Effects of initial microstructure and thermomechanical processing parameters on microstructures and mechanical properties of ultrafine grained dual phase steels

2014 ◽  
Vol 612 ◽  
pp. 54-62 ◽  
Author(s):  
Yousef Mazaheri ◽  
Ahmad Kermanpur ◽  
Abbas Najafizadeh ◽  
Navid Saeidi
Keyword(s):  
Mechanical Properties ◽  
Thermomechanical Processing ◽  
Processing Parameters ◽  
Dual Phase ◽  
Dual Phase Steels ◽  
Initial Microstructure ◽  
Ultrafine Grained ◽  
Microstructures And Mechanical Properties

Mechanical Properties of Fine-Grained and Ultrafine-Grained Ti-6Al-4V with Equiaxed and Bimodal Microstructures

2016 ◽  
Vol 879 ◽  
pp. 344-349 ◽  
Author(s):  
Yan Chong ◽  
Nobuhiro Tsuji
Keyword(s):  
Mechanical Properties ◽  
Thermomechanical Processing ◽  
Uniform Elongation ◽  
True Strain ◽  
Tensile Tests ◽  
Initial Microstructure ◽  
Equiaxed Microstructure ◽  
Fine Grained ◽  
Ultrafine Grained ◽  
Mean Grain Size

With the purpose of fabricating equiaxed and bimodal Ti-6Al-4V alloy with different grain/primary α (αp) sizes, thermomechanical processing and additional annealing were carried out on samples with martensite initial microstructure. Deformation at 700°C with a strain rate of 0.01s-1 to a true strain of 0.8 could effectively break the martensite initial microstructure into ultrafine-grained (UFG) equiaxed microstructure (mean grain size of 0.51μm) with reasonable uniformity. Subsequent annealing at 930°C with different periods were conducted to change the equiaxed microstructure into bimodal microstructures. The holing time proved to be more critical than heating rate for determining the αp size. An UFG bimodal Ti-6Al-4V with the average αp size of 0.55μm was successfully obtained for the first time by annealing the UFG equiaxed Ti-6Al-4V at 930°C for 2 seconds. The mechanical properties of the equiaxed and bimodal Ti-6Al-4V with different grain/αp sizes were evaluated by tensile tests at room temperature. The bimodal Ti-6Al-4V showed superior balance between strength and uniform elongation than that of the equiaxed Ti-6Al-4V. Moreover, the uniform elongation in the bimodal Ti-6Al-4V was nearly unaffected by reduction of the αp size.

Prediction of Ferrite-Martensite Dual-Phase Steels Mechanical Properties by Use of Artificial Neural Networks

2013 ◽  
Vol 773-774 ◽  
pp. 268-274
Author(s):  
Amir Ghiami ◽  
Ramin Khamedi
Keyword(s):  
Mechanical Properties ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Back Propagation ◽  
Total Elongation ◽  
Ultimate Tensile Stress ◽  
Dual Phase ◽  
Dual Phase Steels ◽  
Good Ability ◽  
Artificial Neural

This paper presents an investigation of the capabilities of artificial neural networks (ANN) in predicting some mechanical properties of Ferrite-Martensite dual-phase steels applicable for different industries like auto-making. Using ANNs instead of different destructive and non-destructive tests to determine the material properties, reduces costs and reduces the need for special testing facilities. Networks were trained with use of a back propagation (BP) error algorithm. In order to provide data for training the ANNs, mechanical properties, inter-critical annealing temperature and information about the microstructures of many specimens were examined. After the ANNs were trained, the four parameters of yield stress, ultimate tensile stress, total elongation and the work hardening exponent were simulated. Finally a comparison of the predicted and experimental values indicates that the results obtained from the given input data reveal a good ability of the well-trained ANN to predict the described mechanical properties.

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