This article presents novel non-singular influence functions for homogeneous media. These solutions are displacement and stress fields of a three-dimensional, isotropic full-space under time-harmonic vertical and horizontal loads, which can be used within the framework of boundary element methods to solve elastodynamics problems in engineering practice. In order to account for sharply-varying contact tractions that may occur in such problems, the solutions in this article consider a biquadratic distribution of the loads within the loaded surface. In the present derivation, sets of Fourier transforms are used to uncouple the medium's equation of motion and enable the incorporation of boundary conditions directly as traction discontinuities. The article brings selected numerical results for various geometric and constitutive parameters.
{"title":"A quadratic boundary element for 3D elastodynamics","authors":"Edivaldo Romanini, Josue Labaki, Iago Cavalcante, Euclides Mesquita","doi":"10.1590/1679-78257432","DOIUrl":"https://doi.org/10.1590/1679-78257432","url":null,"abstract":"This article presents novel non-singular influence functions for homogeneous media. These solutions are displacement and stress fields of a three-dimensional, isotropic full-space under time-harmonic vertical and horizontal loads, which can be used within the framework of boundary element methods to solve elastodynamics problems in engineering practice. In order to account for sharply-varying contact tractions that may occur in such problems, the solutions in this article consider a biquadratic distribution of the loads within the loaded surface. In the present derivation, sets of Fourier transforms are used to uncouple the medium's equation of motion and enable the incorporation of boundary conditions directly as traction discontinuities. The article brings selected numerical results for various geometric and constitutive parameters.","PeriodicalId":49021,"journal":{"name":"Latin American Journal of Solids and Structures","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136304555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a primary load-bearing component, accurately predicting the bearing capacity of concrete-filled rectangular steel tube (CFRST) members is an essential prerequisite for ensuring structural safety. Machine learning methods are employed to model and predict the axial load bearing capacity of CFRST columns. A test database containing 1119 members is established, and the input parameters of the machine learning model are determined using a combination of data preprocessing and correlation analysis. Four machine learning algorithms, namely Lasso, ANN, RF, and XGBoost, are selected to build the prediction models for axial load bearing capacity, and a comparative analysis of their predictive performance is conducted. The feature importance analysis is performed using the SHAP method. The results indicate that the model based on the XGBoost algorithm achieves the highest prediction accuracy. Through comparison with six existing calculation methods in domestic and international codes, the reliability of its predictive performance is verified.
{"title":"Machine Learning-Based Prediction of Axial Load Bearing Capacity for CFRST Columns","authors":"Tuo Lei, Jianxiang Xu, Shuangfei Liang, Zhimin Wu","doi":"10.1590/1679-78257807","DOIUrl":"https://doi.org/10.1590/1679-78257807","url":null,"abstract":"As a primary load-bearing component, accurately predicting the bearing capacity of concrete-filled rectangular steel tube (CFRST) members is an essential prerequisite for ensuring structural safety. Machine learning methods are employed to model and predict the axial load bearing capacity of CFRST columns. A test database containing 1119 members is established, and the input parameters of the machine learning model are determined using a combination of data preprocessing and correlation analysis. Four machine learning algorithms, namely Lasso, ANN, RF, and XGBoost, are selected to build the prediction models for axial load bearing capacity, and a comparative analysis of their predictive performance is conducted. The feature importance analysis is performed using the SHAP method. The results indicate that the model based on the XGBoost algorithm achieves the highest prediction accuracy. Through comparison with six existing calculation methods in domestic and international codes, the reliability of its predictive performance is verified.","PeriodicalId":49021,"journal":{"name":"Latin American Journal of Solids and Structures","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135059547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fabiano Fumes, José Luiz Boldrini, Marco Lúcio Bittencourt
Deformation in polymers is highly dependent on molecular structures and motion and relaxation mechanisms, which are highly influenced by temperature and mechanical load history. These features imply that some models can fit for specific classes of polymers and not for others; moreover, these models also include several non-linearities, which turns out to be challenging for computational simulation. This work develops and simulates a thermal-structural phase-field model for the polytetrafluorethylene (PTFE) polymer. The constitutive multimechanism model used considers a non-isothermal non-linear elastoviscoplastic model, able to represent elastic molecular interactions, and viscoplastic flow from polymer segments. Material parameters for complex rheological models are addressed, through a genetic algorithm, to adjust curves from simulated models to stress-strain experiments available in literature. Results of stress-strain curves, followed by rupture, for a temperature ranging from -50° C to 150° C are plotted in comparison with experimental results, presenting a reasonable fit.
{"title":"A thermodynamically consistent elastoviscoplastic phase-field framework for structural damage in PTFE","authors":"Fabiano Fumes, José Luiz Boldrini, Marco Lúcio Bittencourt","doi":"10.1590/1679-78257539","DOIUrl":"https://doi.org/10.1590/1679-78257539","url":null,"abstract":"Deformation in polymers is highly dependent on molecular structures and motion and relaxation mechanisms, which are highly influenced by temperature and mechanical load history. These features imply that some models can fit for specific classes of polymers and not for others; moreover, these models also include several non-linearities, which turns out to be challenging for computational simulation. This work develops and simulates a thermal-structural phase-field model for the polytetrafluorethylene (PTFE) polymer. The constitutive multimechanism model used considers a non-isothermal non-linear elastoviscoplastic model, able to represent elastic molecular interactions, and viscoplastic flow from polymer segments. Material parameters for complex rheological models are addressed, through a genetic algorithm, to adjust curves from simulated models to stress-strain experiments available in literature. Results of stress-strain curves, followed by rupture, for a temperature ranging from -50° C to 150° C are plotted in comparison with experimental results, presenting a reasonable fit.","PeriodicalId":49021,"journal":{"name":"Latin American Journal of Solids and Structures","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135501540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ammar Babiker, Ebtihaj Abu-Elgasim, Mashair Mohammed
Dynamic characterization of cement-based composites is crucial for understanding material behavior. When exposed to highly dynamic loading conditions, the strain-rate dependence of material causes the material response to differ significantly from that under quasi-static loading conditions. In this paper, a numerical investigation on the dynamic tensile behavior of cement-based materials. A gravitational split Hopkinson tension bar was used to characterize the dynamic tensile behavior of cement-based at high strain-rates. The commercial finite element software LS-Dyna is adopted to conduct the computations. The material specifications of cement-based are characterized by the Karagozian & Case (K&C) concrete model that accounts for shear dilation, strain-rate dependence, and strain softening. The model accuracy is verified with available experimental results in the form of strain signals, strain-rates, and tensile strengths. It was found that the results computed with the automatic generation version of K&C are slightly different from the experimental ones. Therefore, to achieve better agreement, the model was extended by calibrating a few parameters of the K&C material formulation. Finally, the simulation predictions were found to represent the experimental results with good agreement.
{"title":"Numerical Analysis of the Dynamic Tensile Behavior of Cement-Based Materials using a Gravity-Driven Hopkinson Tension Bar","authors":"Ammar Babiker, Ebtihaj Abu-Elgasim, Mashair Mohammed","doi":"10.1590/1679-78257483","DOIUrl":"https://doi.org/10.1590/1679-78257483","url":null,"abstract":"Dynamic characterization of cement-based composites is crucial for understanding material behavior. When exposed to highly dynamic loading conditions, the strain-rate dependence of material causes the material response to differ significantly from that under quasi-static loading conditions. In this paper, a numerical investigation on the dynamic tensile behavior of cement-based materials. A gravitational split Hopkinson tension bar was used to characterize the dynamic tensile behavior of cement-based at high strain-rates. The commercial finite element software LS-Dyna is adopted to conduct the computations. The material specifications of cement-based are characterized by the Karagozian & Case (K&C) concrete model that accounts for shear dilation, strain-rate dependence, and strain softening. The model accuracy is verified with available experimental results in the form of strain signals, strain-rates, and tensile strengths. It was found that the results computed with the automatic generation version of K&C are slightly different from the experimental ones. Therefore, to achieve better agreement, the model was extended by calibrating a few parameters of the K&C material formulation. Finally, the simulation predictions were found to represent the experimental results with good agreement.","PeriodicalId":49021,"journal":{"name":"Latin American Journal of Solids and Structures","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135702216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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