A void descriptor function to uniquely characterize pore networks and predict ductile-metal failure properties
Source abstract
Abstract
Porosity, a commonly occurring void defect in casting and additive manufacturing, is known to affect the mechanical response of metals, making it difficult or impossible to predict response variability. We introduce a new method of uniquely characterizing pore networks using a void descriptor function (VDF), which can be used to predict ductile-metal failure properties, namely, toughness modulus, ultimate strength, elongation, and fracture location. The VDF quantifies the inter-relationships of pores by accounting for pore location, size, and distance to free surface. Using a finite-element-modeling framework, 120 tensile specimens with statistically similar pore networks were simulated (virtually tested) to failure. The pore networks were characterized by the proposed VDF, which was then compared to the nominal location of fracture (defined as the fracture-initiation location corresponding to the dominant crack responsible for final rupture). The location of maximum VDF accurately predicted the fracture location (within ± 0.2 mm) for 91 (76%) of the 120 samples and proved to be a more reliable indicator than the location of maximum reduced cross-section area and the location of largest pore diameter for predicting fracture location. Furthermore, the maximum VDF value was found to be more highly correlated than fraction porosity, pore size, reduced-cross section area, and total number of pores to the ultimate tensile strength, elongation, and toughness modulus.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · Additive Manufacturing and 3D Printing Technologies · Injection Molding Process and Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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