| About this Abstract |
| Meeting |
10th International Symposium on Superalloy 718 and Derivatives (2023)
|
| Symposium
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Superalloy 718 and Derivatives
|
| Presentation Title |
Multi-variate Process Models for Predicting Site-specific Microstructure and Properties of Inconel 706 Forgings |
| Author(s) |
Nishan Senanayake, Reese J Capo, Tiffany A Dux, Jennifer LW Carter |
| On-Site Speaker (Planned) |
Jennifer LW Carter |
| Abstract Scope |
The performance of Inconel 706 forgings hinges on the careful design of the thermomechanical history to promote distributions of oft-dependent microstructural features. Establishing predictive process-structure-property (PSP) models to tailor manufacturing routes requires immense cost due to the time and cost-consuming tasks of quantifying statistically significant observations of different predictor and property metrics. Power analysis indicates that for a simple multivariate linear model of one performance metric, P, dependent on six input process predictors (k = 6) (i.e., P = f(k1, k2, … k6)) with 80% predictive power would require over 120 observations; to predict n performance metrics (P1, P2, ...Pn), a statistical study protocol would require 120n observations (ANOVA would require 175n). Most processing and microstructure predictors and property metrics are observed/measured destructively. This motivates the development of high-throughput measurements of both experimental approaches and physics-based simulations that enable dimensionality reduction of the predictor space (i.e., time and temperature are not independent predictors of diffusion-mediated metrics such as precipitate fraction). In this paper, we highlight how thermal profiles from finite element simulations (processing predictors) can establish time-temperature boundary conditions for CALPHAD predictions of the combined 𝛾′, 𝛾′′ precipitate distribution in Inconel 706 (structure predictors). Experimental observations of these precipitate distributions allow for the tailoring of the CALPHAD interfacial energy. In this manner, a 25x reduction in the number of physical observations of 𝛾′ and 𝛾′′ distribution (100 to 4) still results in site-specific PSP models of forged parts with 80% predictive power. |
| Proceedings Inclusion? |
Definite: At-meeting proceedings |
| Keywords |
Ceramics, Biomaterials |