Eleni Chatzi: Katalogdaten im Herbstsemester 2023

NameFrau Prof. Dr. Eleni Chatzi
LehrgebietStrukturmechanik und Monitoring
Adresse
Inst. f. Baustatik u. Konstruktion
ETH Zürich, HIL E 33.3
Stefano-Franscini-Platz 5
8093 Zürich
SWITZERLAND
Telefon+41 44 633 67 55
Fax+41 44 633 10 64
E-Mailchatzi@ibk.baug.ethz.ch
URLhttp://www.chatzi.ibk.ethz.ch/
DepartementBau, Umwelt und Geomatik
BeziehungOrdentliche Professorin

NummerTitelECTSUmfangDozierende
101-0129-00LNon Destructive Evaluation & Rehabilitation of Existing Structures3 KP2GE. Chatzi, B. Herraiz Gómez, G. Kocur
KurzbeschreibungIntroduction to non destructive evaluation tools and quantitative structural analyses and verifications for condition assessment of existing structures and subsequent decisions on their rehabilitation.
LernzielThe goal is for students to familiarize themselves with the handling of assessment and rehabilitation of existing structures from the perspective of a consulting engineer, following a systematic approach as described in current codes and to further learn how to use new non destructive evaluation technologies.
InhaltThis course is organized in two main pillars. The first pillar describes the technologies that are available for non destructive evaluation of structures and delves into description of the principle of operation of such methods (e.g. wave propagation, acoustic emission analysis, tomography). The second pillar, overviews the current implementation of condition assessment processes in codes and standards. Complementary to the topic of structural evaluation, the topic of interventions, rehabilitation and retrofitting of existing structures for different construction materials is next addressed.
SkriptLecture notes
LiteraturJ. D. Achenbach, Wave propagation in elastic solids, North-Holland Publishing Company, 425p, 1973
J. L. Rose, Ultrasonic Guided Waves in Solid Media, Cambridge University Press, 506p, 2014
N. Ida and N. Meyendorf, Handbook of Advanced Nondestructive Evaluation, Springer, 1617p, 2019
Swiss Standards SIA 269, 269/1 to 269/7
SIA-Document D 0239 « Existing Structures – Introduction » (in German/French)
SIA-Document D 0239 « Existing Structures – Consolidation and Practice » (in German/French)
A. Costa, A. Arêde, H. Varum, Strengthening and Retrofitting of Existing Structures, Springer, 339p, 2018
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Entscheidungsfindunggeprüft
Medien und digitale Technologiengeprüft
Problemlösunggeprüft
Projektmanagementgefördert
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgeprüft
Kundenorientierunggeprüft
Menschenführung und Verantwortunggeprüft
Selbstdarstellung und soziale Einflussnahmegeprüft
Sensibilität für Vielfalt gefördert
Verhandlunggefördert
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion gefördert
Selbststeuerung und Selbstmanagement gefördert
101-0159-00LMethod of Finite Elements II3 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:
http://www.chatzi.ibk.ethz.ch/education/method-of-finite-elements-ii.html
SkriptThe course slides serve as Script. These are openly available on: http://www.chatzi.ibk.ethz.ch/education/method-of-finite-elements-ii.html
LiteraturCourse Slides (Script): http://www.chatzi.ibk.ethz.ch/education/method-of-finite-elements-ii.html

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.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Problemlösunggeprüft
Soziale KompetenzenKooperation und Teamarbeitgeprüft
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion geprüft
101-0522-10LDoctoral Seminar Data Science and Machine Learning in Civil, Env. and Geospatial Engineering Belegung eingeschränkt - Details anzeigen 1 KP1SV. Ntertimanis, E. Chatzi, F. Corman, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, B. Soja, M. J. Van Strien
KurzbeschreibungCurrent research in machine learning and data science within the research fields of the department. The goal is to learn about current research projects at our department, to strengthen our expertise and collaboration with respect to data-driven models and methods, to provide a platform where research challenges can be discussed, and also to practice scientific presentations.
Lernziel- learn about discipline-specific methods and applications of data science in neighbouring fields
- network people and methodological expertise across disciplines
- establish links and discuss connections, common challenges and disciplinespecific differences
- practice presentation and discussion of technical content to a broader, less specialised scientific audience
InhaltCurrent research at D-BAUG will be presented and discussed.
Voraussetzungen / BesonderesThis doctoral seminar is intended for doctoral students affiliated with the Department of Civil, Environmental and Geomatic Engineering. Other students who work on related topics need approval by at least one of the organisers to register for the seminar.

Participants are expected to possess elementary skills in statistics, data
science and machine learning, including both theory and practical modelling and implementation. The seminar targets students who are actively working on related research projects.
101-0523-14LFrontiers in Machine Learning Applied to Civil, Env. and Geospatial Engineering1 KP1GV. Ntertimanis, E. Chatzi, F. Corman, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, B. Soja, M. J. Van Strien
KurzbeschreibungThis doctoral seminar organised by the D-BAUG platform on data science and machine learning aims at discussing recent research papers in the field of machine learning and analyzing the transferability/adaptability of the proposed approaches to applications in the field of civil and environmental engineering (if possible and applicable, also implementing the adapted algorithms).
LernzielStudents will
• Critically read scientific papers on the recent developments in machine learning
• Put the research in context
• Present the contributions
• Discuss the validity of the scientific approach
• Evaluate the underlying assumptions
• Evaluate the transferability/adpatability of the proposed approaches to own research
• (Optionally) implement the proposed approaches.
InhaltWith the increasing amount of data collected in various domains, the importance of data science in many disciplines, such as infrastructure monitoring and management, transportation, spatial planning, structural and environmental engineering, has been increasing. The field is constantly developing further with numerous advances, extensions and modifications.
The course aims at discussing recent research papers in the field of machine learning and analyzing the transferability/adaptability of the proposed approaches to applications in the field of civil and environmental engineering (if possible and applicable, also implementing the adapted algorithms).
Each student will select a paper that is relevant for his/her research and present its content in the seminar, putting it into context, analyzing the assumptions, the transferability and generalizability of the proposed approaches. The students will also link the research content of the selected paper to the own research, evaluating the potential of transferring or adapting it. If possible and applicable, the students will also implement the adapted algorithms The students will work in groups of three students, where each of the three students will be reading each other’s selected papers and providing feedback to each other.
Voraussetzungen / BesonderesThis doctoral seminar is intended for doctoral students affiliated with the Department of Civil, Environmental and Geomatic Engineering. Other students who work on related topics need approval by at least one of the organisers to register for the seminar.

Participants are expected to possess elementary skills in statistics, data science and machine learning, including both theory and practical modelling and implementation. The seminar targets students who are actively working on related research projects.
101-1187-00LKolloquium Baustatik und Konstruktion (Herbstsemester) Information 1 KP2KA. Taras, E. Chatzi, A. Frangi, W. Kaufmann, B. Stojadinovic, B. Sudret, M. Vassiliou
KurzbeschreibungDas Institut für Baustatik und Konstruktion (IBK) lädt Professoren in- und ausländischer Hochschulen, Fachleute aus Praxis & Industrie oder wissenschaftliche Mitarbeiter des Institutes als Referenten ein. Das Kolloquium richtet sich sowohl an Hochschulangehörige, als auch an Ingenieure aus der Praxis.
LernzielNeue Forschungsergebnisse aus dem Fachbereich Baustatik und Konstruktion kennen lernen.
InhaltNeue Forschungsergebnisse und neuartige praktische Umsetzungen aus dem Fachbereich Baustatik und Konstruktion kennen lernen.
KompetenzenKompetenzen
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Methodenspezifische KompetenzenProblemlösunggefördert
Soziale KompetenzenKommunikationgefördert
173-0007-00LDynamics Belegung eingeschränkt - Details anzeigen 6 KP13GE. Chatzi, V. Ntertimanis, P. Tiso
KurzbeschreibungThe course offers an introduction to dynamics of engineering systems. The first part focuses on Newtonian dynamics and energy principle to systems of particles and rigid bodies. The second part focuses on the free and forced response of single- and multi-degrees-of-freedom linear systems. Hands-on exercises, computer-based labs and experimental demos will support the theoretical lectures.
LernzielAfter successful completion of this course the students will be able to:
1. Set up the kinematic description of a system of particles and rigid bodies subject to constraints.
2. Formulate the governing equations of motion of a system particles or of rigid bodies using balance law.
3. Alternative from the above, the student will be able to derive the equations of motion using
Lagrange’s equations, d’Alembert’s principle, and Hamilton’s principle.
4. Find the equilibrium configurations of a given system, and perform linearization.
5. Compute the dynamic response of discrete systems to harmonic, periodic, pulse, and impulse excitation using time-history and response-spectrum methods.
InhaltDay-by-day course content:
Week 1
Day 1 – Recap on Newtonian Dynamics for single particle
Day 2 – Kinetics of systems of particles
Day 3 – Kinetics of Rigid bodies
Day 4 – Analytical mechanics

Week 2
Day 6 – Mechanical Vibrations
Day 7 – Elements of Structural Vibration - SDOF
Day 8 – Elements of Vibration Theory - MDOF
Day 9 – State Space Representations
Day 10 – Transformations
SkriptThe material will be organized in lecture slides.
LiteraturA specific list of books will be offered as useful/supplemental reading.