To provide a joint basis of knowledge and team spirit in the project, six training events are organized for project-wide training in important scientific aspects of the projects, engaging the world’s best experts in the field.
The registration for the Workshop B In Toulouse in April 2019 will open soon.
Workshop B: CFD for spray flame simulations.
CERFACS in Toulouse will organise a 4-day workshop to train students on the LES technique for the simulation of spray injection, atomization, evaporation and combustion in transient turbulent reacting flows. This involves mesh generation and quality, discretisation schemes, initial and boundary conditions as well as turbulence modelling, combustion and two-phase flow. Classes and courses will be accompanied by hands-on sessions using the codes of CERFACS (AVBP/AVTP/PRISSMA).
Workshop C: Soft skills, ethics, intellectual property rights and management.
In Munich workshop C will be organized jointly by TUM and GEDE. Experts of GEDE and TUM will provide lectures on intellectual property rights and management, including the GE Fastworks method. Good management, job and personal performance and satisfaction rely heavily on knowledge of ethics and on soft skills. Therefore these will be lectured thoroughly in the 4-day workshop.
Workshop D: Measurements in spray flames in aircraft type combustors.
At the Karlsruhe Institute of Technology (KIT) a 4-day workshop will be organized on the laser diagnostic equipment available for measurements of the properties of liquid and gas fields. World-class experts will provide lectures and hands-on demonstrations will be given on the spray test rigs at KIT. Data management is very important, and therefore instruction will be given on project-wide data storage and consistency of generated data.
Symposium: Aero Gas Turbine Engine Combustion Dynamics and Acoustics: Prediction and Remedy.
For academic training, apart from visiting conferences, the team of ESRs will organize an international symposium on the MAGISTER theme: “Aero gas turbine engine Combustion Dynamics and Acoustics: Prediction and Remedy”. This will take them through all the details of a conference procedure. Very important is the additional outreach and dissemination that is reached through the symposium. The output and results that are open to the public can be presented for wider use within European industry. Location of the event will be Munich at the GEDE/TUM facilities.
When Yuri Gagarin was launched into orbit in 1961, the probability of a rocket blowing up on take-off was around 50%. In those days, one of the most persistent causes of failure was a violent oscillation caused by the coupling between acoustics and heat release in the combustion chamber. Today, such “ thermoacoustic” oscillations still represent a very significant challenge for the development of rocket and gas turbine engines and are being studied extensively.
The ultimate goal of rocket and gas turbine manufacturers is to eliminate or control thermoacoustic oscillations, either through feedback control or passive control. For most applications passive control - either by good initial design, or by adding a passive device to an existing system - is preferable.
In order to control a thermoacoustic system passively, it is necessary to understand why the system oscillates. It is well known that acoustic perturbations to the velocity or pressure cause heat release perturbations some time later, and that these lead to the feedback loop described above. Other mechanisms, such as the reflection of entropy waves at a sonic throat, are also known. However, experiments show that even small changes to a system can significantly alter its stability, showing that the details of these processes are very influential.
The aims of this course are: to describe how thermoacoustic oscillations arise, to show the acoustics-flow-flame interactions that cause fluctuating heat release, to show how these details are uncovered through experimental measurements or high fidelity simulations, to introduce linear and nonlinear methods of stability analysis and to give examples of these processes in industrial combustion systems, in particular aero engine combustors.
WORKSHOP A: WORKSHOP ON PROBABILISTIC MACHINE LEARNING
Models may originate from different sources, such as (i) first principles - e.g. Newtonian mechanics or (ii) observations - e.g. the annual production of timber per hectare of forest, and its dependency on geographical and climatic factors. Most practical models lie somewhere between these two examples, involving both first principles and data. Machine learning is a broad term which covers the theory and practice of mathematical models that rely on data.
Probabilistic models may use priors to express knowledge or beliefs about aspects of the model. Simplifying assumptions often facilitate use of the model, but the conclusions drawn from a model are conditional on the assumptions being valid. Practical modelling is therefore always a trade-off between model expressivity and computational simplicity.
The specification of a model includes the complete structure as well as all assumptions (and priors) used as well as any pre-specified parameters. In practice, we need to be able to (i) treat the unobserved quantities (training); (ii) make predictions on test cases; (iii) interpret the trained model; (iv) evaluate the accuracy of the model; (v) choose between different models. All these tasks need to be solved either exactly or approximately, on a given budget of computation and memory.
This workshop will be an introduction to Probabilistic Machine Learning, which is one approach to the above tasks.
The other training events will be organised in 2019-2020