Published August 6, 2024 | Version 1.0
Dataset Open

Ab-initio data repository for physics-informed data-driven model

  • 1. ROR icon KTH Royal Institute of Technology
  • 1. ROR icon KTH Royal Institute of Technology
  • 2. Centre of Excellence ENSEMBLE3 Sp. z o. o., Wolczynska Str. 133: Warsaw, PL

Description

Ab-initio Data Repository for Physics-Informed Data-Driven Model

This repository saved the precise Density Functional Theory (DFT) calculations and Vienna Ab initio Simulation Package (VASP) codes to provide a comprehensive dataset for physics-informed models. It specifically considers the steelmaking process by focusing on different types of non-metallic inclusions (NMIs) within the steel melt.

Data Sets Included:

  1. Hamaker Constants values
  2. Coagulation coefficients and Entrapment Probabilities
  3. Kinematic Viscosity of SAE 1055 steel
  4. Dynamic Viscosity of SAE 1055 steel
  5. Dielectric function of oxides
  6. Lattice parameters for molten and bulk Iron
  7. Surface Tension of molten Fe.

Purpose and Application: This repository is designed to support advanced physics-informed modeling approaches, such as those using machine learning algorithms to predict clogging and inclusion behaviors in steelmaking processes.

The datasets includes following types of NMIs with detailed characteristics in the size range of 1-10 µm:

  • Al2O3
  • CaO
  • MgO
  • MgAl2O4
  • CaS
  • ZrO2

Files

Al2O3-Al2O3_Van_der_Waals_Force.png

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Additional details

Funding

European Commission
INEVITABLE - Optimization and performance improving in metal industry by digital technologies 869815
European Commission
HIYIELD - Highly efficient technologies for increased yields in steelmaking processes and reduced environmental impact 101058694

Dates

Available
2024-08-06