Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.3547
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dc.contributor.authorAhrens, Robin-
dc.contributor.authorLe Borne, Sabine-
dc.date.accessioned2021-05-20T08:59:36Z-
dc.date.available2021-05-20T08:59:36Z-
dc.date.issued2021-05-02-
dc.identifier.citationAdvances in Computational Mathematics 47 (3): 39 (2021-06-01)de_DE
dc.identifier.issn1019-7168de_DE
dc.identifier.urihttp://hdl.handle.net/11420/9572-
dc.description.abstractThe dynamics of particle processes can be described by population balance equations which are governed by phenomena including growth, nucleation, breakage and aggregation. Estimating the kinetics of the aggregation phenomena from measured density data constitutes an ill-conditioned inverse problem. In this work, we focus on the aggregation problem and present an approach to estimate the aggregation kernel in discrete, low rank form from given (measured or simulated) data. The low-rank assumption for the kernel allows the application of fast techniques for the evaluation of the aggregation integral (O(nlogn) instead of O(n ) where n denotes the number of unknowns in the discretization) and reduces the dimension of the optimization problem, allowing for efficient and accurate kernel reconstructions. We provide and compare two approaches which we will illustrate in numerical tests. 2en
dc.description.sponsorshipDeutsche Forschungsgemeinschaft (DFG)de_DE
dc.language.isoende_DE
dc.publisherSpringer Science + Business Media B.Vde_DE
dc.relation.ispartofAdvances in computational mathematicsde_DE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/de_DE
dc.subjectAggregation kernelde_DE
dc.subjectInverse methodde_DE
dc.subjectLow rank approximationde_DE
dc.subjectPopulation balance equationde_DE
dc.subject.ddc510: Mathematikde_DE
dc.titleReconstruction of low-rank aggregation kernels in univariate population balance equationsde_DE
dc.typeArticlede_DE
dc.identifier.doi10.15480/882.3547-
dc.type.diniarticle-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.0135579-
tuhh.oai.showtruede_DE
tuhh.abstract.englishThe dynamics of particle processes can be described by population balance equations which are governed by phenomena including growth, nucleation, breakage and aggregation. Estimating the kinetics of the aggregation phenomena from measured density data constitutes an ill-conditioned inverse problem. In this work, we focus on the aggregation problem and present an approach to estimate the aggregation kernel in discrete, low rank form from given (measured or simulated) data. The low-rank assumption for the kernel allows the application of fast techniques for the evaluation of the aggregation integral (O(nlogn) instead of O(n ) where n denotes the number of unknowns in the discretization) and reduces the dimension of the optimization problem, allowing for efficient and accurate kernel reconstructions. We provide and compare two approaches which we will illustrate in numerical tests. 2de_DE
tuhh.publisher.doi10.1007/s10444-021-09871-w-
tuhh.publication.instituteMathematik E-10de_DE
tuhh.identifier.doi10.15480/882.3547-
tuhh.type.opus(wissenschaftlicher) Artikel-
dc.type.driverarticle-
dc.type.casraiJournal Article-
tuhh.container.issue3de_DE
tuhh.container.volume47de_DE
dc.relation.projectSPP 1679: Teilprojekt "Numerische Lösungsverfahren für gekoppelte Populationsbilanzsysteme zur dynamischen Simulation multivariater Feststoffprozesse am Beispiel der formselektiven Kristallisation"de_DE
dc.relation.projectProjekt DEAL-
dc.rights.nationallicensefalsede_DE
dc.identifier.scopus2-s2.0-85105236031de_DE
tuhh.container.articlenumber39de_DE
local.status.inpressfalsede_DE
local.type.versionpublishedVersionde_DE
datacite.resourceTypeJournal Article-
datacite.resourceTypeGeneralText-
item.languageiso639-1en-
item.grantfulltextopen-
item.creatorOrcidAhrens, Robin-
item.creatorOrcidLe Borne, Sabine-
item.mappedtypeArticle-
item.creatorGNDAhrens, Robin-
item.creatorGNDLe Borne, Sabine-
item.fulltextWith Fulltext-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
crisitem.author.deptMathematik E-10-
crisitem.author.deptMathematik E-10-
crisitem.author.orcid0000-0003-0473-408X-
crisitem.author.orcid0000-0002-4399-4442-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.funder.funderid501100001659-
crisitem.funder.funderrorid018mejw64-
crisitem.project.funderDeutsche Forschungsgemeinschaft (DFG)-
crisitem.project.funderid501100001659-
crisitem.project.funderrorid018mejw64-
crisitem.project.grantnoBO 4141/1-2-
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