Special Issue "Computational Materials Modeling, Analysis and Applications"

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".

Deadline for manuscript submissions: 1 August 2020.

Special Issue Editor

Dr. Fernando Cortés
E-Mail Website
Guest Editor
Head of the department of Mechanics, Design and Industrial Management, University of Deusto, Avda de las Universidades 24, 48007 Bilbao, Spain
Interests: computational mechanics; materials modeling; structural dynamics; damping

Special Issue Information

Dear Colleagues,

This Special Issue is aimed at publishing original contributions related to the analysis of the behavior of materials by means of computational methods for practical engineering applications. Studies about all types of materials and analyses of different kind of properties are welcome. However, it must be clear that the application in science or engineering is addressed.

The contributions must be focused on computational aspects as the development of new mathematical models and numerical methods, or the application of existing ones in engineering analysis, allowing extracting new relevant conclusions for practical purposes. Results without experimental verification or without comparison with other established models or methods are not recommended.

Dr. Fernando Cortés
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Metals, polymers, ceramics, composites
  • Micro, meso, macro and multi scales
  • Properties: mechanical, electrical, optical, thermal, etc.
  • Mathematical models, numerical methods
  • Science and engineering applications

Published Papers (5 papers)

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Research

Open AccessArticle
Simulation of Thermal Behavior of Glass Fiber/Phenolic Composites Exposed to Heat Flux on One Side
Materials 2020, 13(2), 421; https://doi.org/10.3390/ma13020421 - 16 Jan 2020
Abstract
A 3D thermal response model is developed to evaluate the thermal behavior of glass fiber/phenolic composite exposed to heat flux on one side. The model is built upon heat transfer and energy conservation equations in which the heat transfer is in the form [...] Read more.
A 3D thermal response model is developed to evaluate the thermal behavior of glass fiber/phenolic composite exposed to heat flux on one side. The model is built upon heat transfer and energy conservation equations in which the heat transfer is in the form of anisotropic heat conduction, absorption by matrix decomposition, and diffusion of gas. Arrhenius equation is used to characterize the pyrolysis reaction of the materials. The diffusion equation for the decomposition gas is included for mass conservation. The temperature, density, decomposition degree, and rate are extracted to analyze the process of material decomposition, which is implemented by using the UMATHT (User subroutine to define a material’s thermal behavior) and USDFLD (User subroutine to redefine field variables) subroutines via ABAQUS code. By comparing the analysis results with experimental data, it is found that the model is valid to simulate the evolution of a glass fiber/phenolic composite exposed to heat flux from one side. The comparison also shows that longer time is taken to complete the pyrolysis reaction with increasing depth for materials from the numerical simulation, and the char region and the pyrolysis reaction region enlarge further with increasing time. Furthermore, the decomposition degree and temperature are correlated with depths, as well as the peak value of decomposition rate and the time to reach the peak value. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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Open AccessArticle
Numerical Modeling for Simulation of Compaction of Refractory Materials for Secondary Steelmaking
Materials 2020, 13(1), 224; https://doi.org/10.3390/ma13010224 - 04 Jan 2020
Abstract
The purpose of this work is to simulate the powder compaction of refractory materials, using the discrete element method (DEM). The capability of two cohesive contact models, implemented in different DEM packages, to simulate the compaction of a mixture of two refractory materials [...] Read more.
The purpose of this work is to simulate the powder compaction of refractory materials, using the discrete element method (DEM). The capability of two cohesive contact models, implemented in different DEM packages, to simulate the compaction of a mixture of two refractory materials (dead burnt magnesia (MgO) and calcined alumina (Al2O3)) was analyzed, and the simulation results were compared with experimental data. The maximum force applied by the punch and the porosity and final shape quality of the compact were examined. As a starting point, the influence of Young’s modulus (E), the cohesion energy density (CED), and the diameter of the Al2O3 particles (D) on the results was analyzed. This analysis allowed to distinguish that E and CED were the most influential factors. Therefore, a more extensive examination of these two factors was performed afterward, using a fixed value of D. The analysis of the combined effect of these factors made it possible to calibrate the DEM models, and consequently, after this calibration, the compacts had an adequate final shape quality and the maximum force applied in the simulations matched with the experimental one. However, the porosity of the simulated compacts was higher than that of the real ones. To reduce the porosity of the compacts, lower values of D were also modeled. Consequently, the relative deviation of the porosity was reduced from 40–50% to 20%, using a value of D equal to 0.15 mm. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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Open AccessArticle
Application of Machine Learning to Predict Grain Boundary Embrittlement in Metals by Combining Bonding-Breaking and Atomic Size Effects
Materials 2020, 13(1), 179; https://doi.org/10.3390/ma13010179 - 01 Jan 2020
Abstract
The strengthening energy or embrittling potency of an alloying element is a fundamental energetics of the grain boundary (GB) embrittlement that control the mechanical properties of metallic materials. A data-driven machine learning approach has recently been used to develop prediction models to uncover [...] Read more.
The strengthening energy or embrittling potency of an alloying element is a fundamental energetics of the grain boundary (GB) embrittlement that control the mechanical properties of metallic materials. A data-driven machine learning approach has recently been used to develop prediction models to uncover the physical mechanisms and design novel materials with enhanced properties. In this work, to accurately predict and uncover the key features in determining the strengthening energies, three machine learning methods were used to model and predict strengthening energies of solutes in different metallic GBs. In addition, 142 strengthening energies from previous density functional theory calculations served as our dataset to train three machine learning models: support vector machine (SVM) with linear kernel, SVM with radial basis function (RBF) kernel, and artificial neural network (ANN). Considering both the bond-breaking effect and atomic size effect, the nonlinear kernel based SVR model was found to perform the best with a correlation of r2 ~ 0.889. The size effect feature shows a significant improvement to prediction performance with respect to using bond-breaking effect only. Moreover, the mean impact value analysis was conducted to quantitatively explore the relative significance of each input feature for improving the effective prediction. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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Open AccessArticle
Parametric Study of Flexural Strengthening of Concrete Beams with Prestressed Hybrid Reinforced Polymer
Materials 2019, 12(22), 3790; https://doi.org/10.3390/ma12223790 - 18 Nov 2019
Abstract
The strengthening method of using hybrid fiber reinforced polymer is an effective way to increase the strengthening efficiency and lower the cost. This paper focuses on simulating the flexural behavior of reinforced concrete beam strengthened by prestressed C/GFRP (Carbon-Glass hybrid Fiber Reinforced Polymer) [...] Read more.
The strengthening method of using hybrid fiber reinforced polymer is an effective way to increase the strengthening efficiency and lower the cost. This paper focuses on simulating the flexural behavior of reinforced concrete beam strengthened by prestressed C/GFRP (Carbon-Glass hybrid Fiber Reinforced Polymer) with different hybrid ratios and prestress levels. An elastoplastic damage constitution is used to simulate the mechanical behavior of concrete. A cohesive zone model under mixed mode is adopted to describe the debonding behavior of the FRP-concrete and concrete-steel interface. The results show good agreement with the experiment in the load-deflection curve, load-stress curve of steel, and HFRP. Furthermore, the failure mode of concrete and FRP debonding obtained from numerical simulation is the same as the test. Considering the improvement of the bending capacity, stiffness, and ductility of the strengthened beam in this paper, the best hybrid ratio of carbon to glass fiber is 1:1, and the suitable prestress level is between 30 and 50% of its ultimate strength. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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Open AccessArticle
Self-Gathering Effect of the Hydrogen Diffusion in Welding Induced by the Solid-State Phase Transformation
Materials 2019, 12(18), 2897; https://doi.org/10.3390/ma12182897 - 07 Sep 2019
Cited by 1
Abstract
The hydrogen diffusion in welding was investigated by using thermal-mechanical-hydrogen diffusion sequential coupled procedures based on finite element method. A self-gathering effect induced by the solid-state phase transformation was discovered. Because of the self-gathering effect, the hydrogen concentration in weld metal was accumulated [...] Read more.
The hydrogen diffusion in welding was investigated by using thermal-mechanical-hydrogen diffusion sequential coupled procedures based on finite element method. A self-gathering effect induced by the solid-state phase transformation was discovered. Because of the self-gathering effect, the hydrogen concentration in weld metal was accumulated to a peak value which can be larger than the initial hydrogen concentration in molten pool, and subsequently the hydrogen concentration in heat affect zone was redistributed. In multi-pass welding, the gathered effect not only happened inside a weld pass, but also in the inter-pass, which further increased the sensitivity of the hydrogen-assisted cold cracking. Controlling should be adopted to restrain the hydrogen accumulation. Welding stress evolution during the solid-state phase transformation process had limited effect on the hydrogen diffusion. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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