TKP4175

Thermodynamic Methods

Last taught 2024

Spring

Trondheim

English

Overview

21 candidates

Average grade

E

1.48

0.11

Pass rate

76%

13 points

Grade distribution
Average over time
Pass rate over time

About this course

Content

The theory of partial and total differentials, and the chain rule of differentiation. Energy functions, fundamental relations and canonical variables. Equations of state for the fluid state. Unit operations in chemical engineering. Control volume theory applied to kinetic, potential and chemical energies. Thermodynamic equilibrium. Vapor-liquid equilibrium. Multicomponent phase equilibrium. Chemical equilibria in ideal gases. Adiabatic combustion temperature. Sources of thermodynamic data with emphasis on the standard state. Heat engines using ideal gas as work fluid. Entropy production. Exergy analysis of stationary processes.

Learning outcomes

After completing the course, the student will be able to perform: Thermodynamic analysis of physico-chemical equilibrium problems related to the mathematical modeling of chemical multicomponent systems, computation of chemical and phase equilibria in such systems, and, finally, implementation of thermodynamic equations of state and activity models in canonical form. The implementation must be verified (tested) and must contain partial derivatives of first and second order in the natural (canonical) variables of the model. The model will later be used to calculate a phase diagram problem given by the lecturer. The student will understand the meaning of: Canonical variables and thermodynamic potentials, the thermodynamic equation of state, the thermodynamic equilibrium principle applied to multicomponent mixtures, necessary and sufficient conditions for thermodynamic equilibrium, the Gibbs-Duhem's equation and how to apply this equation for consistency checking of thermodynamic computer code. The student will have skills in: partial derivation of functions with many variables, differential calculus applied to state functions of this type, numerical solution of systems of non-linear equations, and unit testing of own program code and verification of own calculation results.

Teaching methods

Classroom lectures (3 hours per week), tutored programming (2 hours per week), Individual programming (4-6 hours per week) and report writing (4 hours per week). The students can collaborate in groups of 2-3 people if they so wish. Lectures and exercises are mandatory and can be used to bring forward information that is not necessarily written anywhere. Experience based knowledge for example.