Study of numerical algorithms for multi-model simulations of environmental flows

Fields:

Potential flow theory, Navier-Sokes equations, Domain Decomposition

Profile:

The researcher will carry out research activities in the computational fluid dynamics field, using instruments from numerical analysis, scientific computing and data science. The ideal candidate has a multidisciplinary background, with experience in fields such as physics, engineering, mathematics and mathematical modeling, numerical analysis and simulation of complex systems, computer science and knowledge/use of high performance computing platforms and graphical libraries. The candidate must also have the professional background to work in a highly multidisciplinary team such as the IMT School one.

Activity:

The researcher will provide their contribution to the development of reduced order models for urban flows. In particular, the solvers to be studied will be based on the decomposition of the domain into regions in which the flow is vortical and regions in which vorticity is absent. As in the latter regions a Laplace fluid dynamic model can be used, such an approach allows for a significant reduction of the domain portion in which full Navier—Stokes equations need to be solved, with a consequent decrease in the overall computational time. The researcher will then work on algorithms able to interface Navier—Stokes solvers with potential flow solvers based on Boundary Element Method (BEM) discretization, which are currently under development at the IMT School.

Formal requirements:

• Master's Degree in Mathematical Engineering, Physical Engineering, Industrial Engineering (Aerospace, Mechanical, Energetics, Nuclear, etc.), Civil Engineering or equivalent, Mathematics, Physics, Computer Science, Computer Engineering, Data Science and Scientific Computing;
• Good knowledge of written and spoken English.

Specific requirements:

• Research experiences in: mathematical modeling, numerical analysis and simulation of complex systems for biomedical, environmental and industrial problems;
• Experience in optimization and control, data assimilation, data science, computer programming (Matlab, Python, C++), use/development of software libraries for scientific computing, use of high performance computing platforms.

Duration:

1 year, renewable

Gross amount:

€ 25.815,00 per year

SSD:

MATH-05/A Numerical Analysis

Project:

PRIN 2022 PNRR A_MOLA P2022FEZS3 Titolo: "ROMEU: Reduced Order Models for Environmental and Urban flows" (codice UGOV: P0334; Codice MUR: P2022FEZS3; CUP: D53D23018880001) finanziato dall’Unione europea – Next Generation EU nell’ambito del Piano Nazionale di Ripresa e Resilienza PNRR, Missione 4 Componente 2 Linea di Investimento 1.1.