© Department of Materials Science and Technology, IIT Delhi
AI-Augmented Micromechanics for Dual-Phase Steels
Prof. Amarendra K Singh
Department of Materials Science and Engineering
IIT Kanpur
Abstract
Recent advancements in materials modelling combine experimental data with RVE simulations to capture microstructural features such as phases, inclusions, and grain boundaries more accurately. The present study focuses on dual-phase (DP) steels and uses a workflow that includes digitizing microstructures and performing FEM simulation with phase-specific constitutive models. Recognizing localized hardness variation near the ferrite-martensite interface, the interphase is modelled as a distinct phase to improve flow stress predictions. Synthetic microstructures with various banded patterns are generated to expand the dataset. Further, the influence of inclusions is also examined. These microstructures are analyzed using 2-point statistics to extract principal component scores. RVE simulations on the microstructure provide corresponding mechanical properties. A machine learning model is then trained to predict properties based on microstructural features. In the ICME workflow, such models can be used on computed microstructure to provide closure while optimizing the composition and the processing design space.
Bio
Dr. A. K. Singh is a Professor in the Department of Materials Science and Engineering at the Indian Institute of Technology (IIT) Kanpur. He holds a B.Tech in Metallurgical Engineering and an M.Tech and Ph.D. in Metallurgical Engineering and Materials Science, all from IIT Kanpur. Before joining academia in 2015, he spent 23 years at Tata Consultancy Services (TCS) Innovations Lab-TRDDC, Pune, where he used mathematical modeling to optimize manufacturing processes, leading to improved productivity and environmental compliance.
His research interests include mathematical modeling of metallurgical operations, solidification processing, and integrated computational materials engineering. He coordinates the ICME National Hub at IIT Kanpur, a collaboration between IIT Kanpur and TCS. He is also the Professor-in-Charge of the IIT Kanpur Technology and Research Park. Recognized for his contributions, Dr. Singh has received the Metallurgist of the Year Award from the Government of India and the TCS Distinguished Scientist Award.
Abstract
Recent advancements in materials modelling combine experimental data with RVE simulations to capture microstructural features such as phases, inclusions, and grain boundaries more accurately. The present study focuses on dual-phase (DP) steels and uses a workflow that includes digitizing microstructures and performing FEM simulation with phase-specific constitutive models. Recognizing localized hardness variation near the ferrite-martensite interface, the interphase is modelled as a distinct phase to improve flow stress predictions. Synthetic microstructures with various banded patterns are generated to expand the dataset. Further, the influence of inclusions is also examined. These microstructures are analyzed using 2-point statistics to extract principal component scores. RVE simulations on the microstructure provide corresponding mechanical properties. A machine learning model is then trained to predict properties based on microstructural features. In the ICME workflow, such models can be used on computed microstructure to provide closure while optimizing the composition and the processing design space.
Bio
Dr. A. K. Singh is a Professor in the Department of Materials Science and Engineering at the Indian Institute of Technology (IIT) Kanpur. He holds a B.Tech in Metallurgical Engineering and an M.Tech and Ph.D. in Metallurgical Engineering and Materials Science, all from IIT Kanpur. Before joining academia in 2015, he spent 23 years at Tata Consultancy Services (TCS) Innovations Lab-TRDDC, Pune, where he used mathematical modeling to optimize manufacturing processes, leading to improved productivity and environmental compliance.
His research interests include mathematical modeling of metallurgical operations, solidification processing, and integrated computational materials engineering. He coordinates the ICME National Hub at IIT Kanpur, a collaboration between IIT Kanpur and TCS. He is also the Professor-in-Charge of the IIT Kanpur Technology and Research Park. Recognized for his contributions, Dr. Singh has received the Metallurgist of the Year Award from the Government of India and the TCS Distinguished Scientist Award.
Abstract
Recent advancements in materials modelling combine experimental data with RVE simulations to capture microstructural features such as phases, inclusions, and grain boundaries more accurately. The present study focuses on dual-phase (DP) steels and uses a workflow that includes digitizing microstructures and performing FEM simulation with phase-specific constitutive models. Recognizing localized hardness variation near the ferrite-martensite interface, the interphase is modelled as a distinct phase to improve flow stress predictions. Synthetic microstructures with various banded patterns are generated to expand the dataset. Further, the influence of inclusions is also examined. These microstructures are analyzed using 2-point statistics to extract principal component scores. RVE simulations on the microstructure provide corresponding mechanical properties. A machine learning model is then trained to predict properties based on microstructural features. In the ICME workflow, such models can be used on computed microstructure to provide closure while optimizing the composition and the processing design space.
Bio
Dr. A. K. Singh is a Professor in the Department of Materials Science and Engineering at the Indian Institute of Technology (IIT) Kanpur. He holds a B.Tech in Metallurgical Engineering and an M.Tech and Ph.D. in Metallurgical Engineering and Materials Science, all from IIT Kanpur. Before joining academia in 2015, he spent 23 years at Tata Consultancy Services (TCS) Innovations Lab-TRDDC, Pune, where he used mathematical modeling to optimize manufacturing processes, leading to improved productivity and environmental compliance.
His research interests include mathematical modeling of metallurgical operations, solidification processing, and integrated computational materials engineering. He coordinates the ICME National Hub at IIT Kanpur, a collaboration between IIT Kanpur and TCS. He is also the Professor-in-Charge of the IIT Kanpur Technology and Research Park. Recognized for his contributions, Dr. Singh has received the Metallurgist of the Year Award from the Government of India and the TCS Distinguished Scientist Award.
© Department of Materials Science and Engineering, IIT Delhi