Conference Logo ProgramMaster Logo
Conference Tools for 2026 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 2026 TMS Annual Meeting & Exhibition
Symposium Verification, Calibration, and Validation Approaches in Modeling the Mechanical Performance of Metallic Materials
Presentation Title Calibration, Verification, and Validation of Thermal-Mechanical Modeling of Steel Continuous Casting in Funnel Molds
Author(s) Ehsan Jebellat, Brian G. Thomas
On-Site Speaker (Planned) Ehsan Jebellat
Abstract Scope Accurate thermal-mechanical modeling of steel solidification and mold heat transfer in continuous casting is essential for understanding the behavior of the solidification front, shell growth, interfacial gap phenomena, shell shrinkage, stress, and surface defects. This work investigates heat transfer in a funnel mold slab caster using the in-house model Con1D. To capture multidimensional effects near water channels and thermocouples, a two-dimensional finite element model in Abaqus is developed for model calibration. Con1D is verified with detailed Abaqus simulations and validated with plant measurements of mold heat flux and temperature. Results demonstrate that Con1D predictions match plant measurements quantitatively, owing to its physics-based formulation and proper treatment of interfacial gap behavior. This validated and calibrated modeling framework enables new insights into mold heat transfer behavior in continuous casting. For example, the thermal results here are input into thermal-mechanical simulations to predict ideal taper design.
Proceedings Inclusion? Planned:
Keywords Iron and Steel, Modeling and Simulation, Solidification

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

2025 NIST Additive Manufacturing Benchmark Fatigue Challenge to Improve Computational Prediction Techniques: Measurement Description
2025 NIST Additive Manufacturing Benchmark Fatigue Challenge to Improve Computational Prediction Techniques: Prediction Trends
2025 NIST Additive Manufacturing Benchmark Tensile Challenge to Improve Computational Prediction Techniques: Measurement Description
2025 NIST Additive Manufacturing Benchmark Tensile Challenge to Improve Computational Prediction Techniques: Prediction Trends
3D Diffraction Microscopy Imaging Experiments to Calibrate and Validate Crystal Plasticity
A Bayesian Framework for the Calibration of Constitutive Models Across Yield and Creep Regimes Across Alloy Classes
A Critical Discussion of Stress-Based and Stress Increment-Based Elasto-Visco-Plastic Self-Consistent (EVPSC) Models
A proposed framework for the development of microstructurally informed material models for engineering applications: the case study of a deformation model for pure copper
A Unified Gaussian Process Framework for Calibration, Emulation, and Multi-Fidelity Modeling
An In-Situ Monitoring Based Approach to Interpreting Experimental Results in Laser Powder Bed Fusion
Bayesian Calibration of Crystal Plasticity Finite Element Model Parameters
Bridging Machine Learning Constitutive Laws With Classical Model Form to Balance the Variance/Bias Challenge in Constitutive Law Calibration in Computational Homogenization
Calibration of Dislocation Drag Parameters Utilizing Molecular Dynamics Experiments and Gaussian Process Modelling
Calibration, Verification, and Validation of Thermal-Mechanical Modeling of Steel Continuous Casting in Funnel Molds
Cermet Design Through Modeling Residual Stresses and Thermal Cyclic Stability
Crystal Plasticity Calibration and Surrogate Modeling for Thermo-Mechanical Behavior of Additively Manufactured Ti-6Al-4V Alloy
Crystal Plasticity Informed Hill's Constitutive Model for Modeling Mechanical Response and Texture Evolution of Polycrystalline Metals
Establishing Empirical Repeatability of X-Ray Diffraction Measurements During Elastic Cyclic Loading
From Microstructure to Model: A Statistical Framework for Microstructural Uncertainty Quantification
From Process to Properties: Enabling Model-Based Material Definition for Robotic Open-Die Forging
How to Assess the Adequacy of Model Validation?
Integrated Process-Structure-Property Simulations for Additive Manufacturing Using the Open-Source Materialite Package
Integrating 3D Synchrotron Crack Growth Data With Crystal Plasticity Simulations Using the Open-Source Materialite Framework
Latent Learning for Predictive and Generative Modeling of Microstructure-Property Relationships in Metals
Machine Learning Framework for Microstructure and Material State Assessment in Robotic Open-Die Forging
Microstructure-Informed Constitutive Modeling of Fuel Cladding: A Fast-Execution Framework for Performance Assessment and Uncertainty Quantification
Microstructure Dependence of Spall Failure in Mg-Al Alloys at Extreme Strain Rates
Microstructure Evolution via Latent Transformers for 3D Materials Simulations and Characterization
Modeling Hydrogen Influence on Ni201 Plastic Behavior and Validation Using In-Situ X-Ray Diffraction Microscopy Experimental Data
Modeling plastic deformation of metals in fusion reactors: quantifying the homogenized effects of microstructural scale uncertainty
Multiscale Crystal Plasticity Parameter Calibration: Non-Uniqueness in Bayesian and Multi-Objective Approaches
Porous Crystal Plasticity Modeling of Additively Manufactured Alloy 718 for Fatigue Life Prediction
PRISM Plasticity new feature Indentation and Creep
Probing the Effects of Anisotropy on the Micromechanical and Microstructural Evolution of Structural Materials Using In Situ Synchrotron X-Ray Diffraction
Providing a Rigorous Benchmark Measurement Foundation for the AM Modeling Community
Sequential Bayesian Parameter Identification for Ductile Damage Models Using Multimodal Experimental Data
Source-Separated Uncertainty Quantification in the Stochastic Plasticity of Cold Sprayed Al 7075 Using Profilometry-Based Indentation Plastometry and Residual Analysis
Speaking the Same Language: The Role of Model Validation in Shaping Measurement Strategies at the CHESS Structural Materials Beamline
SURGE Ahead: Rethinking Qualification for Additive Manufacturing
The Significance of Capturing Spatial Microstructural Variability in Strut-Level Material Models for Local Stress Analysis of AM Lattices
Towards a Digital Twin of Single Crystal Turbine Blades for Lifetime Assessment Using X-Ray Tomography and Transmission Laue Diffraction
Understanding Elastoplastic Deformation at the Grain Scale Using High-Energy Diffraction Microscopy and Graph Theory
Understanding Machine Learning Model Predictions for In Situ Material Property Estimation in Digital Qualification Frameworks
Using a Calibrated Virtual Beamline to Validate Crystal Plasticity Models Against Far-Field 3DXRD Data on Multiple Length Scales
Variability of Single Crystal Deformation and Failure
Verification, Validation, and Uncertainty Quantification in the OPAL Digital Twin
Questions about ProgramMaster? Contact programming@programmaster.org | TMS Privacy Policy | Accessibility Statement