Browsing by Author "Kruzic, JJ"

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    The effect of microstructure and welding-induced plasticity on the strength of Ni–Mo–Cr alloy welds
    (Elsevier, 2021-06) Danon, AE; Muránsky, O; Zhu, HL; Wei, T; Flores-Johnson, EA; Li, ZJ; Kruzic, JJ
    The mechanical performance of a Ni–Mo–Cr (GH3535) alloy weldment, produced using a matching filler metal, was assessed and compared to the surrounding parent metal. Ambient-temperature mechanical characterisation included hardness testing, small punch testing and uniaxial tensile testing, while a crystal plasticity finite element model was used to assess the impact of crystallographic texture on the mechanical properties. Despite the similar chemical composition, the weld metal exhibited superior strength and ductility to that of the parent metal. The higher strength was primarily attributed to the high dislocation density in the weld metal imbued by the welding-induced thermo-mechanical loading. In contrast, the ductility difference was attributed to M6C carbide stringers in the parent metal that initiated fracture at lower strains when compared to the weld metal, with the latter containing finer, well-dispersed M6C carbides. © 2021 Acta Materialia Inc. Published by Elsevier B.V.
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    Fracture and fatigue behaviour of a laser additive manufactured Zr-based bulk metallic glass
    (Elsevier, 2020-12) Best, JP; Ostergaard, HE; Li, BS; Stolpe, M; Yang, F; Nomoto, K; Hasib, MT; Muránsky, O; Busch, R; Li, XP; Kruzic, JJ
    Laser additive manufacturing of bulk metallic glass (BMG) provides an effective bypassing of the critical casting thickness constraints that limit the size of components that can be produced; however, open questions remain regarding the resulting mechanical properties. In this work, a Zr-based BMG known as AMZ4 with composition Zr59.3Cu28.8Nb1.5Al10.4 was printed using a laser powder bed fusion (LPBF) technique. Micro X-ray computed tomography results together with electron microscopy imaging revealed porous processing defects in LPBF produced AMZ4 that led to a loss in tensile strength. Fatigue crack growth studies revealed a fatigue threshold, ΔKth., of ∼1.33 MPa√m and a Paris law exponent of m = 1.14, which are relatively low values for metallic materials. A KIC fracture toughness of 24−29 MPa√m was found for the LPBF BMG samples, which is much lower than the KQ of 97−138 MPa√m and KJIC of 158−253 MPa√m measured for the cast alloy with the same composition. The lower fracture toughness of the laser processed AMZ4 was attributed to ∼7.5× higher dissolved oxygen in the structure when compared to the cast AMZ4. Despite the higher level of oxygen, the formation of oxide nanocrystals was not observed by transmission electron microscopy. Oxygen induced toughness loss was confirmed by dissolving elevated concentrations of oxygen into cast AMZ4 rods, which led to a reduction in bending ductility and changes in the short-range order of the glass structure, as revealed by synchrotron X-ray diffraction. © 2020 Elsevier B.V.
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    On the prediction of creep behaviour of alloy 617 using Kachanov-Rabotnov model coupled with multi-objective genetic algorithm optimisation
    (Elsevier, 2022-10) Choi, J; Bortolan Neto, L; Wright, RN; Kruzic, JJ; Muránsky, O
    The accurate prediction of elevated-temperature creep behaviour of alloys is important for preventing catastrophic failure of systems operating under prolonged elevated temperature-stress conditions. Here, we couple the Kachanov-Rabotnov (K-R) creep model with a multi-objective genetic algorithm (MOGA) to predict the creep behaviour of Alloy 617 at 800°C, 900°C, and 1000°C, under various stress conditions. It is shown that the MOGA-optimised K-R creep model can capture the overall elevated-temperature behaviour of the alloy at 800°C under a wide range of stress conditions. However, at 900°C and 1000°C, oxidation leads to the atypical accumulation of creep plasticity, which the K-R model cannot account for. Nevertheless, it is shown that the proposed methodology of optimising the K-R model with a MOGA can consistently provide accurate results within the limits of the K-R model. Crown Copyright © 2022 Published by Elsevier Ltd.