Computer Methods in Materials Science
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ISSN 2720-4081
e-ISSN: 2720-3948
Issue Date
2021
Volume
Vol. 21
Number
No 4
Description
Journal Volume
Computer Methods in Materials Science
Vol. 21 (2021)
Projects
Pages
Articles
Processes simulations with multiscale materials models using a dedicated interface
(Wydawnictwa AGH, 2021) Smyk, Grzegorz; Szeliga, Danuta
The main goal of this work is the integration of in-house software with commercial numerical software based on the finite element method (FEM). The main idea is to develop a universal interface to perform process simulations with multiscale models. The interface allows the combination of external procedures with commercial software with minimum programmer's work putting in integration. As an example, the model of material recrystallization of steel was implemented, added to the commercial application, and the software was tested for a process defined as a sequence of compression and cooling. The material model takes into consideration each type of recrystallization that occurs during a sequence of thermal and mechanical processing such as static recrystallization (SRX), dynamic recrystallization (DRX), and meta-dynamic recrystallization (MDRX). It allows the prediction of recrystallized volume fraction (X) and grain growth on each step of numerical simulation for each Gauss point in the computation domain. The presented multiscale model of process sequences not only allows to calculate microscale model parameters such as grain growth and recrystallized volume fraction, but also reflects the impact of the microscale model on macroscale parameters.
Aircraft wing structural design application in MATLAB App Designer
(Wydawnictwa AGH, 2021) Bilal, Ahmed; Siddiqui, Muhammad Faisal; Abbas, Messam; Mansoor, Mohtashim
This study focuses on developing an automated application in the MATLAB® App Designer module, based on basic structural members and different theories for various loading cases, providing ballpark values of bending and torsional stiffness and sizing of the load-carrying structural member at a span wise location. All the code developed on MathWorks (2018) is automated using the App Designer module. In this approach, governing equations of structural members under different types of loading are solved in MATLAB IDE with the assumption that in the preliminary phase MATLAB App Designer provides an easy drag and drop type application developer that can be easily subsumed in any mathematical automation process.
On the approach to the analysis of the growth of epitaxial layers by pulsed laser deposition
(Wydawnictwa AGH, 2021) Pankratov, Evgenij Leonidovič
This paper considers an analytical approach for the prognosis of mass and heat transport during the growth of epitaxial layers by means of pulsed laser deposition. The approach provides the opportunity to make a prognosis which takes into account the spatial and temporal variations of their parameters and, at the same time, the nonlinearity of these processes. Based on this approach, the influence of the variation of several parameters on the growth process is investigated.
A repeatability study of artificial neural network predictions in flow stress model development for a magnesium alloy
(Wydawnictwa AGH, 2021) Siewior, Hubert; Madej, Łukasz
This work is devoted to an evaluation of the capabilities of artificial neural networks (ANN) in terms of developing a flow stress model for magnesium ZE20. The learning procedure is based on experimental flow-stress data following inverse analysis. Two types of artificial neural networks are investigated: a simple feedforward version and a recursive one. Issues related to the quality of input data and the size of the training dataset are presented and discussed. The work confirms the general ability of feedforward neural networks in flow stress data predictions. It also highlights that slightly better quality predictions are obtained using recursive neural networks.
A dedicated sensitivity analysis and optimization application for industrial processes
(Wydawnictwa AGH, 2021) Myczkowska, Kamila; Szeliga, Danuta
The paper describes the architecture and the use case of the developed Modelbox system for sensitivity analysis (SA), uncertainty analysis (UA) and the subsequent optimization of industrial processes. The proposed solution addresses the most common practical and technical problems encountered by researchers and engineers when performing sensitivity analysis. It combines the functions from the numerical toolbox with a simulation management system. Maintaining usability and a good user experience while managing complex investigations of time-consuming industrial process simulations is a very important feature of the system. Several improvements were introduced to optimize the computation time of analysis/modelling tasks, including the automatization of distributed calculations, persistent, transparent caching of simulation data and duration estimations from collected statistics. The system has the ability to perform remote, parallel, asynchronous computations of both analytic algorithms and numerical simulations. The system is dynamically scalable horizontally by using serverless computing endpoints and thus it can be easily adapted to the user's current needs in a flexible way. Modelbox provides web-based access to analysis/modelling tasks from sampling, SA/UA, optimization to metamodelling. It is extended with numerous interactive visualization components for effective results control. In addition, to access data from the completed analysis, the system supports convergence tracking for SA estimates and intermediate optimization results. The process of controlled cooling of rails was considered as a case study. The formulated optimization task was to find a combination of process parameters that ensures a minimum volume fraction of bainite along with required interlamellar spacing and optimal homogeneity of hardness. Different sensitivity analysis methods were used to evaluate the significance of all variables with respect to their influence on the model output.