About this Abstract |
Meeting |
Superalloys 2021
|
Symposium
|
Superalloys 2021
|
Presentation Title |
High-throughput Approaches to Establish Quantitative Process-structure-property Correlations in Ni-base Superalloy |
Author(s) |
Nishan M. Senanayake, Semanti Mukhopadhyay, Jennifer L.W. Carter |
On-Site Speaker (Planned) |
Nishan M. Senanayake |
Abstract Scope |
A high-throughput approach for collecting microstructure and mechanical properties was developed to model the process-structure-property (PSP) correlations in polycrystalline Ni-based superalloy ME3. The semi-automated image processing algorithm captured the area fraction and size distribution of secondary and tertiary ã′ particles from scanning electron microscopy (SEM) images of polished samples. The yield strength and elastic modulus were calculated with an automated algorithm using load-time-displacement data generated by microindentation. Thirty heat treatments were conducted to create various ã′ distributions which are the primary strengthening mechanism of Ni-based superalloys. The PSP correlations among the predictor and response variables were evaluated with regression models and validated with adj-R2 and residual standard error statistics. The PSP statistical models built by using high-throughput protocols align with the previous statistical and theoretical models. |
Proceedings Inclusion? |
Undecided |