journal article·2023-10

X-ray computed μ-tomography analysis to evaluate the crack growth in an additive manufactured Ti-6Al-4V alloy sample stressed with in-phase axial and torsional loading

Danilo A. Renzo, Maria C. Crocco, Carmine Maletta, Leonardo Pagnotta, Emanuele Sgambitterra, Filippo Berto, Franco Furgiuele, Raffaele Filosa, Joseph J. Beltrano, Riccardo C. Barberi, Raffaele G. Agostino, Vincenzo Formoso

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Abstract

Selective laser melting (SLM) is one of the most promising additive manufacturing technologies for obtaining end-use components with excellent mechanical properties. However, the presence of manufacturing defects harms mechanical properties and fatigue performance. This work investigated the crack behaviour within an SLM Ti-6Al-4V alloy sample stressed with in-phase axial and torsional loading by X-ray computed μ-tomography (μ-CT). A sub-volume of material that contains the most significant defects was detected and analysed. The critical defect was identified by evaluating the effective strain intensity factor (SIF) using two different proposed models, that consider the effective area of a detected defect according to Murakami's method. The first model is based on the modified Smith Watson and Topper (MSWT) criterion. The second is based on Liu's virtual strain energy (VSE) method. The trend of the crack growth rate was obtained by measuring the effective area for a different number of cycles. The μ-CT data was also exploited to build a finite element model (FEM) of part of the gauge section containing surface defects. Finite element analysis (FEA) results have provided information on the stress state leading to high-stress concentrations at the crack tip influencing the propagation.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Additive Manufacturing Materials and Processes · Welding Techniques and Residual Stresses · Additive Manufacturing and 3D Printing Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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