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A Comparative Study on Arrhenius-Type Constitutive Models with Regression Methods
Lee, Kyunghoon,Murugesan, Mohanraj,Lee, Seung-Min,Kang, Beom-Soo The Korean Society for Technology of Plasticity 2017 소성가공 : 한국소성가공학회지 Vol.26 No.1
A comparative study was performed on strain-compensated Arrhenius-type constitutive models established with two regression methods: polynomial regression and regression Kriging. For measurements at high temperatures, experimental data of 70Cr3Mo steel were adopted from previous research. An Arrhenius-type constitutive model necessitates strain compensation for material constants to account for strain effect. To associate the material constants with strain, we first evaluated them at a set of discrete strains, then capitalized on surrogate modeling to represent the material constants as a function of strain. As a result, disparate flow stress models were formed via the two different regression methods. The constructed constitutive models were examined systematically against measured flow stresses by validation methods. The predicted material constants were found to be quite accurate compared to the actual material constants. However, notable mismatches between measured and predicted flow stresses were revealed by the proposed validation techniques, which carry out validation with not the entire, but a single tensile test case.
Process Metamorphosis and On-Line FEM for Mathematical Modeling of Metal Rolling-Part I: Theory
Zamanian, A.,Nam, S.Y.,Shin, T.J.,Hwang, S.M. The Korean Society for Technology of Plasticity 2019 소성가공 : 한국소성가공학회지 Vol.28 No.2
This paper introduces a new concept - on-line FE model, as applied to metal rolling. The new technology allows for completion of process simulation within a tiny fraction of a second without loss of high-level prediction accuracy inherent to FEM. The three steps of an on-line FE model design namely, process metamorphosis, mesh design, and process variable design, are described in detail. The procedure is demonstrated step by step through designing actual on-line models for the prediction of the dog-bone profile in edge rolling. The validity and prediction accuracy of the on-line FE models are analyzed and discussed.
Zamanian, A.,Nam, S.Y.,Shin, T.J.,Hwang, S.M. The Korean Society for Technology of Plasticity 2019 소성가공 : 한국소성가공학회지 Vol.28 No.2
In this paper, we examine the application of a new concept - on-line FE model in various metal rolling processes. This technology allows for completion of process simulation within a tiny fraction of a second without losing the high level of prediction accuracy inherent to FEM. The procedure is systematically demonstrated through the design of actual on-line models for the prediction of the width spread in horizontal rolling of the slab using a dog bone profile and horizontal rolling of the strip with a strip profile. The validity and the prediction accuracy of the on-line FE models were analyzed and discussed.
Ductile Fracture in the Central Region of Circular Plate in Rotary Forging
Park, Seogou,Oh, Hung-Kuk The Korean Society for Technology of Plasticity 1996 소성가공 : 한국소성가공학회지 Vol.5 No.4
The present investigation is concerned with application of theory on fracture to the prediction of workability of materials in rotary forging with special reference to center crack. The validity of the theory on ductile fracture was examined by the experimental data. Then the workability of materials in rotary forging was determined.
Further Development of Vision-Based Strain Measurement Methods to Verify Finite Element Analyses
Kim, Hyung jong,Lee, Daeyong The Korean Society for Technology of Plasticity 1996 소성가공 : 한국소성가공학회지 Vol.5 No.4
One of the preferred methods that can be used to verify the results of finite element analysis is to measure surface strains of the deformed part for purpose of direct comparison with simulation results. Instead of using the usual manual method the vision-based measurement method is capable of determining surface geometry and strain from the deformed grid pattern automatically with the help of a computer. To obtain strain distribution over an area, the coordinates of such a surface grid are determined from the multiple video images by applying the photogrammetry principle. Methods to improve the overall accuracy of the vision-based strain measurement system are explored and the possible accuracies that can be attained by such a measurement method are discussed. A major emphasis is placed on the initial grid application method its accuracy and ease of subsequent image processing. Finite element analyses of limiting dome height(LDH) test are carried out and the results of them are compared with exsperimen-tal data.
Comparative Study on Surrogate Modeling Methods for Rapid Electromagnetic Forming Analysis
Lee, Seungmin,Kang, Beom-Soo,Lee, Kyunghoon The Korean Society for Technology of Plasticity 2018 소성가공 : 한국소성가공학회지 Vol.27 No.1
Electromagnetic forming is a type of high-speed forming process to deform a workpiece through a Lorentz force. As the high strain rate in an electromagnetic-forming simulation causes infeasibility in determining constitutive parameters, we employed inverse parameter estimation in the previous study. However, the inverse parameter estimation process required us to spend considerable time, which leads to an increase in computational cost. To overcome the computational obstacle, in this research, we applied two types of surrogate modeling methods and compared them to each other to evaluate which model is best for the electromagnetic-forming simulation. We exploited an artificial neural network and we reduced-order modeling methods. During the construction of a reduced-order model, we extracted orthogonal bases with proper orthogonal decomposition and predicted basis coefficients by utilizing an artificial neural network. After the construction of the surrogate models, we verified the artificial neural network and reduced-order models through training and testing samples. As a result, we determined the artificial neural network model is slightly more accurate than the reduced-order model. However, the construction of the artificial neural network model requires a considerably larger amount of time than that of the reduced-order model. Thus, a reduced order modeling method is more efficient than an artificial neural network for estimating the electromagnetic forming and for the rapid approximation of structural simulations which needs repetitive runs.