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FSI-KEMAcad. year: 2023/2024
The introduction underlines the significance of the course, demonstrated by a series of practical examples showing how measured data is obtained using methods described in lectures and practiced during hands-on exercises. Special emphasis is put on how the course relates to real case studies, i.e. students are introduced to some truly unique experimental devices, with measured data specification and a direct connection to laboratory work.
(Not only) process engineers use a variety of calculations and calculation tools when designing equipment. The values of the calculations’ input parameter, however, might not be available in the literature or are often estimated with a limited accuracy, which leads to a high degree of uncertainty in the process design. Experimental methods allow an engineer to validate the results (model validation) or determine the value more accurately. Some of the most common parameters in process engineering are thermophysical and transport properties, heat and mass transfer coefficients etc.
Laboratory work is even more pronounced in the field of research and development. Experimental methods follow every step of a new technology emergence, from the first proof of concept in a laboratory scale, through troubleshooting and process controls design, to process scale-up and testing of the process capacity, stability and maintenance requirements. The goal of the course is to introduce students to a step-by-step guideline to an experiment, including design and planning of the experiment, as well as increase their familiarity with frequent unit operations in process engineering. The structure of the course complements the theoretical knowledge from previous courses (especially Heat Transfer, Hydraulic, Mass Transfer and Mechanical Processes) with practical experience.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Basic knowledge from relevant courses (e.g., physics, mathematics) completed during the bachelor’s degree at the Faculty of Mechanical Engineering at BUT is required of students.
Rules for evaluation and completion of the course
Course credit requirements: attendance at laboratory exercises and submission of reports from the exercises.
Students demonstrate the level of their acquired knowledge during two-step examination (written and oral).
The attendance at lectures is recommended. The attendance at laboratory exercises is mandatory and monitored. Any absence must be compensated. Compulsory reports of the laboratory exercises are created by students. Both the participation and reports are required in order to be admitted to the examination, which tests the theoretical and practical knowledge of a student.
Aims
The lecture part of the course familiarizes students with engineering measurements and the related instrumentation, structure and design of experiment, data processing and evaluation. The students are led to realize the importance of experimental methods as the only way of verifying the theoretical findings and, conversely, the importance of the experiment as the basic step for developing hypotheses and engineering calculations. This approach is also crucial to design unique process equipment, which no relevant calculations and design procedures exist for.
Students will acquire the knowledge and skills necessary to independently conduct experiments. The goal is to approach an experiment systematically – starting with planning and preparation, followed by the experiment itself and concluded with data processing, evaluation and interpretation. Students will also learn about means to maximize their time efficiency as well as the potential of real data – laboratory, but also plant data. For this reason, the course is partly situated in laboratories and test rooms, where students can practically experience steps that process engineers take during laboratory experiments as well as field experiments at industrial-scale units.
Study aids
Prerequisites and corequisites
Basic literature
Recommended reading
eLearning
Classification of course in study plans
Lecture
Teacher / Lecturer
Syllabus
Laboratory exercise