327-2201-00L  Transport Phenomena II

SemesterSpring Semester 2020
LecturersJ. Vermant
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
327-2201-00 GTransport Phenomena II
13:00-14:00 Vorlesung
14:15-15:15 Übungen in zwei Gruppen
15:30-16:30 Vorlesung
4 hrs
Mon12:45-16:30HCP E 47.4 »
J. Vermant

Catalogue data

AbstractNumerical and analytical methods for real-world "Transport Phenomena"; atomistic understanding of transport properties based on kinetic theory and mesoscopic models; fundamentals, applications, and simulations
ObjectiveThe teaching goals of this course are on five different levels:
(1) Deep understanding of fundamentals: kinetic theory, mesoscopic models, ...
(2) Ability to use the fundamental concepts in applications
(3) Insight into the role of boundary conditions
(4) Knowledge of a number of applications
(5) Flavor of numerical techniques: finite elements, lattice Boltzmann, ...
ContentThermodynamics of Interfaces
Interfacial Balance Equations
Interfacial Force-Flux Relations
Polymer Processing
Transport Around a Sphere
Refreshing Topics in Equilibrium Statistical Mechanics
Kinetic Theory of Gases
Kinetic Theory of Polymeric Liquids
Transport in Biological Systems
Dynamic Light Scattering
Lecture notesThe course is based on the book D. C. Venerus and H. C. Öttinger, A Modern Course in Transport Phenomena (Cambridge University Press, 2018)
Literature1. D. C. Venerus and H. C. Öttinger, A Modern Course in Transport Phenomena (Cambridge University Press, 2018)
2. R. B. Bird, W. E. Stewart, and E. N. Lightfoot, Transport Phenomena, 2nd Ed. (Wiley, 2001)
3. Deen,W. Analysis of Transport Phenomena, Oxford University Press, 2012
4. R. B. Bird, Five Decades of Transport Phenomena (Review Article), AIChE J. 50 (2004) 273-287
Prerequisites / NoticeComplex numbers. Vector analysis (integrability; Gauss' divergence theorem). Laplace and Fourier transforms. Ordinary differential equations (basic ideas). Linear algebra (matrices; functions of matrices; eigenvectors and eigenvalues; eigenfunctions). Probability theory (Gaussian distributions; Poisson distributions; averages; moments; variances; random variables). Numerical mathematics (integration). Statistical thermodynamics (Gibbs' fundamental equation; thermodynamic potentials; Legendre transforms; Gibbs' phase rule; ergodicity; partition functions; Einstein's fluctuation theory). Linear irreversible thermodynamics (forces and fluxes; Fourier's, Newton's and Fick's laws for fluxes). Hydrodynamics (local equilibrium; balance equations for mass, momentum, energy and entropy). Programming and simulation techniques (Matlab, Monte Carlo simulations).

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits5 credits
ExaminersJ. Vermant
Typeend-of-semester examination
Language of examinationEnglish
RepetitionA repetition date will be offered in the first two weeks of the semester immediately consecutive.
Additional information on mode of examinationThe final mark for the course is the weighted average of the marks for the end-of-semester examination (80%) and for the mandatory project work (20%). However a voluntary, graded mid-term assessment test is offered, with problems similar to those in the exercises and the end-of-semester examination. If the grade is better than the written exam (1.5h) it will count 20% towards result of the written exam.
Written aids: A clean copy of the official manuscript.

Learning materials

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Only public learning materials are listed.

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Offered in

ProgrammeSectionType
Materials Science MasterCore CoursesW DrInformation
Mathematics MasterMaterial Modelling and SimulationWInformation
Computational Science and Engineering BachelorElectivesWInformation
Computational Science and Engineering MasterElectivesWInformation