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Meeting 2016 TMS Annual Meeting & Exhibition
Symposium Computational Methods for Uncertainty Quantification, Model Validation, and Stochastic Predictions
Sponsorship TMS Materials Processing and Manufacturing Division
TMS: Computational Materials Science and Engineering Committee
Richard G. Hennig, University of Florida
Mark A. Tschopp, US Army Research Laboratory
Li Ma, Johns Hopkins University Applied Physics Laboratory
Scope Experimental measurements exhibit a certain degree of uncertainty that is described by their precision and accuracy. The same holds true for computational results, as, similarly to the limitation of measuring instruments, the models behind simulation methodologies and their numerical evaluations exhibit limitations. Moreover, in recent years, stochastic computational techniques and data analysis methods have advanced the study of materials in a wide variety of fields. To be interpreted correctly, results obtained using any of the above-mentioned methodologies, at any length scale, need a careful evaluation of their uncertainties. Moreover, a way to evaluate the predictability of simulation techniques is to validate their findings using other, experimental or computational, approaches.
This symposium will focus on stochastic methods, computational methodology validation, as well as uncertainty evaluation for computational approaches at various length scale, including methodologies, like density functional theory (DFT), empirical energy models, etc., whose results have traditionally been reported without error bars. The goal of the symposium is to cover these research topics in an interdisciplinary approach, which connects theory and experiment, with a view towards materials applications.
Topics and 4 planned sessions:
• Advancements in stochastic methodologies (for material discovery)
• Validation and uncertainty evaluation for DFT and other quantum-mechanical based methods
• Validation and uncertainty evaluation for empirical potential/force fields based simulation methodologies
• Validation and uncertainty evaluation for larger scale methodologies (finite element, mesoscale, etc.).
Abstracts Due 07/15/2015
Proceedings Plan Planned: A print-only volume

Accuracy of Kinetics in Coarse-Grained Molecular Dynamics
Advancements in Methods for Materials Discovery and Validation
Assessing the Accuracy of DFT Formation Energies
Atomistic Study of Carbon Nanotubes: Effect of Cut-off Distance
Bayesian Calibration of a Physical Model for Plastic Flow Behavior of TRIP Steels
Citrination: Open Infrastructure for Ingesting, Storing, and Mining Materials Data
Computational Simulation and Physical Validation of Welded Aluminum Structures
Data Analysis in Mesoscale Model of Ductile Damage
Database Optimization for Empirical Interatomic Potentials
Density-Functional Theory Energy Density Method: Extracting Information and Identifying Finite-size Errors
Density Functional Theory and Prediction of Energy Storage Materials Properties
Development of the ReaxFF Force Field for Complex Materials and Interfaces
Effect of K-point Convergence on Derived Properties for Pure Crystals
Elasticity Size Effects in ZnO Nanowires and Subjective Definitions of Cross-sectional Area: An Overlooked Source of Uncertainty
Evaluation of Phase-Field Models Through Stochastic Quantification of Microstructure and Data Analytics
Exploring the Effects of Micro-texture on Engineering-scale Performance
Functional Uncertainty Quantification for Multi-fidelity and Multi-scale Simulations
Grain Deformation in a Cast Ni Superalloy: Comparing Experimental and Modelling Results
How Important are the Smallest Grains on Grain Aggregate Mechanics?
Materials and Data Development for Airframes
Microstructure-Uncertainty Propagation in Sheet Metal Forming FE-Simulations
Multiscale Modeling of with Quantified Uncertainties and Cloud Computing: Towards Computational Materials Design
Probabilistic Homogenization of Crystal Plasticity Modeling for Ti Alloys
Quality Control: Has Your DFT Code Been Δ-approved?
Quantifying Model-Form Uncertainty in Molecular Dynamics Simulation
Searching Transition States under Model-Form Uncertainty in Density Functional Theory Simulation
Uncertainty Propagation in a Computational Fatigue Model of an Airframe Structure
Uncertainty Quantification Algorithms for Large-scale Systems
Uncertainty Quantification and Propagation for Validation of a Microstructure Sensitive Model for Prediction of Fatigue Crack Initiation
Understanding the Effect of Experimental Uncertainty on the Multistage Fatigue Model
Using Correlations between Materials Properties in Potential Development Procedure for Metals

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