Engineering topics
Roy, Indranil
Publications and source records attributed to Roy, Indranil.
Understanding solidification of near eutectic alloy using Cellular Automata (CA)
The solidification microstructure of an alloy strongly influences the mechanical properties. Dendritic and eutectic solidification are two important pathways of alloy solidification. The formation of phases, and their size and distribution depend on which pathway to take. In contrast to the Scheil model that has been widely used in describing the solidification pathways of alloys manufactured from conventional casting approach, more sophisticated solidification models are required to describe the state-of-the art manufacturing processes, such as additive manufacturing where distinctly different phase morphology, size and distribution than conventional casting can form, due to the vast difference in cooling conditions. Therefore, this work is to develop a computational Cellular Automata framework which includes the modeling of nucleation and growth of dendritic and eutectic solidification, as well as their competition as a function of alloy composition, undercooling and cooling rate. Further, after individual solidification models were validated against analytical solutions, the models were then combined to predict the competition between dendritic and eutectic solidification in alloys with off-eutectic compositions. This work predicts increased cooling rates suppress the dendritic solidification and promote eutectic solidification. Although quantitative validation is needed, this finding is consistent with qualitative observation in literature.
Effect of aging and α’ segregation on oxidation and electrochemical behavior of FeCrAl alloys
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Elucidating precipitation in FeCrAl alloys through explainable AI: A case study
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Effect of nickel on the oxidation behavior of FeCrAl alloy in simulated PWR and BWR conditions
FeCrAl alloys are being investigated as candidate materials for light water reactor fuel claddings. The chemical composition of FeCrAl determines its resistance to corrosion under normal operating conditions. The purpose of this paper is to investigate the effect of 0, 1, 3 wt% Ni addition on the passivation characteristics of Fe17Cr5.5Al in oxygenated and hydrogenated simulated reactor waters for 3-month immersion. Current results show that Ni addition improves the passivation of FeCrAl under oxygenated condition and decreases the mass loss under hydrogenated conditions.
Understanding oxidation of Fe-Cr-Al alloys through explainable artificial intelligence
Abstract The oxidation resistance of FeCrAl based on alloying composition and oxidizing conditions is predicted using a combinatorial experimental and artificial intelligence approach. A neural network (NN) classification model was trained on the experimental FeCrAl dataset produced at GE Research. Furthermore, using the SHapley Additive exPlanations (SHAP) explainable artificial intelligence (XAI) tool, we explore how the NN can showcase further material insights that are unavailable directly from a black-box model. We report that high Al and Cr content forms protective oxide layer, while Mo in FeCrAl creates thick unprotective oxide scale that is vulnerable to spallation due to thermal expansion. Graphical abstract