scholarly journals Integrated Computational Materials Engineering (ICME) Tools for Optimizing Strength of Forged Al-Li Turbine Blades for Aircraft Engines Final Report CRADA No. TC02238.0

2021 ◽  
Author(s):  
A Arsenlis ◽  
J Allison
Keyword(s):  
Turbine Blades ◽  
Final Report ◽  
Aircraft Engines ◽  
Materials Engineering ◽  
Integrated Computational Materials Engineering ◽  
Computational Materials

Optimization of Magnesium Alloy Casting Process: An Integrated Computational Materials Engineering (ICME) Approach

2021 ◽  
Vol 1035 ◽  
pp. 808-812
Author(s):  
Xing Yang Chang ◽  
Qi Shen ◽  
Wen Xue Fan ◽  
Hai Hao
Keyword(s):  
Magnesium Alloy ◽  
Process Optimization ◽  
Casting Process ◽  
Mold Temperature ◽  
Pressure Casting ◽  
Alloy Casting ◽  
Materials Engineering ◽  
Integrated Computational Materials Engineering ◽  
Computational Materials ◽  
Low Efficiency

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.

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