Course detail

Experimental Methods in Tribology

FSI-9EXT Acad. year: 2024/2025 Both semester

Learning outcomes of the course unit

Prerequisites

Planned learning activities and teaching methods

Assesment methods and criteria linked to learning outcomes

Conditions for gaining the exam:

  • submission and defense of individual work on measurement or experimental analysis of selected tribological problem. The work would include theoretical description, error and measurement quality analysis and design of results evaluation.

Absence from lessons may be compensated for according to instructions of the teacher.

Language of instruction

Czech

Aims

The main aim is to provide basic knowledge of the experimental methods, theory of measurement and experiments in the field of tribology with respect to the topic of PhD thesis.

  • The ability to identify the key problems for experimental validation of tribological problems.
  • The ability to select proper experimental methods with respect to the specific problems in the field of tribology.
  • The ability to design experiments and assess quality of measurements.
  • The ability to statistically evaluate results.

Specification of controlled education, way of implementation and compensation for absences

The study programmes with the given course

Programme D-KPI-K: Design and Process Engineering, Doctoral
branch ---: no specialisation, 0 credits, recommended course

Programme D-KPI-P: Design and Process Engineering, Doctoral
branch ---: no specialisation, 0 credits, recommended course

Type of course unit

 

Lecture

20 hours, compulsory

Syllabus

- Samples and Characterization of Test Specimens. Lubricant and Process Fluid and Solids Analysis. 
- Sample Preparation. Control of the Test Environment.
- Surface Topography Measurement.
- Tribometers. Controlling of Load, Measurement of Friction and Wear.
- Optical Methods for Analysis of Tribological Processes.
- Wear Analysis, Surface and Subsurface Micrography, Chemical Analysis.
- Design of Experiment.
- Statistical Analysis of Data.
- Measurement Errors, Noise, Precision and Accuracy.