HiDALGO2 explores synergies between modeling, data acquisition, simulation, data analysis, and visualization. It will also efficiently utilize current and future HPC and AI infrastructures to develop highly scalable solutions to global climate and social challenges (e.g., violent weather, floods, pollution). HIDALGO2 aims at bringing together advanced solutions (HPC-AI-HPDA) to provide decision-makers and stakeholders tools that would mitigate the tragic consequences of climate and civilization phenomena, by delivering necessary knowledge.

Use cases and codes

  • Urban air project: In this use case HiDALGO2 team works around the evolution of air in urban areas considering pollution, wind, comfort, and planning. The core of their work here is the Urban Air Flow (UAP.AF) computational model that that relies heavily on modern HPC, mathematical, and AI technologies, and which is based on two main software: OpenFOAM and Fluid-Solver. For both solvers, modeling of more physical properties will be developed including thermal convection, solar heat radiation, transport, and reaction between several species.

  • Urban building model: Here HiDALGO2 focuses on advanced building models for better integration with urban architecture. The team aims to provide a source term for heat and air pollutants (CO2 and NOx) to the urban air pollution model. Their use a simplified monozone model to keep the problem size reasonable.

  • Renewable energy sources: HiDALGO2 aims to advance energy production estimation from renewable energy sources, such as wind farms and solar panels, and also predict damages to the renewable energy system infrastructure. HiDALGO2 team achieves this by applying an uncertainty quantification study to the simulation models and by running the ensembles on a larger scale. Multiscale weather predictions are here based on Fortran and MPI coupled energy production estimation (based on AI/HPDA).

  • Wildfires: To simulate wildfire-atmosphere interactions and smoke dispersion at various scales, HiDALGO2 implements the computational environment necessary in order to assess the risk and potential impacts induced by mesoscale and microscale fire behavior in the vicinity of and within wildland-urban interface zones. Weather scenarios are generated from WRF (Weather Research and Forecasting) and LES (Large-Eddy Simulation) models at detailed scales, and coupled with CFD (Computational Fluid Dynamics) solutions to model airflow at the settlement scale.

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