Course detail
Modelling of Processes
FSI-IMP Acad. year: 2021/2022 Winter semester
In the course, students will get acquainted with basic types of mathematic models used for design, analysis and optimization of process systems and equipment.
• Model of processing line describing mass and energy balance of a continuous process at a steady state
• Model of process equipment describing a transient process
• Model for the optimization of a process or equipment
• Model for detailed analysis of conditions inside of an equipment
Models included in the course are mostly based on a system of equations (mainly linear) and ordinary differential equations. Besides analytical solution of equations systems, students will learn how to apply basic numerical methods to the solution and the application of software tools.
Supervisor
Learning outcomes of the course unit
Students will understand the basic principles of mathematical model design for processing and energy systems. They will also learn about model application in practice. They will get an overview of process and energy systems and the types of models that are used for design, analysis and optimization. After finishing the course, students should be able to choose appropriate type of model for the design, analysis or optimization of a system or equipment and should understand the basic principles of those models.
Prerequisites
Basic knowledge of mathematics and physics from the first four semesters at FME.
Planned learning activities and teaching methods
The course is taught through lectures introducing the basic principles and theory, explaining of solution methods and showing solution methods. Lectures include sample problems that are solved interactively with the students, with emphasis on understanding. Lectures often include repetition of the most important prerequisites that are necessary to master the subject.
Seminars are focused on hands-on solution of problems using the knowledge from lectures, mostly computer aided, program MS Excel.
Assesment methods and criteria linked to learning outcomes
SEMINARS: Regular and active attendance is required and checked. All assignments have to be delivered and written test must be passed successfully. Test is successfully passed if more than half points are obtained. The student has the possibility of one repeat.
EXAM: The exam is written. Maximum overall number of points that can be obtained within the course is 100. The course evaluation is performed by a standard procedure, according to the number of obtained points (0-50 points …F, 51-60 points …E, 61-70 points …D, 71-80 points …C, 81-90 points …B, more than 90 points …A).
Language of instruction
Czech
Aims
The objective is to acquaint students with the basic principles of mathematical models for design, analysis and optimization of industrial units (processes) or equipment. Students should be able to choose a proper model type for the solution of typical problems, understand the corresponding solution methods and be able to solve simple problems.
Specification of controlled education, way of implementation and compensation for absences
The attendance at seminars is checked, necessary condition to pass the course is regular attendance (i.e. maximum of 3 absences at seminars). Attendance at lectures is not checked, but assignments in seminars require the knowledge from lectures.
The study programmes with the given course
Programme B3S-P: Engineering, Bachelor's
branch B-EPP: Power Engineering, Processes and Environment, 6 credits, compulsory
Type of course unit
Lecture
26 hours, optionally
Teacher / Lecturer
Syllabus
1.Introduction to modeling and engineering calculations: system definition, model definition, process flow-sheet, process variables
2. Mass balance: basic balance equation, degrees of freedom, mass balance for complex processes,
3. Mass balance: processes with recycle and by-pass, processes with reactions
4. Energy balance: open-loop and closed-loop system, internal energy, enthalpy
5. Energy balance: processes with reactions,
6. Computer-aided simulation: sequential and equation based methods
7. Balance equation for unsteady states: mass and energy balance, differential equations and analytical and numerical solutions,
8. Balance equation for unsteady statets: an approach for more complex systems
9. Model validation by experiment: modeling, simulation, experimentation, evaluation,
10: Operational data based modeling: linear and non-linear regresssion,
11. Optimization and sensitivity analysis: problem formulation, optimization methods, sensitivity analysis,
12. Technical-economic models: investment evaluation, methods for systems with uncertain parameters,
13. Repetitions, solution of problems covering the whole extent of the lectures.
Computer-assisted exercise
26 hours, compulsory
Teacher / Lecturer
Syllabus
Computer-aided seminars. Solution of assignments related to lecture subjects, mostly in MS Excel.