5 citations · 5 across the 4 of their papers we have counts for
5 papers
Capturing Lifecycle System Degradation in Digital Twin Model Updating
Yifan Tang, Mostafa Rahmani Dehaghani, G. Gary Wang
Digital twin (DT) has emerged as a powerful tool to facilitate monitoring, control, and other decision-making tasks in real-world engineering systems. Online update methods have be…
Selecting Subsets of Source Data for Transfer Learning with Applications in Metal Additive Manufacturing
Yifan Tang, M. Rahmani Dehaghani, Pouyan Sajadi +1
Considering data insufficiency in metal additive manufacturing (AM), transfer learning (TL) has been adopted to extract knowledge from source domains (e.g., completed printings) to…
Real-Time 2D Temperature Field Prediction in Metal Additive Manufacturing Using Physics-Informed Neural Networks
Pouyan Sajadi, Mostafa Rahmani Dehaghani, Yifan Tang +1
Accurately predicting the temperature field in metal additive manufacturing (AM) processes is critical to preventing overheating, adjusting process parameters, and ensuring process…
Online Two-stage Thermal History Prediction Method for Metal Additive Manufacturing of Thin Walls
Yifan Tang, M. Rahmani Dehaghani, Pouyan Sajadi +6
This paper aims to propose an online two-stage thermal history prediction method, which could be integrated into a metal AM process for performance control. Based on the similarity…
System identification and closed-loop control of laser hot-wire directed energy deposition using the parameter-signature-property modeling scheme
M. Rahmani Dehaghani, Atieh Sahraeidolatkhaneh, Morgan Nilsen +4
Hot-wire directed energy deposition using a laser beam (DED-LB/w) is a method of metal additive manufacturing (AM) that has benefits of high material utilization and deposition rat…