Session: DAC-22-01-Multi-fidelity Modeling Under Uncertainty

Paper Number: 89511

89511 - Iterative Uncertainty Calibration for Modeling Metal Additive Manufacturing Processes Using Statistical Moment-Based Metric 

Metal additive manufacturing (AM) has recently attracted attentions due to its potential for batch/mass production of metal parts. This process, however, currently suffers from problems including low productivity, inconsistency in the properties of the printed parts, and defects such as lack of fusion, keyholing, and un-melted powders. Finite Element (FE) modeling cannot accurately model the metal AM process and has a high computational cost. Empirical models based on experiments are time consuming and expensive. This paper improves a previously developed framework that takes advantages of both empirical and FE models. Validity and accuracy of the metamodel developed in the previous framework depend on the initial assumption of parameter uncertainties. This causes problem when the assumed uncertainties are far from the actual values. The proposed framework introduces an iterative calibration process to overcome this limitation. In addition, the u_pooling metric used as the calibration metric in the previous framework is found not as good as the second order statistical moment-based metric (SMM), after comparing several calibration metrics. The proposed framework is then applied to a four-variable porosity modeling problem. The obtained model is more accurate than using other approaches although only 10 experimental data points are available for calibration and validation.

Presenting Author: Mostafa Rahmani Dehaghani Simon Fraser University

Presenting Author Biography: Mostafa graduated from Sharif University of Technology and worked in industry for many years on product design and manufacturing. Mostafa is currently a PhD student at Simon Fraser University under the supervision of Dr. Gary Wang.

Authors:

Mostafa Rahmani Dehaghani Simon Fraser University
Yifan Tang Simon Fraser University
Gary Wang Simon Fraser University