The Physical volcanology and volcanic risk class aims to provide students with an overview of processes that turn volcanic surface phenomena into potential threats to surrounding communities. Starting from field observations, the class will review how parent magma rises to the surface and identify the processes that control the behaviour of the associated phenomena (i.e., effusive vs explosive, fall vs flow etc.). Once identified, these processes will be investigated using controlled experiments in the lab and numerical modelling, and will be use to explore how and why i) natural phenomena becomes hazards and ii) how hazards become a risk to communities.
The class is split into two modules in the fall and spring semesters. In addition to the ressources in this Moodle, a lecture website is also available at https://cerg-c.github.io/CERG-C/.
Using case studies and practical exercises, we explore how theoretical, numerical and experimental modelling can be used to investigate a variety of eruptive processes. The first module introduces concepts of physical volcanology rooted in field observations and reviews how field-based studies can help characterize and classify eruptions. The second and third modules introduce components of lab experiments and numerical modeling to investigate the shortcomings identified during module 1.
Main concepts of volcanic risk reduction are introduced. Using the knowledge gained during the fall semester, this module provides an introduction to the development of eruption scenarios used in stochastic modelling to produce probabilistic hazard assessments. This hazard assessment is then used in combination with key component of risk (e.g., vulnerability, resilience) to illustrate an integrated approach to volcanic risk reduction. La Palma (Spain) is used as a case study to discuss various aspects of volcanic hazard, impact and risk assessment.
At the end of this course, students will be able to:
- characterize the dynamics of eruptions
- describe the physics of main volcanic flows
- understand the basics of numerical and experimental modelling of eruptive processes
- define the main steps of hazard assessments
- understand volcanic hazard maps
- combine the volcanic hazard, exposure and vulnerability for the assessment of risk
- identify key risk reduction strategies
- Prof. Costanza Bonadonna, University of Geneva
- Dr Sébastien Biass, University of Geneva
- Dr Lucía Dominguez, University of Geneva
- Dr Allan Fries, University of Geneva
- Dr Corine Frischknecht, University of Geneva
- Prof Chris Gregg, University of Geneva
- Dr Jonathan Lemus, University of Geneva
- The evaluation of the Fall and the Spring sessions will be combined as follows:
- Fall (50% of the final grade): exercises during lectures + reports of various activities
- Spring (50% of the final grade): written exam without notes
- Field trip validation: presentations during field trip + report of the field trip
- Teacher: Karsten Kruse
The universe is far from being homogenous, but exhibits countless patterns that are generated by sustained nonequilibrium systems. Here, a pattern refers to a state of the system that breaks certain symmetries exhibited by the underlying dynamics. Of particular interest are those patterns that persist for long times and that are stable against external perturbations. They appear in many different contexts in biology, chemistry, mathematics, physics, and other fields including engineering and social sciences. How can we describe systems that form spatiotemporal patterns? Do they fit into a common physical framework? How is a particular pattern selected among all possible patterns? Given the similarity of patterns observed, for example, in biological, chemical, and physical systems, are there general principles underlying their formation? These are some of the questions, we will discuss in this course.
After presenting a number of pattern-forming systems, we will discuss how one can derive partial differential equations that capture essential features of their behavior on macroscopic scales. We will then introduce linear stability analysis as a first approach to study the spontaneous formation of patterns. Subsequently, we will investigate the nonlinear regime and discuss stability balloons. Amplitude equations will be introduced as a means to treat the weakly nonlinear regime from which a number of generic aspects of pattern forming systems can be identified. Throughout the course, we will discuss specific examples, mostly from physics and biology, and numerical methods will be covered notably during the exercises that form an integral part of the course.
M. Cross, H. Greenside, Pattern Formation ad Dynamics in Nonequilibrium Systems, Cambridge University Press (2009)
R. Hoyle, Pattern Formation, An Introduction to Methods, Cambridge University Press (2006)
R.C. Desai, R. Kapral, Dynamics of Self-Organized and Self-Assembled Structures, Cambridge University Press (2009)
S.R. De Groot, P. Mazur, Non-Equilibrium Thermodynamics, Dover Publications, Inc., New York (1984)
S. Strogatz, Nonlinear Dynamics and Chaos, Westview Press; 2nd edition (2014)
- Teacher: Taras Holotyak
Digital forensics, as one of the distinguishable components of the modern cybersecurity, is a societally important and technically challenging research area with just growing interests in the foreseeable future. An overview of the latest achievements in the field of digital forensics will be extended with detailed studying of the selected topics of the subject and complemented by their practical investigation during practical sessions.
Programme CAFE-S : En science les maths ça compte !
Espace de cours pour les documents du stage de remise à niveau en mathématiques qui se déroule du 12 au 15 septembre.
- Teacher: Christian Wuthrich
This course provides an introduction to the history and philosophy of science. It presents the main philosophical problems and positions in the study of the natural sciences and examines key episodes in the history of astronomy, physics, chemistry and biology.
While addressing classical positions and authors in philosophy of science, such as logical empiricism, Popper, and Kuhn, we will focus on the central systematic problems of philosophy of science: the problem of induction and underdetermination of theories by empirical data, empirical evidence and confirmation of theories, Bayesian epistemology, scientific explanation and the role of laws of nature, reduction of theories, and scientific realism.
In addition, we will study the Copernican revolution, the chemical revolution, the biological revolution, the revolutions in physics in the early 20th century, as well as the philosophical issues arising from these historical developments in the natural sciences.
This course will be held in English.