татьяна Александровна} and Аношин, {Сергей Александрович} and Виталий Григорьев and Стояновская, {Ольга Петровна}",
note = "The study was founded by the Russian Science Foundation grant number 23-11-00142.; 9th Russian Supercomputing Days International Conference, RuSCDays 2023 ; Conference date: 25-09-2023 Through 26-09-2023",
year = "2023",
doi = "10.1007/978-3-031-49435-2_14",
language = "English",
isbn = "978-303149434-5",
series = "Lecture Notes in Computer Science (LNCS)",
publisher = "Springer",
pages = "195--208",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "United States",

}

RIS

TY - GEN

T1 - Implementation of Dusty Gas Model Based on Fast and Implicit Particle-Mesh Approach SPH-IDIC in Open-Source Astrophysical Code GADGET-2

AU - Демидова, Татьяна

AU - Савватеева, Татьяна Александровна

AU - Аношин, Сергей Александрович

AU - Григорьев, Виталий

AU - Стояновская, Ольга Петровна

N1 - Conference code: 9

PY - 2023

Y1 - 2023

N2 - Particle approaches considered to study the interaction of dust grains of the same size and a gas medium based on Smoothed Particle Hydrodynamics method. The paper compares two algorithms for solving this problem, described in [1, 2]. Both algorithms were implemented by in a modified version of the GADGET-2 program code. One-dimensional and three-dimensional tests were carried out in order to confirm the properties of the algorithms and to make performance measurements of the code.

AB - Particle approaches considered to study the interaction of dust grains of the same size and a gas medium based on Smoothed Particle Hydrodynamics method. The paper compares two algorithms for solving this problem, described in [1, 2]. Both algorithms were implemented by in a modified version of the GADGET-2 program code. One-dimensional and three-dimensional tests were carried out in order to confirm the properties of the algorithms and to make performance measurements of the code.

KW - Computational Physics

KW - Epstein drag simulation

KW - Hydrodynamics

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85182589468&origin=inward&txGid=20ab225bde164b03abd94254916f730d

UR - https://www.mendeley.com/catalogue/33bd83e8-b8fd-30cf-92f1-1217530362bf/

U2 - 10.1007/978-3-031-49435-2_14

DO - 10.1007/978-3-031-49435-2_14

M3 - Conference contribution

SN - 978-303149434-5

T3 - Lecture Notes in Computer Science (LNCS)

SP - 195

EP - 208

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer

T2 - 9th Russian Supercomputing Days International Conference

Y2 - 25 September 2023 through 26 September 2023

ER -

ID: 59681280