Low-variance Monte Carlo Solutions of the Boltzmann Transport Equation

Low-variance Monte Carlo Solutions of the Boltzmann Transport Equation

We present and discuss a variance-reduced stochastic particle method for simulating the relaxation-time model of the Boltzmann transport equation. The present paper focuses on the dilute gas case, although the method is expected to directly extend to all fields (carriers) for which the relaxation-ti...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2009-05
Hauptverfasser: Hadjiconstantinou, Nicolas G, Radtke, Gregg A, Baker, Lowell L
Format: Artikel
Sprache:eng
Schlagworte:
Boltzmann transport equation
Computational efficiency
Computer simulation
Computing time
Deviation
Equilibrium
Monte Carlo simulation
Particle methods (mathematics)
Transport equations
Variance
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Hadjiconstantinou, Nicolas G
Radtke, Gregg A
Baker, Lowell L
description We present and discuss a variance-reduced stochastic particle method for simulating the relaxation-time model of the Boltzmann transport equation. The present paper focuses on the dilute gas case, although the method is expected to directly extend to all fields (carriers) for which the relaxation-time approximation is reasonable. The variance reduction, achieved by simulating only the deviation from equilibrium, results in a significant computational efficiency advantage compared to traditional stochastic particle methods in the limit of small deviation from equilibrium. More specifically, the proposed method can efficiently simulate arbitrarily small deviations from equilibrium at a computational cost that is independent of the deviation from equilibrium, which is in sharp contrast to traditional particle methods.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2087646812</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2087646812</sourcerecordid><originalsourceid>FETCH-proquest_journals_20876468123</originalsourceid><addsrcrecordid>eNqNyrsKwjAUgOEgCBbtOxxwLqRJb7OlxUEnu5eDpNgSc9pcFHx6FXwAp3_4vxWLhJRpUmVCbFjs3MQ5F0Up8lxGrD3RM3mgHdFcFZzJeAU1Wk1wIR38SMYBDeBvCg6k_euOxkBn0biZrIdmCfhFO7YeUDsV_7pl-7bp6mMyW1qCcr6fKFjzWb3gVVlkRZUK-Z96A8KzO20</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2087646812</pqid></control><display><type>article</type><title>Low-variance Monte Carlo Solutions of the Boltzmann Transport Equation</title><source>Freely Accessible Journals</source><creator>Hadjiconstantinou, Nicolas G ; Radtke, Gregg A ; Baker, Lowell L</creator><creatorcontrib>Hadjiconstantinou, Nicolas G ; Radtke, Gregg A ; Baker, Lowell L</creatorcontrib><description>We present and discuss a variance-reduced stochastic particle method for simulating the relaxation-time model of the Boltzmann transport equation. The present paper focuses on the dilute gas case, although the method is expected to directly extend to all fields (carriers) for which the relaxation-time approximation is reasonable. The variance reduction, achieved by simulating only the deviation from equilibrium, results in a significant computational efficiency advantage compared to traditional stochastic particle methods in the limit of small deviation from equilibrium. More specifically, the proposed method can efficiently simulate arbitrarily small deviations from equilibrium at a computational cost that is independent of the deviation from equilibrium, which is in sharp contrast to traditional particle methods.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Boltzmann transport equation ; Computational efficiency ; Computer simulation ; Computing time ; Deviation ; Equilibrium ; Monte Carlo simulation ; Particle methods (mathematics) ; Transport equations ; Variance</subject><ispartof>arXiv.org, 2009-05</ispartof><rights>2009. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>777,781</link.rule.ids></links><search><creatorcontrib>Hadjiconstantinou, Nicolas G</creatorcontrib><creatorcontrib>Radtke, Gregg A</creatorcontrib><creatorcontrib>Baker, Lowell L</creatorcontrib><title>Low-variance Monte Carlo Solutions of the Boltzmann Transport Equation</title><title>arXiv.org</title><description>We present and discuss a variance-reduced stochastic particle method for simulating the relaxation-time model of the Boltzmann transport equation. The present paper focuses on the dilute gas case, although the method is expected to directly extend to all fields (carriers) for which the relaxation-time approximation is reasonable. The variance reduction, achieved by simulating only the deviation from equilibrium, results in a significant computational efficiency advantage compared to traditional stochastic particle methods in the limit of small deviation from equilibrium. More specifically, the proposed method can efficiently simulate arbitrarily small deviations from equilibrium at a computational cost that is independent of the deviation from equilibrium, which is in sharp contrast to traditional particle methods.</description><subject>Boltzmann transport equation</subject><subject>Computational efficiency</subject><subject>Computer simulation</subject><subject>Computing time</subject><subject>Deviation</subject><subject>Equilibrium</subject><subject>Monte Carlo simulation</subject><subject>Particle methods (mathematics)</subject><subject>Transport equations</subject><subject>Variance</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNyrsKwjAUgOEgCBbtOxxwLqRJb7OlxUEnu5eDpNgSc9pcFHx6FXwAp3_4vxWLhJRpUmVCbFjs3MQ5F0Up8lxGrD3RM3mgHdFcFZzJeAU1Wk1wIR38SMYBDeBvCg6k_euOxkBn0biZrIdmCfhFO7YeUDsV_7pl-7bp6mMyW1qCcr6fKFjzWb3gVVlkRZUK-Z96A8KzO20</recordid><startdate>20090513</startdate><enddate>20090513</enddate><creator>Hadjiconstantinou, Nicolas G</creator><creator>Radtke, Gregg A</creator><creator>Baker, Lowell L</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20090513</creationdate><title>Low-variance Monte Carlo Solutions of the Boltzmann Transport Equation</title><author>Hadjiconstantinou, Nicolas G ; Radtke, Gregg A ; Baker, Lowell L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_20876468123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Boltzmann transport equation</topic><topic>Computational efficiency</topic><topic>Computer simulation</topic><topic>Computing time</topic><topic>Deviation</topic><topic>Equilibrium</topic><topic>Monte Carlo simulation</topic><topic>Particle methods (mathematics)</topic><topic>Transport equations</topic><topic>Variance</topic><toplevel>online_resources</toplevel><creatorcontrib>Hadjiconstantinou, Nicolas G</creatorcontrib><creatorcontrib>Radtke, Gregg A</creatorcontrib><creatorcontrib>Baker, Lowell L</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hadjiconstantinou, Nicolas G</au><au>Radtke, Gregg A</au><au>Baker, Lowell L</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Low-variance Monte Carlo Solutions of the Boltzmann Transport Equation</atitle><jtitle>arXiv.org</jtitle><date>2009-05-13</date><risdate>2009</risdate><eissn>2331-8422</eissn><abstract>We present and discuss a variance-reduced stochastic particle method for simulating the relaxation-time model of the Boltzmann transport equation. The present paper focuses on the dilute gas case, although the method is expected to directly extend to all fields (carriers) for which the relaxation-time approximation is reasonable. The variance reduction, achieved by simulating only the deviation from equilibrium, results in a significant computational efficiency advantage compared to traditional stochastic particle methods in the limit of small deviation from equilibrium. More specifically, the proposed method can efficiently simulate arbitrarily small deviations from equilibrium at a computational cost that is independent of the deviation from equilibrium, which is in sharp contrast to traditional particle methods.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2009-05
issn 2331-8422
language eng
recordid cdi_proquest_journals_2087646812
source Freely Accessible Journals
subjects Boltzmann transport equation
Computational efficiency
Computer simulation
Computing time
Deviation
Equilibrium
Monte Carlo simulation
Particle methods (mathematics)
Transport equations
Variance
title Low-variance Monte Carlo Solutions of the Boltzmann Transport Equation
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T15%3A26%3A51IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Low-variance%20Monte%20Carlo%20Solutions%20of%20the%20Boltzmann%20Transport%20Equation&rft.jtitle=arXiv.org&rft.au=Hadjiconstantinou,%20Nicolas%20G&rft.date=2009-05-13&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2087646812%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2087646812&rft_id=info:pmid/&rfr_iscdi=true