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Meeting 2016 TMS Annual Meeting & Exhibition
Symposium Computational Methods for Uncertainty Quantification, Model Validation, and Stochastic Predictions
Presentation Title Multiscale Modeling of with Quantified Uncertainties and Cloud Computing: Towards Computational Materials Design
Author(s) Alejandro Strachan
On-Site Speaker (Planned) Alejandro Strachan
Abstract Scope Predictive, physics-based modeling with quantified uncertainties has the potential to revolutionize design and certification of materials and devices. Accomplishing this requires not only advances in modeling and simulation but also their synergistic combination with experiments via rigorous methods to quantify uncertainties and arrive at the desired decision in an optimal manner. I will illustrate our recent progress in the field by way of predictions of the performance of RF MEMS switches combining mulstiscale, multiphysics modeling and experiments and accounting for uncertainties in models, parameters and experimental measurements. In addition I will describe recent efforts to add uncertainty quantification capabilities to nanoHUB a cyberinstructure effort supported by the US National Science Foundation that enables users from around the world to perform fully interactive simulations from the web-browser or tablets using cloud computing, without the need to download or install any software.
Proceedings Inclusion? Planned: A print-only volume

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

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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