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Cl\u00faster de recerca<\/p>\n
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Persona de contacte<\/p>\n
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Xavier Mart\u00ednez<\/p>\n
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L\u00edders acad\u00e8mics<\/p>\n
[\/et_pb_text][et_pb_text admin_label=\u00bbAcademic Leaders\u00bb _builder_version=\u00bb4.27.6″ _module_preset=\u00bbf199e95e-376a-4f66-b51b-482255312542″ locked=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb]<\/p>\n
Luc\u00eda G. Barbu, Gabriel Bugeda, Ester Comellas, \u00c1lex Ferrer, Xavier Mart\u00ednez, Enrique Ortega, Ferm\u00edn Otero, Jacques Francis Periaux, Jordi Pons-Prats, Borja Servan.<\/p>\n
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Assessors externs<\/p>\n
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Spencer Sherwin, Michael Kleiber, Josef Eberhardsteiner<\/p>\n
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Research groups<\/p>\n
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<\/div>\n
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El Cl\u00faster de Recerca d’Enginyeria Aeron\u00e0utica, Marina, Automoci\u00f3 i Energia desenvolupa models num\u00e8rics per a reptes aeroespacials, marins, automocionals i energ\u00e8tics mitjan\u00e7ant simulacions estructurals termomec\u00e0niques, interacci\u00f3 fluid-estructura i optimitzaci\u00f3 del rendiment per crear solucions de transport ambientalment sostenibles.<\/p>\n
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El cl\u00faster s’especialitza en el desenvolupament de marcs num\u00e8rics avan\u00e7ats per abordar reptes complexos en els sectors aeroespacial, oce\u00e0nic i mar\u00edtim, automoci\u00f3 i energia. La seva experi\u00e8ncia abasta l’an\u00e0lisi termomec\u00e0nica, la interacci\u00f3 fluid-estructura i l’optimitzaci\u00f3 del rendiment per crear solucions innovadores que equilibrin l’excel\u00b7l\u00e8ncia t\u00e8cnica amb la sostenibilitat ambiental.<\/p>\n
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Els \u00e8xits recents inclouen el desenvolupament de models digitals per a convertidors d’energia oce\u00e0nica, formulacions avan\u00e7ades per simular materials compostos, t\u00e8cniques d’optimitzaci\u00f3 topol\u00f2gica i algorismes de simulaci\u00f3 de fatiga. El cl\u00faster tamb\u00e9 est\u00e0 actiu en el disseny de dispositius de control de flux per a aplicacions aeron\u00e0utiques i e\u00f2liques, aix\u00ed com en l’optimitzaci\u00f3 del disseny d’infraestructures i operacions de transport aeri, com ara aeroports i vertiports en el paradigma emergent de la mobilitat a\u00e8ria urbana (UAM).<\/p>\n
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El cl\u00faster utilitza algorismes de modelatge d’ordre redu\u00eft (ROM) per a la predicci\u00f3 del rendiment en temps real de components complexos a gran escala i integra l’aprenentatge autom\u00e0tic i la intel\u00b7lig\u00e8ncia artificial en els processos de disseny de materials i estructurals. Amb un fort enfocament en la reducci\u00f3 de les emissions de CO\u2082 i la depend\u00e8ncia dels combustibles f\u00f2ssils, el cl\u00faster \u00e9s pioner en la investigaci\u00f3 de materials neutres en carboni, materials de transformaci\u00f3 amb capacitats adaptatives i t\u00e8cniques de proves virtuals que minimitzen els requisits f\u00edsics del laboratori.<\/p>\n
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Les \u00e0rees d’inter\u00e8s emergents inclouen simulacions CFD de vehicles de mobilitat a\u00e8ria urbana multirotor, an\u00e0lisi de propagaci\u00f3 de soroll aerodin\u00e0mic al voltant de la infraestructura de transport, an\u00e0lisis de c\u00e0rrega hidroel\u00e0stiques i integrades totalment acoblades de vaixells i estructures flotants, algorismes de fatiga avan\u00e7ats basats en aprenentatge autom\u00e0tic que tenen en compte els efectes de la fabricaci\u00f3 i la integraci\u00f3 de materials innovadors d’autoreparaci\u00f3 en aplicacions estructurals de nova generaci\u00f3.<\/p>\n
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