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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: closed (31 March 2021) | Viewed by 49906

Special Issue Editor


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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

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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

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Published Papers (16 papers)

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Research

16 pages, 3339 KiB  
Article
Experimental Analysis of the Enzymatic Degradation of Polycaprolactone: Microcrystalline Cellulose Composites and Numerical Method for the Prediction of the Degraded Geometry
by Jacob Abdelfatah, Rubén Paz, María Elena Alemán-Domínguez, Mario Monzón, Ricardo Donate and Gabriel Winter
Materials 2021, 14(9), 2460; https://doi.org/10.3390/ma14092460 - 10 May 2021
Cited by 14 | Viewed by 3198
Abstract
The degradation rate of polycaprolactone (PCL) is a key issue when using this material in Tissue Engineering or eco-friendly packaging sectors. Although different PCL-based composite materials have been suggested in the literature and extensively tested in terms of processability by material extrusion additive [...] Read more.
The degradation rate of polycaprolactone (PCL) is a key issue when using this material in Tissue Engineering or eco-friendly packaging sectors. Although different PCL-based composite materials have been suggested in the literature and extensively tested in terms of processability by material extrusion additive manufacturing, little attention has been paid to the influence of the fillers on the mechanical properties of the material during degradation. This work analyses the possibility of tuning the degradation rate of PCL-based filaments by the introduction of microcrystalline cellulose into the polymer matrix. The enzymatic degradation of the composite and pure PCL materials were compared in terms of mass loss, mechanical properties, morphology and infrared spectra. The results showed an increased degradation rate of the composite material due to the presence of the filler (enhanced interaction with the enzymes). Additionally, a new numerical method for the prediction of the degraded geometry was developed. The method, based on the Monte Carlo Method in an iterative process, adjusts the degradation probability according to the exposure of each discretized element to the degradation media. This probability is also amplified depending on the corresponding experimental mass loss, thus allowing a good fit to the experimental data in relatively few iterations. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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19 pages, 5350 KiB  
Article
Mechanical Behavior Modeling of Containers and Octabins Made of Corrugated Cardboard Subjected to Vertical Stacking Loads
by Javier Gallo, Fernando Cortés, Elisabete Alberdi and Aitor Goti
Materials 2021, 14(9), 2392; https://doi.org/10.3390/ma14092392 - 4 May 2021
Cited by 13 | Viewed by 3081
Abstract
The aim of this paper is to characterize the mechanical behavior of corrugated cardboard boxes using simple models that allow an approach to the load capacity and the deformation of the boxes. This is very interesting during a box design stage, in which [...] Read more.
The aim of this paper is to characterize the mechanical behavior of corrugated cardboard boxes using simple models that allow an approach to the load capacity and the deformation of the boxes. This is very interesting during a box design stage, in which the box does not exist yet. On the one hand, a mathematical model of strength and deformation of boxes with different geometry is obtained from experiments according to the Box Compression Test and Edge Crush Test standards. On the second hand, a finite element simulation is proposed in which only the material elastic modulus in the compression direction is needed. For that, corrugated cardboard sheets are glued to build billets for testing, and an equivalent elastic modulus is obtained. This idea arises from the fact that the collapse of the box is given by the local bucking of the corrugated cardboard panels, due to the slenderness itself, and the properties in the compression direction are predominant. As a result, the numerical models show satisfactory agreement with experiments, concluding that it is an adequate methodology to simulate in a simple and efficient way this type of boxes built with corrugated cardboard. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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13 pages, 2666 KiB  
Article
Random Material Property Fields of 3D Concrete Microstructures Based on CT Image Reconstruction
by George Stefanou, Dimitrios Savvas and Panagiotis Metsis
Materials 2021, 14(6), 1423; https://doi.org/10.3390/ma14061423 - 15 Mar 2021
Cited by 9 | Viewed by 2103
Abstract
The purpose of this paper is to determine the random spatially varying elastic properties of concrete at various scales taking into account its highly heterogeneous microstructure. The reconstruction of concrete microstructure is based on computed tomography (CT) images of a cubic concrete specimen. [...] Read more.
The purpose of this paper is to determine the random spatially varying elastic properties of concrete at various scales taking into account its highly heterogeneous microstructure. The reconstruction of concrete microstructure is based on computed tomography (CT) images of a cubic concrete specimen. The variability of the local volume fraction of the constituents (pores, cement paste and aggregates) is quantified and mesoscale random fields of the elasticity tensor are computed from a number of statistical volume elements obtained by applying the moving window method on the specimen along with computational homogenization. Based on the statistical characteristics of the mesoscale random fields, it is possible to assess the effect of randomness in microstructure on the mechanical behavior of concrete. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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16 pages, 12853 KiB  
Article
Mechanical Characterization of the Elastoplastic Response of a C11000-H2 Copper Sheet
by Matías Pacheco, Claudio García-Herrera, Diego Celentano and Jean-Philippe Ponthot
Materials 2020, 13(22), 5193; https://doi.org/10.3390/ma13225193 - 17 Nov 2020
Cited by 3 | Viewed by 2050
Abstract
This work presents an elastoplastic characterization of a rolled C11000-H2 99.90% pure copper sheet considering the orthotropic non-associated Hill-48 criterion together with a modified Voce hardening law. One of the main features of this material is the necking formation at small strains levels [...] Read more.
This work presents an elastoplastic characterization of a rolled C11000-H2 99.90% pure copper sheet considering the orthotropic non-associated Hill-48 criterion together with a modified Voce hardening law. One of the main features of this material is the necking formation at small strains levels causing the early development of non-homogeneous stress and strain patterns in the tested samples. Due to this fact, a robust inverse calibration approach, based on an experimental–analytical–numerical iterative predictor–corrector methodology, is proposed to obtain the constitutive material parameters. This fitting procedure, which uses tensile test measurements where the strains are obtained via digital image correlation (DIC), consists of three steps aimed at, respectively, determining (a) the parameters of the hardening model, (b) a first prediction of the Hill-48 parameters based on the Lankford coefficients and, (c) corrected parameters of the yield and flow potential functions that minimize the experimental–numerical error of the material response. Finally, this study shows that the mechanical characterization carried out in this context is capable of adequately predicting the behavior of the material in the bulge test. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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15 pages, 1962 KiB  
Article
Application of an Incremental Constitutive Model for the FE Analysis of Material Dynamic Restoration in the Rotary Tube Piercing Process
by Alberto Murillo-Marrodán, Eduardo García, Jon Barco and Fernando Cortés
Materials 2020, 13(19), 4289; https://doi.org/10.3390/ma13194289 - 25 Sep 2020
Cited by 13 | Viewed by 3079
Abstract
In the numerical simulation of hot forming processes, the correct description of material flow stress is very important for the accuracy of the results. For complex manufacturing processes, such as the rotary tube piercing (RTP), constitutive laws based on both power and exponential [...] Read more.
In the numerical simulation of hot forming processes, the correct description of material flow stress is very important for the accuracy of the results. For complex manufacturing processes, such as the rotary tube piercing (RTP), constitutive laws based on both power and exponential mathematical expressions are commonly used due to its inherent simplicity, despite the limitations that this approach involves, namely, the use of accumulated strain as a state parameter. In this paper, a constitutive model of the P91 steel derived from the evolution of dislocation density with strain, which takes into account the mechanisms of dynamic recovery (DRV) and dynamic recrystallization (DRX), is proposed for the finite element (FE) analysis of the RTP process. The material model is developed in an incremental manner to allow its implementation in the FE code FORGE®. The success of this implementation is confirmed by the good correlation between results of the simulation and experimental measurements of the manufactured tube (elongation, twist angle, mean wall thickness and eccentricity). In addition, this incremental model allows addressing how the restoring mechanisms of DRV and DRV occur during the RTP process. The analysis puts into evidence that DRV and DRX prevail over each other cyclically, following an alternating sequence during the material processing, due mainly to the effect of the strain rate on the material. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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15 pages, 2268 KiB  
Article
Biomechanics of the Human Middle Ear with Viscoelasticity of the Maxwell and the Kelvin–Voigt Type and Relaxation Effect
by Rafal Rusinek, Marcin Szymanski and Robert Zablotni
Materials 2020, 13(17), 3779; https://doi.org/10.3390/ma13173779 - 27 Aug 2020
Cited by 3 | Viewed by 2994
Abstract
The middle ear is one of the smallest biomechanical systems in the human body and is responsible for the hearing process. Hearing is modelled in different ways and by various methods. In this paper, three-degree-of-freedom models of the human middle ear with different [...] Read more.
The middle ear is one of the smallest biomechanical systems in the human body and is responsible for the hearing process. Hearing is modelled in different ways and by various methods. In this paper, three-degree-of-freedom models of the human middle ear with different viscoelastic properties are proposed. Model 1 uses the Maxwell type viscoelasticity, Model 2 is based on the Kelvin–Voigt viscoelasticity, and Model 3 uses the Kelvin–Voigt viscoelasticity with relaxation effect. The primary aim of the study is to compare the models and their dynamic responses to a voice excitation. The novelty of this study lies in using different models of viscoelasticity and relaxation effect that has been previously unstudied. First, mathematical models of the middle ear were built, then they were solved numerically by the Runge–Kutta procedure and finally, numerical results were compared with those obtained from experiments carried out on the temporal bone with the Laser Doppler Vibrometer. The models exhibit differences in the natural frequency and amplitudes near the second resonance. All analysed models can be used for modelling the rapidly changing processes that occur in the ear and to control active middle ear implants. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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15 pages, 1939 KiB  
Article
Crystal-Plasticity-Finite-Element Modeling of the Quasi-Static and Dynamic Response of a Directionally Solidified Nickel-Base Superalloy
by Rafael Sancho, Javier Segurado, Borja Erice, María-Jesús Pérez-Martín and Francisco Gálvez
Materials 2020, 13(13), 2990; https://doi.org/10.3390/ma13132990 - 5 Jul 2020
Cited by 2 | Viewed by 2786
Abstract
The flow stress behaviour of a directionally solidified nickel-base superalloy, MAR-M247, is presented through the combination of experiments and crystal-plasticity simulations. The experimental campaign encompassed quasi-static and dynamic testing in the parallel and perpendicular orientation with respect to the columnar grains. The material [...] Read more.
The flow stress behaviour of a directionally solidified nickel-base superalloy, MAR-M247, is presented through the combination of experiments and crystal-plasticity simulations. The experimental campaign encompassed quasi-static and dynamic testing in the parallel and perpendicular orientation with respect to the columnar grains. The material showed low strain-rate sensitivity in all cases. Virtual samples were generated with DREAM3d and each grain orientation was established according to the DS nature of the alloy. The elasto-visco-plastic response of each crystal is given by phenomenological-base equations, considering the dislocation–dislocation interactions among different slip systems. The hardening-function constants and the strain-rate sensitivity parameter were fitted with the information from tests parallel to the grain-growth direction and the model was able to predict with accuracy the experimental response in the perpendicular direction, confirming the suitability of the model to be used as a tool for virtual testing. Simulations also revealed that in oligocrystalline structures of this type, the yield-strength value is controlled by the grains with higher Schmid factor, while this influence decreases when plastic strain increases. Moreover, the analysis of the micro-fields confirmed that grains perpendicular to the loading axis are prone to nucleate cavities since the stresses in these regions can be twice the external applied stress. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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41 pages, 939 KiB  
Article
Robust Multiscale Identification of Apparent Elastic Properties at Mesoscale for Random Heterogeneous Materials with Multiscale Field Measurements
by Tianyu Zhang, Florent Pled and Christophe Desceliers
Materials 2020, 13(12), 2826; https://doi.org/10.3390/ma13122826 - 23 Jun 2020
Cited by 7 | Viewed by 2446
Abstract
The aim of this work is to efficiently and robustly solve the statistical inverse problem related to the identification of the elastic properties at both macroscopic and mesoscopic scales of heterogeneous anisotropic materials with a complex microstructure that usually cannot be properly described [...] Read more.
The aim of this work is to efficiently and robustly solve the statistical inverse problem related to the identification of the elastic properties at both macroscopic and mesoscopic scales of heterogeneous anisotropic materials with a complex microstructure that usually cannot be properly described in terms of their mechanical constituents at microscale. Within the context of linear elasticity theory, the apparent elasticity tensor field at a given mesoscale is modeled by a prior non-Gaussian tensor-valued random field. A general methodology using multiscale displacement field measurements simultaneously made at both macroscale and mesoscale has been recently proposed for the identification the hyperparameters of such a prior stochastic model by solving a multiscale statistical inverse problem using a stochastic computational model and some information from displacement fields at both macroscale and mesoscale. This paper contributes to the improvement of the computational efficiency, accuracy and robustness of such a method by introducing (i) a mesoscopic numerical indicator related to the spatial correlation length(s) of kinematic fields, allowing the time-consuming global optimization algorithm (genetic algorithm) used in a previous work to be replaced with a more efficient algorithm and (ii) an ad hoc stochastic representation of the hyperparameters involved in the prior stochastic model in order to enhance both the robustness and the precision of the statistical inverse identification method. Finally, the proposed improved method is first validated on in silico materials within the framework of 2D plane stress and 3D linear elasticity (using multiscale simulated data obtained through numerical computations) and then exemplified on a real heterogeneous biological material (beef cortical bone) within the framework of 2D plane stress linear elasticity (using multiscale experimental data obtained through mechanical testing monitored by digital image correlation). Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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15 pages, 4182 KiB  
Article
Simulation of the Light Transmittance in Macroporous Silica
by Wenqi Zhu, Xingzhong Guo, Lan Wu and Hui Yang
Materials 2020, 13(7), 1635; https://doi.org/10.3390/ma13071635 - 1 Apr 2020
Cited by 5 | Viewed by 2554
Abstract
This paper focuses on the light transmittance of macroporous silica as a photocatalyst carrier. In addition to the characteristics of photocatalysts, the structure of porous bulk is also important since it affects the propagation of light. Realistic porous structures are generated by a [...] Read more.
This paper focuses on the light transmittance of macroporous silica as a photocatalyst carrier. In addition to the characteristics of photocatalysts, the structure of porous bulk is also important since it affects the propagation of light. Realistic porous structures are generated by a Voronoi-based approach. Four morphological parameters are highly controlled during generating, that is, porosity, coefficient of variation, diameter ratio and normalized curvature. Finite element method (FEM) is used to simulate the propagation of light in the porous models in the visible light range. The intensity shows a quadratic decrease with the increase of the depth of light propagation. The influences of the morphological parameters on the light transmittance are analysed. It turns out that the porosity has a great influence on the light transmittance while the coefficient of variation and the diameter ratio have small ones. Moreover, the influence of the normalized curvature is little. Besides, the effect of the wavelength of visible light can not be ignored. With the simulation, the depth of visible light entering the porous silica can be estimated, which is challenging to access experimentally. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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21 pages, 24970 KiB  
Article
Peridynamics Model with Surface Correction Near Insulated Cracks for Transient Heat Conduction in Functionally Graded Materials
by Yang Tan, Qiwen Liu, Lianmeng Zhang, Lisheng Liu and Xin Lai
Materials 2020, 13(6), 1340; https://doi.org/10.3390/ma13061340 - 15 Mar 2020
Cited by 11 | Viewed by 2747
Abstract
A peridynamic (PD) model of functionally graded materials (FGMs) is presented to simulate transient heat conduction in the FGM plate with insulated cracks. The surface correction is considered in the model to reduce the surface effect near the domain boundary and insulated cracks. [...] Read more.
A peridynamic (PD) model of functionally graded materials (FGMs) is presented to simulate transient heat conduction in the FGM plate with insulated cracks. The surface correction is considered in the model to reduce the surface effect near the domain boundary and insulated cracks. In order to verify the proposed model, a numerical example for the FGM plate is carried out. The results show good agreement with the analytical solution. The convergence of the model with the surface correction for FGMs without cracks is then investigated. The results reveal that our model converges to the classical solutions in the limit of the horizon going to zero. The effects of two material points discretization schemes on the accuracy of numerical results are investigated. For transient heat conduction of FGMs with a static crack, the results obtained from the proposed PD model agree well with that from the finite element method. Finally, transient heat conduction of the FGM plate with a dynamic horizontal crack and intersecting cracks is simulated and discussed. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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27 pages, 9469 KiB  
Article
Effect of Temperature on Deformation and Fatigue Behaviour of A356–T7 Cast Aluminium Alloys Used in High Specific Power IC Engine Cylinder Heads
by Elanghovan Natesan, Stefan Eriksson, Johan Ahlström and Christer Persson
Materials 2020, 13(5), 1202; https://doi.org/10.3390/ma13051202 - 7 Mar 2020
Cited by 12 | Viewed by 3518
Abstract
Aggressive downsizing of the internal combustion engines used as part of electrified powertrains in recent years have resulted in increasing thermal loads on the cylinder heads and consequently, the susceptibility to premature thermo-mechanical fatigue failures. To enable a reliable computer aided engineering (CAE) [...] Read more.
Aggressive downsizing of the internal combustion engines used as part of electrified powertrains in recent years have resulted in increasing thermal loads on the cylinder heads and consequently, the susceptibility to premature thermo-mechanical fatigue failures. To enable a reliable computer aided engineering (CAE) prediction of the component lives, we need more reliable material deformation and fatigue performance data. Material for testing was extracted from the highly loaded valve bridge area of specially cast cylinder heads to study the monotonic and cyclic deformation behaviour of the A356–T7 + 0.5% Cu alloy at various temperatures. Monotonic tensile tests performed at different temperatures indicate decreasing strength from 211 MPa at room temperature to 73 MPa at 300 °C and a corresponding increase in ductility. Completely reversed, strain controlled, uniaxial fatigue tests were carried out at 150, 200 and 250 °C. A dilatometric study carried out to study the thermal expansion behaviour of the alloy in the temperature range 25–360 °C shows a thermal expansion coefficient of (25–30) × 10−6 °C−1. Under cyclic loading, increasing plastic strains are observed with increasing temperatures for similar load levels. The experimental data of the cyclic deformation behaviour are calibrated against a nonlinear combined kinematic–isotropic hardening model with both a linear and non-linear backstress. Full article
(This article belongs to the Special Issue Computational Materials Modeling, Analysis and Applications)
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19 pages, 5001 KiB  
Article
Simulation of Thermal Behavior of Glass Fiber/Phenolic Composites Exposed to Heat Flux on One Side
by Han Li, Nasidan Wang, Xuefei Han, Baoxin Fan, Zhenyu Feng and Shijun Guo
Materials 2020, 13(2), 421; https://doi.org/10.3390/ma13020421 - 16 Jan 2020
Cited by 9 | Viewed by 4655
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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21 pages, 5396 KiB  
Article
Numerical Modeling for Simulation of Compaction of Refractory Materials for Secondary Steelmaking
by Cristina Ramírez-Aragón, Joaquín Ordieres-Meré, Fernando Alba-Elías and Ana González-Marcos
Materials 2020, 13(1), 224; https://doi.org/10.3390/ma13010224 - 4 Jan 2020
Cited by 6 | Viewed by 3620
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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11 pages, 1284 KiB  
Article
Application of Machine Learning to Predict Grain Boundary Embrittlement in Metals by Combining Bonding-Breaking and Atomic Size Effects
by Xuebang Wu, Yu-xuan Wang, Kan-ni He, Xiangyan Li, Wei Liu, Yange Zhang, Yichun Xu and Changsong Liu
Materials 2020, 13(1), 179; https://doi.org/10.3390/ma13010179 - 1 Jan 2020
Cited by 15 | Viewed by 3392
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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17 pages, 6329 KiB  
Article
Parametric Study of Flexural Strengthening of Concrete Beams with Prestressed Hybrid Reinforced Polymer
by Xiaomeng Wang, Michal Petrů, Jun Ai and Shikun Ou
Materials 2019, 12(22), 3790; https://doi.org/10.3390/ma12223790 - 18 Nov 2019
Cited by 5 | Viewed by 3300
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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15 pages, 4190 KiB  
Article
Self-Gathering Effect of the Hydrogen Diffusion in Welding Induced by the Solid-State Phase Transformation
by Zhiliang Xiong, Wenjian Zheng, Liping Tang and Jianguo Yang
Materials 2019, 12(18), 2897; https://doi.org/10.3390/ma12182897 - 7 Sep 2019
Cited by 6 | Viewed by 2931
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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