Conference Tools for 2025 TMS Annual Meeting & Exhibition

Help

About this Abstract
Meeting	2025 TMS Annual Meeting & Exhibition
Symposium	Verification, Calibration, and Validation Approaches in Modeling the Mechanical Performance of Metallic Materials
Presentation Title	Micromechanical Model Verification of Additively Manufactured Inconel 625 Informed by In Situ High-Energy X-Ray Diffraction
Author(s)	Reilly Knox, Robert Carson, Matthew Rolchigo, Katherine Shanks, Jim Belak, Darren C. Pagan
On-Site Speaker (Planned)	Darren C. Pagan
Abstract Scope	Macroscopic stress-strain responses can often be captured by a non-unique set of micromechanical material parameters and microstructure instantiations. As a result, confidence in full-field micromechanical results, necessary for predicting properties such as strength, ductility, and fatigue-life, is reduced. One means to address this issue is to use micromechanical experimental data, such as lattice strain data collected synchrotron X-ray sources. Here we present lattice strain data collected at the Cornell High Energy Synchrotron Source during in situ compression testing of additively manufactured (AM) Inconel 625. This data is used to verify the role of microstructure in micromechanical response predictions from ExaConstit, a high-performance crystal plasticity finite element method code developed as part of the DOE ExaAM project for property prediction of metal AM components. Model instantiation with accurate texture and grain morphology is shown to be critical for micromechanical prediction accuracy.
Proceedings Inclusion?	Planned:
Keywords	Additive Manufacturing, Modeling and Simulation, Characterization

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

Questions about ProgramMaster? Contact programming@programmaster.org