Computer Methods in Materials Science
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ISSN 2720-4081
e-ISSN: 2720-3948
Issue Date
2021
Volume
Vol. 21
Number
No 3
Description
Journal Volume
Computer Methods in Materials Science
Vol. 21 (2021)
Projects
Pages
Articles
The role of neighborhood density in the random cellular automata model of grain growth
(Wydawnictwa AGH, 2021) Czarnecki, Michał; Sitko, Mateusz; Madej, Łukasz
The paper focuses on adapting the random cellular automata (RCA) method concept for the unconstrained grain growth simulation providing digital microstructure morphologies for subsequent multi-scale simulations. First, algorithms for the generation of initial RCA cells alignment are developed, and then the influence of cells density in the computational domain on grain growth is discussed. Three different approaches are proposed based on the regular, hexagonal, and random cells' alignment in the former case. The importance of cellular automata (CA) cell neighborhood definition on grain growth model predictions is also highlighted. As a research outcome, random cellular automata model parameters that can replicate grain growth without artifacts are presented. It is identified that the acceptable microstructure morphology of the solid material is obtained when a mean number of RCA cells in the investigated neighborhood is higher than ten.
Effective properties of periodic media in elastodynamic problems
(Wydawnictwa AGH, 2021) Yera, Rolando; Méndez, Carlos Gustavo; Sánchez, Pablo Javier; Huespe, Alfredo Edmundo
This paper describes a homogenization model for evaluating the effective elastodynamic properties of acoustic metamaterials in problems involving wave propagation. The methodology is based on determining the constitutive equations in terms of averaged quantities observed at the macroscale. In this sense, the approach very closely follows the pioneering ideas introduced by Willis, and afterwards, followed by several authors in the last ten years. The distinctive characteristic of our approach is that we write the microscale equation in the spatial domain. The model is validated with previous results published in the literature, and our results replicate them almost exactly. The resulting homogenization model could be used as an additional tool for the topology design of acoustic metamaterials.
Mathematical modelling of the continuous casting of blooms and beam blanks
(Wydawnictwa AGH, 2021) Gomes, Daniela Fátima; Braga, Bernardo Martins; Tavares, Roberto Parreiras; Bagatini, Maurício Covcevich
Defects and discontinuities generated in continuous casting are directly related to heat transfer during the process and the stresses to which the material is subjected. Knowledge of these phenomena is essential for both process safety and the quality of the final product. The aim of this work is to analyze the thermo-mechanical behavior of blooms and beam blanks during continuous casting. The continuous casting machine considered in this study is used to cast both blooms and beam blanks. The secondary cooling can be divided into cooling zone z0, cooling zone z1, cooling zone z2, and cooling zone z3. For each geometry, there are specific molds, z0, z1, z2 (sprays and support rollers), which need to be replaced when there is a geometry shift. The changing of the cooling segments brings security risks for the operators and reduces the continuous casting availability. Therefore, it is desired to have a common z2 for both blooms and beam blanks to reduce operational risk exposure and increase the machine production rate. For this to be possible, it is necessary to assess the temperature and resistance of the solidified skin, the effects of thermal stresses, ferrostatic pressure, and contact stresses. This work is the first step in this study. A thermo-mechanical model was developed for both geometries. The thermal model was verified by temperature measurement and shell measurements of blackouts. Finally, the results were analyzed and compared.
Conversion of compression test data into flow curve, accounting for barrelling
(Wydawnictwa AGH, 2021) Khoddam, Shahin; Hodgson, Peter D.
Current solutions to convert the axis-symmetric compression test (ACT) data to flow data ignore the barrelling deformation in the sample. This work presents a solution for the test which accounts for the sample's barrelling by discretising it into a finite number of layers of different radii. The solution assumes a constant and sliding friction at the anvil-sample interface. The sample's flow behaviour is identified by combining a recent kinematic solution of the test, Prandtl-Reuss-Mises's equations and a slab-analysis of the layers. It also involves an averaging of the effective plastic stresses developed in the individual layers. The solution is verified for a special case of no-barrelling which matches the currently used solution.
Evolutionary data driven modelling and many objective optimization of non linear noisy data in the blast furnace iron making process
(Wydawnictwa AGH, 2021) Mahanta, Bashista Kumar; Chakraborti, Nirupam
The optimization of process parameters in modern blast furnace operation, where both control and accessing large data set with multiple variables and objectives is a challenging task. To handle such non-linear and noisy data set deep learning techniques have been used in recent time. In this study an evolutionary deep neural network algorithm (EvoDN2) has been applied to derive a data driven model for blast furnace. The optimal front generated from deep neural network is compared against the optimal models developed from bi-objective genetic programming algorithm (BioGP) and evolutionary neural network (EvoNN). The optimization process is applied to all the training models by using constraint based reference vector evolutionary algorithm (cRVEA).