Mechanical characterisation of AlSi-hBN, NiCrAl-Bentonite, and NiCrAl-Bentonite-hBN freestanding abradable coatings

This paper reports recent research on abradable materials employed for aero-engine applications. Such thermal spray coatings are used extensively within the gas turbine, applied to the inner surface of compressor and turbine shroud sections, coating the periphery of the blade rotation path. The function of an abradable seal is to wear preferentially when rotating blades come into contact with it, while minimising over-tip clearance and improving the efficiency of the engine. Historically, our understanding of abradables has been limited, with their design and service operation often described as a “black art.” For instance, there is a distinct lack of materials property data for all abradable systems, mainly due to the difficulty of testing this unique class of material under bulk loading conditions (tension or compression). The present paper will describe the mechanical assessment of two families of abradables with either aluminium or nickel as the matrix phase. A novel method was developed to produce the free-standing abradable test specimens, employing thermal spraying and dissolvable moulds. These specimens were suitable for evaluation under static and cyclic tensile stress conditions. The absence of any substrate and associated mechanical interactions has meant that unique measurements of Young's modulus, tensile strength, and strain to failure were obtained for these complex composite materials in their own right. This work forms part of a wider programme to gain a greater understanding of abradable materials, how they perform, and ultimately how to improve their performance in-service. ►Proved repeatability of novel specimen manufacturing method and tensile test ►Generated tensile properties for 3 freestanding abradable coatings ►The modulus and UTS of the AlSi-based system are higher than the2 Ni-based systems ►Provided mechanical properties where none previously existed ►Measured properties will feed into computational models and material selection