Computer Methods in Materials Science
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ISSN 2720-4081
e-ISSN: 2720-3948
Issue Date
2023
Volume
Vol. 23
Number
No. 2
Description
Journal Volume
Computer Methods in Materials Science
Vol. 23 (2023)
Projects
Pages
Articles
Physical and numerical simulation of the production chain of fasteners manufactured of 32CrB4 steel control-cooled in the stelmor process to develop the multiphase microstructure
(Wydawnictwa AGH, 2023) Piwowarczyk, Michał; Wolańska, Natalia; Wilkus, Marek; Pietrzyk, Maciej; Rauch, Łukasz; Kuziak, Roman; Pidvysots'kyy, Valery; Radwański, Krzysztof
The development of the concept of Thermomechanical Controlled Processing (TMCP) in the wire rod rolling mill of CMC Poland has opened up new opportunities for the production of fasteners without the application of heat treatment. The crucial effect of TMCP in the case of wire rod rolling is its capability of shaping fine austenite grain size following the last pass, typically below 20-25 μm in the wire rod cross-section. This is a prerequisite for obtaining the required cold workability level for the cold forming of fasteners, even if hard constituents (bainite, martensite) are present in the wire rod structure. In this paper, the physical simulation and numerical modelling capabilities were described for the design of cooling conditions in the Stelmor process and cold heading operation. The investigated material was conventional 32CrB4 grade used for the fasteners production with the application of heat treatment.
Accounting for the random character of nucleation in the modelling of phase transformations in steels
(Wydawnictwa AGH, 2023) Poloczek, Łukasz; Kuziak, Roman; Foryś, Jakub; Szeliga, Danuta; Pietrzyk, Maciej
In our earlier work, a stochastic model of multi-stage deformation at elevated temperatures was developed. The model was applied to calculate histograms of dislocation density and grain size at the onset of phase transformation. The histograms were used as input data for the simulation of phase transitions using the traditional deterministic model. Following this approach, microstructural inhomogeneity was predicted for different cooling conditions. The results obtained, showing the effect of dislocation density and inhomogeneity of austenite grain size on the microstructural inhomogeneity of the final product, can be considered reliable as they are based on material models determined in previous publications and validated experimentally. The aim of the present work was to extend the model by taking into account the stochastic nature of nucleation during phase transitions. The analysis of existing stochastic models of nucleation was performed, and a model for ferritic transformation in steels was proposed. Simulations for constant cooling rates as well as for industrial cooling processes of steel rods were performed. In the latter case, uncertainties in defining the boundary conditions and segregation of elements were also considered. The reduction of the computing costs is an important advantage of the model, which is much faster when compared to full field models with explicit microstructure representation.
Comparing deterministic and statistical approaches for predicting »short can« defects in aluminium beverage can production
(Wydawnictwa AGH, 2023) Baran, Wojciech; Regulski, Krzysztof; Kąc, Sławomir; Milenin, Andriy
In the production of beverage cans, »short can« defects in the form of material discontinuities can occur during the deep drawing of cylindrical thin-walled aluminium products. These defects have a significant impact on production efficiency and scrap generation, and their occurrence is influenced by material and process properties. To determine the main influence of material on defect occurrence, two approaches were used: deterministic analysis of mechanical properties and microstructure, as well as statistical processing of production data using decision tree models. The latter approach was found to be more efficient, and a numerical tool was developed based on this approach to predict and reduce defect occurrence in the production process.
Viscoelastic characterization of additively manufactured acrylonitrile butadiene styrene
(Wydawnictwa AGH, 2023) Witek, Szczepan
The main objective of this work was to characterize the viscoelastic properties of additively manufactured Acrylonitrile Butadiene Styrene based on tensile stress relaxation tests. The stress relaxation measurements were conducted with a temperature range of 25-100°C. The two-layer viscoplastic constitutive model was adopted to describe the elastic and viscous behavior of the investigated material. The model parameters were calibrated using an inverse analysis and stress relaxation data. The model's predictive capabilities were assessed by comparing the model predictions with experimental data not included in the calibration process.
Machine learning methods for diagnosing the causes of die-casting defects
(Wydawnictwa AGH, 2023) Okuniewska, Alicja; Perzyk, Marcin; Kozłowski, Jacek
The research was focused on analyzing the causes of high-pressure die-casting defects, more specifically on casting leakage, which is considered perhaps the most important and common defect. The real data used for modelling was obtained from a high-pressure die-casting foundry that manufactures aluminum cylinder blocks for the world's leading automotive brands. This paper compares and summarizes the results of applying advanced modelling using artificial neural networks, regression trees, and support vector machines methods to select artificial neural networks as the most effective method to perform a multidimensional optimization of process parameters to diagnose the causes of die-casting defects and to indicate the future research scope in this area. The developed system enables the prediction of the level of defects in castings with satisfactory accuracy and is therefore a highly relevant reference for process engineers of high-pressure foundries. This article indicates exactly which process parameters significantly influence the formation of a defect in a casting.