Learning outcome

A candidate who has completed the course will have a learning outcome in the form of aquired knowledge, skills, and general competence, as described below.

KNOWLEDGE
The candidate will:

• Understand the standard terminology within the topics of modelling
• Understand the basic principles and ideas associated with modelling
• Understand how to identify the crucial components of a system, needed for model design
• Understand how to use relevant simplifying assumptions that give efficient models

SKILLS
The candidate will:

• Be able to build dynamic models by use of modelling principles appropriate for the case
• Be able to do basic simulation of dynamic models
• Be able to find, read and understand information in journals, books, internet, etc. relevant for the modeling problem
• Be able to draw the right conclusions from the analysis

GENERAL COMPETENCE
The candidate will:

• Be able to communicate/discuss with engineering colleagues problems related to modeling of dynamic systems, and to report work in writing

Course Description

Material, momentum and energy balances, stochiometric reactions and mass conservation, reaction kinetics, thermodynamic models, transport laws and coupled systems.

The main principles of simplifying assumptions. Classification of model quantities.

Analysis of developed models through linear approximation and solution of approximate model, time constants, and numerical solution/simulation using relevant tools.

Applications of dynamic models. Although lumped and distributed modeling examples will be used to illustrate the topics, the core topic is systematic model development principles for process and energy systems

Teaching and Learning Methods

The course is offered both for campus based students and for on-line students, and both student categories will have access to the same learning material.

The course will continue to be taught with traditional lectures for campus based students (2016). Some of the these live lectures will be recorded and made available as on-line videos. Also, some of the material will be made available as instructional videos. Self-study based on lecture notes forms an important part of the course; the lecture notes contain many detailed examples, and some exercises and problems. Practicing with a (free) computer simulation tool will improve the understanding of the course.

A group project will be handed out early in the semester, and is important for getting hands-on experience with the course content.

Weekly (video) meetings will be offered based on demand, where questions from students may be discussed.These weekly sessions will be recorded, and made available for everyone.

Assessment Methods

The course will contain a compulsory group project, an individual digital test/quiz, and an individual final test. There will not be separate grades for the project, the digital test, and the final test; the course grade will be based on a weighted assessment where the group project will count 40%, the digital test 30%, and the final test 30%. It is necessary with a passed assessment on the group project, and with a passed assessment on the sum of individual tests.

The assessment of the group project will be based both on a written report (maximum 15 pages, PDF format) and a short (10 min) oral presentation of the work with examination; participation in the oral presentation is compulsory.

Minor adjustments may occur during the academic year, subject to the decision of the Dean