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Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method

We present the validation of the hybrid sSSA-SDPD method for advection-diffusion-reaction problems coupled to discrete biochemical systems, as presented in the publication “A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-r...

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Detalles Bibliográficos
Autores principales: Drawert, Brian, Jacob, Bruno, Li, Zhen, Yi, Tau-Mu, Petzold, Linda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6293021/
https://www.ncbi.nlm.nih.gov/pubmed/30581900
http://dx.doi.org/10.1016/j.dib.2018.11.103
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author Drawert, Brian
Jacob, Bruno
Li, Zhen
Yi, Tau-Mu
Petzold, Linda
author_facet Drawert, Brian
Jacob, Bruno
Li, Zhen
Yi, Tau-Mu
Petzold, Linda
author_sort Drawert, Brian
collection PubMed
description We present the validation of the hybrid sSSA-SDPD method for advection-diffusion-reaction problems coupled to discrete biochemical systems, as presented in the publication “A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems” (Drawert et al., 2019). We validate 1D diffusion, and 2D diffusion cases against their analytical solutions. We present graphs and tables of data showing the error in the simulation method.
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spelling pubmed-62930212018-12-21 Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method Drawert, Brian Jacob, Bruno Li, Zhen Yi, Tau-Mu Petzold, Linda Data Brief Energy We present the validation of the hybrid sSSA-SDPD method for advection-diffusion-reaction problems coupled to discrete biochemical systems, as presented in the publication “A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems” (Drawert et al., 2019). We validate 1D diffusion, and 2D diffusion cases against their analytical solutions. We present graphs and tables of data showing the error in the simulation method. Elsevier 2018-12-05 /pmc/articles/PMC6293021/ /pubmed/30581900 http://dx.doi.org/10.1016/j.dib.2018.11.103 Text en © 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Energy
Drawert, Brian
Jacob, Bruno
Li, Zhen
Yi, Tau-Mu
Petzold, Linda
Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method
title Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method
title_full Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method
title_fullStr Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method
title_full_unstemmed Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method
title_short Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method
title_sort validation data for a hybrid smoothed dissipative particle dynamics (sdpd) spatial stochastic simulation algorithm (sssa) method
topic Energy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6293021/
https://www.ncbi.nlm.nih.gov/pubmed/30581900
http://dx.doi.org/10.1016/j.dib.2018.11.103
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