Search result: Catalogue data in Autumn Semester 2023
Mechanical Engineering Master ![]() | ||||||||||||||||||||||||||||||||||||||||||
![]() | ||||||||||||||||||||||||||||||||||||||||||
![]() ![]() The courses listed in this category “Core Courses” are recommended. Alternative courses can be chosen in agreement with the tutor. | ||||||||||||||||||||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
151-1116-00L | Introduction to Aircraft and Car Aerodynamics | W | 4 credits | 3G | M. Immer, F. Schröder-Pernet | |||||||||||||||||||||||||||||||||||||
Abstract | Aircraft aerodynamics: Atmosphere; aerodynamic forces (lift, drag); thrust. Vehicle aerodynamics: Aerodynamic and mass forces, drag, lift, car aerodynamics and performence. Passenger cars, trucks, racing cars. | |||||||||||||||||||||||||||||||||||||||||
Learning objective | An introduction to the basic principles and interrelationships of aircraft and automotive aerodynamics. To understand the basic relations of the origin of aerodynamic forces (ie lift, drag). To quantify the aerodynamic forces for basic configurations of aircraft and car components. Illustration of the intrinsic problems and results using examples. Using experimental and theoretical methods to illustrate possibilities and limits. | |||||||||||||||||||||||||||||||||||||||||
Content | Aircraft aerodynamics: atmosphere, aerodynamic forces (ascending force: profile, wings. Resistance, residual resistance, induced resistance); thrust (overview of the propulsion system, aerodynamics of the propellers), introduction to static longitudinal stability. Automobile aerodynamics: Basic principles: aerodynamic force and the force of inertia, resistance, drive, aerodynamic and driving performance. Cars commercial vehicles, racing cars. | |||||||||||||||||||||||||||||||||||||||||
Lecture notes | Preparation materials & slides are provided prior to each class | |||||||||||||||||||||||||||||||||||||||||
Literature | Aircraft Aerodynamics: - Anderson Jr, John D: Introduction to Flight, Mc Graw Hill, Ed 06, 2007; ISBN: 9780073529394 - Mc Cormick, B.W.: Aerodynamics, Aeronautics and Flight Mechanics, John Wiley and Sons, 1979 - Wilcox, David C, Basic Fluid Mechanics. DCW Industries, Inc., 1997 - Schlichting,H. und Truckenbrodt, E: Aerodynamik des Flugzeuges (Bd I und II), Springer Verlag, 1960 - Abbott, I. and van Doenhoff, A.: Theory of Wing Sections, McGraw-Hill Book Company, Inc., 1949 - Hoerner, S.F.: Fluid Dynamic Drag, Hoerner Fluid Dynamics, 1951/1965 - Hoerner, S.F.: Fluid Dynamic Lift, Hoerner Fluid Dynamics, 1975 - Perkins, C.D. and Hage, R.E.: Airplane Performance, Stability and Control, John Wiley ans Sons, 1949 Vehicle Aerodynamics - Hucho, Wolf-Heinrich: Aerodynamics of Road Vehicles, SAE International, 1998 - Gillespi, Thomas D: Fundamentals of Vehicle Dynamics, SAE, 1992 - Katz Joseph: New Directions in Race Car Aerodynamics, Robert Bentley Publishers, 1995 | |||||||||||||||||||||||||||||||||||||||||
101-0187-00L | Structural Reliability and Risk Analysis | W | 3 credits | 2G | S. Marelli | |||||||||||||||||||||||||||||||||||||
Abstract | Structural reliability aims at quantifying the probability of failure of systems due to uncertainties in their design, manufacturing and environmental conditions. Risk analysis combines this information with the consequences of failure in view of optimal decision making. The course presents the underlying probabilistic modelling and computational methods for reliability and risk assessment. | |||||||||||||||||||||||||||||||||||||||||
Learning objective | The goal of this course is to provide the students with a thorough understanding of the key concepts behind structural reliability and risk analysis. After this course the students will have refreshed their knowledge of probability theory and statistics to model uncertainties in view of engineering applications. They will be able to analyze the reliability of a structure and to use risk assessment methods for decision making under uncertain conditions. They will be aware of the state-of-the-art computational methods and software in this field. | |||||||||||||||||||||||||||||||||||||||||
Content | Engineers are confronted every day to decision making under limited amount of information and uncertain conditions. When designing new structures and systems, the design codes such as SIA or Euro- codes usually provide a framework that guarantees safety and reliability. However the level of safety is not quantified explicitly, which does not allow the analyst to properly choose between design variants and evaluate a total cost in case of failure. In contrast, the framework of risk analysis allows one to incorporate the uncertainty in decision making. The first part of the course is a reminder on probability theory that is used as a main tool for reliability and risk analysis. Classical concepts such as random variables and vectors, dependence and correlation are recalled. Basic statistical inference methods used for building a probabilistic model from the available data, e.g. the maximum likelihood method, are presented. The second part is related to structural reliability analysis, i.e. methods that allow one to compute probabilities of failure of a given system with respect to prescribed criteria. The framework of reliability analysis is first set up. Reliability indices are introduced together with the first order-second moment method (FOSM) and the first order reliability method (FORM). Methods based on Monte Carlo simulation are then reviewed and illustrated through various examples. By-products of reliability analysis such as sensitivity measures and partial safety coefficients are derived and their links to structural design codes is shown. The reliability of structural systems is also introduced as well as the methods used to reassess existing structures based on new information. The third part of the course addresses risk assessment methods. Techniques for the identification of hazard scenarios and their representation by fault trees and event trees are described. Risk is defined with respect to the concept of expected utility in the framework of decision making. Elements of Bayesian decision making, i.e. pre-, post and pre-post risk assessment methods are presented. The course also includes a tutorial using the UQLab software dedicated to real world structural reliability analysis. | |||||||||||||||||||||||||||||||||||||||||
Lecture notes | Slides of the lectures are available online every week. A printed version of the full set of slides is proposed to the students at the beginning of the semester. | |||||||||||||||||||||||||||||||||||||||||
Literature | Ang, A. and Tang, W.H, Probability Concepts in Engineering - Emphasis on Applications to Civil and Environmental Engineering, 2nd Edition, John Wiley & Sons, 2007. S. Marelli, R. Schöbi, B. Sudret, UQLab user manual - Structural reliability (rare events estimation), Report UQLab-V0.92-107. | |||||||||||||||||||||||||||||||||||||||||
Prerequisites / Notice | Basic course on probability theory and statistics | |||||||||||||||||||||||||||||||||||||||||
252-0834-00L | Information Systems for Engineers ![]() | W | 4 credits | 2V + 1U | G. Fourny | |||||||||||||||||||||||||||||||||||||
Abstract | This course provides the basics of relational databases from the perspective of the user. We will discover why tables are so incredibly powerful to express relations, learn the SQL query language, and how to make the most of it. The course also covers support for data cubes (analytics). | |||||||||||||||||||||||||||||||||||||||||
Learning objective | Do you want to be able to query your own data productively and efficiently in your future semester projects, bachelor's thesis, master thesis, or PhD thesis? Are you looking for something beyond the Python+Pandas hype? This courses teaches you how to do so as well as the dos and don'ts. This lesson is complementary with Big Data for Engineers as they cover different time periods of database history and practices -- you can take them in any order, even though it might be more enjoyable to take this lecture first. After visiting this course, you will be capable to: 1. Explain, in the big picture, how a relational database works and what it can do in your own words. 2. Explain the relational data model (tables, rows, attributes, primary keys, foreign keys), formally and informally, including the relational algebra operators (select, project, rename, all kinds of joins, division, cartesian product, union, intersection, etc). 3. Perform non-trivial reading SQL queries on existing relational databases, as well as insert new data, update and delete existing data. 4. Design new schemas to store data in accordance to the real world's constraints, such as relationship cardinality 5. Explain what bad design is and why it matters. 6. Adapt and improve an existing schema to make it more robust against anomalies, thanks to a very good theoretical knowledge of what is called "normal forms". 7. Understand how indices work (hash indices, B-trees), how they are implemented, and how to use them to make queries faster. 8. Access an existing relational database from a host language such as Java, using bridges such as JDBC. 9. Explain what data independence is all about and didn't age a bit since the 1970s. 10. Explain, in the big picture, how a relational database is physically implemented. 11. Know and deal with the natural syntax for relational data, CSV. 12. Explain the data cube model including slicing and dicing. 13. Store data cubes in a relational database. 14. Map cube queries to SQL. 15. Slice and dice cubes in a UI. And of course, you will think that tables are the most wonderful object in the world. | |||||||||||||||||||||||||||||||||||||||||
Content | Using a relational database ================= 1. Introduction 2. The relational model 3. Data definition with SQL 4. The relational algebra 5. Queries with SQL Taking a relational database to the next level ================= 6. Database design theory 7. Databases and host languages 8. Databases and host languages 9. Indices and optimization 10. Database architecture and storage Analytics on top of a relational database ================= 12. Data cubes Outlook ================= 13. Outlook | |||||||||||||||||||||||||||||||||||||||||
Literature | - Lecture material (slides). - Book: "Database Systems: The Complete Book", H. Garcia-Molina, J.D. Ullman, J. Widom (It is not required to buy the book, as the library has it) | |||||||||||||||||||||||||||||||||||||||||
Prerequisites / Notice | The lecture is hybrid, meaning you can attend with us in the lecture hall, or on Zoom, or watch the recordings on YouTube later. Exercise sessions are in presence. For non-CS/DS students only, BSc and MSc Elementary knowledge of set theory and logics Knowledge as well as basic experience with a programming language such as Pascal, C, C++, Java, Haskell, Python | |||||||||||||||||||||||||||||||||||||||||
Competencies![]() |
|
Page 2 of 2
All