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Research groups<\/p>\n
[\/et_pb_text][et_pb_code disabled_on=\u00bboff|off|off\u00bb admin_label=\u00bbCluster groups code\u00bb _builder_version=\u00bb4.27.4″ _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb]<\/p>\n
<\/div>\n
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Este cl\u00faster aprovecha la experiencia de los grupos Kratos Multiphysics y Intelligent Multiphase Modelling in Microsystems (IM\u00b3) para desarrollar marcos computacionales avanzados para fen\u00f3menos multif\u00edsicos complejos, combinando capacidades de HPC con enfoques impulsados \u200b\u200bpor IA para aplicaciones industriales.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row admin_label=\u00bb1px Line Row\u00bb _builder_version=\u00bb4.27.4″ _module_preset=\u00bbdefault\u00bb width=\u00bb100%\u00bb max_width=\u00bb2500px\u00bb custom_margin=\u00bb0px||0px||true|false\u00bb custom_padding=\u00bb0px||0px||true|false\u00bb collapsed=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb][et_pb_column type=\u00bb4_4″ _builder_version=\u00bb4.27.4″ _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb][et_pb_divider show_divider=\u00bboff\u00bb _builder_version=\u00bb4.27.4″ _module_preset=\u00bbdefault\u00bb width=\u00bb100%\u00bb height=\u00bb0px\u00bb custom_margin=\u00bb0px||0px||true|false\u00bb custom_padding=\u00bb0px||0px||true|false\u00bb border_width_bottom=\u00bb1px\u00bb border_color_bottom=\u00bb#d9d9d9″ global_colors_info=\u00bb{}\u00bb][\/et_pb_divider][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\u00bb1_3,1_3,1_3″ _builder_version=\u00bb4.27.4″ _module_preset=\u00bbc7c24b71-68f1-4ba2-bc79-49dcbcce5ea1″ custom_margin=\u00bb|0px||0px|false|false\u00bb custom_padding=\u00bb50px|0px|50px|0px|false|false\u00bb collapsed=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb][et_pb_column type=\u00bb1_3″ _builder_version=\u00bb4.27.0″ _module_preset=\u00bb56e57fde-4561-4cf6-a771-0a733a7201b1″ global_colors_info=\u00bb{}\u00bb][\/et_pb_column][et_pb_column type=\u00bb1_3″ _builder_version=\u00bb4.27.0″ _module_preset=\u00bb56e57fde-4561-4cf6-a771-0a733a7201b1″ global_colors_info=\u00bb{}\u00bb][et_pb_text _builder_version=\u00bb4.27.4″ _module_preset=\u00bbdefault\u00bb global_colors_info=\u00bb{}\u00bb]<\/p>\n El Cl\u00faster de Investigaci\u00f3n en Computaciones Multif\u00edsicas a Gran Escala del CIMNE representa un esfuerzo integrador entre dos grupos de investigaci\u00f3n especializados: el grupo de Multif\u00edsica Kratos, dirigido por el Dr. Riccardo Rossi, y el grupo de Modelado Inteligente Multif\u00e1sico en Microsistemas (IM\u00b3), dirigido por el Dr. Pavel Ryzhakov. Esta colaboraci\u00f3n crea un potente ecosistema de investigaci\u00f3n dedicado al desarrollo de soluciones computacionales para problemas multif\u00edsicos complejos.<\/span><\/p>\n <\/p>\n El grupo Kratos Multiphysics se centra en el desarrollo de un marco integral de investigaci\u00f3n de c\u00f3digo abierto que integra capacidades de vanguardia en m\u00faltiples campos. Su misi\u00f3n se centra en aprovechar los recursos de la Computaci\u00f3n de Alto Rendimiento (HPC) para simular problemas de ingenier\u00eda realistas mediante tecnolog\u00edas de soluci\u00f3n innovadoras y la integraci\u00f3n de modelos interdisciplinarios. El grupo promueve el desarrollo de c\u00f3digo abierto y la colaboraci\u00f3n internacional, trabajando para unificar diversas tecnolog\u00edas dentro del marco de Kratos.<\/span><\/p>\n <\/p>\n Como complemento a este esfuerzo, el grupo de Modelado Inteligente Multif\u00e1sico en Microsistemas (IM\u00b3) aporta experiencia especializada en din\u00e1mica de fluidos computacional para sistemas microflu\u00eddicos. Su investigaci\u00f3n abarca el desarrollo de modelos CFD robustos mediante t\u00e9cnicas avanzadas como M\u00e9todos de Elementos Finitos Enriquecidos, t\u00e9cnicas de Conjuntos de Niveles Mejorados y enfoques de Conjuntos de Niveles Conservativos para flujos multif\u00e1sicos. El grupo tambi\u00e9n realiza estudios experimentales de fen\u00f3menos microflu\u00eddicos e integra inteligencia artificial mediante aplicaciones de aprendizaje autom\u00e1tico y procesamiento de im\u00e1genes.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=\u00bb1_3″ _builder_version=\u00bb4.27.0″ _module_preset=\u00bb56e57fde-4561-4cf6-a771-0a733a7201b1″ global_colors_info=\u00bb{}\u00bb][et_pb_text _builder_version=\u00bb4.27.4″ _module_preset=\u00bbdefault\u00bb custom_padding=\u00bb|5px||||\u00bb global_colors_info=\u00bb{}\u00bb]<\/p>\n El impacto del cl\u00faster se demuestra a trav\u00e9s de proyectos pr\u00e1cticos que incluyen DECIMA, que desarrolla modelos computacionales para la fabricaci\u00f3n digital basada en microfluidos; DIDRO, centrado en la creaci\u00f3n de gemelos digitales para impresoras de inyecci\u00f3n de tinta; y AMADEUS, que estableci\u00f3 nuevos marcos para el an\u00e1lisis de evacuaci\u00f3n de agua l\u00edquida en celdas de combustible.<\/span><\/p>\n <\/p>\n Este grupo de investigaci\u00f3n aborda desaf\u00edos de ingenier\u00eda cada vez m\u00e1s complejos para su aplicaci\u00f3n directa en la industria y las cargas sociales, manteniendo al mismo tiempo un enfoque colaborativo y un compromiso con las soluciones de c\u00f3digo abierto.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\u00bb1_3,1_3,1_3″ _builder_version=\u00bb4.27.0″ _module_preset=\u00bbc7c24b71-68f1-4ba2-bc79-49dcbcce5ea1″ custom_margin=\u00bb|0px||0px|false|false\u00bb custom_padding=\u00bb50px|0px|50px|0px|false|false\u00bb locked=\u00bboff\u00bb collapsed=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb][et_pb_column type=\u00bb1_3″ _builder_version=\u00bb4.27.0″ _module_preset=\u00bb56e57fde-4561-4cf6-a771-0a733a7201b1″ global_colors_info=\u00bb{}\u00bb][et_pb_image src=\u00bbhttps:\/\/cimne.com\/wp-content\/uploads\/2025\/07\/rc9_1.jpg\u00bb title_text=\u00bbrc9_1″ 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