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Meeting 2018 TMS Annual Meeting & Exhibition
Symposium Building an ICME Infrastructure: Developing Tools that Integrate Across Length and Time Scales to Accelerate Materials Design
Presentation Title Uncertainty Quantification and Propagation through CALPHAD Thermodynamics and Integrated Computational Materials Engineering (ICME)
Author(s) Jeff W. Doak, Abhinav Saboo, Dana Frankel, Nick Hatcher, James Saal, Greg Olson
On-Site Speaker (Planned) Jeff W. Doak
Abstract Scope ICME models rely heavily on CALPHAD thermodynamics fit to experimental and ab-initio data. Uncertainty in this underlying data can drive uncertainty in the CALPHAD and ICME models. However, traditionally, once a CALPHAD database has been fit, the experimental data and statistics of the fit are discarded and the CALPHAD database is taken as ground truth. By discarding this information, considerable value to the material design process is lost. At QuesTek Innovations, we are developing tools to incorporate Bayesian inference into CALPHAD thermodynamics and ICME modeling. Bayesian inference simultaneously fits thermodynamic models to data and quantifies the uncertainty in the resulting models due to this fitting. Because this uncertainty comes in the form of probability distributions over model parameters, the uncertainty in CALPHAD thermodynamic models can be straightforwardly propagated through ICME models. We will discuss the development of tools for Bayesian inference and their application to thermoelectrics and high-entropy alloys.
Proceedings Inclusion? Planned: Supplemental Proceedings volume

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Coupled Experimental and Computational Investigation of Creep-resistant Mg-RE-Zn Alloy
Accelerating the Process-structure-property Discovery Cycle
Application of Diffusion Multiples to the Study of Kinetics and Modulus Properties in the Ti-Mo-Nb-Ta-Zr System
Atomistic Polymer Simulations in the Cloud at nanoHUB.org
Challenges in Multiscale Modeling of Emergent Phenomena in Solid Mechanics
Conceptual and Computational Challenges in Multiscale Modeling
Coupled Crystal Plasticity-phase Field Method to Model Crack Initiation and Propagation in Ti64 Alloys.
Data Science and Informatics: Key Integrators of Multiscale Experiments and Multiscale Models in ICME
Differences between Measured and Simulated Elastic Strain States Using High Energy X-ray Diffraction in Titanium Using Crystal Plasticity Models
Enabling Connection of Online Simulation Tools and Databases: nanoHUB.org
Gaps in Multiscale Modeling to Address Mechanical Properties of Metal Alloys
Integrated Computational Materials Engineering (ICME) in Support of Business Decision Making and Open Innovation Through Interdisciplinary Collaboration.
Integrating Materials Microstructure Information into Engineering Design and Manufacturing
Integration of ICME Tools for the Design of Co-base Single Crystals
Making Materials Science Resources Discoverable and Accessible with the NIST Materials Resource Registry
Modeling Plastic Anisotropy of Textured Polycrystalline Materials
Modeling the Microstructural Evolution and Yield Strength in an Advanced Die Casting Aluminum Alloy
Need for Uncertainty Quantification in Multiscale Materials Modeling Need for Uncertainty Quantification in Multiscale Materials Modeling
Prediction of Hole Expansion Ratio Using Microstructure Based Dual-scale Finite Element Approach
Quantitative Approaches to Identification and Characterization of Microtexture Regions in Titanium Alloys
TAMMAL : High throughput Materials Design Suite
TESSRA: A Cloud-based Multiscale Platform for Modern Alloys Design
The Materials Commons: A Collaboration Platform and Information Repository for the Global Materials Community
The PRISMS Framework: An Integrated Multi-scale Capability for Accelerated Predictive Materials Science
Uncertainty Quantification and Propagation through CALPHAD Thermodynamics and Integrated Computational Materials Engineering (ICME)
Yield Stress, Proportional Limit: Do They Exist?

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