Single view

Title: Computational science and engineering applied to air conditioning systems
Short Code: EVA_DSH
ECTS Credits: 3
Organizer Details: Frank Tillenkamp:, Christian Ghiaus:

33.3% Written 1h, w/o documents on 26/05/2023

33.3% Written report of group work due on 24/05/2023

33.3% Oral presentation of group work on 26/05/2023
Decision Date: 21 February 2023 
Start Date: 10 April 2023 
End Date: 26 May 2023 
Date Details:

Face to face lectures and tutorials

(10/04/2023 – 12/04/2023)

20 h (22 %)

Tutorial and accompanied mini-project

(12/04/2023 – 14/04/2023)

20 h (22 %)

Autonomous group project

(17/04/2023 – 24/05/2023)

50 h (56 %)


90 h (100 %)



Description (max. 300 characters):

Air conditioning increases productivity and comfort but it is responsible for about 15 % of total energy consumption. The course develops competences for practical optimization of air conditioning systems coupled to buildings by using computational thinking and Python implementation.

Contents and Learning Objectives:

Face to face


Module 1: Psychrometrics (numerical calculation of moist air properties, typical transformations). Thermal comfort.

Module 2: Modelling of typical elements of air conditioning systems

Module 3: Modelling and simulation of air conditioning systems coupled to buildings



Tutorial 1: Calculation of moist air properties

Tutorial 2: Numerical modelling of air conditioning systems

Tutorial 3: Coupling air conditioning systems to buildings


Accompanied individual project:


Air mixing and heating

Air-mixing, heating, humidification

Heat recovery, heating, adiabatic humidification

Heat recovery and cooling


Autonomous group project:

The students will define their own subject on indoor climate control (temperature and humidity): a building and its air conditioning system will be modelled. On this model, optimisation of design parameters and energy management will be done.

Examples of projects: detached house, school, office building, green house, supermarket, research laboratory, restaurant.
Admission: The course is self-contained. Subjects useful at undergraduate level: linear algebra, thermodynamics, heat transfer, computer programming (MATLAB / Octave or Python).

All teaching materials are provided as PDF (bibliography, supporting materials and slides for lectures and tutorials).



G. Strang (2007). Computational Science and Engineering, Wellesley-Cambridge Press, ISBN-10 0-9614088-1-2


ASHRAE Fundamentals, chapters F01 Psychrometrics, F07. Fundamentals of controls, F09 Thermal Comfort, F16 Ventilation and Infiltration, F17 and F18 Heating and Cooling Loads


C. Ghiaus (2014). Linear algebra solution to psychometric analysis of air-conditioning systems, Energy vol. 74, pp. 555-566


C. Ghiaus (2022) Computational psychrometric analysis as a control problem: case of cooling and dehumidification systems, International Journal of Building Performance Simulation, 15(1), pp. 21-38,

C. Ghiaus. (2021). PsychroAn_cool: Psychrometric analysis of cooling systems as a control problem. In Journal of Building Performance Simulation (0.0.0, Vol. 15, Number 1, pp. 21–38). Zenodo.


C. Ghiaus (2022). Computational psychrometric analysis of HVAC systems: tutorials,


Required (undergraduate level): linear algebra, calculus, thermodynamics, heat transfer, computer programming (MATLAB / Octave or Python).

Desirable (but not compulsory): dynamic systems, control engineering

Every student needs to have a laptop during the course.


Before the beginning of the course, students need to have Python (Anaconda distribution is recommended) on their laptops.


Prof. Dr.-Ing. Frank Tillenkamp:

Contact Person E-Mail:
Status: registration open
Specialization: Energy and Environment (EE)

Industrial Technologies (InT)

Information and Communication Technologies (ICT)

Building Technologies (BT)

Computer Science (CS)

Energy & Environment (EnEn)

Mechanical Engineering (ME)

Mechatronics & Automation (MA)


[Responsible for this text: Tillenkamp Frank]