Stellenangebote
Bachelor- und Masterarbeiten
Master Thesis - Efficiency and redundancy of power flow patterns in the European electricity network
Background:
Measures from information theory allow the quantification of efficiency as well as redundancy in networks with directed transport. The application of these measures to ecosystems, for example, shows that above a certain system size the ratio of efficiency to redundancy seems to concentrate in a small range of values, which raises the question of whether there is a connection between the classification in this range of values and the stability of the system.
In the proposed Master Thesis this relation between efficiency and redundancy is studied for power flow patterns in the European electricity system. In the interconnected European power grid, nodal imports and exports result in power flows connecting different regions both on a national and international scale. The basis for the thesis work are time series for imports, exports, and power flows, which are analyzed using measures from information theory to assess efficiency and redundancy of flows as a transport mechanism in this system. The analysis considers direct physical flows between neighboring regions, as well as distributed bilateral import-export relationships derived from flow allocation methods. The research studies how efficiency and redundancy depend on different system characteristics for current and future electricity systems and discusses the applicability of these measures for energy system analysis.
Tasks:
The following tasks are subject of the proposed topic:
- Familiarization with data format of power flow patterns in the European electricity system
- Application of information theoretic measures to the available data, characterizing efficiency and redundancy
- Comparison of measures for neighboring as well as distributed import-export relationships
- Comparison of current and future electricity system scenarios in view of efficiency and redundancy
- Discussion of the informative value of these measures for energy system analysis, as a basis for optimization of the latter
Your profile:
- You are a student of SSE, general engineering, physics, mathematics, or computer science
- Highly interested in theoretical models and techniques to study energy systems
- Programming skills (e.g. in Python) welcome (but not mandatory)
What you can expect:
- Novel theoretical approaches in an interdisciplinary research environment
- Data from cutting edge energy system models
- Creative freedom in combination with intense support
Dates:
- Start date: as soon as possible
- Duration: According to examination regulations (typically 6 months)
Contact:
- Prof. Dr. Alexander Stolz, Resilience Engineering for Technical Systems
alexander.stolz@inatech.uni-freiburg.de
- Dr. Mirko Schäfer, Control and Integration of Grids
mirko.schaefer@inatech.uni-freiburg.de
MASTER THESIS - SUSTAINABLE BUILDING MATERIALS: HYBRID ORGANIC CONCRETE
The Professorship for Resilience of Technical Systems and the Professorship for Sustainable Systems Engineering offer an Experimental Student Thesis (Master)
Background
The global construction Industry accounts for 38% of total global CO2 emissions. 8% of these are solely due to production of concrete. Within the construction industry one of the basic building elements are concrete bricks. Its production accounts for 3% CO2 emission worldwide every year (5% by total cement). These numbers need to be reduced.
One way of achieving reduced emissions is to lower the cement content by using composite materials. Fungae offer one promising direction and substantial research is carried in this field, in particular for Mycelium. Mycelium is the mass of branched fibers (hyphae) comprising the vegetative part of a fungus. These hyphae can grow on various substrate materials such as wood chips, agricultural wastes, manure, soil, sand, etc.
Mycelium has many positive characteristics such as being light weight, water repellent, and good thermal insulators. Mycelium is also biodegradable rendering it a promising candidate for the use in the building sector.
Nevertheless, pure Mycelium materials developed so far do not show sufficient strength and stiffness characteristics for a wide range application in the building sector.
Hence, using a mycelium-cement hybrid brick could provide many benefits along with reduction of cement production. This Master thesis establishes key characteristics of such a material.
Tasks
Within the context given, the master thesis will elaborate the following tasks based on progress of the different steps:
- Derive a working recipe for a mycelium concrete brick, based on literature review
- Grow mycelium and experimentally derive single mycelium fibre strength parameters
- Make mycelium/cement hybrid bricks with different amounts of mycelium fibres
- Conduct static testing of the fabricated bricks to derive material characteristics strength in compression, tension and bending and the corresponding bulk modulus’ as well as ductility of the material.
- Optimize material in terms of most CO2 in combination with material strength
Your profile
- You are a student of SSE or physics, biology or general engineering
- The topic of sustainable materials is highly motivating for you
- You are interested in the combination of theoretical models and practical test and laboratory work
What you can expect
- Exciting fundamentally new research with insights into cross-institute collaborations
- Creative freedom with respect to the content of the work and intensive support
Dates
Starts: As soon as possible
Duration: According to examination regulations, typically 6 months
Contact Persons
Prof. Dr. Alexander Stolz
alexander.stolz@inatech.uni-freiburg.de
Dr. Georg Ganzenmüller
georg.ganzenmueller@inatech.uni-freiburg.de
SAFETY ANALYSIS OF AUTONOMOUS DRIVING BY MARKOV MODELING
Experimental Student Thesis (Master)
Background
Autonomous driving functions up to SAE Level 3 and even more so in the future up to Level 5 place enormous demands on the safety case, since numerous possible scenarios must be evaluated in terms of safety.
Task
In the context of a larger national research project, the master thesis will use advanced vehicle system-level Markov models and simulations to identify critical scenarios, overall system state transitions and sequences. The objective is to provide a scalable and adaptable modeling and simulation to control state explosions. At the same time, the goal is to go far beyond the classical Markov assumption that overall system state transitions depend only on the current state and are time-independent.
Planned Tasks
- Literature research on Markov modeling previously used for safety assessment of autonomous driving
- Systems Modelling Language (SysML) model development of a generic vehicle architecture including driver, environment and other road users
- Development of a scaling Markov diagram modeling based on the vehicle architecture
- Transition, failure and recovery modeling and their parameterization
- Markov simulation using different numerical methods in comparison, also combined and nested, to determine safety parameters
- Evaluation of the feasibility, scalability and quality of the results with regard to possible key statements
What you bring with you
- You are perusing a scientific university degree (Bachelor, Diploma or Master) in applied engineering or natural sciences, or in a comparable field (MINT subjects)
- You have elementary knowledge in solving matrix equations (inversion of a matrix) and partial differential equations
- You have first experiences in a programming language, e.g. Python, C++
- Knowledge of system modeling in a sub-discipline or of technologies relevant to autonomous driving would be an advantage
- With your independent and structured way of working you enrich the interdisciplinary team of our department
What you can expect
- We are committed to excellent supervision and comprehensive training, while at the same time giving you a great deal of freedom to shape contents and implementations
- You be part of an interdisciplinary team of scientists from a wide range of disciplines
- We have a very good office atmosphere in a modern working environment with excellent IT infrastructure and technical equipment of laptops and workstations
Starts: As soon as possible
Timeframe: According to examination regulations
More topics on request
Contact
Prof. Dr. Alexander Stolz
alexander.stolz@inatech.uni-freiburg.de
Resilience Engineering for Technical Systems| INATECH RTS
Faculty of Engineering | University of Freiburg
Dr. Ivo Häring
COOPERATIVE MASTERTHESIS:
INVESTIGATION OF THE POTENTIAL FOR AUTOMATED RESILIENCE ANALYSIS OF IT INFRASTRUCTURES
Professorship: Prof. Alexander Stolz (Universität Freiburg, D) and Client: CuriX AG
Initial situation:
The existing software solution CuriX collects automatically measurement data (e.g. CPU utilization, free memory on hard disks, failed login attempts) and structural data (e.g. operating systems used, persons responsible, services provided) from IT infrastructures. The data is analyzed using various methods (e.g., statistical methods, machine learning, static analysis methods) to alert users on impending problems (e.g., system failure). Currently, these predictions are communicated as raw alerts (e.g., email, alert icon in the user interface) without any relation to resilience.
In the future, the alerting functionality of CuriX should enhanced in the way that problems should be placed in the context of resilience, e.g. by grouping similar alerts to resilience incidents or issues. This should enable the user (i.e., typically the IT administrator) to derive and implement measures that can increase the resilience of the IT infrastructure.
Goal of the Master:
The existing and planned functionalities for CuriX-software should be analyzed and evaluated with regard to the existing taxonomy of resilience research.
For example, it is planned to classify upcoming bottlenecks in the free memory on a hard disk into the category "resource bottleneck"; here, among other things, existing categorizations are to be assigned or elaborated. Likewise, anomalies in the system are analyzed, which are to be brought into the context of resilience. CuriX AG would like to follow existing glossaries of resilience research and use terms from or the vocabulary of resilience research for the software.
Key task is to investigate and evaluate the extent to which automated statements can be made about the resilience of IT infrastructures. It is planned to investigate two dimensions:
- Generic or generally valid statements: Assuming that the structure of IT infrastructures is known and sufficient measurement data is available, the aim is to investigate which and how generally valid statements about the resilience of IT infrastructures can be derived automatically. E.g., an indication of whether a higher homogeneity/heterogeneity of the operating systems used is more favorable or less favorable.
- Regarding given resilience goals: it should be investigated which statements about resilience (e.g. a resilience score) and resilience-increasing measures can be made and how.
Within the scope of the work, statements are to be verified experimentally (by means of existing or to be developed software components and existing IT infrastructure).
For both dimensions, preconditions are to be worked out that must be fulfilled in order to be able to make statements, e.g. which information on technology, organization, training, budget must be available.
Organisation:
The work takes place as a cooperative work with CuriX AG.
The student will have a temporary contract for the duration of the Master work.
Starts: As soon as possible
Timeframe: According to examination regulations
More topics on request
Contact
Prof. Dr. Alexander Stolz
alexander.stolz@inatech.uni-freiburg.de
Resilience Engineering for Technical Systems| INATECH RTS
Faculty of Engineering | University of Freiburg
CuriX AG:
Dr. Uli Siebold
Head of Research | CuriX AG (Pratteln, Switzerland)
Experimental Student Thesis (Master) zum Thema RESILIENTES PATH-FINDING FÜR AGENTENBASIERTES MODELLIEREN
Agentenbasierte Modelle (ABM) mit individuell agierenden Agenten sind vor allem auf zwei Algorithmen angewiesen: das Path-Finding und die Kollisionsvermeidung. Besonders der Path-Finding Algorithmus hat einen großen Einfluss auf die Simulation und vor allem die benötigten Ressourcen, da er bei jeder Berechnung einer Route für jeden Agenten aufgerufen werden muss. D.h. die Dauer der Simulation hängt von der Anzahl an Agenten ab und der Effizienz des Path-Findings. Der bevorzugte Weg vom Standort eines Agenten zu einem bestimmten Ziel ist eine gerade Linie. Liegen allerdings Hindernisse auf diesem Weg, gibt es viele verschiedene Möglichkeiten einen geeigneten Weg zu finden. Ein Vergleich existierender Algorithmen wird angestrebt und die Idee eines resilienten Path-Findings wird untersucht. Das Ziel dieser Masterarbeit ist es zu bestimmen was einen Path-Finding Algorithmus resilient macht gegenüber diversen Hindernissen, die sich z.B. in Größe, Form, Position und Zeit verändern. Außerdem soll untersucht werden wie die Leistung des Algorithmus quantifiziert werden kann abgesehen von seiner Schnelligkeit. Szenarien werden entwickelt (z.B. mehrere aufeinandertreffende Menschenmassen) um den Algorithmus zu testen, welche anhand von frei verfügbaren Daten validiert werden sollen. Die generelle Ausrichtung der Arbeit kann individuell gestaltet werden. Eine mögliche Ausrichtung könnte sein, dass selbstlernende Ansätze untersucht werden um Path-Finding Algorithmen zu verbessern.
Voraussetzungen:
- Studium in einem technischen oder naturwissenschaftlichen Fach, z.B. Informatik, Mathematik, Ingenieurwissenschaften, Physik, Mediendesign
- Gute Programmierkenntnisse (z.B. C++, Java, Python)
- Interesse an Programmierung und Softwareentwicklung für relevante wissenschaftliche Fragestellungen
Starts: As soon as possible
Timeframe: According to examination regulations More topics on request
Contact: Prof. Dr. Alexander Stolz, alexander.stolz@inatech.uni-freiburg.de
STUD. HILFSKRAFT (m/w/d) IM BEREICH
DER DATENANALYSE UND RESILIENZFORSCHUNG
Die Fraunhofer-Gesellschaft (www.fraunhofer.de) betreibt in Deutschland derzeit 76 Institute und Forschungseinrichtungen und ist die weltweit führende Organisation für anwendungsorientierte Forschung. Rund 30.000 Mitarbeitende erarbeiten das jährliche Forschungsvolumen von 2,9 Milliarden Euro.
Das Fraunhofer-Institut für Kurzzeitdynamik, Ernst-Mach-Institut EMI, in Freiburg mit seinen 300 Mitarbeitern*innen bietet engagierten Menschen anspruchsvolle und abwechslungsreiche Aufgaben mit Verantwortung sowie viel Gestaltungsspielraum. Im Auftrag unserer Kunden aus den verschiedensten Bereichen von Wirtschaft und Staat wenden wir neueste Erkenntnisse aus Wissenschaft und Forschung interdisziplinär auf konkrete Projekte an. Die Anwendungen liegen in den Bereichen Verteidigung, Sicherheit, Raumfahrt, Automotive und Luftfahrt.
Für unseren Institutsstandort Standort Freiburg und/ oder Efringen-Kirchen suchen wir in der Abteilung Sicherheit und Resilienz Technischer Systeme zum nächstmöglichen Zeitpunkt eine studentische Hilfskraft (m/w/d) im Bereich der Datenanalysen und Resilienzforschung.
Was sie bei uns tun
Hintergrund:
Die Gruppe Robustheits- und Resilienzanalysen beschäftigt sich aktuell in einem nationalen Forschungsprojekt mit der Entwicklung eines Datenraums zur Bewertung der Krisenfestigkeit und Resilienz von Kommunen. In enger Zusammenarbeit mit verschiedenen Städten und Landkreisen werden vielfältige Datenquellen herangezogen und ausgewertet um mögliche Kausalitäten für die Anwendungsfälle Extremwetter und Pandemie zu identifizieren sowie entsprechende Schutzmaßnahmen abzuleiten.
Aufgabenstellung:
- Literaturrecherchen im Bereich Katastrophenschutz, kommunales Krisenmanagement, Resilienzbewertung
- Sichtung und Auswertung verschiedener Datenquellen
- Anwendung statistischer Methoden zur Datenanalyse
- Dokumentation von Ergebnissen
Was sie mitbringen
- Studium im Bereich der Mathematik, Physik, Informatik, Ingenieurwissenschaften oder einem vergleichbaren Fachgebiet
- Interesse an innovativen Methoden der Datenanalyse und Datenräumen
- Engagiertes, selbstständiges, ergebnis- und teamorientiertes Arbeiten
- Gute Deutschkenntnisse
- Interesse an längerfristiger Zusammenarbeit
Was sie erwarten können
- Exzellente technische Ausstattung der Labore und Arbeitsplätze
- Abwechslungsreiche Aufgaben in exzellenter Forschungsumgebung
- Eine gründliche Einarbeitung und Betreuung der Arbeit
Wir wertschätzen und fördern die Vielfalt der Kompetenzen unserer Mitarbeitenden und begrüßen daher alle Bewerbungen – unabhängig von Alter, Geschlecht, Nationalität, ethnischer und sozialer Herkunft, Religion, Weltanschauung, Behinderung sowie sexueller Orientierung und Identität. Schwerbehinderte Menschen werden bei gleicher Eignung bevorzugt eingestellt.
Mit ihrer Fokussierung auf zukunftsrelevante Schlüsseltechnologien sowie auf die Verwertung der Ergebnisse in Wirtschaft und Industrie spielt die Fraunhofer-Gesellschaft eine zentrale Rolle im Innovationsprozess. Als Wegweiser und Impulsgeber für innovative Entwicklungen und wissenschaftliche Exzellenz wirkt sie mit an der Gestaltung unserer Gesellschaft und unserer Zukunft.
Haben wie Ihr Interesse geweckt? Dann bewerben Sie sich jetzt online mit Ihren aussagekräftigen Bewerbungsunterlagen. Wir freuen uns darauf, Sie kennenzulernen!
Dr.-Ing. Kai Fischer, Fraunhofer EMI, kai.fischer@emi.fraunhofer.de