Research Interests

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This page provides a short brief on my most active and current research topics, carried out in different contexts: sometimes for engineering purposes through in-house projects, often with internships from various French engineering schools (full list here), and occasionally for academic purposes through external collaborations.

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Urban scale climatic studies

I focus on modeling the interactions between built environments and climate at the city scale. This includes CFD/BES couplings, UHI modeling, and urban geometry analysis.

Urban CFD

• CFD / BES Couplings
  • Pressure coefficients estimation on building envelopes, Cp,
  • Natural ventilation assesments,
  • Weak coupling between surface temperatures (from outdoor EnergyPlus simulations) and CFD results for every wind directions.

Urban scale Thermal Comfort and UHI modelling

• Urban Geometries
  • Extractions,
  • Pre-processing,
  • Model built-ups.
• Outdoor thermal comfort simulations
  • Thermal models, couplings of simulation tools,
  • Urban scale with GIS approaches

  • Post-doctoral co-supervision: Abricocoda: A Novel Approach to Urban Heat Mitigation Through Bio-Analogous Climate Shelters

Radiative View Factors

• Exact calculations of urban view factors,
• Integration to comfort studies (EnergyPlus + inhouse AREP’s codes).
• Maintaining the pyViewFactor python library

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Air Quality in underground train stations

My work combines data analysis, physics-based modeling, experimentation, and simulation to improve air quality in confined railway environments.

Data analysis

• Numerical methods for long term time-series analysis

  Ph.D. co-supervision: Evaluation and Optimization of Air Quality in Underground Railway Enclosures: Analysis of Particle Concentrations and Filtration System Efficiency Valisoa Rakotonirinjanahary (CIFRE–SNCF, Université de Lille, supervised by Benjamin Hanoune).

Equational modeling of air quality

• Physics-based modeling of PM concentration dynamics using differential equations

Experimentations to lower PM levels in active trains station

• Designing instrumentation and experimentation protocols
• Follow-up and analysis of experimental data

AI-based forecasting

• Time series forecasting of PM concentrations with neural networks

CFD simulations

• Forced ventilation studies
• Train-induced “piston effect” modeling
• Pollutant dispersion dynamics

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Datavisualisation and post-processing

A key part of research is being able to communicate results clearly. Effective visualization often conveys insights more powerfully than words.

I work extensively with Paraview and Pyvista for simulation results, but also with some more “classical” Python libraries (Matplotlib / Seaborn / Plotly) for data analysis.

• 2D / 3D renderings,
• Statistical information displays and summaries,
• …

You can have a look at some of my production here !