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Meeting	MS&T22: Materials Science & Technology
Symposium	Uncertainty Quantification in Data-Driven Materials and Process Design
Presentation Title	Bayesian Calibrated Yield Strength Model for High-entropy Alloys
Author(s)	Xin Wang, Wei Xiong
On-Site Speaker (Planned)	Xin Wang
Abstract Scope	Yield strength prediction is vital in new alloy design, and the solid solution strengthening effect is essential for accurately predicting yield strength. However, the conventional solid solution strengthening model is less accurate for the high-entropy alloys (HEAs) since the HEAs nature of the complex concentrations breaks the concept of solutes and solvents. In this work, we conducted a Bayesian model calibration to optimize the solid solution strengthening model parameters and quantified the model uncertainties based on a relatively large dataset collected from the literature. The accuracy of our model is higher compared with existing models. Moreover, we also evaluated the confidence in each model parameter. The parameter uncertainties were further discussed to identify the knowledge gaps in the physics-based understanding of the strengthening effect in HEAs.

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