2006 Fiscal Year Final Research Report Summary
Prediction of deformation in fast cold metal forming based on microstructure
| Project/Area Number |
16560091
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Production engineering/Processing studies
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| Research Institution | The University of Electro-Communications |
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Principal Investigator |
KUBOKI Takashi The University of Electro-Communications, Faculty of Electro-Communications, Associate Professor, 電気通信学部, 助教授 (90361823)
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| Co-Investigator(Kenkyū-buntansha) |
MURATA Makoto The University of Electro-Communications, Faculty of Electro-Communications, Professor, 電気通信学部, 教授 (10106883)
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| Project Period (FY) |
2004 – 2006
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| Keywords | Aging / Diffusion of carbon / Strain hardening / Transfer of carbon / Fraction of ferrite / upsetting / Cold metal forming |
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| Research Abstract |
This research project has been carried out in the following three stages for "Prediction of deformation behaviour in fast cold metal forming based on microstructure"
Stage 1.Modelling of carbon diffusion in microstructure
Aging progress was quantitatively evaluated by experiments under the condition of constant temperature. A new evaluation factor, "hardening ratio" was introduced selecting medium-carbon steel, which has ferrite-pearlite microstructure. Based on SEM image of carbon steel, FEM mesh was constructed and an analytical method was developed for the prediction of aging. With comparison of analytical and experimental results, a new coefficient, "carbon transfer coefficient", was qualitatively determined.
Stage 2.Analytical method of deformation in cold metal forming considering carbon diffusion in microstructure
An analytical method was proposed and developed for calculation of (1)plastic deformation and (2)thermal history in macro scale and (3)diffusion of carbon in microstructure in micro scale. A new assumption on carbon diffusion under the changing temperature was introduced and the analytical method proposed in stage 1 was expanded. Moreover, by enabling transfer of data between macro and micro scales, total analytical model was developed to calculate (1)plastic deformation and (2)thermal history in macro scale and (3)diffusion of carbon in micro scale simultaneously.
Stage 3.Neural network for the prediction of deformation in cold metal forming
Correlation between microstructure and aging progress was investigated for concise calculation of aging progress. As the result, it was revealed that the total boundary length around the spine shaped cementite was a dominant factor of aging progress. By considering the characteristics of aging related to the boundary length around cementite, a neural network was constructed in order to evaluate the aging progress based on microstructure.
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