Richard / Shabadi / Sommitsch Computational Materials Science and Materials Informatics

Erscheinungsjahr 2026
ISBN: 978-3-0364-3064-5
Verlag: Trans Tech Publications
Format: PDF
Kopierschutz: 0 - No protection

E-Book, Englisch, 100 Seiten

This special edition is dedicated to advances in computational materials science and modelling approaches that underpin the understanding and prediction of mechanical properties, behaviour and microstructure of modern materials. The articles collection offers a comprehensive and forward-looking perspective on theory-driven and computationally assisted materials engineering, providing valuable insights for many specialists in materials science.

Autoren/Hrsg.

Richard, Caroline

Shabadi, Raj

Sommitsch, Christof

Ionescu, Mihail

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
• Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie

Inhaltsverzeichnis

Preface
Reduced-Order Representations of Crystallographic Texture for Application to Surrogate Models of Material Behaviour
Simple Flow Rules for Three-Phase Viscoplastic Materials
Modelling Combined Hardening Mechanisms in Alloys through the Analysis of Dislocation Percolation
Redesign of Low-Activation Vanadium Alloys Based on Impurity Control for Fusion Reactor Applications
CALPHAD-Based Modelling of Microstructural Evolution during D.C. Casting and Homogenization of AA3003 Aluminium Alloy
Atomistic Investigation of Stability and Segregation of Alphagenic and Betagenic Solutes in Hexagonal Titanium
Simulation-Driven Insights into Heat Transfer during Copper Mold Casting of Magnesium-Based Bulk Metallic Glasses
Verification of a Novel Mathematical Model for Determination of the Biomass Specific Growth Rate in Bioprocesses Using Relative Change in Biomass Measurements
Numerical Investigation of the Influence of Residual Stresses after Additive Manufacturing on the Fatigue Crack Propagation in 5xxx Aluminum Alloys
Application of Artificial Neural Networks for Microstructure Models ALFLOW and ALSOFT
Sintering Process Analysis of Aluminum Matrix Composites Using Machine Learning
Testing Theories and Simulations on Phase Coarsening by Experiments