Contact
Engler-Bunte-Ring 7
76131 Karlsruhe
Building number 40.13.I
Tel: +49(0)721 608-42571
Fax: +49(0)721 608-47770
E-Mail: Secretariat
Please try out our program for calculating the gas phase equilibrium state.
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Engler-Bunte-Ring 7
76131 Karlsruhe
Building number 40.13.I
Tel: +49(0)721 608-42571
Fax: +49(0)721 608-47770
E-Mail: Secretariat
Current proposals for topics of bachelor- and master thesis you find on the following page.
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A gas turbine is a combustion engine that converts the heat energy of a hot gas into mechanical energy. Gas turbines are used in engineering as drive units, e.g. for generators to produce electrical current (so-called stationary gas turbines), in power stations or as propulsion of aircraft. |
Within this research focus the following research projects are associated: |
Within the EU-H2020 project "Emissions Soot Model" (ESTiMatE), a modelling strategy will be developed to predict carbon particle (soot) emissions from the operation of aircraft engines. This requires the improvement or development of sophisticated models for the relevant sub-processes and validation using reference experiments to ensure a reliable prediction of soot emissions. The aim of the work of the Institute of Combustion Technology within the project is to generate data sets under representative combustion conditions which can be used to validate the models developed. In this respect, laminar counterflowmodel flames of a kerosene surrogate and its individual components (e.g. dodecane and iso-octane) are investigated fundamentally to explain the influence of fuel composition and pressure (up to 8 bar) on the flame structure and in particular on the formation of soot precursors [benzene (A1), naphthalene (A2), pyrene (A4), etc.] and soot particles. The data obtained are first compared with already developed chemistry models and then used to validate the models developed in ESTiMatE. The figure shows experimental and numerically calculated concentrations of gaseous species in a non-premixed counterflow flame of iso-octane. |
![]() The project is funded in the framework of Marie Skłodowska-Curie Actions as Innovative Training Network (ITN).
Air transportation is expected to grow persistently over the next decades. Clean combustion technology for aircraft engines is a key enabler to reduce the impact of this growth on ecosystems and humans’ health. The vision for European aviation is shaped by the Advisory Council for Aviation Research and Innovation in Europe in the Flight Path 2050 goals, which define stringent regulations on pollutant emissions.
To meet these goals, the major engine manufacturers develop lean premixed combustors operated at very high pressure. This development introduces a large risk for reduced reliability and lifetime of engines: pressure oscillations in the combustor called thermoacoustics.
Aviation industry encounters currently the fourth industrial revolution: cyber-physical systems analyze and monitor technical systems and take automated decisions. This industrial revolution is known as “Industry 4.0” in Germany and “Industrial Internet” in the USA. An essential enabler of the fourth industrial revolution is Machine Learning.
The ITN MAGISTER will utilize Machine Learning to predict and understand thermoacoustics in aircraft engine combustors, and to lead combustion research to a revolutionary new approach in this area. |
Within this research focus in the past the following research projects were associated: |
Improvement and optimisation of PERM system (together with AVIO, UNI FI, CIAM)
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The energy sector accounts for two thirds of the global CO2 emissions and is therefore crucial to ensure future green growth and to achieve the global emission reduction targets. Substantial reduction of CO2 emissions can only be achieved by large scale deployment of renewable energy sources, including in particular the most abundant energy sources, wind and sun. Their intermittent nature however poses significant challenges for the energy system as peak demand from the system and peak production form those intermittent sources do not overlap. As there are no large scale storage solutions available yet, other backup capacities are needed. The installed fossil capacity is large enough to provide this back-up power. However, the plants were designed for baseload operation, which results in increased wear and costs through cyclic operation and unnecessarily high emissions in the start-up phase. Providing technology upgrades to retrofit the installed power plants to enable flexible operation without penalties on life, cost and emissions is an opportunity to quickly provide the necessary backup capacity to keep the energy system stable and resilient and at the same time enabling higher renewable shares. The mission of TURBO-REFLEX is the development and optimisation of technologies, applicable to a selected set of turbomachinery engine components, which can be used to retrofit existing power plants as well as new machines in order to enable more flexible operation, providing the flexible back-up capacity needed for introducing a larger share of renewables in the energy system. TURBO-REFLEX will assess the impact of such technologies at plant level and prepare the transfer of component technology gains into reduction of both (unplanned and planned) outages and maintenance and operation costs.
The Lean Blow Off (LBO) limit is a significant hurdle to further reduce the part load of gas turbines as the operating zone of the combustor is restricted by the LBO limit. Jet stabilized premixed flames will be forecasted with blow off stability down to 1000°C–1200°C combustion temperature with or without using pilot flames. 1000°C–1200°C combustion temperature would equal emission compliant part load operation down to 20%-25%. Better blow-off stability in the combustor is a prerequisite to running higher load gradients. Therefore, it is expected that jet stabilized premixed flames with better LBO limits will allow also gradients faster than 40MW/min.
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The research carried out withing the subproject 3H contributes to the fulfillment of the projects' goal "operation flexibility and fuel flexibility". Operation stability is mainly depending on the the stability limit of combustion, which is still difficult to predict. Fuel flexibility requires the thorough design of a combustor which is able to operate on gaseous and liquid fuels. The goals of the subproject 3H, which continues the successful work of the subproject 1F stem from these requirements and challenges. |
The SOPRANO project’s main scientific objective is to make a breakthrough in the overall investigation efforts in the field of soot particles chemistry, particles size distribution (PSD), and their radiative effect on combustors typical of aero-engines. SOPRANO aims at a qualitative shift in the knowledge and experimental and numerical approaches related to the characterization and prediction of soot emission and interaction with radiative Low NOx combustor environment.
![]() The main industrial objective of SOPRANO is to carry out an in-depth characterization of soot particles emitted by a modern combustor at engine relevant operating conditions and at increased pressures to pave the way for the future design of high-performance combustors: a more accurate evaluation of the radiation effect and, therefore, a more reliable liner temperature prediction, will drive a review of the design criteria in terms of combustor air distribution and will improve durability of some key modules, e.g. the combustor’s liners. |
In the context of the objective of the German government and the European Union's energy policy, it is crucial to increase the share of renewable energy. However, due to the fect that renewable engergy production due fluctuating wind and sun energy does not correlate with the customer demand, it is neccesary to compensate this energy generation gap with flexible power plants. Such plants need to be operated in a flexible load range. In this context, gas power plants play an important role because they allow rapid load changes and provide energy at high efficiencies.
The true representation of the realistic subprocesses represent the scientific part of the project goals 1F
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