# 327-1201-00L Transport Phenomena I

Semester | Autumn Semester 2016 |

Lecturers | H. C. Öttinger |

Periodicity | yearly recurring course |

Language of instruction | English |

Abstract | Phenomenological approach to "Transport Phenomena" based on balance equations supplemented by thermodynamic considerations to formulate the undetermined fluxes in the local species mass, momentum, and energy balance equations; fundamentals, applications, and simulations |

Objective | The teaching goals of this course are on five different levels: (1) Deep understanding of fundamentals: local balance equations, constitutive equations for fluxes, entropy balance, interfaces, idea of dimensionless numbers, ... (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, finite differences, lattice Boltzmann, Brownian dynamics, ... |

Content | Approach to Transport Phenomena Diffusion Equation Brownian Dynamics Refreshing Topics in Equilibrium Thermodynamics Balance Equations Forces and Fluxes Measuring Transport Coefficients Pressure-Driven Flows Driven Separations Complex Fluids |

Lecture notes | A detailed manuscript is provided; this manuscript will be developed into a book entitled "A Modern Course in Transport Phenomena" by David C. Venerus and Hans Christian Öttinger |

Literature | 1. R. B. Bird, W. E. Stewart, and E. N. Lightfoot, Transport Phenomena, 2nd Ed. (Wiley, 2001) 2. S. R. de Groot and P. Mazur, Non-Equilibrium Thermodynamics, 2nd Ed. (Dover, 1984) 3. W. M. Deen, Analysis of Transport Phenomena (Oxford University Press, 1998) 4. R. B. Bird, Five Decades of Transport Phenomena (Review Article), AIChE J. 50 (2004) 273-287 |

Prerequisites / Notice | Complex 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). Equilibrium thermodynamics (Gibbs' fundamental equation; thermodynamic potentials; Legendre transforms). Maxwell equations. Programming and simulation techniques (Matlab, Monte Carlo simulations). |