Pub Date : 2024-05-17DOI: 10.1088/1361-651x/ad4d0b
Erik Hanson, W Beck Andrews, Max Powers, Kaila Jenkins, Katsuyo Thornton
Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the Smoothed Boundary Method (SBM) to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.
{"title":"Simulating hindered grain boundary diffusion using the smoothed boundary method","authors":"Erik Hanson, W Beck Andrews, Max Powers, Kaila Jenkins, Katsuyo Thornton","doi":"10.1088/1361-651x/ad4d0b","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4d0b","url":null,"abstract":"\u0000 Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the Smoothed Boundary Method (SBM) to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"9 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140964044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.1088/1361-651x/ad4d0a
Ritesh Ramdayal Gupta, Gaurav Mittal, Krishna Kumar, U. Pandel
Shape memory polymers (SMPs) are capable of enduring significant deformations and returning to their original form upon activation by certain external stimuli. However, their restricted mechanical and thermal capabilities have limited their broader application in engineering fields. To address this, the integration of graphene nanoplatelets (GnPs) with SMPs has proven effective in enhancing their mechanical and thermal properties while maintaining inherent shape memory functions. The study evaluated shape memory nanocomposites (SMNCs) using dynamic mechanical, thermogravimetric, and static tensile, flexural, and shape memory tests, along with scanning electron microscopy to analyse tensile fractures. The results indicate that the optimal content of GnP is 0.6 wt%, resulting in excellent shape memory, thermal, and mechanical properties. Specifically, this composition demonstrates a shape recovery ratio of 94.02%, a storage modulus of 4580.07 MPa, a tensile strength of 61.42 MPa, and a flexural strength of 116.37 MPa. Additionally, the incorporation of GnPs into epoxy reduces recovery times by up to 52% at the 0.6 wt% concentration. While there is a slight decrease in the shape fixity ratio from 98.77% to 93.02%, the shape recoverability remains consistently high across all samples. Current finite element (FE) models often necessitate complex, problem-specific user subroutines, which can impede the straightforward application of research findings in real-world settings. To address this, the current study introduces an innovative finite element simulation method using the widely used ABAQUS software to model the thermomechanical behaviour of SMNCs, importantly incorporating the time-dependent viscoelastic behaviour of the material. The effectiveness of this new approach was tested by comparing experimental results from bending test of SMNCs cantilever beam with outcomes derived from FE simulations. The strong agreement between the experimental data and simulation results confirmed the precision and reliability of this novel technique.
{"title":"Analysing the shape memory behaviour of GnP-enhanced nanocomposites: A comparative study between experimental and finite element analysis","authors":"Ritesh Ramdayal Gupta, Gaurav Mittal, Krishna Kumar, U. Pandel","doi":"10.1088/1361-651x/ad4d0a","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4d0a","url":null,"abstract":"\u0000 Shape memory polymers (SMPs) are capable of enduring significant deformations and returning to their original form upon activation by certain external stimuli. However, their restricted mechanical and thermal capabilities have limited their broader application in engineering fields. To address this, the integration of graphene nanoplatelets (GnPs) with SMPs has proven effective in enhancing their mechanical and thermal properties while maintaining inherent shape memory functions. The study evaluated shape memory nanocomposites (SMNCs) using dynamic mechanical, thermogravimetric, and static tensile, flexural, and shape memory tests, along with scanning electron microscopy to analyse tensile fractures. The results indicate that the optimal content of GnP is 0.6 wt%, resulting in excellent shape memory, thermal, and mechanical properties. Specifically, this composition demonstrates a shape recovery ratio of 94.02%, a storage modulus of 4580.07 MPa, a tensile strength of 61.42 MPa, and a flexural strength of 116.37 MPa. Additionally, the incorporation of GnPs into epoxy reduces recovery times by up to 52% at the 0.6 wt% concentration. While there is a slight decrease in the shape fixity ratio from 98.77% to 93.02%, the shape recoverability remains consistently high across all samples. Current finite element (FE) models often necessitate complex, problem-specific user subroutines, which can impede the straightforward application of research findings in real-world settings. To address this, the current study introduces an innovative finite element simulation method using the widely used ABAQUS software to model the thermomechanical behaviour of SMNCs, importantly incorporating the time-dependent viscoelastic behaviour of the material. The effectiveness of this new approach was tested by comparing experimental results from bending test of SMNCs cantilever beam with outcomes derived from FE simulations. The strong agreement between the experimental data and simulation results confirmed the precision and reliability of this novel technique.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"9 49","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140962336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.1088/1361-651x/ad4b4c
Balduin Katzer, Daniel Betsche, Felix von Hoegen, Benjamin Jochum, Klemens Böhm, Katrin Schulz
Several computational models have been introduced in recent years to yield comprehensive insights into microstructural evolution analyses. However, the identification of the correct input parameters to a simulation that corresponds to a certain experimental result is a major challenge on this length scale. To complement simulation results with experimental data (and vice versa) is not trivial since, e.g., simulation model parameters might lack a physical understanding or uncertainties in the experimental data are neglected. Computational costs are another challenge mesoscale models always have to face, so comprehensive parameter studies can be costly. In this paper, we introduce a surrogate model to circumvent continuum dislocation dynamics simulation by a data-driven linkage between well-defined input parameters and output data and vice versa. We present meaningful results for a forward surrogate formulation that predicts simulation output based on the input parameter space, as well as for the inverse approach that derives the input parameter space based on simulation as well as experimental output quantities. This enables, e.g., a direct derivation of the input parameter space of a continuum dislocation dynamics simulation based on experimentally provided stress-strain data.
{"title":"Combining simulation and experimental data via surrogate modelling of continuum dislocation dynamics simulations","authors":"Balduin Katzer, Daniel Betsche, Felix von Hoegen, Benjamin Jochum, Klemens Böhm, Katrin Schulz","doi":"10.1088/1361-651x/ad4b4c","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4b4c","url":null,"abstract":"\u0000 Several computational models have been introduced in recent years to yield comprehensive insights into microstructural evolution analyses. However, the identification of the correct input parameters to a simulation that corresponds to a certain experimental result is a major challenge on this length scale. To complement simulation results with experimental data (and vice versa) is not trivial since, e.g., simulation model parameters might lack a physical understanding or uncertainties in the experimental data are neglected. Computational costs are another challenge mesoscale models always have to face, so comprehensive parameter studies can be costly. In this paper, we introduce a surrogate model to circumvent continuum dislocation dynamics simulation by a data-driven linkage between well-defined input parameters and output data and vice versa. We present meaningful results for a forward surrogate formulation that predicts simulation output based on the input parameter space, as well as for the inverse approach that derives the input parameter space based on simulation as well as experimental output quantities. This enables, e.g., a direct derivation of the input parameter space of a continuum dislocation dynamics simulation based on experimentally provided stress-strain data.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"9 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140982028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.1088/1361-651x/ad4b4a
Peter Christie, M. Siddiq, U. Asim, R. McMeeking, M. Kartal
Due to attractive mechanical properties, metastable β titanium alloys have become very popular in many industries including aerospace, marine, biomedical, and many more. It is often the complex interplay among the different deformation mechanisms that produces many of the sought-after properties, such as enhanced ductility, super-elasticity, and shape memory effects. Stress induced martensitic transformation is an important deformation mechanism for these alloys. Understanding of it and the influence it has on the microstructural evolution of materials is of great importance. To this end we have developed a crystal plasticity based constitutive model which accounts for both martensitic phase transformation and slip based plasticity simultaneously in metastable β titanium alloys. We present a new formulation for the evolution of martensite transformation, based on physical principles and crystal plasticity theory. To understand and demonstrate this feature of the model, a parametric assessment of the newly developed constitutive model is conducted. This is followed by first of its kind analyses of stress induced martensitic transformation in metastable β titanium alloys. We firstly present validations against uniaxial loading experiments for different metastable β titanium alloys exhibiting stress induced martensite (SIM) transformation. As part of this, single crystal simulations in metastable β titanium alloys are used for the first time to investigate the interaction of individual transformation systems during unconstrained transformation. This study shows good agreement between the experimental and simulated responses during all stages of deformation in which elastic, transformation and finally the slip stage are exhibited. Relatively “strong” and “weak” orientations for transformation are observed, consistent with experimental studies. The work done here demonstrates the ability of this crystal plasticity finite element method (CPFEM) to capture physical mechanisms while bringing new insight about the interaction of different deformation mechanisms in metastable β titanium alloys.
{"title":"Crystal Plasticity based Constitutive Model for Deformation in Metastable β Titanium Alloys","authors":"Peter Christie, M. Siddiq, U. Asim, R. McMeeking, M. Kartal","doi":"10.1088/1361-651x/ad4b4a","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4b4a","url":null,"abstract":"\u0000 Due to attractive mechanical properties, metastable β titanium alloys have become very popular in many industries including aerospace, marine, biomedical, and many more. It is often the complex interplay among the different deformation mechanisms that produces many of the sought-after properties, such as enhanced ductility, super-elasticity, and shape memory effects. Stress induced martensitic transformation is an important deformation mechanism for these alloys. Understanding of it and the influence it has on the microstructural evolution of materials is of great importance. To this end we have developed a crystal plasticity based constitutive model which accounts for both martensitic phase transformation and slip based plasticity simultaneously in metastable β titanium alloys. We present a new formulation for the evolution of martensite transformation, based on physical principles and crystal plasticity theory. To understand and demonstrate this feature of the model, a parametric assessment of the newly developed constitutive model is conducted. This is followed by first of its kind analyses of stress induced martensitic transformation in metastable β titanium alloys. We firstly present validations against uniaxial loading experiments for different metastable β titanium alloys exhibiting stress induced martensite (SIM) transformation. As part of this, single crystal simulations in metastable β titanium alloys are used for the first time to investigate the interaction of individual transformation systems during unconstrained transformation. This study shows good agreement between the experimental and simulated responses during all stages of deformation in which elastic, transformation and finally the slip stage are exhibited. Relatively “strong” and “weak” orientations for transformation are observed, consistent with experimental studies. The work done here demonstrates the ability of this crystal plasticity finite element method (CPFEM) to capture physical mechanisms while bringing new insight about the interaction of different deformation mechanisms in metastable β titanium alloys.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"35 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140981237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.1088/1361-651x/ad4b4e
wei guo, Yanxiang Liang, Qiang Wan
Austenitic steels are recognized as excellent structural materials for pressurized water reactors (PWRs) due to their outstanding mechanical properties and radiation resistance. However, compared to the widely studied FeCrNi series of steels, little is known about the radiation resistance of FeCrNiMn steel. In this study, the generation and evolution of radiation-induced defects in FeCrNiMn steel were investigated by molecular dynamics (MD) simulations. The results showed that more defect atoms were produced in the thermal spike stage, but fewer defects survived at the end of the cascades in FeCrNiMn compared to pure Fe. Point defect properties were analyzed by molecular static (MS), and the formation energies of defects in FeCrNiMn were lower than those of pure Fe, while the migration energies were higher. Compared to FeCrNi, FeCrNiMn had smaller migration energies and a larger overlap of vacancy and interstitial migration energies. The low vacancy formation energies and widely overlapping migration energies suggested that the number of point defects in the thermal spike stage was higher, but the possibility of recombination was greater. Additionally, Mn exhibited the smallest interstitial formation energy and migration energy. The difference in defect migration energies revealed that vacancy and interstitial defects migrate through different alloy constituent elements. This study revealed the underlying mechanism for the excellent irradiation resistance of FeCrNiMn.
{"title":"Properties of radiation-induced point defects in austenitic steels: a molecular dynamics study","authors":"wei guo, Yanxiang Liang, Qiang Wan","doi":"10.1088/1361-651x/ad4b4e","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4b4e","url":null,"abstract":"\u0000 Austenitic steels are recognized as excellent structural materials for pressurized water reactors (PWRs) due to their outstanding mechanical properties and radiation resistance. However, compared to the widely studied FeCrNi series of steels, little is known about the radiation resistance of FeCrNiMn steel. In this study, the generation and evolution of radiation-induced defects in FeCrNiMn steel were investigated by molecular dynamics (MD) simulations. The results showed that more defect atoms were produced in the thermal spike stage, but fewer defects survived at the end of the cascades in FeCrNiMn compared to pure Fe. Point defect properties were analyzed by molecular static (MS), and the formation energies of defects in FeCrNiMn were lower than those of pure Fe, while the migration energies were higher. Compared to FeCrNi, FeCrNiMn had smaller migration energies and a larger overlap of vacancy and interstitial migration energies. The low vacancy formation energies and widely overlapping migration energies suggested that the number of point defects in the thermal spike stage was higher, but the possibility of recombination was greater. Additionally, Mn exhibited the smallest interstitial formation energy and migration energy. The difference in defect migration energies revealed that vacancy and interstitial defects migrate through different alloy constituent elements. This study revealed the underlying mechanism for the excellent irradiation resistance of FeCrNiMn.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"31 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-13DOI: 10.1088/1361-651x/ad4ab0
Xiaohua Hu, Jiahao Cheng, Kashif Nawaz, Michael S Kesler, Yan Chen, Ke An
An integrated in-situ neutron diffraction and elastic plastic self-consistent crystal plasticity (EPSC-CP) modeling scheme is performed on a binary Al-12Ce alloy and a ternary Al-12Ce-0.4Mg alloys. Using this scheme, the constitutive parameters, i.e. elastic constants and slip system parameters of individual phases can be calibrated which can be used in microstructure-based crystal plasticity models to predict materials performance. From this study, it is shown that the elastic constants of Al11Ce3 intermetallics calculated from DFT calculation in the literature are rather accurate. When applied to the EPSC-CP model, the lattice strains of both the binary and ternary alloys are correctly predicted as compared with experiments, and large lattice strain differences between Al (100) plane and Al11Ce3 (010) plane are demonstrated. The slip system parameters calibrated by the scheme shows that the addition of 0.4 wt% Mg in the alloy has little influence on the critical resolved shear stress (CRSS) of initial dislocation glide in the Al matrix which caused plastic yield in the material. This can be explained by the very dilute Mg solute content in the Al solid solution, causing large spacing of Al-Mg lattice misfit sites and little impact on resistance of dislocation glide at initial yield. The 0.4 wt% Mg addition, on the other hand, has a large influence on the hardening term in the slip system parameters, indicating those Al-Mg misfit sites do help dislocation accumulation during the deformation. The impact of dilute Mg addition on the Al slip system parameters is also reflected in the flow behavior of the ternary alloy: little impact on the yield stress, but a large impact on working hardening and tensile strength of the materials which is consistent with the literature.
{"title":"Utilizing integrated neutron diffraction and elastoplastic self-consistent crystal plasticity model to quantitatively assess the strengthening mechanism in Al-12.5Ce and Al-12.5Ce-0.4Mg alloys","authors":"Xiaohua Hu, Jiahao Cheng, Kashif Nawaz, Michael S Kesler, Yan Chen, Ke An","doi":"10.1088/1361-651x/ad4ab0","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4ab0","url":null,"abstract":"\u0000 An integrated in-situ neutron diffraction and elastic plastic self-consistent crystal plasticity (EPSC-CP) modeling scheme is performed on a binary Al-12Ce alloy and a ternary Al-12Ce-0.4Mg alloys. Using this scheme, the constitutive parameters, i.e. elastic constants and slip system parameters of individual phases can be calibrated which can be used in microstructure-based crystal plasticity models to predict materials performance. From this study, it is shown that the elastic constants of Al11Ce3 intermetallics calculated from DFT calculation in the literature are rather accurate. When applied to the EPSC-CP model, the lattice strains of both the binary and ternary alloys are correctly predicted as compared with experiments, and large lattice strain differences between Al (100) plane and Al11Ce3 (010) plane are demonstrated. The slip system parameters calibrated by the scheme shows that the addition of 0.4 wt% Mg in the alloy has little influence on the critical resolved shear stress (CRSS) of initial dislocation glide in the Al matrix which caused plastic yield in the material. This can be explained by the very dilute Mg solute content in the Al solid solution, causing large spacing of Al-Mg lattice misfit sites and little impact on resistance of dislocation glide at initial yield. The 0.4 wt% Mg addition, on the other hand, has a large influence on the hardening term in the slip system parameters, indicating those Al-Mg misfit sites do help dislocation accumulation during the deformation. The impact of dilute Mg addition on the Al slip system parameters is also reflected in the flow behavior of the ternary alloy: little impact on the yield stress, but a large impact on working hardening and tensile strength of the materials which is consistent with the literature.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"2 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140982569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-08DOI: 10.1088/1361-651x/ad48a0
Chen Li, Wanzhou Ren, Jing Wang
In the field of femtosecond laser machining, it is essential to select the appropriate process parameters to obtain near thermal damage-free and high efficient machining of SiC wafer. In this work, a method of process parameter optimization for femtosecond laser machining of 4H-SiC was proposed by using the predictive ability of the Artificial Neural Network (ANN) and the optimization algorithm of the non-dominated sorting genetic algorithm (NSGA-II). Firstly, the femtosecond laser was used to fabricate microgrooves on SiC wafers, and the effects of process parameters (laser average power, scanning speed and repetition rate) on groove depth, width, heat affected zone (HAZ) and material removal rate (MRR) were investigated. Secondly, The ANN model is established based on experimental data. Other experiments verify the accuracy of the model, and the average error in the model's predictions is around 5%. Thirdly, Pareto optimal solutions are obtained by global optimization of the ANN model using the NSGA-II. The experimental results show that the Pareto optimal solutions are effective and reliable. This proposed method offers dependable guidance for the selecting and optimizing process parameters of high hardness and brittle materials in the field of femtosecond laser processing, and reduces the cost of selecting the appropriate processing parameters in the production process. The method can also be extended to other machining means, such as turning and milling.
在飞秒激光加工领域，选择合适的工艺参数对于获得接近无热损伤和高效率的碳化硅晶片加工至关重要。本研究利用人工神经网络（ANN）的预测能力和非支配排序遗传算法（NSGA-II）的优化算法，提出了一种用于 4H-SiC 飞秒激光加工的工艺参数优化方法。首先，利用飞秒激光在碳化硅晶片上制作微槽，并研究了工艺参数（激光平均功率、扫描速度和重复率）对槽深、槽宽、热影响区（HAZ）和材料去除率（MRR）的影响。其次，根据实验数据建立了 ANN 模型。其他实验验证了模型的准确性，模型预测的平均误差约为 5%。第三，利用 NSGA-II 对 ANN 模型进行全局优化，获得帕累托最优解。实验结果表明，帕累托最优解是有效和可靠的。该方法为飞秒激光加工领域高硬度和脆性材料工艺参数的选择和优化提供了可靠的指导，降低了生产过程中选择合适工艺参数的成本。该方法还可扩展到其他加工手段，如车削和铣削。
{"title":"Optimization of femtosecond laser processing parameters of SiC using ANN-NSGA-II","authors":"Chen Li, Wanzhou Ren, Jing Wang","doi":"10.1088/1361-651x/ad48a0","DOIUrl":"https://doi.org/10.1088/1361-651x/ad48a0","url":null,"abstract":"\u0000 In the field of femtosecond laser machining, it is essential to select the appropriate process parameters to obtain near thermal damage-free and high efficient machining of SiC wafer. In this work, a method of process parameter optimization for femtosecond laser machining of 4H-SiC was proposed by using the predictive ability of the Artificial Neural Network (ANN) and the optimization algorithm of the non-dominated sorting genetic algorithm (NSGA-II). Firstly, the femtosecond laser was used to fabricate microgrooves on SiC wafers, and the effects of process parameters (laser average power, scanning speed and repetition rate) on groove depth, width, heat affected zone (HAZ) and material removal rate (MRR) were investigated. Secondly, The ANN model is established based on experimental data. Other experiments verify the accuracy of the model, and the average error in the model's predictions is around 5%. Thirdly, Pareto optimal solutions are obtained by global optimization of the ANN model using the NSGA-II. The experimental results show that the Pareto optimal solutions are effective and reliable. This proposed method offers dependable guidance for the selecting and optimizing process parameters of high hardness and brittle materials in the field of femtosecond laser processing, and reduces the cost of selecting the appropriate processing parameters in the production process. The method can also be extended to other machining means, such as turning and milling.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"213 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141001896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-08DOI: 10.1088/1361-651x/ad489f
Ang Zhao, Kui Liu, Pei Li, Yehui Cui
The tunable deformation design of porous ceramics has raised many interests in many engineering and manufacturing fields, where its corresponding design methodologies still suffer from the lower efficiency and higher computational cost. To handle this problem, a novel optimization and design methodology based on the Direct FE2 method has been proposed in this study, and several numerical examples of the porous Al2O3 tunable deformation design has been performed by this novel methodology. Compared with the traditional methodologies, the proposed method is more convenient to conduct the tunable deformation design and improves the optimization efficiency. Based on this method, the distribution and assembly of the microscale RVE could be tailored along the space dimension to handle the sinusoidal deformation and variable Poisson’s ratio ceramic design at the macroscale. By comparing the simulation results with the Direct Numerical Simulation (DNS) model, the effectiveness and accuracy of this methodology is well validated. Meanwhile, the simulation results based on the proposed methodology found that the predictability of porous Al2O3 deformation could be enhanced by changing the micro structure parameters such as the elliptical hole angle and aspect ratio. This methodology holds great potential for applications in the design and optimization of porous ceramics with tailored deformation characteristics.
{"title":"Tunable deformation design of porous Al2O3 based on the Direct FE2 method","authors":"Ang Zhao, Kui Liu, Pei Li, Yehui Cui","doi":"10.1088/1361-651x/ad489f","DOIUrl":"https://doi.org/10.1088/1361-651x/ad489f","url":null,"abstract":"\u0000 The tunable deformation design of porous ceramics has raised many interests in many engineering and manufacturing fields, where its corresponding design methodologies still suffer from the lower efficiency and higher computational cost. To handle this problem, a novel optimization and design methodology based on the Direct FE2 method has been proposed in this study, and several numerical examples of the porous Al2O3 tunable deformation design has been performed by this novel methodology. Compared with the traditional methodologies, the proposed method is more convenient to conduct the tunable deformation design and improves the optimization efficiency. Based on this method, the distribution and assembly of the microscale RVE could be tailored along the space dimension to handle the sinusoidal deformation and variable Poisson’s ratio ceramic design at the macroscale. By comparing the simulation results with the Direct Numerical Simulation (DNS) model, the effectiveness and accuracy of this methodology is well validated. Meanwhile, the simulation results based on the proposed methodology found that the predictability of porous Al2O3 deformation could be enhanced by changing the micro structure parameters such as the elliptical hole angle and aspect ratio. This methodology holds great potential for applications in the design and optimization of porous ceramics with tailored deformation characteristics.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":" 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140998504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-03DOI: 10.1088/1361-651x/ad472f
Sushan Nakarmi, Jihyeon Kim, Lindsey Bezek, Jeffrey A. Leiding, Kwan-Soo Lee, Nitin Daphalapurkar
Additive manufacturing has enabled a transformational ability to create cellular structures (or foams) with tailored topology. Compared to their monolithic polymer counterparts, cellular structures are potentially suitable for systems requiring materials with high specific energy-absorbing capability to provide enhanced damping. In this work, we demonstrate the utility of controlling unit-cell topology with the intent of obtaining a desired stress-strain response and energy density. Using mesoscale simulations that resolve the unit-cell sub-structures, we validate the role of unit-cell topology in selectively activating a buckling mode and thereby modulating the characteristic stress-strain response. Simulations incorporate a linear viscoelastic constitutive model and a hyperelastic model for simulating large deformation of the polymer under both tension and compression. Simulated results for nine different cellular structures are compared with experimental data to gain insights into three different modes of buckling and the corresponding stress-strain response.
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Magnesium-aluminum alloy is one of the most common alloy materials in the industry, widely utilized due to its low density and excellent mechanical properties. Investigating the properties or predicting new structures through experimentation inevitably involves complex processes, which consume significant time and resources. To facilitate the discovery, simulations such as Density Functional Theory (DFT) and machine learning (ML) methods are primarily employed. However, DFT incurs significant computational costs. While ML methods are versatile and efficient, they demand high-quality datasets and may exhibit some degree of inaccuracy. To address these challenges, we employ a combination of generative model and automatic differentiation (AD), reducing the search space and accelerating the discovery of target materials. We have predicted a variety of magnesium-aluminum alloys. We conducted structure optimization and property evaluation for ten potentially valuable intermetallic compounds. Ultimately, we identified five stable structures: Mg3Al3, Mg2Al6, Mg4Al12, Mg15Al and Mg14Al2. Among these, Mg4Al12, Mg15Al and Mg14Al2 may hold higher potential for practical applications.
镁铝合金是工业中最常见的合金材料之一，因其密度低、机械性能优异而被广泛使用。通过实验研究其特性或预测新结构必然涉及复杂的过程，耗费大量时间和资源。为了便于发现，人们主要采用密度泛函理论（DFT）和机器学习（ML）等模拟方法。然而，密度泛函理论需要大量的计算成本。虽然 ML 方法具有通用性和高效性，但它们需要高质量的数据集，而且可能会表现出一定程度的不准确性。为了应对这些挑战，我们采用了生成模型和自动分化（AD）相结合的方法，从而缩小了搜索空间，加快了目标材料的发现。我们已经预测了多种镁铝合金。我们对十种有潜在价值的金属间化合物进行了结构优化和性能评估。最终，我们确定了五种稳定的结构：Mg3Al3、Mg2Al6、Mg4Al12、Mg15Al 和 Mg14Al2。其中，Mg4Al12、Mg15Al 和 Mg14Al2 具有更高的实际应用潜力。
{"title":"Discovery of Magnesium-Aluminum Alloys by Generative Model and Automatic Differentiation Approach","authors":"Shuwei Cheng, Zhelin Li, Hongfei Zhang, Xiaohong Yan, Shibing Chu","doi":"10.1088/1361-651x/ad38d0","DOIUrl":"https://doi.org/10.1088/1361-651x/ad38d0","url":null,"abstract":"\u0000 Magnesium-aluminum alloy is one of the most common alloy materials in the industry, widely utilized due to its low density and excellent mechanical properties. Investigating the properties or predicting new structures through experimentation inevitably involves complex processes, which consume significant time and resources. To facilitate the discovery, simulations such as Density Functional Theory (DFT) and machine learning (ML) methods are primarily employed. However, DFT incurs significant computational costs. While ML methods are versatile and efficient, they demand high-quality datasets and may exhibit some degree of inaccuracy. To address these challenges, we employ a combination of generative model and automatic differentiation (AD), reducing the search space and accelerating the discovery of target materials. We have predicted a variety of magnesium-aluminum alloys. We conducted structure optimization and property evaluation for ten potentially valuable intermetallic compounds. Ultimately, we identified five stable structures: Mg3Al3, Mg2Al6, Mg4Al12, Mg15Al and Mg14Al2. Among these, Mg4Al12, Mg15Al and Mg14Al2 may hold higher potential for practical applications.","PeriodicalId":503047,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"34 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140372486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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