CFD Modeling for Classroom Energy Efficiency H/F

Position offered

0.

Research work :

Buildings account for a significant portion of global energy consumption1,2, and accurate modeling of energy consumption in buildings is crucial for reducing energy usage and costs3,4. Traditional black box models5, which rely solely on measured data, can have limitations in predicting energy consumption. Grey box models6, which combine measured data and physical knowledge, are more accurate in predicting energy consumption. However, these models can struggle with capturing non-uniform airflow and convective heat transfer—particularly around features like windows—due to variations in air distribution7.

To address this limitation, this project aims to develop a grey box model to predict energy consumption specifically in classroom environments, enhanced by preliminary Computational Fluid Dynamics (CFD) simulations. The primary focus of the training is to conduct CFD simulations, which will establish accurate parameters for airflow patterns, temperature distribution, and indoor air quality, ultimately enhancing the grey-box model’s predictive precision.

Work program:

The trainee will work on the CFD simulation of airflow, thermal distribution, and IAQ in a real-world classroom environment. The classroom, located in the CESI 3 building in Arras, is equipped with CO₂, temperature, and humidity sensors, providing a valuable dataset for validation purposes. This role falls within Phase 1 of the project and will focus on the following tasks:

1. Literature Review: Understand the fundamentals of CFD and its application to indoor environments, with emphasis on turbulence modeling and boundary condition setup.
2. Pre-Analysis and Geometry Setup: Define the computational domain and prepare a 3D geometry of the classroom.
3. Mesh Generation and Model Setup: Generate a high-quality computational grid and configure CFD models with appropriate turbulence and heat transfer parameters.
4. Simulation and Analysis: Run simulations to capture airflow patterns, temperature gradients, and pollutant dispersion.
5. Validation: Compare CFD outputs with experimental data from the CESI 3 classroom.
6. Sensitivity Analysis: Perform a parametric study to evaluate the impact of mesh resolution, turbulence models, and boundary conditions on results.

Expectations:

1. A validated CFD model of the CESI 3 classroom environment, capable of predicting airflow, temperature distribution, and IAQ under varying conditions.

2. Sensitivity analysis results identifying key parameters affecting CFD accuracy.

3. Fluency in English to write an international peer-reviewed conference paper or an indexed journal paper.

4. A presentation on findings and recommendations for integration into grey-box modeling in future phases of the project (beyond the scope of the current training).

Context

Positioning of the laboratory

LINEACT CESI (EA 7527), Digital Innovation Laboratory for Business and Learning at the service of the Competitiveness of Territories, anticipates and accompanies the technological mutations of the sectors and services related to industry and construction. CESI’s historical proximity to companies is a determining factor for our research activities, and has led us to focus our efforts on applied research close to companies and in partnership with them. A human-centered approach coupled with the use of technologies, as well as the territorial network and the links with training, have allowed us to build a transversal research; it puts the human being, his needs and his uses, at the center of its problems and approaches the technological angle through these contributions.

Its research is organized according to two interdisciplinary scientific themes and two application areas.

– Theme 1 “Learning and Innovation” is mainly concerned with Cognitive Sciences, Social Sciences and Management Sciences, Training Sciences and Techniques and Innovation Sciences. The main scientific objectives of this theme are to understand the effects of the environment, and more particularly of situations instrumented by technical objects (platforms, prototyping workshops, immersive systems, etc.) on the learning, creativity and innovation processes.

– Theme 2 “Engineering and Digital Tools” is mainly concerned with Digital Sciences and Engineering. The main scientific objectives of this theme concern the modeling, simulation, optimization and data analysis of industrial or urban systems. The research work also focuses on the associated decision support tools and on the study of digital twins coupled with virtual or augmented environments.

These two themes develop and cross their research in the two application areas of the Industry of the Future and the City of the Future, supported by research platforms, mainly the one in Rouen dedicated to the Factory of the Future and the one in Nanterre dedicated to the Factory and Building of the Future.