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Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Additive Manufacturing Modeling, Simulation and Artificial Intelligence
Presentation Title Development of the 3D Heat Transfer and Material Flow Model for the Consumable Tool- Additive Friction Stir Deposition process
Author(s) Prachi Sharma, Mo Rizwan Ahmad Qureshi, Amit Arora
On-Site Speaker (Planned) Amit Arora
Abstract Scope Consumable Tool- Additive Friction Stir Deposition (CT-AFSD) employs a consumable rotating tool to deposit material by generating heat through friction and plastic deformation. Numerical modeling plays a crucial role in optimizing process parameters and understanding the physics of the process, reducing the reliance on extensive experimental trials. The present study focusses on the development of a finite-volume-based heat transfer and material flow model for depositing aluminium on steel substrate. This quasi-steady state moving heat source model incorporates temperature-dependent thermo-mechanical properties of the materials. The model is capable of predicting the heat generation, temperature distribution, thermal cycle and material flow during the process. The thermal cycle and peak temperature is validated with fair agreement with the experimental measurements. The effect of process parameters and model outcomes on the grain size and mechanical properties are also analysed in this study. Further, the work successfully establishes a process-structure-property correlation during the CT-AFSD process.
Proceedings Inclusion? Planned:
Keywords Additive Manufacturing, Modeling and Simulation, Aluminum

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A Framework for Efficient Part-Scale Microstructure Prediction in Laser Powder Bed Ti-6Al-4V Using Combined Physics-Based Modeling and Machine Learning Surrogate Methods
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An Experimentally Validated Defect Mapping Strategy for Laser Powder Bed Fusion Processed Nickel Alloys
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Bridging and Coupling Models with Microstructure and Thermo-Fluid Flow in Powder Bed Fusion
Columnar-To-Equiaxed Transition in Laser Fusion Additive Manufacturing
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Computational Prediction of Grain Structure Evolution in Thermoelectric Bulk Parts Processed by Laser Powder Bed Fusion
Crystal Plasticity–Informed Surrogate Modeling for Predictive Laser Powder Bed Fusion Simulation of Ti-6Al-4V
Crystal Plasticity Finite Element Modeling of Polycrystalline Metals Produced by Additive Manufacturing
Development of the 3D Heat Transfer and Material Flow Model for the Consumable Tool- Additive Friction Stir Deposition process
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F-22: An Artificial Neural Network Modeling Approach to Electroforming of Micro-Tubes in the Presence of Surfactants
F-23: Computational Thermodynamics-Based Optimization of Ti-6Al-4V via Al and V Substitution for Additive Manufacturing
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F-29: Impact of Intermittent Laser on Fluid and Thermal Response in Directed Energy Deposition: A Numerical Study
F-30: Influence of Inoculants on Aluminum Alloy Microstructure Evolution During Fast Solidification: A Computational Approach Under Laser Powder Bed Fusion Conditions
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F-38: Simulation and Experimental Investigation of Dual-Side Deposition Strategy for Deformation Control in DED-Arc
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Prediction of Pore-Driven Debit in Fatigue Performance of Additively Manufactured Materials Via Graph Neural Networks
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