Search

Your search keyword '"Seede, Raiyan"' showing total 24 results
Start Over Author "Seede, Raiyan"
24 results on '"Seede, Raiyan"'

2. Finite Interface Dissipation Phase Field Modeling of Ni-Nb under Additive Manufacturing Conditions

Author

Karayagiz, Kubra, Johnson, Luke, Seede, Raiyan, Attari, Vahid, Zhang, Bing, Huang, Xueqin, Ghosh, Supriyo, Duong, Thien, Karaman, Ibrahim, Elwany, Alaa, and Arroyave, Raymundo

Subjects
Physics - Applied Physics, Condensed Matter - Materials Science
Abstract

During the laser powder bed fusion (L-PBF) process, the built part undergoes multiple rapid heating-cooling cycles, leading to complex microstructures with nonuniform properties. In the present work, a computational framework, which weakly couples a finite element thermal model to a non-equilibrium PF model was developed to investigate the rapid solidification microstructure of a Ni-Nb alloy during L-PBF. The framework is utilized to predict the spatial variation of the morphology and size of cellular segregation structure as well as the microsegregation in single-track melt pool microstructures obtained under different process conditions. A solidification map demonstrating the variation of microstructural features as a function of the temperature gradient and growth rate is presented. A planar to cellular transition is predicted in the majority of keyhole mode melt pools, while a planar interface is predominant in conduction mode melt pools. The predicted morphology and size of the cellular segregation structure agrees well with experimental measurements.

Published
2019
Full Text
View/download PDF

17. Ductile failure and damage localization in Al6061‐T6 characterized by in situ X‐ray computed tomography and neural network segmentation.

Author

Seede, Raiyan, Johnson, Kyle, and Noell, Philip J.

Subjects
*COMPUTED tomography, *X-rays, *ALLOY testing
Abstract

Damage initiation and localization in uniaxial tension tests of an Al6061‐T6 alloy are evaluated and quantified using in situ X‐ray computed tomography and a neural network segmentation strategy. This segmentation strategy offers significant advantages over traditional thresholding in quantifying microstructural and damage evolution metrics. Void nucleation was observed to occur throughout the deformation process, whereas void volume did not grow significantly until later stages of deformation. Localized analysis determined that void nucleation begins in and around the necked region during the early stages of deformation, whereas limited damage nucleation occurs outside of the neck until late stages of deformation. Lastly, inhomogeneities in void and particle spacing in the initial undeformed state of the material are observed to correlate well with the location of damage localization and necking during deformation. These results provide new insights into the ductile failure of Al alloys and how preexisting defects influence damage and rupture. Highlights: Void nucleation occurs throughout the deformation process.Void volume is constant until later stages of deformation.Void nucleation is concentrated in the neck region during early stages of deformation.Void and particle spacing in the undeformed state correlate with damage localization. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

22. Microstructural and microhardness evolution from homogenization and hot isostatic pressing on selective laser melted inconel 718: Structure, texture, and phases

Author

Seede, Raiyan, Mostafa, Ahmad, Brailovski, Vladimir, Jahazi, Mohammad, Medraj, Mamoun, Seede, Raiyan, Mostafa, Ahmad, Brailovski, Vladimir, Jahazi, Mohammad, and Medraj, Mamoun

Abstract

In this work, the microstructure, texture, phases, and microhardness of 45° printed (with respect to the build direction) homogenized, and hot isostatically pressed (HIP) cylindrical IN718 specimens are investigated. Phase morphology, grain size, microhardness, and crystallographic texture at the bottom of each specimen differ from those of the top due to changes in cooling rate. High cooling rates during the printing process generated a columnar grain structure parallel to the building direction in the as-printed condition with a texture transition from (001) orientation at the bottom of the specimen to (111) orientation towards the specimen top based on EBSD analysis. A mixed columnar and equiaxed grain structure associated with about a 15% reduction in texture is achieved after homogenization treatment. HIP treatment caused significant grain coarsening, and engendered equiaxed grains with an average diameter of 154.8 µm. These treatments promoted the growth of δ-phase (Ni3Nb) and MC-type brittle (Ti, Nb)C carbides at grain boundaries. Laves phase (Fe2Nb) was also observed in the as-printed and homogenized specimens. Ostwald ripening of (Ti, Nb)C carbides caused excessive grain growth at the bottom of the HIPed IN718 specimens, while smaller grains were observed at their top. Microhardness in the as-fabricated specimens was 236.9 HV and increased in the homogenized specimens by 19.3% to 282.6 HV due to more even distribution of secondary precipitates, and the nucleation of smaller grains. A 36.1% reduction in microhardness to 180.5 HV was found in the HIPed condition due to γ′′ phase dissolution and differences in grain morphology.

Published
2018

24. Bayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach

Author

Ye, Jiahui, Mahmoudi, Mohamad, Karayagiz, Kubra, Johnson, Luke, Seede, Raiyan, Karaman, Ibrahim, Arroyave, Raymundo, and Elwany, Alaa

Abstract

Modeling and simulation for additive manufacturing (AM) are critical enablers for understanding process physics, conducting process planning and optimization, and streamlining qualification and certification. It is often the case that a suite of hierarchically linked (or coupled) simulation models is needed to achieve the above tasks, as the entirety of the complex physical phenomena relevant to the understanding of process-structure-property-performance relationships in the context of AM precludes the use of a single simulation framework. In this study using a Bayesian network approach, we address the important problem of conducting uncertainty quantification (UQ) analysis for multiple hierarchical models to establish process-microstructure relationships in laser powder bed fusion (LPBF) AM. More significantly, we present the framework to calibrate and analyze simulation models that have experimentally unmeasurable variables, which are quantities of interest predicted by an upstream model and deemed necessary for the downstream model in the chain. We validate the framework using a case study on predicting the microstructure of a binary nickel-niobium alloy processed using LPBF as a function of processing parameters. Our framework is shown to be able to predict segregation of niobium with up to 94.3% prediction accuracy on test data.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results