Search result: Catalogue data in Autumn Semester 2020

Mechanical Engineering Bachelor Information
5. Semester
151-0573-00LSystem Modeling Information W4 credits2V + 1UL. Guzzella
AbstractIntroduction to system modeling for control. Generic modeling approaches based on first principles, Lagrangian formalism, energy approaches and experimental data. Model parametrization and parameter estimation. Basic analysis of linear and nonlinear systems.
ObjectiveLearn how to mathematically describe a physical system or a process in the form of a model usable for analysis and control purposes.
ContentThis class introduces generic system-modeling approaches for control-oriented models based on first principles and experimental data. The class will span numerous examples related to mechatronic, thermodynamic, chemistry, fluid dynamic, energy, and process engineering systems. Model scaling, linearization, order reduction, and balancing. Parameter estimation with least-squares methods. Various case studies: loud-speaker, turbines, water-propelled rocket, geostationary satellites, etc. The exercises address practical examples.
Lecture notesThe handouts in English will be sold in the first lecture.
LiteratureA list of references is included in the handouts.
151-0575-01LSignals and Systems Information W4 credits2V + 2UA. Carron
AbstractSignals arise in most engineering applications. They contain information about the behavior of physical systems. Systems respond to signals and produce other signals. In this course, we explore how signals can be represented and manipulated, and their effects on systems. We further explore how we can discover basic system properties by exciting a system with various types of signals.
ObjectiveMaster the basics of signals and systems. Apply this knowledge to problems in the homework assignments and programming exercise.
ContentDiscrete-time signals and systems. Fourier- and z-Transforms. Frequency domain characterization of signals and systems. System identification. Time series analysis. Filter design.
Lecture notesLecture notes available on course website.
Prerequisites / NoticeControl Systems I is helpful but not required.
151-0917-00LMass TransferW4 credits2V + 2US. E. Pratsinis, A. Güntner, V. Mavrantzas
AbstractThis course presents the fundamentals of transport phenomena with emphasis on mass transfer. The physical significance of basic principles is elucidated and quantitatively described. Furthermore the application of these principles to important engineering problems is demonstrated.
ObjectiveThis course presents the fundamentals of transport phenomena with emphasis on mass transfer. The physical significance of basic principles is elucidated and quantitatively described. Furthermore the application of these principles to important engineering problems is demonstrated.
ContentFick's laws; application and significance of mass transfer; comparison of Fick's laws with Newton's and Fourier's laws; derivation of Fick's 2nd law; diffusion in dilute and concentrated solutions; rotating disk; dispersion; diffusion coefficients, viscosity and heat conduction (Pr and Sc numbers); Brownian motion; Stokes-Einstein equation; mass transfer coefficients (Nu and Sh numbers); mass transfer across interfaces; Analogies for mass-, heat-, and momentum transfer in turbulent flows; film-, penetration-, and surface renewal theories; simultaneous mass, heat and momentum transfer (boundary layers); homogeneous and heterogeneous reversible and irreversible reactions; diffusion-controlled reactions; mass transfer and first order heterogeneous reaction. Applications.
LiteratureCussler, E.L.: "Diffusion", 3nd edition, Cambridge University Press, 2009.
Prerequisites / NoticeStudents attending this highly-demanding course are expected to allocate sufficient time within their weekly schedule to successfully conduct the exercises.
151-0973-00LFundamentals in Process EngineeringW4 credits2V + 2UF. Donat, C. Müller
AbstractOverview of process engineering, reactions, balances and residence time analysis; overview of the thermal separation processes; equilibria for multiphase systems; introduction into mechanical process engineering and particle technology
ObjectiveTo expound fundamentals in process engineering
ContentOverview of process engineering, reactions, balances and residence time analysis; overview of the thermal separation processes; equilibria for multiphase systems; introduction into mechanical process engineering and particle technology
Lecture notesscript in German available
151-3207-00LLightweightW4 credits2V + 2UP. Ermanni
AbstractThe elective course Lightweight includes numerical methods for the analysis of the load carrying and failure behavior of lightweight structures, as well as construction methods and design principles for lightweight design.
ObjectiveThe goal of this course is to convey substantiated background for the understanding and the design and sizing of modern lightweight structures in mechanical engineering, vehicle and airplane design.
ContentLightweight design
Thin-walled beams and structures
Instability behavior of thin walled structures
Reinforced shell structures
Load introduction in lightweight structures
Joining technology
Sandwich design
Lecture notesScript, Handouts, Exercises
227-0076-00LElectrical Engineering IIW4 credits2V + 2UC. Studer
AbstractSinusoidal signals and systems in the time and frequency domain, principle of operation and design of basic analog and digital circuits as well as analog-digital conversion. Basic power electronic circuits, design of magnetic components, electromechanical energy conversion, principle of operation and characteristics of transformators and selected rotating electrical machines.
Objectivesee above
ContentBeschreibung von sinusförmigen Signalen und Systemen im Zeit- und Frequenzbereich, Funktion grundlegender analoger und digitaler Schaltungen sowie von Analog-Digital-Wandlern. Grundlagen leistungselektronischer Konverter, Berechnung magnetischer Kreise, elektromechanische Energiewandlung, Funktionsprinzip von Transformatoren und ausgewählter rotierender elektrischer Maschinen.
363-0511-00LManagerial Economics
Not for MSc students belonging to D-MTEC!
W4 credits3VP. Egger, M. Köthenbürger, N. Loumeau
Abstract"Managerial Economics" provides an introduction to the theories and methods from Economics and Management Science to analyze economic decision-making in the context of markets. The course targets students with no prior knowledge in Economics and Management.
ObjectiveThe objective of this course is to provide an introduction to microeconomic thinking. Based on the fundamental principles of economic analysis (optimization and equilibrium), the focus lies on understanding key economic concepts relevant for understanding and analyzing economic behavior of firms and consumers in the context of markets. Market demand and supply are derived from the individual decision-making of economic agents and market outcomes under different assumptions about the market structure and market power (perfect competition, monopoly, oligopoly, game theory) are studied. This introductory course aims at providing essential knowledge from the fields of Economics and Management relevant for economic decision-making in the context of both the private and public sector.
Literature"Mikroökonomie" von Robert Pindyck & Daniel Rubinfeld, aktualisierte 8. Auflage, 8/2013, (Pearson Studium - Economic VWL).
Prerequisites / NoticeThe course targets both Bachelor and Master students. No prior knowledge in the areas of Economics and Management is required.
401-0435-00LComputational Methods for Engineering Applications Information Restricted registration - show details W4 credits2V + 2UC. Pares Pulido
AbstractThe course gives an introduction to the numerical methods for the solution of ordinary and partial differential equations that play a central role in engineering applications. Both basic theoretical concepts and implementation techniques necessary to understand and master the methods will be addressed.
ObjectiveAt the end of the course the students should be able to:

- implement numerical methods for the solution of ODEs (= ordinary differential equations);
- identify features of a PDE (= partial differential equation) based model that are relevant for the selection and performance of a numerical algorithm;
- implement the finite difference, finite element and finite volume method for the solution of simple PDEs using C++;
- read engineering research papers on numerical methods for ODEs or PDEs.
ContentInitial value problems for ODE: review of basic theory for ODEs, Forward and Backward Euler methods, Taylor series methods, Runge-Kutta methods, basic stability and consistency analysis, numerical solution of stiff ODEs.

Two-point boundary value problems: Green's function representation of solutions, Maximum principle, finite difference schemes, stability analysis.

Elliptic equations: Laplace's equation in one and two space dimensions, finite element methods, implementation of finite elements, error analysis.

Parabolic equations: Heat equation, Fourier series representation, maximum principles, Finite difference schemes, Forward (backward) Euler, Crank-Nicolson method, stability analysis.

Hyperbolic equations: Linear advection equation, method of characteristics, upwind schemes and their stability.
Lecture notesScript will be provided.
LiteratureChapters of the following book provide supplementary reading and are not meant as course material:

- A. Tveito and R. Winther, Introduction to Partial Differential Equations. A Computational Approach, Springer, 2005.
Prerequisites / Notice(Suggested) Prerequisites:
Analysis I-III (for D-MAVT), Linear Algebra, Models, Algorithms and Data: Introduction to Computing, basic familiarity with programming in C++.
401-0603-00LStochastics (Probability and Statistics) Information Restricted registration - show details W4 credits2V + 1UM. H. Maathuis
AbstractThis class covers the following concepts: random variables, probability, discrete and continuous distributions, joint and conditional probabilities and distributions, the law of large numbers, the central limit theorem, descriptive statistics, statistical inference, inference for normally distributed data, point estimation, and two-sample tests.
ObjectiveKnowledge of the basic principles of probability and statistics.
ContentIntroduction to probability theory, some basic principles from mathematical statistics and basic methods for applied statistics.
Lecture notesLecture notes
LiteratureLecture notes
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