Course detail

Computer Aided Design in Chemical Engineering

FSI-9SVCAcad. year: 2021/2022

The postgraduate students will get acquainted with process simulations and computer-aided design computations. They will enhance their knowledge of balancing in complex systems including multiphase, reactive or transient processes. The course includes classification of mathematical modelling approaches for chemical systems, namely mass transfer, heat transfer, fluid flow and reacting systems. Attention is given also to numerical methods for the solution of model equations and description of time domain dynamics. Students will get an overview of optimization techniques for process systems. Error propagation and data regression are covered as important concepts in the treatment of experimental data.

Language of instruction

Czech

Mode of study

Not applicable.

Learning outcomes of the course unit

Students will understand the principles of mathematical modelling and simulations in complex systems. They will get insight into computer-aided models and simulations that are used for design, analysis and optimization.

Prerequisites

Graduate-level knowledge of mathematics, physics and chemistry.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course is taught through lectures focused on topics required for the individual doctoral project. It includes work in appropriate software tools.

Assesment methods and criteria linked to learning outcomes

Students are required to develop a process model or simulation related to their doctoral project.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

Students will get acquainted with advanced concepts of mathematical models for design, analysis and optimization of industrial units (processes) or equipment. Students should be able to develop, implement and apply a proper model type for the solution of problems related to their doctoral research project.

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

Teaching is provided in the form of consultations and discussions over a model the student develops, at pre-arranged meetings.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Dahlquist, G; Björck, Å.: Numerical Methods in Scientific Computing, SIAM, Philadelphia, PA, USA (2008) (EN)
Felder, R. M.; Rousseau, R. W.; Bullard, L. G.: Elementary Principles of Chemical Processes, 4th ed., Wiley, Hoboken, NJ, USA (2015) (EN)
Chaves, I. D.; López, J. R.; Zapata, J. L.; Robayo, A. L.; Niño, G. R.: Process Analysis and Simulation in Chemical Engineering, Springer, Cham, Switzerland (2016) (EN)

Recommended reading

Press, W. H.; Teukolsky, S. A.; Vetterling, W. T.; Flannery, B. P.: Numerical Recipes: The Art of Scientific Computing, 3rd ed., Cambridge University Press, Cambridge, UK (2007) (EN)
Puigjaner, L.; Heyen, H. (Eds.): Computer Aided Process and Product Engineering, Wiley-VCH Verlag GmbH, Weinheim, Germany, (2006) (EN)
Upreti, S. R.: Process Modeling and Simulation for Chemical Engineers: Theory and Practice, Wiley, Hoboken, NJ, USA (2017) (EN)

Classification of course in study plans

  • Programme D-ENE-P Doctoral 1 year of study, winter semester, recommended course
  • Programme D-ENE-K Doctoral 1 year of study, winter semester, recommended course

Type of course unit

 

Lecture

20 hod., optionally

Teacher / Lecturer

Syllabus

• Classification of mathematical modelling approaches
• Balancing in complex systems including multiphase, reactive or transient processes
• Chemical systems modelling with mass transfer, heat transfer, fluid flow and chemical reactions
• Process simulation using modular approach
• Process simulation using equation-solving approach
• Numerical methods for the solution of model equations
• Time domain dynamics simulation
• Optimization techniques for process systems
• Error propagation analysis
• Data regression