Duration
26h Th, 14h Pr, 12h Labo., 1d FW
Number of credits
| Master of Science in Energy Engineering | 5 crédits | |||
| Master of Science (MSc) in Electromechanical Engineering | 3 crédits |
Lecturer
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course is dedicated to the application of measurement techniques and to the associated data processing for the performance evaluation components and processes in energy conversion. These techniques are applied in the frame of new component development as well as in the performance monitoring of components used industrial production environment.
The course begins with an introduction describing the measurement chain and continues with the following chapters:
- Sensors characteristics, specification and calibration (principle, methods and reports),
- Propagation of uncertainties and choice of the appropriate instrumentation,
- Uncertainty and statistical data processing of measurement (data rejection),
- Overview of different measurement techniques: temperature, pressure and mass flow rate measurement, directional probes, velocity and humidity measurement and mass flow meters,
- Model calibration and parameters identification,
- Design of vapor compression test rigs (redundancy of measurement, energy and mass balance verifications, importance of calibration and method of reconciliation of measured data).
- Pressure and temperature sensor calibration,
- Experimental characterization of a vapor compression cycle (illustration of the use of measurement technique and uncertainty propagation seen previously).
Exercises related to real life applications are solved to illustrate the theoretical concepts studied in class.
Learning outcomes of the learning unit
At the end of this course, the student masters the measurement techniques for establishing the performance of components, vapor compression cycles and industrial processes (measurement chain, selection of sensors, propagation of uncertainties).
The student is able to select the appropriate data processing technique for the application at hand.
The student knows the statistical techniques enabling a reliable analysis of experimental data (outlier rejection, model calibration, parameters identification and data reconciliation).
Prerequisite knowledge and skills
Prerequisite or corequisite units are presented within each program.
Planned learning activities and teaching methods
The course is divided into 5 lectures that take place each Tuesday morning.
The theoretical concepts seen during the course are illustrated with exercises.
Two laboratory sessions are organized. One concerns the calibration of sensors and the other one focuses on the experimental characterization of a vapor compression cycle. The laboratory sessions are not rated but attendance is mandatory.
A company visit is also organised. Attendance is also mandatory.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Recommended or required readings
Slides are available for theory and exercise sessions.
Exam(s) in session
Any session
- In-person
written exam ( open-ended questions )
Additional information:
Slides allowed
Work placement(s)
Organisational remarks and main changes to the course
The exact schedule and the deadlines are communicated during the first lecture.
The theoretical lectures will be taught in English.
Contacts
Samuel GENDEBIEN
Laboratoire de Thermodynamique, B49 tél : +32 (0)4 366 4800 sgendebien@uliege.be
Pierre DEWALLEF
Laboratoire de Thermodynamique, B49 tél : +32 (0)4 366 99 95 p.dewallef@uliege.be