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PDC2022-133663-C21

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DESARROLLO DE HERRAMIENTAS PARA LA EVALUACION DE RIEGOS, ALERTA TEMPRANA Y COMPU...

DESARROLLO DE HERRAMIENTAS PARA LA EVALUACION DE RIEGOS, ALERTA TEMPRANA Y COMPUTACION EFICIENTE PARA MAREMOTOS, FLUJOS DE LAVA Y DESLIZAMIENTOS I SUBPROJECT I AIMS TO DEVELOP EFFICIENT TOOLS FOR THE PREDICTION AND SIMULATION OF NATURAL HAZARDS THAT WOULD BE THEN INCORPORATED INTO EARLY WARNING SYSTEMS (EWS) ALLOWING TO MITIGATE PERSONAL AND ECONOMICAL LOSES DUE TO SUCH DISA... ver más

01/01/2022

UMA

104K€

Presupuesto del proyecto: 104K€

Líder del proyecto

UNIVERSIDAD DE MÁLAGA No se ha especificado una descripción o un objeto social para esta compañía.

Total investigadores 1951

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Financiación concedida El organismo AGENCIA ESTATAL DE INVESTIGACIÓN notifico la concesión del proyecto el día 2022-01-01

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Líder del proyecto

UNIVERSIDAD DE MÁLAGA

Total investigadores 1951

Presupuesto del proyecto 104K€

Descripción del proyecto SUBPROJECT I AIMS TO DEVELOP EFFICIENT TOOLS FOR THE PREDICTION AND SIMULATION OF NATURAL HAZARDS THAT WOULD BE THEN INCORPORATED INTO EARLY WARNING SYSTEMS (EWS) ALLOWING TO MITIGATE PERSONAL AND ECONOMICAL LOSES DUE TO SUCH DISASTERS. IN THE LAST 10 YEARS THE RESEARCH TEAM OF SUBPROJECT I HAS CONTRIBUTED TO IMPROVE SOME EXISTING TSUNAMI EWS BY THE DESIGN OF EFFICIENT NUMERICAL MODELS THAT TAKE ADVANTAGE OF THE USE OF NEW HPC TECHNIQUES. IN PARTICULAR, THEY HAVE FOCUSED ON THE DEVELOPMENT OF EFFICIENT GEOPHYSICAL FLOW SIMULATORS WHOSE MAIN INGREDIENTS ARE: (A) MATHEMATICAL MODELS BASED ON THE SHALLOW WATER AND HYDROSTATIC PRESSURE ASSUMPTIONS, (B) EFFICIENT AND ROBUST NUMERICAL METHODS, (C) INNOVATIVE HPC IMPLEMENTATION THAT USES MODERN GPUS. THESE SIMULATORS HAVE RECEIVED GREAT ATTENTION BY THE GEOPHYSICAL FLOW COMMUNITY AND, VERY ESPECIALLY, BY THE TSUNAMI COMMUNITY. THE TEAM HAS SUCCESSFULLY DEVELOPED THE FIRST GPU-BASED NUMERICAL MODEL, KNOWN AS TSUNAMI-HYSEA, TO ACCELERATE TSUNAMI SIMULATIONS. TSUNAMI-HYSEA IS NOWADAYS A TOOL USED BY DIFFERENT NATIONAL TSUNAMI EWS ACHIEVING TRL9, AND HAS BEEN AWARDED WITH THE 2018 NVIDIA GLOBAL IMPACT PRIZE. THE KEY OF THIS SUCCESS HAS BEEN THE ROBUSTNESS AND THE SPEED OF THE SOLVERS, THAT ARE ABLE TO GIVE FASTER THAN REAL TIME (FTRT) RELIABLE SIMULATIONS. DURING THE MEGAFLOW PROJECT, THE RESEARCH TEAM OF SUBPROJECT I HAS DEVELOPED SEVERAL USEFUL TOOLS FOR TSUNAMI MODELLING THAT INCORPORATES DISPERSIVE AND NON-HYDROSTATIC EFFECTS. SUCH DISPERSIVE EFFECTS ARE IMPORTANT IN ORDER TO CORRECTLY PREDICT THE PHASE SPEED OF THE WAVES, WHICH DEPENDS ON THEIR FREQUENCY. THIS IS CRUCIAL TO BETTER PREDICT THE ARRIVAL TIME OF THE WAVE TO THE COAST OR TO REPRODUCE ACCURATELY ITS SHAPE IN TSUNAMI EVENTS. THE FIRST OBJECTIVE OF SUBPROJECT I WILL BE TO IMPROVE THE PROTOTYPE NAMED AS NONHYDROHYP-HYSEA MODEL THAT INCORPORATES DISPERSIVE EFFECTS AND WHICH MAY BE NOW CONSIDERED AS TRL3. THE GOAL IS TO UPGRADE IT TO TRL9, TAKING ADVANTAGE OF THE KNOWLEDGE ACQUIRED DURING THE DEVELOPMENT AND INTEGRATION IN EWS OF TSUNAMI-HYSEA.THE SECOND GOAL IS TO UPGRADE TO TRL7 THE PROTOTYPE NAMED AS MULTILAYER-HYSEA SO THAT IT CAN BE INTEGRATED IN OPERATION ENVIRONMENTS. THIS PROTOTYPE, DEVELOPED DURING THE MEGAFLOW PROJECT, IS BASED ON A MULTILAYER NON-HYDROSTATIC MODEL THAT SIGNIFICANTLY IMPROVES THE QUALITY OF THE VERTICAL STRUCTURE OF THE FLOW, WHAT ALLOWS TO BETTER REPRODUCE TSUNAMI EVENTS GENERATED BY LANDSLIDES. THE THIRD OBJECTIVE IS RELATED TO THE KNOWLEDGE PROTECTION OF THE RESEARCH RESULTS AND THEIR EXPLOITATION AND TRANSFER TO OTHER INTERESTED THIRD PARTIES. SUBPROJECT I TEAM HAS ALREADY AN OPEN-SOURCE REPOSITORY WHERE A LIMITED VERSION OF TSUNAMI-HYSEA IS AVAILABLE FOR RESEARCH PURPOSES. THIS REPOSITORY HAS A BIG IMPACT IN THE DISSEMINATION OF THE RESEARCH RESULTS, MAKING THEM AVAILABLE TO A LARGER PUBLIC. WE INTEND TO IMPROVE THIS OPEN-SOURCE REPOSITORY BY ENHANCING THE ALREADY EXISTING NUMERICAL TOOLS.

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