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Meeting 2025 TMS Annual Meeting & Exhibition
Symposium Verification, Calibration, and Validation Approaches in Modeling the Mechanical Performance of Metallic Materials
Presentation Title Computational Materials for Qualification and Certification Steering Group and Community Vision Roadmap
Author(s) Edward Glaessgen, Michael Gorelik
On-Site Speaker (Planned) Edward Glaessgen
Abstract Scope The Computational Materials for Qualification and Certification (CM4QC) Steering Group is a recently assembled team from U.S. industry, government, and academia that is exploring ways of maturing Computational Materials (CM) framework capabilities to enable their use in the context of qualification and certification (Q&C) of metallic process intensive materials (PIM) for aeronautics applications, including, but not limited to metal additive manufacturing (AM). CM4QC will inform the industry and the certifying agencies on how to enhance the current Q&C practices through the insertion of CM capabilities in aeronautical metallic PIM components/applications. Additionally, CM4QC will identify technical and regulatory considerations that should enable a broader use and acceptance of CM methods within a Q&C framework. In this presentation, we will provide an overview of the CM4QC steering group and its community vision roadmap including identification of regulatory gaps, enablers, and requirements; identification of key CM and enabling technologies, assessment of their current maturity levels and required future development.
Proceedings Inclusion? Planned:

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Constitutive Framework for Modeling Dynamic Recrystallization in Pure Copper
A Critical Analysis on the Predictive Capabilities of Different Criteria for Ductile Failure Initiation in Metallic Materials
Advanced Calibration of the GTN Damage Model for Aluminum Alloy AA6111 via Bayesian Inference and Digital Image Correlation Techniques
An Open-Source Framework for Data Augmentation and Emulation: Application to Process Optimization in AM
Bayesian Calibration and Validation of a Physics-Based Crystal Plasticity and Damage Model for Shock Compression and Spall
Computational Materials for Qualification and Certification Steering Group and Community Vision Roadmap
Digital Twins to Accelerate AM Qualification: Defining Challenge Problems to Validate Model Performance
Establishing Temperature-Based Relationships for Mechanical Properties and Crystal Plasticity Parameters of Additively Manufactured Haynes-214 Alloy
Experiment and Crystal Plasticity Model-Based Investigation of Surface Roughness Influence in the Fatigue Life of Additive Manufactured Nickel-Supperalloys
Experiments and Methods to Calibrate and Validate Defect-Sensitive Fatigue Models
Explicit Finite Element Model of Composite Metal Foam’s Mechanical Response During Quasi-Static & Dynamic Compression
Improved Representation of Grain-Level Microstructures to Support Advanced In-Situ Mechanical Testing
Investigating Reduced Order and Surrogate Models of Crystal Plasticity Finite Element Models for Calibration Against Strain Field Data
Micromechanical Model Verification of Additively Manufactured Inconel 625 Informed by In Situ High-Energy X-Ray Diffraction
Microstructure Dependence of Spall Failure in Mg-Al Alloys at Extreme Strain Rates
Non-Uniqueness in Crystal Plasticity Fitting Parameters: Effects on Intragranular Mechanical Behavior
Physics-Informed Neural Networks with LuGre Model for Friction Force Analysis in Tribological Systems
Predicting Mechanical Properties of Ti-6Al-4V Alloy Using a Physics-Informed Neural Network (PINN) for Crystal Plasticity Modeling
Predicting the Variability in Performance of Zircaloy in Nuclear Reactors
Probabilistic Global-Local Calibration of Crystal Plasticity Parameters for Additively Manufactured Metals Using Synthetic Data
Quantifying Error in Machine Learning Predictions of Macroscopic Yield Surfaces of Polycrystalline Materials
Quantifying Uncertainties Using Crystal Plasticity Modeling of Microstructural Clones
Strain-Gradient Crystal Plasticity Finite Element Modeling of Phenomena Pertaining to the Sequential Strain Path Changes in AA6016-T4
Substructure-Sensitive Crystal Plasticity: A Consistent Approach Across Materials, Loading Conditions and Temperatures
Synchrotron-Based Experiments and Microstructure-Sensitive Modeling
Uncertainty-Aware Validation in Modeling of Metal Plasticity: Beyond Mean Squared Error
Uncertainty Quantification of Crystal Plasticity Parameters Using ExaConstit
Uncertainty Quantified Parametrically Upscaled Constitutive Models for Fatigue Nucleation in Polycrystalline Metallic Materials

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