Suchergebnis: Katalogdaten im Herbstsemester 2021

Bauingenieurwissenschaften Master Information
Master-Studium (Studienreglement 2020)
Fächer Digital
101-0524-00LLean, Integrated and Digital Project DeliveryW4 KP3GD. Hall
KurzbeschreibungThis course is an introduction to innovative construction project delivery through three strategies: integrated information, integrated organization, and integrated processes. Students will be introduced to project and production management concepts such as Lean Construction, Building Information Modeling, the Tri-Constraint Method, & Integrated Project Delivery.
LernzielBy the end of the course, students will be able to plan and manage the lean, integrated, and digital project delivery of a construction project.
Students will know they are able to achieve this overall course goal when they can:
1. Apply the fundamental theories of lean production to the context of construction management. This includes the ability to describe the three views of production: transformation, flow and value generation; evaluate the benefits of a pull production system compared to push production systems; evaluate how production variability and uncertainty contributes to work-in-process and 'waste'; and apply the concepts of lean production to several construction management tools including the Last Planner System, Pull Planning, Target Value Design, and Takt Planning.
2. Understand the fundamentals of Virtual Design and Construction and Building Information Modeling. This includes the ability to prepare a model breakdown structure capable of integrating project information for all stakeholders; describe the upcoming transition to a common data environment for BIM that will use platforms such as Autodesk Forge; and describe the barriers to successful implementation of BIM within construction and design firms
3. Plan and schedule an integrated '5D' scope schedule cost model using the Tri-Constraint Method. This includes the ability to understand the TCM algorithm, apply parametric logic to the creation of a virtual model for construction production; and evaluate the limitations of the critical path method when compared to resource- and space-constrained scheduling
4. Evaluate benefits of integrated project governance compared to the organization of traditional construction project delivery systems. This includes the ability to evaluate the risks, benefits and considerations for integrated teams using multi-party relational contracts that cross disciplinary and firm boundaries; and explain to others the 'elements' of integrated projects (e.g. colocation, early involvement of key stakeholders, shared risk/reward, collaborative decision making)
InhaltThe construction industry is continually seeking to deliver High-Performance (HP) projects for their clients. HP buildings must meet the criteria of four focus areas – buildability, operability, usability, and sustainability. The project must be buildable, as measured by metrics of cost, schedule, and quality. It must be operable, as measured by the cost of maintaining the facility for the duration of its lifecycle. It must be usable, enabling productivity, efficiency and well-being of those who will inhabit the building. Finally, it must be sustainable, minimizing the use of resources such as energy and water. Buildings that succeed in all four of these areas can be considered HP projects.
HP buildings require the integration of building systems. However, the traditional methods of planning and construction do not use an integrated approach. Project fragmentation between many stakeholders is often cited as the cause of poor project outcomes and the reason for poor productivity gains in the construction industry. In response, the construction industry has turned to new forms of integration in order to integrate the processes, organization, and information required for high performance projects.
This course investigates emerging trends in the construction industry – e.g. colocation, shared risk/reward contracts, lean construction methods, and use of shared building information models (BIM) for virtual design and construction (VDC) – as a way to achieve HP projects.
For integrated processes, students will be introduced to the fundamentals of lean construction management. This course will look at the causes of variability in construction production and teach the theory of lean production for construction. Processes and technologies will be introduced for lean management, such as the last planner system, takt time planning, production tracking, and target value design.
For integrated information, students will be introduced to the fundamentals of virtual design and construction, including how to use work breakdown structures and model breakdown structures for building information modeling, and the fundamentals and opportunities for 4D scheduling, clash detection, and “5D and 6D” models. Future technologies emerging to integrate information such as the use of Autodesk Forge will be presented. Students will have the opportunity to discuss barriers in the industry to more advanced implementation of BIM and VDC.
For integrated organization, students will study the limitations of the construction industry to effectively organize for complex projects, including the challenges of managing highly interdependent tasks and generating knowledge and learning within large multi-organizational project teams. One emerging approach in North America known as IPD will be studied as a case example. Students will explore the benefits of certain ‘elements’ of IPD such as project team colocation, early involvement of trade contractors, shared risk/reward contracts, and collaborative decision making.
The course will also include several guest lectures from industry experts to further demonstrate how these concepts are applied in practice.
SkriptLecture Presentation slides will be available for viewing and download the day before each lecture.

The class will be presented in a "flipped classroom" environment where students will be required to do readings or watch video before class. In-class activities will act to reinforce and expand upon these primary concepts.

If possible due to COVID restrictions, students will be expected to attend a half-day workshop on the Last Planner System. The date of this workshop will be provided at a later point in time.
LiteraturA full list of required readings will be made available to the students via Moodle
Voraussetzungen / BesonderesProject Management for Construction Projects (101-0007-00L) is a recommended but not required prerequisite for this course
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Medien und digitale Technologiengeprüft
Soziale KompetenzenKommunikationgefördert
Kooperation und Teamarbeitgeprüft
Menschenführung und Verantwortunggeprüft
Selbstdarstellung und soziale Einflussnahmegefördert
Sensibilität für Vielfalt gefördert
Persönliche KompetenzenKritisches Denkengeprüft
Selbststeuerung und Selbstmanagement gefördert
101-0317-00LUntertagbau IW3 KP2GG. Anagnostou, E. Pimentel
KurzbeschreibungVermittlung grundlegender Aspekte der Statik und Konstruktion im Untertagbau. Aufzeigen von verschiedenen Ausbruchsmethoden sowie Sicherungs- und Bauhilfsmassnahmen unter Berücksichtigung geologischer, statischer und ausführungstechnischer Gesichtspunkte.
LernzielVermittlung grundlegender Aspekte der Statik und Konstruktion im Untertagbau. Aufzeigen von verschiedenen Ausbruchsmethoden sowie Sicherungs- und Bauhilfsmassnahmen unter Berücksichtigung geologischer, statischer und ausführungstechnischer Gesichtspunkte.
InhaltGrundlagen und Anwendungen numerischer Methoden in der Tunnelstatik
Ausbruchsmethoden (Bau- und Betriebsweisen)
Sicherungs- und Bauhilfsmassnahmen:
- Injektionen
- Jet Grouting
- Gefrierverfahren
- Wasserhaltung
- Rohrschirme
- Brustanker
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
101-0187-00LStructural Reliability and Risk AnalysisW3 KP2GS. Marelli
KurzbeschreibungStructural 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.
LernzielThe 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.
InhaltEngineers 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.
SkriptSlides 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.
LiteraturAng, 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.
Voraussetzungen / BesonderesBasic course on probability theory and statistics
101-0437-00LTraffic EngineeringW6 KP4GA. Kouvelas
KurzbeschreibungFundamentals of traffic flow theory and control.
LernzielThe objective of this course is to fully understand the fundamentals of traffic flow theory in order to effectively manage traffic operations. By the end of this course students should be able to apply basic techniques to model different aspects of urban and inter-urban traffic performance, including congestion.
InhaltIntroduction to fundamentals of traffic flow theory and control. Includes understanding of traffic data collection and processing techniques, as well as data analysis, traffic modeling, and methodologies for traffic control.
SkriptThe lecture notes and additional handouts will be provided during the lectures.
LiteraturAdditional literature recommendations will be provided during the lectures.
Voraussetzungen / BesonderesVerkehr III - Road Transport Systems 6th Sem. BSc (101-0415-00L)
Special permission from the instructor can be requested if the student has not taken Verkehr III
101-0417-00LTransport Planning MethodsW6 KP4GK. W. Axhausen
KurzbeschreibungThe course provides the necessary knowledge to develop models supporting and also evaluating the solution of given planning problems.
The course is composed of a lecture part, providing the theoretical knowledge, and an applied part in which students develop their own models in order to evaluate a transport project/ policy by means of cost-benefit analysis.
Lernziel- Knowledge and understanding of statistical methods and algorithms commonly used in transport planning
- Comprehend the reasoning and capabilities of transport models
- Ability to independently develop a transport model able to solve / answer planning problem
- Getting familiar with cost-benefit analysis as a decision-making supporting tool
InhaltThe course provides the necessary knowledge to develop models supporting the solution of given planning problems and also introduces cost-benefit analysis as a decision-making tool. Examples of such planning problems are the estimation of traffic volumes, prediction of estimated utilization of new public transport lines, and evaluation of effects (e.g. change in emissions of a city) triggered by building new infrastructure and changes to operational regulations.

To cope with that, the problem is divided into sub-problems, which are solved using various statistical models (e.g. regression, discrete choice analysis) and algorithms (e.g. iterative proportional fitting, shortest path algorithms, method of successive averages).

The course is composed of a lecture part, providing the theoretical knowledge, and an applied part in which students develop their own models in order to evaluate a transport project/ policy by means of cost-benefit analysis. Interim lab session take place regularly to guide and support students with the applied part of the course.
SkriptMoodle platform (enrollment needed)
LiteraturWillumsen, P. and J. de D. Ortuzar (2003) Modelling Transport, Wiley, Chichester.

Cascetta, E. (2001) Transportation Systems Engineering: Theory and Methods, Kluwer Academic Publishers, Dordrecht.

Sheffi, Y. (1985) Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods, Prentice Hall, Englewood Cliffs.

Schnabel, W. and D. Lohse (1997) Verkehrsplanung, 2. edn., vol. 2 of Grundlagen der Strassenverkehrstechnik und der Verkehrsplanung, Verlag für Bauwesen, Berlin.

McCarthy, P.S. (2001) Transportation Economics: A case study approach, Blackwell, Oxford.
101-0491-00LAgent Based Modeling in TransportationW6 KP4GM. Balac
KurzbeschreibungThis course provides an introduction to agent-based modeling in transportation. The lectures and exercises offer an opportunity to learn about agent-based models' current methodology, focusing on MATSim, how agent-based models are set up, and perform a practical case study by working in teams.
LernzielAt the end of the course, the students should:
- have an understanding of agent-based modeling
- have an understanding of MATSim
- have an understanding of the process needed to set up an agent-based study
- have practical experience of using MATSim to perform practical transportation studies
InhaltThis course provides an introduction to agent-based models for transportation policy analysis. Four essential topics are covered:

1) Introduction of agent-based modeling and its comparison to the traditional state of practice modeling
2) Introduction of MATSim, an open-source agent-based model, developed at ETH Zurich and TU Berlin, and its various parts
3) Setting up an agent-based model simulation, where different statistical methods used in the process will be introduced and explained. Here the open-source eqasim framework used at ETH Zurich to set up agent-based models will be introduced
4) Conducting a transport policy study. The case study will be performed in groups and will include a paper-like report.

During the course, outside lecturers will give several lectures on using MATSim in practice (i.e., SBB).
LiteraturAgent-based modeling in general
Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the national academy of sciences, 99(suppl 3), 7280-7287.
Helbing, D (2012) Social Self-Organization, Understanding Complex Systems, Springer, Berlin.
Heppenstall, A., A. T. Crooks, L. M. See and M. Batty (2012) Agent-Based Models of Geographical Systems, Springer, Dordrecht.


Horni, A., K. Nagel and K.W. Axhausen (eds.) (2016) The Multi-Agent Transport Simulation MATSim, Ubiquity, London

Additional relevant readings, primarily scientific articles, will be recommended throughout the course.
Voraussetzungen / BesonderesThere are no strict preconditions in terms of which lectures the students should have previously attended. However, knowledge of basic statistical theory is expected, and experience with at least one high-level programming language (Java, R, Python, or other) is recommended.
101-0507-00LInfrastructure Management 3: Optimisation Tools
Findet dieses Semester nicht statt.
W6 KP2GB. T. Adey
KurzbeschreibungThis course will provide an introduction to the methods and tools that can be used to determine optimal inspection and intervention strategies and work programs for infrastructure.
LernzielUpon successful completion of this course students will be able:
- to use preventive maintenance models, such as block replacement, periodic preventive maintenance with minimal repair, and preventive maintenance based on parameter control, to determine when, where and what should be done to maintain infrastructure
- to take into consideration future uncertainties in appropriate ways when devising and evaluating monitoring and management strategies for physical infrastructure
- to use operation research methods to find optimal solutions to infastructure management problems
InhaltPart 1:
Explanation of the principal models of preventative maintenance, including block replacement, periodic group repair, periodic maintenance with minimal repair and age replacement, and when they can be used to determine optimal intervention strategies

Part 2:
Explanation of preventive maintenance models that are based on parameter control, including Markovian models and opportunistic replacement models

Part 3:
Explanation of the methods that can be used to take into consideration the future uncertainties in the evaluation of monitoring strategies

Part 4:
Explanation of how operations research methods can be used to solve typical infrastructure management problems.
SkriptA script will be given out at the beginning of the course.
Class relevant materials will be distributed electronically before the start of class.
A copy of the slides will be handed out at the beginning of each class.
Voraussetzungen / BesonderesSuccessful completion of IM1: 101-0579-00 Evaluation tools is a prerequisite for this course.
101-0267-01LNumerical HydraulicsW3 KP2GM. Holzner
KurzbeschreibungIn the course Numerical Hydraulics the basics of numerical modelling of flows are presented.
LernzielThe goal of the course is to develop the understanding of the students for numerical simulation of flows to an extent that they can later use commercial software in a responsible and critical way.
InhaltThe basic equations are derived from first principles. Possible simplifications relevant for practical problems are shown and their applicability is discussed. Using the example of non-steady state pipe flow numerical methods such as the method of characteristics and finite difference methods are introduced. The finite volume method as well as the method of characteristics are used for the solution of the shallow water equations. Special aspects such as wave propagation and turbulence modelling are also treated.

All methods discussed are applied pratically in exercises. This is done using programs in MATLAB which partially are programmed by the students themselves. Further, some generelly available softwares such as BASEMENT for non-steady shallow water flows are used.
SkriptLecture notes, powerpoints shown in the lecture and programs used can be downloaded. They are also available in German.
LiteraturGiven in lecture
101-0159-00LMethod of Finite Elements IIW3 KP2GE. Chatzi, K. Tatsis
KurzbeschreibungThe Method of Finite Elements II is a continuation of Method of Finite Elements I. Here, we explore the theoretical and numerical implementation concepts for the finite element analysis beyond the linear elastic behavior. This course aims to offer students with the skills to perform nonlinear FEM simulations using coding in Python.
*This course offers no introduction to commercial software.
LernzielThis class overviews advanced topics of the Method of Finite Elements, beyond linear elasticity. Such phenomena are particularly linked to excessive loading effects and energy dissipation mechanisms. Their understanding is necessary for reliably computing structural capacity.
In this course, instead of blindly using generic structural analysis software, we offer an explicit understanding of what goes on behind the curtains, by explaining the algorithms that are used in such software.

The course specifically covers the treatment of the following phenomena:
- Material Nonlinearity (Plasticity)
- Geometric Nonlinearity (Large Displacement Problems)
- Nonlinear Dynamics
- Fracture Mechanics
The concepts are introduced via theory, numerical examples, demonstrators and computer labs in Python (starting Fall 2021).

Upon completion of the course, the participants will be able to:
- Recognize when linear elastic analysis is insufficient
- Solve nonlinear dynamics problems, which form the core for limit state calculations (e.g. ultimate capacity, failure) of structures
- Numerically simulate fracture; a dominant failure phenomenon for structural systems.

See the class webpage for more information:
SkriptThe course slides serve as Script. These are openly available on: Link
LiteraturCourse Slides (Script): Link

Useful (optional) Reading:
- Nonlinear Finite Elements of Continua and Structures, T. Belytschko, W.K. Liu, and B. Moran.
- Bathe, K.J., Finite Element Procedures, Prentice Hall, 1996.
- Crisfield, M.A., Remmers, J.J. and Verhoosel, C.V., 2012. Nonlinear finite element analysis of solids and structures. John Wiley & Sons.
- De Souza Neto, E.A., Peric, D. and Owen, D.R., 2011. Computational methods for plasticity: theory and applications. John Wiley & Sons.
Voraussetzungen / BesonderesPrerequisites:
-101-0158-01 Method of Finite Elements I (FS)
- A good knowledge of Python is necessary for attending this course.
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Soziale KompetenzenKooperation und Teamarbeitgeprüft
Persönliche KompetenzenKreatives Denkengeprüft
Kritisches Denkengeprüft
101-0617-02LComputational Science Investigation for Material MechanicsW4 KP2SD. Kammer, F. Wittel
KurzbeschreibungIntroduction to computational sciences with focus on numerical modeling of the mechanics of materials. Simulation of material damage and failure with advanced finite element methods.
LernzielLearning from mistakes and failures is as old as the engineering discipline. Understanding why things went wrong is essential for improvement, but often impossible without the help of numerical modelling. Real world problems are often highly nonlinear, dependent on multiple physical fields, involve fundamental material behavior far from equilibrium and reversibility, and can often only be understood by addressing different relevant scales.

In this course, we will use real-life cases to learn how to deal with such problems. Starting from the problem description with governing equations, you will learn how to tackle non-linear and multi-field problems using numerical simulations. A particular focus will be on fracture. Starting from the failed state, we will investigate potential causes and find the conditions that resulted in failure. For doing so, you will learn how to predict it with the Finite Element Method (FEM). To correctly assess failure, plastic behavior and size effects, originating from the underlying material microstructure, need to be considered. You will learn how to deal with plasticity in FEM and how you can get information from the heterogeneous material scale into your FEM framework.
Inhalt1 Introduction to (numeric) forensic engineering
2 The nature of engineering problems (governing equations)
3 Numerical recipes for dealing with non-linear problems
4 Multi-field problems (HTM; Comsol)
5 On the nature of failure - Physics of damage and fracture
6 Cracks and growth in structures (LEFM and beyond)
7 A practical approach to LEFM with FEM (Abaqus)
8 Introduction to metal plasticity
9 Damage and fracture in heterogeneous materials
10 Mechanics of fatigue
11 Visco-elastic failure
12 Student μ-Project presentation
SkriptWill be provided during the lecture via moodle.
LiteraturWill be provided during the lecture.
101-0185-01LCAD für Bauingenieure Belegung eingeschränkt - Details anzeigen
Maximale Teilnehmerzahl: 30.
Es zählt der Zeitpunkt der Einschreibung.
W2 KP2GK.‑H. Hamel, F. Ortiz Quintana
KurzbeschreibungEinführung in das computergestützte Konstruieren in 2D und 3D an Beispielen aus dem konstruktiven Ingenieurbau
LernzielNach Abschluss des Kurses können die Absolventen eine 2D-Konstruktion erstellen (Schalungsplan) und sie kennen das Prinzip eines Bewehrungsmoduls. Ferner haben sie eine Einführung in ein 3D-Programm enthalten (3D-Bewehren).
Sie sind somit besser vorbereitet auf
- die Bachelorarbeit im 6. Semester,
- ein allfälliges Praktikum zwischen Bachelor- und Masterstudium,
- die Projektarbeiten im Masterstudium,
- die Masterarbeit.
Ausserdem schulen sie das räumliche Vorstellungsvermögen und erwerben sich Orientierungswissen als spätere Vorgesetzte von Zeichnern und Konstrukteuren.
SkriptCAD für Bauingenieure
Voraussetzungen / BesonderesSpezialbewilligung der Dozierenden notwendig.
Arbeit ausschliesslich am eigenen Laptop. Die rechtzeitige Installation der Software ist Bedingung für die Teilnahme. Eine Anleitung zur Installation wird ausgegeben.
101-0250-00LSolving Partial Differential Equations in parallel on GPUs Belegung eingeschränkt - Details anzeigen W4 KP3GL. Räss, S. Omlin, M. Werder
KurzbeschreibungThis course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering.
LernzielWhen quantitative assessment of physical processes governing natural and engineered systems relies on numerically solving differential equations, fast and accurate solutions require performant algorithms leveraging parallel hardware. The goal of this course is to offer a practical approach to solve systems of differential equations in parallel on GPUs using the Julia language. Julia combines high-level language conciseness to low-level language performance which enables efficient code development.

The course will be taught in a hands-on fashion, putting emphasis on you writing code and completing exercises; lecturing will be kept at a minimum. In a final project you will solve a solid mechanics or fluid dynamics problem of your interest, such as the shallow water equation, the shallow ice equation, acoustic wave propagation, nonlinear diffusion, viscous flow, elastic deformation, viscous or elastic poromechanics, frictional heating, and more. Your Julia GPU application will be hosted on a git-platform and implement modern software development practices.
InhaltPart 1 - Discovering a modern parallel computing ecosystem
- Learn the basics of the Julia language;
- Learn about the diffusion process and how to solve it;
- Understand the practical challenges of parallel and distributed computing: (multi-)GPUs, multi-core CPUs;
- Learn about software development tools: git, version control, continuous integration (CI), unit tests.

Part 2 - Developing your own parallel algorithms
- Implement wave propagation (or more advanced physics);
- Apply spatial and temporal discretisation (finite-differences, various time-stepper);
- Implement efficient iterative algorithms;
- Implement shared (on CPU and GPU) and, if time allows, distributed memory parallelisation (multi-GPUs/CPUs);
- Learn about main simulation performance limiters.

Part 3 - Final project
- Apply your new skills in a final project;
- Implement advanced physical processes (solid and fluid dynamic - elastic and viscous solutions).
SkriptDigital lecture notes, interactive Julia notebooks, online material.
LiteraturLinks to relevant literature will be provided during classes.
Voraussetzungen / BesonderesCompleted BSc studies. Interest in and basic knowledge of numerics, applied mathematics, and physics/engineering sciences. Basic programming skills (in e.g. Matlab, Python, Julia); advanced programming skills are a plus.
101-0139-00LScientific Machine and Deep Learning for Design and Construction in Civil Engineering Belegung eingeschränkt - Details anzeigen W3 KP4GM. A. Kraus, D. Griego
KurzbeschreibungThis course will present methods of scientific machine and deep learning (ML / DL) for applications in design and construction in civil engineering. After providing proper background on ML and the scientific ML (SciML) track, several applications of SciML together with their computational implementation during the design and construction process of the built environment are examined.
LernzielThis course aims to provide graduate level introduction into Machine and especially scientific Machine Learning for applications in the design and construction phases of projects from civil engineering.

Upon completion of the course, the students will be able to:
1. understand main ML background theory and methods
2. assess a problem and apply ML and DL in a computational framework accordingly
3. Incorporating scientific domain knowledge in the SciML process
4. Define, Plan, Conduct and Present a SciML project
InhaltThe course will include theory and algorithms for SciML, programming assignments, as well as a final project assessment.

The topics to be covered are:
1. Fundamentals of Machine and Deep Learning (ML / DL)
2. Incorporation of Domain Knowledge into ML and DL
3. ML training, validation and testing pipelines for academic and research projects

A comprehensive series of computer/lab exercises and in-class demonstrations will take place, providing a "hands-on" feel for the course topics.
SkriptThe course script is composed by lecture slides, which are available online and will be continuously updated throughout the duration of the course.
LiteraturSuggested Reading:
Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong Mathematics for Machine Learning
K. Murphy. Machine Learning: a Probabilistic Perspective. MIT Press 2012
C. Bishop. Pattern Recognition and Machine Learning. Springer, 2007
S. Guido, A. Müller: Introduction to machine learning with python. O'Reilly Media, 2016
O. Martin: Bayesian analysis with python. Packt Publishing Ltd, 2016
Voraussetzungen / BesonderesFamiliarity with MATLAB and / or Python is advised.
101-0120-00LStructural Glass Design and Facade Engineering Belegung eingeschränkt - Details anzeigen W3 KP3GV.‑A. Silvestru
KurzbeschreibungThe course gives an introduction to structural glass design and related façade engineering aspects. It will focus on the properties of the material glass and glass products, as well as on the structural design of glass elements and their supporting systems and connections.
LernzielAfter successful completion of the course, students will be able to:
-Understand and apply the fundamentals of the material glass and glass products, the basic principles for using glass as a load-carrying building material for structural applications and the types of connections used for glass elements;
-Recognize requirements for glass elements depending on their application area and chose the appropriate glass products and assemblies accordingly;
-Structurally design out-of-plane loaded glass elements based on available standards, both by hand calculations and specific software applications;
-Apply selected approaches for the structural design of in-plane loaded glass elements;
-Select suitable supporting systems (post-and-beam façade, curtain wall, etc.) and connections (point fixings, brackets, etc.) for the glass elements and structurally design them.
InhaltThis course introduces civil engineering students to structural glass design and related façade engineering aspects. It aims to provide the students the knowledge required in engineering offices to design glass elements but at the same time, the necessary fundamentals for later performing research in this field. To achieve this, the course includes lectures, design exercises and a design project.

The lectures will cover the following contents:
-Production methods and properties of the material glass and glass products and their structurally relevant properties (annealed glass, thermally tempered glass, chemically tempered glass, laminated glass, insulating glass, curved glass);
-Connection principles and types for glass elements (mechanical fixing, adhesive bonding);
-Requirements for glass elements depending on the application area (vertical glazing, overhead glazing, walk-on glazing, barrier glazing);
-Structural design of glass elements based on standards and research results (out-of-plane loaded glass elements and in-plane loaded glass elements);
-Typologies and design of structural systems for transparent façades;
-Requirements and functions for transparent facades.

Design exercises:
The principles and methods presented in the lectures are practiced with the students in design exercises. Hand calculation methods and their limitations as well as the software for structural glass design SJ Mepla are used for out-of-plane loaded glass elements. For in-plane loaded glass elements, the specifics of numerical calculation procedures are exemplified with the software Abaqus.

Design project:
The students will consolidate the knowledge gained in the theory-lectures and in the design exercises by working on a small design task (e.g. a glass canopy, a glass façade, a glass pavilion) in the form of a group work (ideally groups of 2-3 students). Within this task, the students will: conceptually design the structure and selected connection details; identify requirements for the glass elements and define their assembly; structurally design selected glass components, their support systems and their connections. The students will work on the design task in the second half of the semester and will get feedback on their progress in weekly review sessions. At the end of the semester, the groups will submit a project report and give an oral presentation of their projects.
SkriptThe lectures are based on lecture slides and handouts.
LiteraturRecommended and supplementary literature:
-Schneider J., Kuntsche J., Schula S., Schneider F., Wörner J.-D.: Glasbau – Grundlagen, Berechnung, Konstruktion; Springer Vieweg, Berlin Heidelberg, 2. Auflage, 2016.
-Kasper R., Pieplow K., Feldmann M.: Beispiele zur Bemessung von Glasbauteilen nach DIN 18008; Ersnst & Sohn, Berlin, 2016.
-Haldimann M., Luible A., Overend M.: Structural Use of Glass; IABSE, 2008.
-Knaack U., Klein T., Bilow M., Auer T.: Facades – Principles of Construction; Birkhäuser, Basel, 2007.
-Watts A.: Modern construction envelopes – Systems for architectural design and prototyping; Birkhäuser, Basel, 2019.
Voraussetzungen / BesonderesPrior knowledge of structural analysis, especially steel structures is necessary. Prior basic knowledge on the method of finite elements is recommended.
101-0509-00LInfrastructure Management 1: ProcessW6 KP3GB. T. Adey
KurzbeschreibungInfrastructure asset management is the process used to ensure that infrastructure provides adequate levels of service for specified periods of time. This course provides an overview of the process, from setting goals to developing intervention programs to analyzing the process itself. It consists of weekly lectures and a group project. Additionally, there is a weekly help session.
LernzielThere are a large number of efforts around the world to obtain more net benefits from infrastructure assets. This can be seen through the proliferation of codes and guidelines and the increasing amount of research in road infrastructure asset management. Many of these codes and guidelines and much of the research, however, are focused on only part of the large complex problem of infrastructure asset management.

The objective of this course is to provide an overview of the entire infrastructure management process. The high-level process described can be used as a starting point to ensure that infrastructure management is done professionally, efficiently and effectively. It also enables a clear understanding of where computer systems can be used to help automate parts of the process. Students can use this process to help improve the specific infrastructure management processes in the organisations in which they work in the future.

More specifically upon completion of the course, students will
• understand the main tasks of an infrastructure manager and the complexity of these tasks,
• understand the importance of setting goals and constraints in the management of infrastructure,
• be able to predict the deterioration of individual assets using discrete states that are often associated with visual inspections,
• be able to develop and evaluate simple management strategies for individual infrastructure assets,
• be able to develop and evaluate intervention programs that are aligned with their strategies,
• understand the principles of guiding projects and evaluating the success of projects,
• be able to formally model infrastructure management processes, and
• understand the importance of evaluating the infrastructure management process and have a general idea of how to do so.
InhaltThe weekly lectures are structured as follows:
1 Introduction: An introduction to infrastructure management, with emphasis on the consideration of the benefits and costs of infrastructure to all members of society, and balancing the need for prediction accuracy with analysis effort. The expectations of your throughout the semester, including a description of the project.
2 Positioning infrastructure management in society: As infrastructure plays such an integral part in society, there is considerable need to ensure that infrastructure managers are managing it as best possible. A prominent network regulator explains the role and activities of a network regulator.
3 Setting goals and constraints – To manage infrastructure you need to know what you expect from it in terms of service and how much you are willing to pay for it. We discuss the measures of service for this purpose, as well as the ideas of quantifiable and non-quantifiable benefits, proxies of service, and valuing service.
4 Predicting the future – As infrastructure and our expectations of service from it change over time, these changes need to be included in the justification of management activities. This we discuss the connection between provided service and the physical state of the infrastructure and one way to predict their evolution over time.
5 Help session 1
6 Determining and justifying general interventions - It is advantageous to be able to explain why infrastructure assets need to be maintained, and not simply say that they need to be maintained. This requires explanation of the types of interventions that should be executed and how these interventions will achieve the goals. It also requires explaining which interventions are to be done if it is not possible to do everything due to for example budget constraints. This week we cover how to determine optimal intervention strategies for individual assets, and how to convert these strategies into network level intervention programs.
7 Determining and justifying monitoring - Once it is clear how infrastructure might change over time, and the optimal intervention strategies are determined, you need to explain how you are going to know that these states exist. This requires the construction of monitoring strategies for each of asset. This week we focus on how to develop monitoring strategies that ensure interventions are triggered at the right time.
8 Converting programs to projects / Analysing projects – Once programs are completed and approved, infrastructure managers must create, supervise and analyse projects. This week we focus on this conversion and the supervision and analysis of projects.
9 Help session 2
10 Ensuring good information – Infrastructure management requires consistent and correct information. This is enabled by the development of a good information model. This week we provide an introduction to information models and how they are used in infrastructure management.
11 Ensuring a well-run organization – How people work together affects how well the infrastructure is managed. This week we focus on the development of the human side of the infrastructure management organisation.
12 Describing the IM process – Infrastructure management is a process that is followed continually and improved over time. It should be written down clearly. This week we will concentrate on how this can be done using the formal modelling notation BPMN 2.0.
13 Evaluating the IM process – Infrastructure management processes can always be improved. Good managers acknowledge this, but also have a plan for continual improvement. This week we concentrate on how you can systematically evaluate the infrastructure management process.
14 Help session 3 and submission of project report.

The course uses a combination of qualitative and quantitative approaches. The quantitative analysis required in the project requires at least the use of Excel. Some students, however, prefer to use Python or R.
Skript• The lecture materials consist of handouts, the slides, and example calculations in Excel.
• The lecture materials will be distributed via Moodle two days before each lecture.
LiteraturAppropriate literature will be handed out when required via Moodle.
Voraussetzungen / BesonderesThis course has no prerequisites.
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Medien und digitale Technologiengeprüft
Soziale KompetenzenKommunikationgefördert
Kooperation und Teamarbeitgefördert
Menschenführung und Verantwortunggefördert
Selbstdarstellung und soziale Einflussnahmegefördert
Sensibilität für Vielfalt gefördert
Persönliche KompetenzenAnpassung und Flexibilitätgefördert
Kreatives Denkengefördert
Kritisches Denkengefördert
Integrität und Arbeitsethikgefördert
Selbstbewusstsein und Selbstreflexion gefördert
Selbststeuerung und Selbstmanagement gefördert
101-0492-00LMicroscopic Modelling and Simulation of Traffic OperationsW3 KP2GM. Makridis
KurzbeschreibungThe course introduces basics of microscopic modelling and simulation of traffic operations, including model design and development, calibration, validation, data analysis, identification of strategies for improving traffic flow performance, and evaluation of such strategies.
The aim is to provide the fundamentals for building a realistic traffic-engineering project from beginning to end.
LernzielThe objective of this course is to conduct a realistic traffic engineering project from beginning to end. The students will first familiarize themselves with microscopic traffic models. Students will work in groups on a project that includes a base scenario on a real traffic network. Throughout the semester, along with theoretical concepts, the students will build the base scenario (design, calibration and validation) and will develop alternative scenarios regarding modification on the infrastructure, simulation of in-vehicle technologies and vehicle-to-everything (V2X) communication.
Simulations will be implemented in Aimsun software. The students will be asked to understand, analyze, interpret and present traffic properties. Evaluation of alternative scenarios over the same network will be performed. Finally, students will be asked to design, implement, analyze and present a novel proposal, which will be compared with the base scenario.
Upon completion of the course, the students will:
• Understand the basic models used in microsimulation software (car-following, lane changing, gap acceptance, give ways, on/off-ramps, etc.).
• Design a road transport network inside the simulation software.
• Understand the basics behind modeling traffic demand and supply, vehicle dynamics, performance indicators for evaluation and network design for a realistic road transport network.
• Understand how to design a complete study, implement and validate it for planning purposes, e.g. creating a new road infrastructure.
• Make valid and concrete engineering proposals based on the simulation model and alternative scenarios.
InhaltIn this course, the students will first learn some microscopic modelling and simulation concepts, and then complete a traffic-engineering project with microscopic traffic simulator Aimsun.
Microscopic modelling and simulation concepts will include:
1) Car following models
2) Lane change models
3) Calibration and validation methodology
Specific tasks for the project will include:
1) Building a model with the simulator Aimsun in order to replicate and analyze the traffic conditions measured/observed.
2) Calibrating and validating the simulation model.
3) Redesigning/extending the model to improve the traffic performance through Aimsun and with/without programming in Python or C++.
The course will be based on a project that each group of students will build (design, calibrate, analyze and presentation) across the semester. A mid-term and final presentation of the work will be asked from each group of students.
It consists of weekly 2-hour lectures. The students work in pairs on a group project that completes in the end of the semester. The modelling software used is Aimsun and lectures (theory and hands on experience) are taking place in a computer room.
The course Road Transport Systems (Verkehr III), or simultaneously taking the course Traffic Engineering is encouraged. Previous experience with Aimsun/Python/C++ is helpful but not mandatory.
SkriptThe lecture notes and additional handouts will be provided before the lectures.
LiteraturAdditional literature recommendations will be provided at the lectures.
Voraussetzungen / BesonderesStudents need to know some basic road transport concepts. The course Road Transport Systems (Verkehr III), or simultaneously taking the course Traffic Engineering is encouraged. Previous experience with Aimsun is helpful but not mandatory.
101-0123-00LStructural Design Information W3 KP2GP. Ohlbrock, P. Block, J. Schwartz
KurzbeschreibungThe goal of the course is to introduce the civil engineering students to Structural Design, which is regarded as a discipline that relates structural behavior, construction technologies and architectural concepts. The course encourages the students to understand the relationship between the form of a structure and the forces within it by promoting the development of designed projects.
LernzielAfter successfully completing this course the students will able to:
1. Critically question structural design concepts of historical and contemporary references
2. Use graphic statics and strut-and-tie models based on the Theory of Plasticity to describe the load bearing behavior of structures
3. Understand different construction technologies and have an awareness of their potential for structural design
4. Use contemporary digital tools for the design of structures in equilibrium
5. Design an appropriate structural system for a given design task taking into account architectural considerations
InhaltThe goal of the course is to introduce the civil engineering students to Structural Design, which is understood as a discipline that relates structural behavior, construction technologies and architectural concepts. Hence, the course encourages the students to develop an intuitive understanding of the relationship between the form of a structure and the forces within it by promoting the development of designed projects, in which the static and architectural aspects come together. The course is structured in two main parts, each developed in half of a semester: a mainly theoretical one (including the teaching of graphic statics) and a mainly applied one (focused on the development of a design project by the students using digital form-finding tools).

Graphic statics is a graphical method developed by Prof. Karl Culmann and firstly published in 1864 at ETH Zurich. In this approach to structural analysis and design, geometric construction techniques are used to visualize the relation between the geometry of a structure and the forces acting in and on it, represented by geometrically dependent form and force diagrams.
The course will firstly review the main principles of graphic statics through a series of frontal lectures and discuss the relationship to analytical statics. Graphic statics is then used as an operative tool to design structures in equilibrium based on the lower bound theorem of the Theory of Plasticity. Additionally, the course will introduce contemporary methodologies and tools (parametric CAD software) for the interactive application of equilibrium modelling in the form of short workshops. The students will familiarize with the topic by solving exercises and confronting themselves with simple design tasks.

Design Project:
Specific structural design approaches and design methodologies based on graphic statics and references from construction history will be introduced to the students by means of seminars and workshops. By developing a design project, the students will apply these concepts and techniques in order to become proficient with open design tasks (such as the design of a bridge, a large span hall or a tower). At the end of the semester, the students present their projects to a jury of internal and external critics in a final review. The main criterion of evaluation is the students' ability to integrate architectural considerations into their structural design.
Literatur"Faustformel Tragwerksentwurf"
(Philippe Block, Christoph Gengangel, Stefan Peters,
DVA Deutsche Verlags-Anstalt 2015, ISBN 978-3-421-04012-1)

"Form and Forces: Designing Efficient, Expressive Structures"
(Edward Allen, Waclaw Zalewski, October 2009, ISBN: 978-0-470-17465-4)

"The art of structures, Introduction to the functioning of structures in architecture"
(Aurelio Muttoni, EPFL Press, 2011, ISBN-13: 978-0415610292, ISBN-10: 041561029X)
102-0468-10LWatershed ModellingW6 KP4GP. Molnar
KurzbeschreibungWatershed Modelling is a practical course on numerical water balance models for a range of catchment-scale water resource applications. The course covers GIS use in watershed analysis, models types from conceptual to physically-based, parameter calibration and model validation, and analysis of uncertainty. The course combines theory (lectures) with a series of practical tasks (exercises).
LernzielThe main aim of the course is to provide practical training with watershed models for environmental engineers. The course is built on thematic lectures (2 hrs a week) and practical exercises (2 hrs a week). Theory and concepts in the lectures are underpinned by many examples from scientific studies. A comprehensive exercise block builds on the lectures with a series of 4 practical tasks to be conducted during the semester in group work. Exercise hours during the week focus on explanation of the tasks. The course is evaluated 50% by performance in the graded exercises and 50% by a semester-end oral examination (30 mins) on watershed modelling concepts.
InhaltThe first part (A) of the course is on watershed properties analysed from DEMs, and on global sources of hydrological data for modelling applications. Here students learn about GIS applications (ArcGIS, Q-GIS) in hydrology - flow direction routines, catchment morphometry, extracting river networks, and defining hydrological response units. In the second part (B) of the course on conceptual watershed models students build their own simple bucket model (Matlab, Python), they learn about performance measures in modelling, how to calibrate the parameters and how to validate models, about methods to simulate stochastic climate to drive models, uncertainty analysis. The third part (C) of the course is focussed on physically-based model components. Here students learn about components for soil water fluxes and evapotranspiration, they practice with a fully-distributed physically-based model Topkapi-ETH, and learn about other similar models at larger scales. They apply Topkapi-ETH to an alpine catchment and study simulated discharge, snow, soil moisture and evapotranspiration spatial patterns.
SkriptThere is no textbook. Learning materials consist of (a) video-recording of lectures; (b) lecture presentations; and (c) exercise task documents that allow independent work.
LiteraturLiterature consist of collections from standard hydrological textbooks and research papers, collected by the instructors on the course moodle page.
Voraussetzungen / BesonderesBasic Hydrology in Bachelor Studies (engineering, environmental sciences, earth sciences). Basic knowledge of Matlab (Python), ArcGIS (Q-GIS).
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Medien und digitale Technologiengeprüft
Soziale KompetenzenKommunikationgefördert
Kooperation und Teamarbeitgeprüft
Persönliche KompetenzenKritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion gefördert
Selbststeuerung und Selbstmanagement gefördert
101-0121-00LFatigue and Fracture in Materials and StructuresW4 KP3GE. Ghafoori, A. Taras
KurzbeschreibungThe fundamentals in fatigue and fracture mechanics, which are used in different engineering disciplines (e.g., for mechanical, aerospace, civil and material engineers) will be discussed. The focus will be on fundamental theories (based on fracture mechanics) that model fatigue damage and crack propagation.
LernzielIn this course, the students will learn:
• Mechanisms of fatigue crack initiations in materials.
• Linear elastic and elastic-plastic fracture mechanics.
• Modern computer-based techniques (using ABAQUS Finite Element Package) to simulate cracks in both bulk materials and bonded joints/interfaces.
• Laboratory fatigue and fracture tests on details with cracks.
InhaltThe course starts with a discussion on the importance of fatigue and fracture in different engineering disciplines such as mechanical, aerospace, civil and material engineering domains. The preliminary topics that are covered in this course are:

I) Fatigue of materials:
• Mechanisms of fatigue crack initiation in (ductile and brittle) metals.
• Crack initiation under uni-axial high-cycle fatigue (HCF) loadings: Wöhler (S-N) curves, constant life diagram approach (mean-stress effects), rainflow analysis and Miner's damage rule.
• Crack initiation under multi-axial HCF loadings: multi-axial fatigue mechanisms, critical plane approach (critical distance theory), equivalent stress approach, proportional and non-proportional loading.

II) Fracture mechanics:
• ELinear elastic fracture mechanics (LEFM): limits of LEFM, stress intensity factors, crack opening displacement, mixed-mode fracture, etc.
• Elastic-plastic fracture mechanics: Irwin and Dugdale models, plastic zone shapes, crack-tip opening displacement and J-integral.
• Fatigue crack growth (FCG): FCG models, Paris' law, cyclic plastic zones, crack closure effects. This also includes FE modeling of the FCG and laboratory tests (at Empa).

III) Introduction to cohesive zone models (CZMs):
• Advantages and disadvantages of CZMs compared to fracture mechanics.
• Different bond-slip models for the bonded joints/interfaces.

IV) Computer laboratory to simulate cracks and debonding problems:
• Finite Element (FE) modeling of complex details with cracks.
• FE simulations of debonding problems using CZMs.
• Computer laboratory: FE training and exercises using (the student edition of) the ABAQUS FE Package.

V) Introduction to fatigue and fracture design in civil structures. Different methods for fatigue strengthening will be disscussed.

VI) Visits to the Empa (Swiss Federal Laboratories for Materials Science and Technology) in Dübendorf, and “Laboratory Competition”. The students will:
• Visit different small-scale and large-scale fatigue testing equipment.
• Get to know different ongoing fatigue- and fracture-related projects.
• Witness and help to conduct a fatigue test on a steel plate with a pre-crack and a fracture test on an adhesively-bonded joint.
• Compare the experimental results with their own calculations (from the fracture theories).
• “Laboratory Competition” at Empa: the students with the closest predictions will win the “Empa Laboratory Competition” and will be awarded by a prize.
SkriptLectures are based on the lecture slides and the handouts, which will be given to the students during the semester.
Literatur1. Schijve J. “Fatigue of Structures and Materials”, 2008: New York: Springer.
2. Anderson T.L. “Fracture Mechanics - Fundamentals and Applications”, 3rd Edition, Taylor & Francis Group, LLC. 2005.
3. Budynas R.G., Nisbett J.K. “Shigley's Mechanical Engineering Design”, 2008, New York: McGraw-Hill.
Voraussetzungen / BesonderesNote 1: A basic knowledge on mechanics of structures and structural analysis (i.e., stress-strain analysis and calculations of internal deformations, strains and stresses within structures) is recommended and will be helpful in the course.

Note 2: Laboratory demonstrations and fatigue/fracture tests at the Structural Engineering Research Laboratory of Empa in Dübendorf. This includes laboratory tours and showcasing the Empa large-scale 7-MN fatigue testing machine for bridge cables, different fatigue and fracture testing equipment for structural components, etc.
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