The Doctoral School of Engineering and Science
Aalborg University
Ph.D. Summer School 2023
Power Electronics for Green Transition (PEGT)
Power electronics play an underpinning role in green transition in a wide range of applications and it is the main energy processing unit in e-transportation, renewable energies, power to gas systems, electric power grid applications, motor drives, etc., and are becoming the key elements of the green transition. This summer school aims to give hands-on experience on different fundamental and technical aspects of power electronics engineering from design to operation and from the device level up to the power-system level in several applications, including e-transportation, renewable energies, energy storage, power grid applications, and microgrids. This year, the school is planned from August 21nd to 25th 2023 (from Monday to Friday). More info at www.energy.aau.dk/pegt (available soon).
Targeted participants are Ph.D. candidates, PostDocs, and industrial engineers.
The summer school will feature:
· An opening speech, given by Prof. Frede Blaabjerg;
· A series of sixteen 45-min long lectures (total ~12 hours of theory), given by experts in renewable energy from both AAU Energy and other universities/industrial companies;
· Three inspiring invited talks given by experts from the industry;
· Four 6-hours long practice sessions, hosted at the Power Electronics and the Reliability Laboratories at AAU energy;
· A City-walk event through Aalborg downtown;
· An excursion to an exciting company and historical venue
The fee per person includes:
12 hours of lectures (16 x 45 min) from the principles to the emerging topics:
L1. Frede Blaabjerg (AAU Energy): Opening – introduction to the role of power electronics in green transition |
L2. Huai Wang (AAU Energy): Reliability software & condition monitoring |
L3. Norbert Hanigovszki (Danfoss): Smart motor drive |
L4. Tamas Kerekes (AAU Energy): Current control of grid-connected converters |
L5. Francesco Iannuzzo (AAU Energy): Power devices & test-for-reliability opportunities at the X-Power center |
L6. Pooya Davari (AAU Energy): EMI/EMC in Power Electronics: Part 1 |
L7. Pooya Davari (AAU Energy): EMI/EMC in Power Electronics: Part 2 |
L8. Tamas Kerekes (AAU Energy): Harmonic compensation |
L9. Erik Schaltz (AAU Energy): Power electronics for e-transportation |
L10. Heng Wu (AAU Energy): Stability studies of power electronic dominated power system: an overview |
L11. Heng Wu (AAU Energy): Transient stability analysis of inverter-based resources |
L12. Subham Sahoo (AAU Energy): Cybersecurity in power electronics systems |
L13. Abhijit Kulkarni (AAU Energy): Hardware design of Smart Battery |
L14. Shuai Zhao (AAU Energy): AI& data analytics in power electronics systems |
L15. Rui Wu (Vestas): Design Failure Mode and Effect Analysis for Power Electronics |
L16. Mostafa Abarzadeh (SmartD Technologies): High power density high efficiency WBG based converters for variable frequency drive applications |
6 hours of hands-on workshops (4 x 1.5 hours):
W1. hands-on workshop on Design and practical implementation for CC in PV systems
W2. hands-on workshop on Design and practical implementation for HC in PV systems
W3. hands-on workshop on Reliability of power electronics converters
W4. hands-on workshop on AI and its application in power electronics
Organizer: Saeed Peyghami, Assistant Professor, sap@energy.aau.dk
Payment: Registration fee for Danish PhD students = DKK 0
Registration fee for non-Danish PhD students is EUR 800. Registration fee for other participants is EUR 1067.
Reception, city walk and excursion are also free of charge.
All participants must pay for catering - see the link to payment below:
Please remember to sign up below and also pay for the catering at the link above.
- Teacher: Saeed Peyghami
Description:
Computational fluid dynamics (CFD) computer codes have become an integral part of the analysis and scientific investigation of complex systems. Unfortunately, inherent in the solutions from simulations performed with these computer codes is error or uncertainty in the results. Validation of numerical model using experimental model can help to better unwrap this issue, nevertheless also experimental modelling are affect by errors and thus uncertainty. The issue of numerical and experimental uncertainty addresses the development of methods to define the magnitude of error or to bound the error in a given range.
In the course we will have investigate the status of methods for evaluation of numerical and experimental uncertainty, and provides a direction for the effective use of some techniques in estimating uncertainty.
Organizer: Francesco Ferri
Lecturers: Francesco Ferri, Morten Kramer
ECTS: 4.0
Place: Aalborg, Department of the Built Environment
Number of seats: 24
Deadline: August 1, 2023
Payment: Registration fee for Danish PhD students = DKK 0
Registration fee for non-Danish PhD students is EUR 800. Registration fee for other participants is EUR 1067.
Reception, city walk and excursion are also free of charge.
All participants must pay for catering - see the link to payment below:
Please remember to sign up below and also pay for the catering at the link above.
- Teacher: Francesco Ferri
The Doctoral School of Engineering and Science Aalborg University
Ph.D. Summer School 2023
Perspectives of Plastics Recycling
The aim is to provide the PhD student with a broad insight in recycling plastics. This course will cover selected aspects shown in detail below. This second year of the summer school bioconversion is included.
The plastics consumption is more than 300 mill. ton annually. This is around 10% of the oil and it contribute to landfill, ocean waste, increasing the amount of microplastics in the environment and carbon dioxide emissions. It is possible to recycle plastics fully (reuse, refurbish, recycle mechanically and chemical). To transform the current plastics, use towards recycling there are several barriers to overcome.
This year, the school is planned from August xxnd to xxth 2023 (from Monday to Friday). Targeted participants are Ph.D. candidates, Postdocs, and industrial engineers.
The summer school will feature:
· An opening speech, given by Prof. Jesper de Claville Christiansen.
· A series of sixteen 45-min long lectures (total ~12 hours of theory), given by experts in fields of mechanical and chemical recycling, bioconversion, supply chain and strategic risks and opportunities adapting a cyclic material strategy.
· Three inspiring invited talks given by experts from the industry. (Quantafuel, Makeen Energy and LEGO)
· Four 6-hours long practice sessions, hosted by 3 different laboratories at AAU.
· A City-walk event through Aalborg downtown.
· An excursion with a combination of exciting companies and a historical venue
Tentative lectures will be announced asap.
Reception on Monday: Monday evening at 19:00 hrs. there will be a small reception with snacks at the cantina at Kroghstræde 3.
Refreshments:
· Coffee, tea and rolls for each day at 08.30 (outside the location of the course).
· Coffee, tea and cake Monday, Tuesday and Thursday at 13:15 (outside the location of the course)
· Cantina at Kroghstræde 3 for lunch Monday, Tuesday and Thursday (11..45 – 12.45)
Friday there will be sandwiches/water outside the lecture room.
Excursion: The excursion will be announced asap
Organizers: Professor Jesper de Claville Christiansen, jc@mp.aau.dk. Professor Brian Vejrum Wæhrens, bvw@mp.aau.dk. Associate Professor Thomas Helmer Pedersen, thp@energy.aau.dk.
Payment: Registration fee for Danish PhD students = DKK 0
Registration fee for non-Danish PhD students is EUR 800. Registration fee for other participants is EUR 1067.
Reception, city walk and excursion are also free of charge.
All participants must pay for catering - see the link to payment below:
Please remember to sign up below and also pay for the catering at the link above.
- Teacher: Jesper de Claville Christiansen
- Teacher: Thomas Helmer Pedersen
- Teacher: Cristiano Varrone
- Teacher: Brian Vejrum Wæhrens
Course: Microscopy and Spectroscopy Characterization Methods
Organiser: Dr. Vladimir Popok, e-mail: vp@mp.aau.dk
Lecturers: Vladimir Popok, MP; Peter Fojan, MP; Leonid Gurevich, MP; Lars Diekhöner, MP; Mikael Larsen, MP; Lars Rosgaard Jensen, MP; Esben Skovsen, MP; Reinhard Wimmer, BIO.
ECTS: 3.0
Time: week 34 (21-25 August) 2023
Place: Aalborg University: Skjernvej 4A, Fibigerstræde 14, Fredrik Bajers vej 7
Number of seats: 15
Description: Characterization methods are important for many applied oriented projects. In this course, principles of operation and applicability of several microscopy and spectroscopy techniques to investigation of different materials including bio- and nanoscale objects will be overviewed. The course is developed at a level suitable for the participants with different background (physics, chemistry, biology, medicine, mechanical/materials/electronic engineering and similar). Essential part of the course will be hands-on training using particular microscopy and spectroscopy tools. The participants can prioritise up to 3 methods of interest for the hands-on training. The course is divided into six themes.
Theme 1: Electron and X-ray diffraction (L. Diekhöner)
- Brief summary of crystal structure and reciprocal lattice;
- Short theoretical background on wave diffraction and crystal structure determination;
- Principles and examples of experimental diffraction techniques: X-ray diffraction (XRD) and low energy electron diffraction (LEED);
- Hands-on training.
Theme 2: Scanning electron microscopy (SEM) and X-ray microanalysis (L. Gurevich, M. Larsen)
- Physical background: Interaction of electromagnetic radiation and electrons with matter. Physical techniques for elemental analysis;
- SEM, energy dispersive X-ray spectroscopy (EDS) and electron backscatter diffraction (EBSD): Interaction of electrons with matter, image formation, hardware;
- Selected applications: environmental SEM and life science applications;
- Hands-on training.
Theme 3: Scanning probe microscopy (SPM) (V. Popok and P. Fojan)
- Short historical introduction about invention of different SPM modes;
- Principles and technical realisation of atomic force microscopy (AFM);
- Advanced (electric, magnetic, etc.) SPM modes;
- Hands-on training in AFM.
Theme 4: Infrared (IR) and Raman spectroscopy (L.R. Jensen)
- Introduction to IR absorption, Rayleigh and Raman scattering;
- Instrumentation in Fourie transform IR and Raman spectroscopy;
- Applications;
- Hands-on training.
Theme 5: Terahertz (THz) spectroscopy (E. Skovsen)
- Introduction to terahertz spectroscopy;
- Time-domain THz spectroscopy (THz-TDS) and applications of THz-TDS;
- Frequency-domain THz spectroscopy (THz-FDS) and applications of THz-FDS;
- Brief introduction to THz imaging;
- Hands-on training.
Theme 6: Nuclear Magnetic Resonance (NMR) (R. Wimmer)
- Short theoretical background of NMR;
- Information content of NMR spectra;
- Different types of NMR spectra and limitations;
- Cases;
- Hands-on training.
Payment: Registration fee for Danish PhD students = DKK 0
Registration fee for non-Danish PhD students is EUR 800. Registration fee for other participants is EUR 1067.
Reception, city walk and excursion are also free of charge.
All participants must pay for catering - see the link to payment below:
Please remember to sign up below and also pay for the catering at the link above.
- Teacher: Lars Diekhöner
- Teacher: Peter Fojan
- Teacher: Leonid Gurevich
- Teacher: Lars Rosgaard Jensen
- Teacher: Mikael Larsen
- Teacher: Vladimir Popok
- Teacher: Esben Skovsen
- Teacher: Reinhard Wimmer
Statistical design of experiments
Almost any experiment implies investigation of how various factors and experimental conditions influence outcomes of the experiment. This can be quite challenging especially if there are more than just 1-2 factors and when the factors influence each others effects. This course will show how to plan such experiments properly, carry out the experimental runs, and analyse the results, so at the end you get a reliable and reproducible knowledge about combination of the most important factors and their values, which give the best outcome or the desirable effect. You will learn necessary theoretical background and implement main methods in R by creating your own DoE toolbox. You will also have a chance to try these methods on several small real projects we will be working on during the course.
Organizer: Associate Professor Sergey Kucheryavskiy, email: svk@bio.aau.dk
Time: August 21 - 25, 2023
Place: Aalborg University, room to be announced
Zip code: 9220
City: Aalborg
Number of seats: 25
Deadline: August 1, 2023
Payment: Registration fee for Danish PhD students = DKK 0
Registration fee for non-Danish PhD students is EUR 800. Registration fee for other participants is EUR 1067.
Reception, city walk and excursion are also free of charge.
Payment: Registration fee for Danish PhD students = DKK 0
Registration fee for non-Danish PhD students is EUR 800. Registration fee for other participants is EUR 1067.
Reception, city walk and excursion are also free of charge.
All participants must pay for catering - see the link to payment below:
Please remember to sign up below and also pay for the catering at the link above.
- Teacher: Sergey Kucheryavskiy
The summer school will consist of three interconnected parts. The first part will review some of the fundamental mathematical tools which are needed in order to understand the reason for why approximation with neural networks works. The second part will take this further and investigate in more detail what are the best rates of convergence for a given data. The third part will focus on some concrete neural networks and their implementation, and also make the connection with other approximation methods used in Topological Data Analysis. Here are some more details:
Part 1: The basic mathematical concepts behind the approximation of continuous functions with neural networks. The main reference is the paper
H.N. Mhaskar: Approximation properties of a multilayered feedforward artificial neural network. Advances in Computational Mathematics 1, 61-80 (1993). Link: https://link.springer.com/article/10.1007/BF02070821
Very roughly said, one of the main results we will prove here states that any ”nice” function can be arbitrarily well approximated by a neural network which has at least one hidden layer, provided that the hidden layer consists of sufficiently many neurons and the activation function is either a sigmoid or a ReLU. In order to ease the understanding of the arguments, we will review/explain/motivate a few fundamental ingredients like the convergence of discrete Fourier series and the Taylor formula with remainder.
Part 2: General approximation with
deep neural networks. The main reference is the paper Approximation
Spaces of Deep Neural Networks, Constructive Approximation (2021), https://doi.org/10.1007/s00365-021-09543-4.
We will review some classical results in (nonlinear) approximation theory with
a particular focus on spline approximation. Based on this, we are going to
measure a network’s complexity by its number of connections or by its number of
neurons, and consider the class of functions for which the error of best
approximation with networks of a given complexity decays at a certain rate when
increasing the complexity budget. It will be shown that some functions of very
low smoothness can nevertheless be well approximated by neural networks, if
these networks are sufficiently deep.
Part 3: Neural networks and clustering
algorithms in Python. The main references are Deep Learning with
PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann, and Persistence
Theory: From Quiver Representations to Data Analysis by Steve Y. Oudot.
These lectures target newcomers in machine learning and AI. We will in a first
part learn how to use Python and its library Pytorch to import data in a
suitable format. We will then show on various examples how to implement several
neural networks, including the ones viewed in the past lectures. In a second
part, we will review some clustering algorithms and show how mathematical
topology may be used to improve existing clustering methods by determining the
number of clusters or improve robustness against noise. To that end we will
present the ToMaTo algorithm and illustrate its use on several datasets using
the Python’s library GHUDI.
Prerequisites: Basic knowledge in mathematics and
statistics given by standard courses like Calculus and Linear Algebra. Also,
the student is expected to be familiar with (but not expert in) concepts like
continuity, differentiability, convergence of series, metric spaces, abstract
vector spaces.
Payment: Registration fee for Danish PhD students = DKK 0
Registration fee for non-Danish PhD students is EUR 800. Registration fee for other participants is EUR 1067.
Reception, city walk and excursion are also free of charge.
All participants must pay for catering - see the link to payment below:
Please remember to sign up below and also pay for the catering at the link above.
- Teacher: Horia Cornean