<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-17T16:14:49Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2117/329638" metadataPrefix="qdc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2117/329638</identifier><datestamp>2026-02-07T01:19:14Z</datestamp><setSpec>com_2072_1033</setSpec><setSpec>col_2072_452949</setSpec></header><metadata><qdc:qualifieddc xmlns:qdc="http://dspace.org/qualifieddc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
   <dc:title>An adaptive N -fidelity metamodel for design and operational-uncertainty space exploration of complex industrial problems</dc:title>
   <dc:creator>Serani, A.</dc:creator>
   <dc:creator>Pellegrini, R.</dc:creator>
   <dc:creator>Broglia, R.</dc:creator>
   <dc:creator>Wackers, J.</dc:creator>
   <dc:creator>Visonneau, M.</dc:creator>
   <dc:creator>Diez, M.</dc:creator>
   <dc:subject>Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits</dc:subject>
   <dc:subject>Finite element method</dc:subject>
   <dc:subject>Marine engineering</dc:subject>
   <dc:subject>Multi-ﬁdelity, adaptive metamodels, simulation-based design optimization, uncertainty  quantiﬁcation, adaptive-grid reﬁnement, multi-grid acceleration</dc:subject>
   <dc:subject>Enginyeria naval</dc:subject>
   <dcterms:abstract>An adaptive N -ﬁdelity (NF) metamodel is presented for the solution of simulation-&#xd;
&#xd;
based design optimization and uncertainty quantiﬁcation problems.  A multi-ﬁdelity approximation is &#xd;
 built  by  an  additive  correction  of  a  low-ﬁdelity  metamodel  with  metamodels  of  &#xd;
hierarchical diﬀerences (errors) between higher-ﬁdelity levels.  The metamodel is based on the &#xd;
expected value of an ensemble of stochastic radial-basis functions, which also provides the &#xd;
uncertainty associated to the prediction.  New training points are added to the appropriate ﬁdelity &#xd;
level, based on the NF  prediction  uncertainty  and  the  computational  cost.   The  method  is  &#xd;
demonstrated  for  an analytical  test  function,  the  shape  optimization  of  a  NACA  &#xd;
hydrofoil,  and  the  operational- uncertainty  quantiﬁcation  of  a  RoPax  ferry.   The  ﬁdelity  &#xd;
levels  are  deﬁned  by  adaptive-grid reﬁnement and multi-grid approach, for the NACA hydrofoil &#xd;
and the RoPax ferry, respectively. The generalization of the multi-ﬁdelity concept to  N ﬁdelities &#xd;
shows promising results both in terms of accuracy and computational cost.</dcterms:abstract>
   <dcterms:issued>2019</dcterms:issued>
   <dc:type>Conference report</dc:type>
   <dc:rights>Open Access</dc:rights>
   <dc:publisher>CIMNE</dc:publisher>
</qdc:qualifieddc></metadata></record></GetRecord></OAI-PMH>