Effect of cell grain on the shear band spacing of a AISI 316L stainless steel fabricated by laser powder bed fusion
Source abstract
Abstract
Cell grains in additive manufacturing NiCrFe-based alloys are one of the key factors for enhancing mechanical properties and damage resistance. The research on the shear band spacing is an indispensable and important component in the field of dynamic damage mechanisms and prediction. In this work, the influence of cell grains on the shear bands of additive manufacturing AISI 316L stainless steel (AM AISI 316L SS) specimens over a wide strain rate range was studied. The specimens have ultimate compressive strength and impact energy of 1301 MPa and 193 MJ/m 3 , respectively. Specimens are used to conduct radial explosion tests on gradient thick-walled cylinders, enabling the rapid acquisition of multiple shear band characteristics within a wide strain range. Scanning electron microscopy (SEM), transmission electron microscopy (TEM) are applied to study the influence of molten pools and cell grains on the shear bands. When the equivalent strain of the specimens ranges from 36.7% to 90.3%, shear bands evolve from being absent to being extensively distributed in the inner ring of the specimens. The maximum length of the shear bands is 1.36 mm, the minimum spacing reaches 0.43 mm, and the width reaches 11 μm. A machine learning-based model suitable for the spacing of shear band of additive manufacturing materials is proposed. Larger-sized cell grain (400-600 nm) can better coordinate shear band deformation by deformation and elongation. Cell grains can impede the initiation and growth of shear bands, thereby increasing the threshold for the reduction of shear band spacing. Cell grain regulation techniques provide both a theoretical foundation and technical support for modulating the dynamic damage of AM alloys.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · High Entropy Alloys Studies · Laser Material Processing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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