IDENTIFYING DATA 2016_17
Subject (*) ADVANCED THERMODYNAMICS AND MOLECULAR SIMULATION Code 20695102
Study programme
Chemical Engineering (2013)
 Cycle 2nd
Descriptors Credits Type Year Period
6 Compulsory First 1Q
Language
Anglès
Department Chemical Engineering
Coordinator
MACKIE ., ALLAN DONALD
 E-mail allan.mackie@urv.cat
katarzyna.glinska@urv.cat
Lecturers
MACKIE ., ALLAN DONALD
GLINSKA ., KATARZYNA
Web
General description and relevant information This course gives a brief introduction to Statistical Mechanics and an overview of molecular simulation techniques relevant for applications in Chemical Engineering

Competences
Type A Code Competences Specific
 A1.1 Effectively apply knowledge of basic, scientific and technological materials pertaining to engineering.
 A1.2 Design, execute and analyze experiments related to engineering.
 A1.4 Know how to establish and develop mathematical models by using the appropriate software in order to provide the scientific and technological basis for the design of new products, processes, systems and services and for the optimization of existing ones. (G5)
 A3.3 Conceptualize engineering models and apply innovative problems solving methods and appropriate IT applications to the design, simulation, optimization and control of processes and systems (I3).
Type B Code Competences Transversal
 B1.1 Communicate and discuss proposals and conclusions in a clear and unambiguous manner in specialized and non-specialized multilingual forums (G9).
Type C Code Competences Nuclear
 C1.1 Have an intermediate mastery of a foreign language, preferably English

Learning outcomes
Type A Code Learning outcomes
 A1.1 Be familiar with the tools for modelling the macroscopic behaviour of systems of interest in chemical engineering from a microscopic point of view.
 A1.2 Use computer simulation to check the theoretical concepts explained in the classroom.
 A1.4 Be proficient in molecular dynamics.
 A3.3 Master simulation by the Monte Carlo method.
Type B Code Learning outcomes
 B1.1 Intervene effectively and transmit relevant information.
Prepare and deliver structured presentations that satisfy the stipulated requirements.
Plan the communication: generate ideas, look for information, select and order information, make sketches, identify the audience and the aims of the communication, etc.
Draft documents using the appropriate format, content, structure, language accuracy, and register. Illustrate concepts using the correct conventions: format, headings, footnotes, captions, etc.
Employ the strategies used to make effective oral presentations (audio-visual aids, eye contact, voice, gestures, timing, etc.).
Use language appropriate to the situation.
Type C Code Learning outcomes
 C1.1 Express opinions on abstract or cultural topics in a limited fashion.
Explain and justify briefly their opinions and projects.
Understand instructions about classes or tasks assigned by the teaching staff.
Understand the basic ideas of radio and television programmes.
Understand routine information and articles.
Understand the general meaning of texts that have non-routine information in a familiar subject area.
Take notes during a class.
Write letters or take notes about foreseeable, familiar matters.

Contents
Topic Sub-topic
1. Thermodynamic postulates
2. Classical mechanics and quantum mechanics. Statistical Mechanics Boltzmann Distribution Law
The ideal gas
The non-ideal gas
The liquid state
3. Molecular dynamics Integration of the equations of motion
Estimation of statistical information
4. The Monte Carlo technique. Importance sampling
Metropolis algorithm
Basic Monte Carlo algorithm
Trial moves
5. Monte Carlo simulation in different ensembles Microcanonical
Isothermal-isobaric
Grand canonical

Planning
Methodologies  ::  Tests
  Competences (*) Class hours
 Hours outside the classroom
 (**) Total hours
Introductory activities
1 1 2
Lecture
A1.1
C1.1
 16 32 48
Problem solving, classroom exercises
A1.1
B1.1
C1.1
 10 20 30
Practicums/Case studies
A1.1
A1.2
A1.4
A3.3
B1.1
C1.1
 24 24 48
Personal tuition
1 1 2
 
Extended-answer tests
A1.1
A3.3
4 8 12
Oral tests
B1.1
C1.1
 4 4 8
 
(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies
  Description
Introductory activities An overview of the course
Lecture Lectures on the course material based on material from the recommended books
Problem solving, classroom exercises exercises in order to gain a better understanding of the material given in the lectures
Practicums/Case studies molecular simulation case studies to be solved during the laboratory sessions
Personal tuition specific questions and doubts to be resolved on an individual basis

Personalized attention
Description
Individual Tutorials: during office hours

Assessment
Methodologies Competences Description Weight        
Problem solving, classroom exercises
A1.1
B1.1
C1.1
 Exercises to be handed in based on work done both inside and outside of class 20
Practicums/Case studies
A1.1
A1.2
A1.4
A3.3
B1.1
C1.1
 Written reports based on simulation exercises carried out in the computer laboratory 30
Oral tests
B1.1
C1.1
 A selected recent research article where Statistical Thermodyamics is used will be presented in front of the class during a short talk 20
Extended-answer tests
A1.1
A3.3
A written exam to be resolved individually 30
Others  
 
Other comments and second exam session

During any test or exam, mobile telephone, tablets and other electronic devices not explicitly authorised should be turned off and kept out of sight.

In the case that the student does not pass the first call, a second call is available. In the second call some or all of the assessment elements from the first can be used in the case that they help to pass the subject; the other elements will be repeated with the same weights as in the first call.

Sources of information

Basic D. Frenkel and B. Smit, Understanding Molecular Simulation, Academic Press,
B Widom, Statistical Mechanics: A Concise Introduction for Chemists, Cambridge University Press,

Complementary D. A. McQuarrie, Statistical Thermodynamics, University Science Books,
J-P. Hansen and I.R. McDonald, Theory of Simple Liquids, Academia Press,
D. Chandler, Introduction to Modern Statistical Mechanics, Oxford University Press,
P. Ungerer, B.Tavitian and A. Boutin, Applications of Molecular Simulation in the Oil and Gas Industry. Monte Carlo Methods, Editions Technip,
M. P. Allen and D.J. Tildesley, Computer Simulation of Liquids, Oxford Science Publications,

Recommendations
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.