Researcher - Adaptive Mesh Refinement for Wind Farm

hace 5 meses

Barcelona, España Barcelona Supercomputing Center (BSC) A tiempo completo

**Job Reference**:

- 573_24_CASE_PNM_R3_T1**Position**:

- Researcher - Adaptive mesh refinement for wind farm simulation (RE3_T1) - AI4S**Closing Date**:

- Sunday, 01 September, 2024**Reference**: 573_24_CASE_PNM_R3_T1**Job title**: Researcher - Adaptive mesh refinement for wind farm simulation (RE3_T1) - AI4S**About BSC**
- The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large-scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries.

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We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.**Context And Mission**
- CASE department mission is to develop scientific and engineering software to efficiently exploit super-computing capabilities (biomedical, geophysics, atmospheric, energy, social and economic simulations). The position is for the Physical and Numerical Modelling (PNM) group of this department. On one hand, the group engages in both transversal and vertical (applied) activities. We are primarily responsible for the development and maintenance of the Alya multi-physics and high-performance computing simulation code. On the other hand, one of the focus of our applied research is the energy sector.
The Physical and Numerical Modelling group from the CASE department at BSC-CNS is seeking a highly motivated researcher to join our team. The focus will be on advancing the meshing kernel of the wind farm simulation pipeline in our in-house solver, Alya, through mesh optimization and adaptation techniques enhanced by machine learning tools. All the algorithms will be implemented in a massively parallel context.

The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.es to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.

"La financiación de estas actuaciones/becas y contratos, procede del Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, en el marco de la Invitación General de la entidad pública empresarial Red.es para participar en los programas de atracción y retención del talento dentro de la Inversión 4 del Componente 19 del Plan de Recuperación, Transformación y Resiliencia.**Key Duties**
- Develop Error Estimation techniques for Mesh Adaptation, with a focus on optimizing accuracy and efficiency in wind farm simulations, ensuring high-quality results in complex fluid dynamics and turbulence scenarios.
- Implement Adaptive Mesh Refinement (AMR) in Alya using a Continuous Integration/Continuous Deployment (CI/CD) approach to ensure robust, automated testing and flawless integration of new features, enhancing the solver's performance in various simulation scenarios.
- Advance the meshing kernel in Alya, including the simplicial adaptation framework and the mesh optimization tool.
- Develop an adaptive simulation framework in Alya, and develop a tailored version for wind farm simulations.
- Contribute to the Code Documentation and Maintenance, ensuring a comprehensive and clear documentation of all developed algorithms and simulation frameworks within Alya, adhering to best practices to support maintainability, collaboration, and effective knowledge transfer within the team.
- Contribute to the verification and validation (V&V) of the simulation models within the Alya solver. This includes ensuring that the meshing algorithms, simulation frameworks, and machine learning models are rigorously tested and validated against real-world data and industry benchmarks.
- Mentor bachelor, master and PhD students, contribute to their academic growth, and possibly participate in teaching and transfer activities

**Requirements**:

- Education
- PhD in Applied Mathematics
- Essential Knowledge and Professional Experience
- Proficiency in Fortran 2008 programming language.
- Extensive experience in high-performance computing (HPC) and parallelization techniques, including MPI and OpenMP.
- Strong background in performance analysis and optimization of computational proc

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