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Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Verification, Calibration, and Validation Approaches in Modeling the Mechanical Performance of Metallic Materials
Presentation Title Source-Separated Uncertainty Quantification in the Stochastic Plasticity of Cold Sprayed Al 7075 Using Profilometry-Based Indentation Plastometry and Residual Analysis
Author(s) Aaron E. Tallman, Astrid Rodriguez Negron, Denny John, Tanaji Paul, Arvind Agarwal
On-Site Speaker (Planned) Aaron E. Tallman
Abstract Scope Additive manufacturing of metal components produces spatial variations in microstructure. Measuring these inconsistencies is important: localized plasticity in neighborhoods of grains can influence part performance, especially at geometric stress risers. Suitable testing methods must balance throughput and precision to deliver statistically significant datasets. Fortunately, certain statistical methods employed to discover trends not captured by a model called residual analysis can leverage test arrays. Here, residual analysis and uncertainty quantification (UQ) are connected to estimate profilometry variations due to surface tilt, load differences, heterogeneity, and plasticity variations in 100 indentation tests of cold sprayed (CS) Al 7075. Using residual analysis, linear regression, and principal component analysis, the unique contributions of different uncertainties were approximated. Source-specific UQ was employed to isolate material variability in the CS material, with a relative precision improvement of 20% over standard practice. The use of residual analysis in model validation and CS property qualification is discussed.
Proceedings Inclusion? Planned:
Keywords Additive Manufacturing, Mechanical Properties, ICME

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