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Title: Computational science and engineering applied to intelligent energy buildings
Short Code: EVA_DMBEM
ECTS Credits: 3
Organizer Details: Frank Tillenkamp:, Christian Ghiaus:

33.3% Written 1h, w/o documents on 2/12/2022

33.3% Written report of group work due on 30/11/2022

33.3% Oral presentation of group work on 2/12/2022

Decision Date: 20 September 2022 
Start Date: 31 October 2022 
End Date: 2 December 2022 
Date Details:

Face to face period: 31/10/2022 09:00 – 4/11/2022 18:00
Exam: 2.12.2022


Face to face lectures and tutorials

(31/10/2022 – 2/11/2022)

20h (22%)

Accompanied exercises and project

(2/11/2022 – 4/11/2022)

20h (22%)

Autonomous group project

(7/11/2022 – 30/11/2022)

50h (56%)


90h (100%)



Description (max. 300 characters):

Buildings are responsible for about 40 % of the energy consumption and CO2 emissions. The course develops computational skills in Python for modelling and problem solving of coupled heat transfer with special applications to optimize energy consumption for indoor climate control.

Contents and Learning Objectives:

Face to face

Lecture module 1

·     thermal transfer: conduction, convection, and radiation


Lecture module 2

·     continuous and discrete models

·     thermal networks

·     transforming the thermal networks into state-space and transfer functions

·     coupling the models


Tutorial 1: Read weather data and calculate solar radiation:

1)    introduction to linear algebra and tools (Python, Numpy, Matplotlib);

2)    use Pyhton for reading (weather) data

3)    calculating the solar load


Tutorial 2: Simple wall

1)    physical analysis and mathematical models

2)    discretization of mathematical models

3)    numerical stability

4)    implementation


Tutorial 3: Simple building in free-running: controlled natural ventilation

1)    physical analysis and mathematical models

2)    discussion of examples

3)    implementation


Tutorial 4: Simple building controlled by an HVAC system

1)    physical analysis and mathematical models

2)    discussion of examples

3)    implementation


Accompanied individual mini-project:

Intelligent control of a single zone building


Autonomous group project:

Students define their own subject on indoor climate control, for example:

- dynamic insulation,

- dynamic solar protection,

- control of floor-heating and fan coils,

- influence of set-point setback,

- control of intermittently heated buildings,

- model predictive control.

Admission: Required (undergraduate level): linear algebra, calculus, heat transfer, thermodynamics, computer programming. Desirable (but not compulsory): dynamic systems, control engineering

The course is self-contained: all teaching materials are provided as PDF (bibliography, supporting materials, slides for lectures, and tutorials in Python).



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

·      J.A. Clarke (2001) Energy Simulation in Building Design, 2nd edition, Butterworth Heinemann, ISBN 0 7506 5082 6

·      C. Ghiaus (2013) Causality issue in the heat balance method for calculating the design heating and cooling load, Energy, vol. 50, pp. 292-301

·      Ghiaus, C., & Ahmad, N. (2020). Thermal circuits assembling and state-space extraction for modelling heat transfer in buildings. Energy195, 117019

·      The Pyhton Tutorial

·      Ghiaus, C. (2022). Dynamic models for building energy management,


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]