ProgramMaster Logo
Conference Tools for 2017 TMS Annual Meeting & Exhibition
Login
Register as a New User
Help
Submit An Abstract
Propose A Symposium
Presenter/Author Tools
Organizer/Editor Tools
About this Abstract
Meeting 2017 TMS Annual Meeting & Exhibition
Symposium Computational Methods and Experimental Approaches for Uncertainty Quantification and Propagation, Model Validation, and Stochastic Predictions
Presentation Title A Novel Method of Analyzing Constitutive Model Parameters Using Canonical Correlation Analysis
Author(s) Sudipto Mandal, Anthony Rollett
On-Site Speaker (Planned) Sudipto Mandal
Abstract Scope Successful modeling of a material’s deformation behavior is dependent on the development of realistic constitutive models. In-depth knowledge about the parameters in a constitutive model will lead to a better understanding of the relationship between flow stress and deformation conditions and will eventually aid in better design of the deformation process. Curve-fitting is generally employed to train constitutive models using experimental data. However, relative impact of constitutive model parameters on the mechanical response for different models has not been explored much. In this study, both local and global sensitivity analysis methods are used. Canonical correlation analysis (CCA) has been used to understand the effect of constitutive model parameters on the flow stress behavior of titanium alloys. The limitations of local sensitivity methods have been highlighted and it has been shown that CCA provides a measure of both individual variable’s contribution and the effectiveness of the parameter set as a whole.
Proceedings Inclusion? Undecided

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Novel Method of Analyzing Constitutive Model Parameters Using Canonical Correlation Analysis
A Statistical FEA Method for Predicting Glass Fracture in Consumer Electronic Products
Advancements in Parameterization and Validation of Empirical Potentials
An Integrated Microstructure Development and Crystal Plasticity Approach with Uncertainty Quantification for Multi-scale Constitutive Model Development.
Automatized Convergence and Error Analyses for High Precision Density Functional Theory Calculations
B-1: Error Reduction in Cross-Sectional Measurements of Materials from Imaged Grayscale Volumes
B-2: Fidelity in Gas Dynamics Simulations
B-3: Numerical Simulation of Ultrasonic Propagation in Calcium Ferrite Melt
B-4: Ab Initio Scaling Laws for the Formation Energy of Interstitial Defect Clusters in Body-centered-cubic Metals
B-5: Coupled Elasto-plastic Self-consistent and Finite Element Crystal Plasticity Modeling: Applications to Sheet Metal Forming Processes
B-6: Finite Element Prediction of Single Particle Cold Spray Impact
B-7: Numerical Simulation of the Mechanical Behavior of Zr-Nb Alloys over a Wide Range of Strain Rates
Community-driven Benchmark Problems for Phase Field Modeling
Density Functionals and the Finite Temperature Properties of Ferroelectric Oxides
Development of Semi-Empirical Potentials Suitable for Simulation of Phase Transformations in Titanium
Evaluation and Comparison of Classical Interatomic Potentials through a User-friendly Interactive Web-interface
Evaluation of Atomistic Potentials for Silicon
Finite Element Analysis of Influence of Phase Distribution and Shape Variation of Phases on Charge Transport in a Dual Phase System
Functional Uncertainty Quantification in Materials Modeling
Hierarchical Multiscale Modeling and Parametric Analysis of Polyvinyl Alcohol/Montmorillonite Nanocomposites
Information-theoretic Tools for Uncertainty Quantification of High Dimensional Stochastic Models
Molecular Dynamics, Dislocation Interactions and Uncertainty
Numerical Simulation of Electomagnetic Field, Flow Field, and Temperature Field in Secondary Cooling Zone of Round Billet under the Impact of Pulsed Magneto-oscillation
Peierls Barrier in Ta-W Alloys: Estimating Aleatory Variability
Quantifying Material Variability and Uncertainty for Welded and Additively-manufactured Structures Using Multiscale A Posteriori Error-estimation Techniques
Quantifying Uncertainty from (Pseudo)potentials for First Principles and Classical Atomistic Simulations
Uncertainty Quantification in Density Functional Theory: Non-intrusive vs. Intrusive Methodologies
Uncertainty Quantification in the Multiscale Simulation of Materials
Uncertainty Quantification of Classical Interatomic Potentials
Uncertainty Quantification, Molecular Dynamics, and the Glass-Transition Temperature of Aerospace Polymers
Using Information Geometry to Relate Parametric Uncertainty and Model Predictivity
Using Metropolis-Hasting Algorithm to Calibrate NiTi Precipitation Model Implemented in MatCalcİ Code
Validation and Uncertainty Assessment of Bond-order Potentials for Transition Metals

Questions about ProgramMaster? Contact programming@programmaster.org