scholarly journals Progress of Physics-based Mean-field Modeling and Simulation of Steel

Author(s):  
Philipp Retzl ◽  
Yao V. Shan ◽  
Evelyn Sobotka ◽  
Marko Vogric ◽  
Wenwen Wei ◽  
...  

AbstractThe progress of mean-field modeling and simulation in steel is presented. In the modeling, the focus is put on the development and application of a physical modeling base, including Calphad, diffusion assessment, nucleation and growth of precipitates, and dislocation dynamics. This leads to an improved prediction of the materials response after different thermo-mechanical treatments in terms of microstructure evolution and mechanical properties. The presented case studies represent the success of the integrated computational materials engineering approach.

2021 ◽  
Vol 1035 ◽  
pp. 808-812
Author(s):  
Xing Yang Chang ◽  
Qi Shen ◽  
Wen Xue Fan ◽  
Hai Hao

Traditional casting process optimization usually adopts empirical trial and error method. Process parameters were modified repeatedly within a certain range until a satisfactory solution is obtained, which is costly and inefficient. Therefore, based on integrated computational materials engineering, Magnesium Alloy Simulation Integrated Platform (MASIP) was constructed. MASIP completed the automatic operation of the entire simulation process from the CAD model data input to the process-microstructure-performance. It realized the rapid optimization simulation prediction of process-microstructure-performance, and solved the problems of long cycle and low efficiency of traditional process optimization. This paper studied the low-pressure casting optimization process of magnesium alloy thin-walled cylindrical parts based on MASIP. The calculation took casting temperature, mold temperature and holding pressure as the optimized variables, and the yield strength of the casting as the target variable. The experimental results showed that MASIP can fairly complete the structure simulation and performance prediction of castings, greatly reduce the time cost of the calculation process, and improve the efficiency of process optimization.


JOM ◽  
2017 ◽  
Vol 69 (12) ◽  
pp. 2532-2537 ◽  
Author(s):  
Xiaowo Wang ◽  
Zhijie Xu ◽  
Ayoub Soulami ◽  
Xiaohua Hu ◽  
Curt Lavender ◽  
...  

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