In cooperation with the Institute for Machine Tools at the University of Stuttgart, funded through the InnovationCampus Future Mobility (ICM) under a Bottom-Up grant, we are evaluating the feasibility of innovative injection concepts for liquid CO2-neutral fuels (e.g., Ammonia, SAF) that can be manufactured using additive manufacturing (PBF/LB-M).
Our research focus lies specifically on Airblast Designs. The functionality of fuel injection is achieved through stochastically distributed defects in the component, i.e. media-permeable structures. As a result, targeted geometry optimisation using CAD is not possible. Instead, the PBF/LB-M process parameters such as laser energy, scan speed, scan orientation and hatch distance must be correlated with the optimisation targets, namely droplet size and liquid loading uniformity, creating a nonlinear and complex parameter space.
Our goal is to develop a holistic optimization process that directly correlates the AM process parameters with the desired outcomes. The current research tasks include:
CAD design of innovative liquid fuel injectors optimized for AM production.
Decarbonising gas turbines with carbon-neutral fuels (e.g., hydrogen, ammonia, SAFs) is essential for future energy systems. While gaseous fuel flexibility is proven in high-momentum jet stabilised combustors, expansion to liquid-fuels face challenges in atomisation and mixing, especially in compact systems.
Our additively manufactured film-laying airblast injector overcomes these limitations. To characterise the spray performance, we employ a range of laser-based diagnostics from shadowgraphy, structured laser induced planar imaging (SLIPI) and phase Doppler interferometry. By supplying liquid fuel via innovative AM microchannels with a 50 µm slit width, thin liquid films are formed. The film atomisation, driven by aerodynamic forces, results in extremely small droplets (< 25 µm) that favour prompt vaporisation and mixing. The injector concept offers improved flame stability, symmetry, and reduced non-CO2 emissions.
Experimental investigations using AM-manufactured injectors.
The complete process, combining additive manufacturing, standardised experimental tests, and AI-driven optimization, defines a "hybrid twin" (analogous to digital twins), which can greatly accelerate the development of corresponding technologies. This innovative manufacturing process can thus increase reliability and significantly reduce production costs.
Project duration
August 1, 2023 – July 30, 2024 (expected)
Additional Information / Get Involved
If you are interested in our project, have further questions, or would like to support us through student work, internships, or thesis projects, we would be delighted to hear from you via email or phone. Contact details can be found below.
Contact
Fabian Hampp
Dr.Junior Research Group Leader