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Computational Fluid Dynamics (CFD) in Building Ventilation

November 5 - November 26

Welcome to Computational Fluid Dynamics (CFD) in Building Ventilation


The application of Computational Fluid Dynamics in building ventilation systems is crucial for creating environments that are not only energy – efficient and compliant with regulations but also prioritize occupant health, safety, and comfort. CFD provides a comprehensive understanding of airflow dynamics, enabling engineers and designers to make informed decisions that positively impact the performance of building ventilation systems in the real world.

 This Ph D course delves into the intricacies of Computational Fluid Dynamics ( CFD) as applied to building ventilation. Participan ts will explore advanced numerical methods and s imulation techniques essential for understanding and optimizing airflow within built environments. The course emphasizes practical applications, bridging theoretical concepts with real- world scenarios to enha nce participants’ skills in addressing ventilation challenges.

The course is organized in three days. In the f i rst day, the course gives a n introduction of CFD fundamentals and building ventilation designs by using CFD commonly in practice through different case studies. In the second day, the concepts previously learnt are used to implement concepts from the theory to benchmark study. In the third day, the impact of CFD on IAQ, infection r isk and thermal comfort studies is discussed with through different case studies and exercises.

Day 1 : Introduction to CFD in Ventilation ( Theoretical day)

–          Background and Introduction to CFD principles.

–          Basics of f luid dynamics in the context of building ventilation.

–          Laminar, Transitional and Turbulent f lows in buildings.

–          Application of CFD in building ventilation design

–          The use of Benchmarks for model validation.

Day 2 : CFD techniques in ventilation

–          Problems and possibilities to consider prior to a CFD prediction

–          Building geometry and mesh generation using CFD s imulation software.

–          Boundary conditions as diffusers , people etc.

–          Numerical solver setup.

–          Hands- on workshop: CFD Benchmark study and problem description Practical exercise: https:// www. cfd- benchmarks. com/ Backwardflow/

 Day 3 : Practical Applications

–          CFD for Thermal Comfort, infection r isk and IAQ.

–          Interactive session: Participants present their s imulation results , supplemented with feedbacks and discussion.

–          Validation and verification of CFD simulations through benchmark studies.

–          Discussion on challenges and best practices in CFD for building ventilation.

–          Future trends and advancements in the f ield.

 Participants will gain hands – on experience through practical exercises and real- world case studies, ensuring they leave the course with a comprehensive understanding of applying CFD to optimize building ventilation systems.



·         Basic knowledge of thermo- fluid dynamics in buildings

·         Basic knowledge on building ventilation systems

·         Basic knowledge of CFD s imulation tools.


Learning objectives:

After the course, participants will be able t o increase their knowledge about the most recent CFD techniques and their applications in the built environment.


Teaching methods:

Teaching will be provided as a mix of lecture presentations, hands – on trainings, simulation exercises and discussions .


Criteria for assessment:

Participants will be evaluated through a f inal assignment, which consists in the preparation of a report to be delivered 2 weeks after the end of the course.

Key literature:

  • Nielsen, P. V. ( 2015 ) . Fifty years of CFD for room air distribution, Building and Environment , Volume 91 , September 2015 , Pages 78 – 90 , ldenv.2015.02.035
  • Li, Y., & Nielsen, P. V. ( 2011 ) . CFD and ventilation research. Indoor air 21 ( 6 ) , 442 – 453 .
  • Cuce, E., Sher, F., Sadiq, H., Cuce, P. M., Guclu, T., & Besir, A. B. ( 2019 ) . Sustainable ventilation strategies in buildings: CFD research. Sustainable Energy Technologies and Assessments, 36 , 100540 .
  • Michael Wetter, Wangda Zuo, Thierry S. Nouidui & Xiufeng Pang . ( 2014 ) . Modelica Buildings l ibrary, Journal of Building Performance Simulation, 7 : 4 , 253 – 270 .
  • Chen, Q. ( 2009 ) . Ventilation performance prediction for buildings: A method overview and recent applications. Building and environment, 44 ( 4 ) , 848 – 858 .
  • CFD benchmark:
  • Peng, L., Nielsen, P. V., Wang, X., Sadrizadeh, S., Liu, L., & Li, Y. ( 2016 ) . Possible user dependent CFD predictions of t ransitional f low in building ventilation.  Building and Environment, 99 , 130 – 141 . https:// doi. org/ 10 . 1016 / j . buildenv. 2016 . 01 . 014
  • Van Hooff, T., Nielsen, P. V., & Li, Y. ( 2018 ) . Computational f luid dynamics predictions of non- isothermal ventilation f low — How can the user factor be minimized? Indoor Air, 28 ( 6 ) , 866 – 880 . https:// doi. org/ 10 . 1111 / ina. 12492

Prof. Alireza Afshari


Peter V. Nielsen, Professor ( Aalborg University)

Chen Zhang, Associate Professor ( Aalborg University) 

Haider Latif, Postdoc ( Aalborg University)



5,6 & 26 November 2024


Aalborg University ( Copenhagen campus). Online participation will be available.


Number of seats:

15 October 2024

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November 5
November 26
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