053 Inverse analysis on stress-strain curve of single phase microstructures based on the phase-field secant method with data assimilation technique

2015 ◽  
Vol 2015.28 (0) ◽  
pp. _053-1_-_053-2_
Author(s):  
Toshiyuki Koyama ◽  
Yuhki Tsukada ◽  
Yuichiro Kawai
2010 ◽  
Vol 638-642 ◽  
pp. 3325-3330 ◽  
Author(s):  
Toshiyuki Koyama ◽  
Hidehiro Onodera

The secant method proposed by Weng [1] is a practical calculation method to evaluate the stress-strain curve of the two-phase materials, but the shape of the inclusion phase has been often assumed to be a sphere or an ellipsoid in the calculation. In this study, we modified the secant method by utilizing the phase-field micro-elasticity theory [2,3] so as to be able to calculate the SS-curve of the materials consisting arbitrary morphology of microstructure, and applied this method to the conventional microstructures in steels, i.e., the ferrite-bainite two-phase microstructure.


2018 ◽  
Vol 20 (2) ◽  
Author(s):  
Emilio Medrano ◽  
Mauro Quiroga ◽  
Felipe A. Reyes

After fabricating five metallographic specimens of the Cu0.95Al0.05 alloy from electrolytic copper and aluminum, these ones were both microstructurally characterized by using a metallographic optical microscope at room temperature and subjected to mechanical traction in order to chart the stress-strain curve. From the characterization, it has been found out that the Cu0.95Al0.05 microstructure is composed of a single phase, and from the tensile tests, it has been obtained its rupture point, 249.361 MPa. The obtained results were explained in the framework of the theory of metals and metal alloys.


2014 ◽  
Vol 626 ◽  
pp. 81-84
Author(s):  
Akinori Yamanaka ◽  
Tomohiro Takaki

A numerical model of dynamic strain-induced ferrite transformation (DSFT) was developed by combining the multi-phase field model with the Kocks–Mecking model. Using the developed model, a three-dimensional simulation of the DSFT in a Fe-C alloy was performed to study the correlation between the variation in flow stress and the microstructure evolution during the DSFT. The simulation results indicated that the developed model successfully simulated the characteristic DSFT behavior, i.e., both the stress–strain curve with a single peak and the formation of an ultrafine-grained ferrite microstructure. The variation in the flow stress during the DSFT was characterized by the volume fraction of the ferrite phase.


SIMULATION ◽  
2021 ◽  
pp. 003754972110315
Author(s):  
B Girinath ◽  
N Siva Shanmugam

The present study deals with the extended version of our previous research work. In this article, for predicting the entire weld bead geometry and engineering stress–strain curve of the cold metal transfer (CMT) weldment, a MATLAB based application window (second version) is developed with certain modifications. In the first version, for predicting the entire weld bead geometry, apart from weld bead characteristics, x and y coordinates (24 from each) of the extracted points are considered. Finally, in the first version, 53 output values (five for weld bead characteristics and 48 for x and y coordinates) are predicted using both multiple regression analysis (MRA) and adaptive neuro fuzzy inference system (ANFIS) technique to get an idea related to the complete weld bead geometry without performing the actual welding process. The obtained weld bead shapes using both the techniques are compared with the experimentally obtained bead shapes. Based on the results obtained from the first version and the knowledge acquired from literature, the complete shape of weld bead obtained using ANFIS is in good agreement with the experimentally obtained weld bead shape. This motivated us to adopt a hybrid technique known as ANFIS (combined artificial neural network and fuzzy features) alone in this paper for predicting the weld bead shape and engineering stress–strain curve of the welded joint. In the present study, an attempt is made to evaluate the accuracy of the prediction when the number of trials is reduced to half and increasing the number of data points from the macrograph to twice. Complete weld bead geometry and the engineering stress–strain curves were predicted against the input welding parameters (welding current and welding speed), fed by the user in the MATLAB application window. Finally, the entire weld bead geometries were predicted by both the first and the second version are compared and validated with the experimentally obtained weld bead shapes. The similar procedure was followed for predicting the engineering stress–strain curve to compare with experimental outcomes.


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