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Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Computational Materials for Qualification and Certification
Presentation Title Accelerating the Qualification of New Structural Materials for High Temperature Nuclear Reactors With Physics- and Data-Driven Models
Author(s) Mark C. Messner
On-Site Speaker (Planned) Mark C. Messner
Abstract Scope Developers contributing to the boom in the design and construction of advanced, high temperature fission reactors must contend with nearly the same material library available to designers in the 1980s. Qualifying a new material for safety critical high temperature nuclear applications is a time consuming and expensive process, relying on collecting and correlating large amounts of long-term tests before putting the new material into service. The time and expense of this process limits the palette of materials available to reactor designers. This presentation will summarize recent work aimed at accelerating this qualification process by supplementing short-term testing with microstructural characterization with advanced modeling and simulation. The talk will cover case studies demonstrating that physics-based models and machine learning can reduce required test durations by a factor of four and could reduce the number of tests by a factor of ten or more.
Proceedings Inclusion? Planned:
Keywords Additive Manufacturing, High-Temperature Materials, Modeling and Simulation

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Accelerating the Qualification of New Structural Materials for High Temperature Nuclear Reactors With Physics- and Data-Driven Models
Achievements, Challenges, and Opportunities of a Zone-Based Probabilistic Damage Tolerance Framework for AM Components
Bayesian Modeling for Concurrent Process and Part Design for Large Scale Additive Manufacturing
Challenges in Prediction Microstructure Variability in SS316
Computational Materials for Qualification and Certification Steering Group and Community Vision Roadmap
Computational Materials Tools for Qualification and Certification: Technology Maturation Path
Parametrically Upscaled Model-Based Predictive Platform for Fatigue with Location-Specific Microstructural Linkages
Robust and Efficient Design of Additively Manufactured Alloys by Integrating Uncertainty Quantification and Modeling Using Generative AI
The Critical Roles of Verification, Validation, and Uncertainty Quantification for Qualification and Certification of Metal AM Components for the Aviation Industry
Towards a Computational Digital Twin of Metals AM

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