-
targets the development of advanced coatings to prevent cell-to-cell propagation during runaway events. It combines experimental studies, numerical modelling, and real-world burner rig testing, culminating
-
equivalent in a relevant discipline such as aerospace engineering, or mechanical engineering. Prior experience in numerical fluid dynamics particularly in turbomachinery, multi-phase flows is beneficial
-
operation costs significantly. Besides, there is an opportunity to explore the commercialisation paths of the developed smart sensor prototype. You will gain from the experience in numerous ways, whether it
-
deploy these technologies in the industry context without the need for big datasets. You will gain from the experience in numerous ways, whether it be transferable skills in the technical area of
-
, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
-
utilise numerical techniques including the finite element method to describe biofluid flow and deformation in the human brain tissue. Parameters are inferred from clinical data including medical images
-
advanced simulation methods, including Reynolds-Averaged Navier-Stokes (RANS), Direct Numerical Simulations (DNS), and/or Large Eddy Simulations (LES), will be employed to accurately model the complex flow
-
cyclic loading, varied surface conditions, and exposure to gaseous impurities, and advanced numerical modelling (Finite Element Analysis), this project aims to significantly enhance our understanding