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Updated: Jul 27, 2025

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
Published on: June 7, 2018
An operator splitting scheme for numerical simulation of spinodal decomposition and microstructure evolution of
Abdullah Shah1, Sana Ayub2, Muhammad Sohaib1,2,3
1Department of Mathematics, King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia.
The operator splitting scheme is more computationally efficient for solving the Cahn-Hilliard equation, as demonstrated by simulating spinodal decomposition. All tested numerical schemes exhibit conditional stability.
Area of Science:
- Computational physics
- Materials science
- Numerical analysis
Background:
- The Cahn-Hilliard equation models phase separation phenomena.
- Accurate numerical solutions are crucial for understanding materials evolution.
- Various numerical schemes exist, each with unique computational properties.
Purpose of the Study:
- To compare the computational efficiency and stability of three numerical schemes for the Cahn-Hilliard equation.
- To validate the numerical solutions by simulating spinodal decomposition.
- To identify the most efficient scheme for practical applications.
Main Methods:
- Numerical simulation of spinodal decomposition using the Cahn-Hilliard equation.
- Implementation and comparison of operator splitting, linearly stabilized splitting, and semi-implicit Euler's schemes.
- Analysis of conditional stability and computational performance.
Main Results:
- All three numerical schemes were found to be conditionally stable.
- The operator splitting scheme demonstrated superior computational efficiency compared to the other two.
- Numerical experiments successfully validated the simulation of spinodal decomposition.
Conclusions:
- The operator splitting scheme is a computationally efficient method for solving the Cahn-Hilliard equation.
- The choice of numerical scheme impacts computational performance without compromising stability.
- This study provides valuable insights for selecting numerical methods in materials science simulations.
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