Radionuclide dispersion from waste piles

dc.contributor.authorTSUTSUMIUCHI, VICTOR K.
dc.coverageInternacional
dc.creator.eventoWASTE MANAGEMENT SYMPOSIUM
dc.date.accessioned2025-01-29T19:35:05Z
dc.date.available2025-01-29T19:35:05Z
dc.date.eventoMarch 10-14, 2024
dc.description.abstractThis project aims to understand radionuclide dispersion in mining, emphasizing safety. Minerals in various industries often contain radionuclides, elevating dispersion risks. Wind plays a key role, potentially contaminating nearby areas. We utilize advanced predictive models, particularly Recurrent Neural Networks, to grasp dispersion patterns. These insights guide safety protocols and responsible decision-making. Our focus is on integrating safety measures and promoting sustainable mining practices, effectively mitigating dispersion risks.
dc.event.siglaWM
dc.identifier.citationTSUTSUMIUCHI, VICTOR K. Radionuclide dispersion from waste piles: a predictive modeling approach using simulations and Recurrent Neural Networks. In: WASTE MANAGEMENT SYMPOSIUM, March 10-14, 2024, Phoenix, AZ, USA. <b>Abstract...</b> Tempe, AZ, USA: WM Symposia, 2024. Disponível em: https://repositorio.ipen.br/handle/123456789/48930.
dc.identifier.urihttps://repositorio.ipen.br/handle/123456789/48930
dc.localTempe, AZ, USA
dc.local.eventoPhoenix, AZ, USA
dc.publisherWM Symposia
dc.rightsopenAccess
dc.titleRadionuclide dispersion from waste piles
dc.typeResumo de eventos científicos
dspace.entity.typePublication
ipen.autorVICTOR KEICHI TSUTSUMIUCHI
ipen.codigoautor15273
ipen.contributor.ipenauthorVICTOR KEICHI TSUTSUMIUCHI
ipen.event.datapadronizada2024
ipen.identifier.ipendoc30987
ipen.notas.internasAbstract
ipen.subtituloa predictive modeling approach using simulations and Recurrent Neural Networks
ipen.type.genreResumo
relation.isAuthorOfPublication87c21f44-e567-4a60-91ca-abf982079690
relation.isAuthorOfPublication.latestForDiscovery87c21f44-e567-4a60-91ca-abf982079690
sigepi.autor.atividadeVICTOR KEICHI TSUTSUMIUCHI:15273:1120:S

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