Khaled Boumezbeur, Mourad Khebizi, M. Guenfoud, Ilies Guendouz
Functionally Graded Material (FGM) is a new generation of composite materials, it can be used for different engineering fields according to the loading environment, but the study of its mechanical behavior requires sophisticated numerical and analytical models. Several investigations in these models are available in the literature, however, most of those investigations are based on simplifying assumptions. In this paper, we present a three-dimensional finite element modeling of functionally graded material (FGM) beams subjected to static loading. Material properties are assumed to vary continuously along the beam thickness according to the power-law distribution with linear elastic behavior. The FGM beams are discretized by hexahedral finite elements type C3D20R (continuum stress/displacement, three-dimensional 20-node, reduced integration). We studied several numerical examples of FGM beams and compare the obtained numerical results with those of analytical models in the literature.
{"title":"Mechanical Response of Thin Composite Beams Made of Functionally Graded Material Using Finite Element Method","authors":"Khaled Boumezbeur, Mourad Khebizi, M. Guenfoud, Ilies Guendouz","doi":"10.3311/ppci.21909","DOIUrl":"https://doi.org/10.3311/ppci.21909","url":null,"abstract":"Functionally Graded Material (FGM) is a new generation of composite materials, it can be used for different engineering fields according to the loading environment, but the study of its mechanical behavior requires sophisticated numerical and analytical models. Several investigations in these models are available in the literature, however, most of those investigations are based on simplifying assumptions. In this paper, we present a three-dimensional finite element modeling of functionally graded material (FGM) beams subjected to static loading. Material properties are assumed to vary continuously along the beam thickness according to the power-law distribution with linear elastic behavior. The FGM beams are discretized by hexahedral finite elements type C3D20R (continuum stress/displacement, three-dimensional 20-node, reduced integration). We studied several numerical examples of FGM beams and compare the obtained numerical results with those of analytical models in the literature.\u0000 \u0000 ","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75733446","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}
The load-settlement and monolithic behaviors of a new type of deep foundation in sand named Box-Shaped Deep Foundation (BSDF) were studied, and a comparison to Conventional Piled Raft Foundations (CPRF) was made by carrying out extensive numerical analysis. Physical model tests were also conducted to validate the numerical approach presented in this study, and it turned out to be a reasonable agreement. In the scope of this paper, the results of the parametric study are presented, and design strategies for an optimized design of BSDFs are discussed.
{"title":"Investigation of the Load-settlement Behavior of Box-shaped Deep Foundations","authors":"Serdar Günay, Özer Çinicioğlu","doi":"10.3311/ppci.22359","DOIUrl":"https://doi.org/10.3311/ppci.22359","url":null,"abstract":"The load-settlement and monolithic behaviors of a new type of deep foundation in sand named Box-Shaped Deep Foundation (BSDF) were studied, and a comparison to Conventional Piled Raft Foundations (CPRF) was made by carrying out extensive numerical analysis. Physical model tests were also conducted to validate the numerical approach presented in this study, and it turned out to be a reasonable agreement. In the scope of this paper, the results of the parametric study are presented, and design strategies for an optimized design of BSDFs are discussed.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87555252","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}
P. Beiranvand, A. Kazemi, A. Amiri, M. Hosseini, Esfandyar Abasi
The shear walls are divided into two types of reinforced concrete and steel, which behave differently. In the present study, the linear and nonlinear static behavior of coupled reinforced concrete shear walls is investigated. Therefore, to validate the results, Yuan Cheng and coworkers’ laboratory model is investigated. The results of this study show that the stresses caused by external loading in the coupled shear walls are lower compared to the separate shear walls. In addition, the behavior of this system depends on the rigidity of the coupling beams. The excessive rigidity of the coupling beams does not significantly affect the behavior of these structures. Therefore, by using the continuous analytical method and ABAQUS software, a formula is proposed to calculate the dimensions of the ideal coupling beams cross-section. Based on the reviews, the proposed formula accurately predicts the nonlinear performance of the systems under investigation.
{"title":"Evaluation of Static Nonlinear Behavior of Coupled Reinforced Concrete Shear Walls with Steel Beams","authors":"P. Beiranvand, A. Kazemi, A. Amiri, M. Hosseini, Esfandyar Abasi","doi":"10.3311/ppci.21476","DOIUrl":"https://doi.org/10.3311/ppci.21476","url":null,"abstract":"The shear walls are divided into two types of reinforced concrete and steel, which behave differently. In the present study, the linear and nonlinear static behavior of coupled reinforced concrete shear walls is investigated. Therefore, to validate the results, Yuan Cheng and coworkers’ laboratory model is investigated. The results of this study show that the stresses caused by external loading in the coupled shear walls are lower compared to the separate shear walls. In addition, the behavior of this system depends on the rigidity of the coupling beams. The excessive rigidity of the coupling beams does not significantly affect the behavior of these structures. Therefore, by using the continuous analytical method and ABAQUS software, a formula is proposed to calculate the dimensions of the ideal coupling beams cross-section. Based on the reviews, the proposed formula accurately predicts the nonlinear performance of the systems under investigation.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83108668","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}
It is vital to assess the health of buildings following a major earthquake. New technologies such as deep learning algorithms have grown increasingly tempting in such rapid applications because of their increased reliabilities and simplicity to traditional methods. Due to the kinematics of steel moment frames, inelastic deformations tend to concentrate within the steel column during an earthquake, resulting in local or global buckling. Rapid failure mode detection of the existing deep steel W-shape columns (DSWCs) cannot be quickly identified due to a lack of comprehensive empirical and mechanics-based models. This research proposed a machine learning (ML) algorithm based on the state-of-the-art techniques of dynamic classifiers for failure mode forecasting of the DSWCs using an experimental database and illustrated why the ML model suggests a specific failure mode for a particular sample. The database was created by combining 939 instances from various studies that have been published. A total of six machine learning models based on Dynamic Selection strategy were implemented. Three metrics, i.e., accuracy, precision, and recall, were used to evaluate the performance of models. As a result of the extensive examination, a machine learning model based on the META-DES model was proposed. In the training stage, Overall Local Accuracy, A-Priori, and META-DES algorithms, received the highest score (>0.96) across all criteria. The META-DES model correctly predicted the failure mode of the DSWCs with an accuracy of 0.907 in the testing phase. The META-DES algorithm performed better than previous methods which are employed to identify the failure mode.
大地震后对建筑物的健康状况进行评估是至关重要的。深度学习算法等新技术在如此快速的应用中变得越来越有吸引力，因为它们比传统方法更可靠，更简单。由于钢弯矩框架的运动特性，在地震中，非弹性变形往往集中在钢柱内部，导致局部或整体屈曲。由于缺乏全面的经验和基于力学的模型，现有深钢w形柱(dswc)的快速失效模式检测无法快速识别。本研究提出了一种基于最先进的动态分类器技术的机器学习(ML)算法，用于使用实验数据库预测dswc的故障模式，并说明了为什么ML模型会对特定样本提出特定的故障模式。该数据库是通过结合已发表的各种研究中的939个实例创建的。实现了基于动态选择策略的6个机器学习模型。三个指标，即准确性，精密度和召回率，被用来评估模型的性能。在此基础上，提出了基于META-DES模型的机器学习模型。在训练阶段，Overall Local Accuracy、A-Priori和META-DES算法在所有标准中得分最高(>0.96)。META-DES模型在测试阶段准确预测了dswc的失效模式，准确率为0.907。META-DES算法在故障模式识别方面优于以往的方法。
{"title":"Data-driven Dynamic-classifiers-based Seismic Failure Mode Detection of Deep Steel W-shape Columns","authors":"M. S. Barkhordari, M. Tehranizadeh","doi":"10.3311/ppci.21427","DOIUrl":"https://doi.org/10.3311/ppci.21427","url":null,"abstract":"It is vital to assess the health of buildings following a major earthquake. New technologies such as deep learning algorithms have grown increasingly tempting in such rapid applications because of their increased reliabilities and simplicity to traditional methods. Due to the kinematics of steel moment frames, inelastic deformations tend to concentrate within the steel column during an earthquake, resulting in local or global buckling. Rapid failure mode detection of the existing deep steel W-shape columns (DSWCs) cannot be quickly identified due to a lack of comprehensive empirical and mechanics-based models. This research proposed a machine learning (ML) algorithm based on the state-of-the-art techniques of dynamic classifiers for failure mode forecasting of the DSWCs using an experimental database and illustrated why the ML model suggests a specific failure mode for a particular sample. The database was created by combining 939 instances from various studies that have been published. A total of six machine learning models based on Dynamic Selection strategy were implemented. Three metrics, i.e., accuracy, precision, and recall, were used to evaluate the performance of models. As a result of the extensive examination, a machine learning model based on the META-DES model was proposed. In the training stage, Overall Local Accuracy, A-Priori, and META-DES algorithms, received the highest score (>0.96) across all criteria. The META-DES model correctly predicted the failure mode of the DSWCs with an accuracy of 0.907 in the testing phase. The META-DES algorithm performed better than previous methods which are employed to identify the failure mode.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78046293","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}
Yielding dampers operate based on plastic deformations and energy dissipation. Given its low yield stress point and high ductility, low-yield steel is a suitable choice to build yielding dampers. In the present study, using the ABAQUS software, a number of pushover analyses have been carried out on a steel frame equipped with low-yield yielding dampers (LYDs). Therefore, using 40 pushover analyses, the effects of the number of the LYDs and the column’s axial force have been evaluated. All of the models were analyzed and their force-displacement curves were obtained. Using the obtained, different seismic aspects of the frame – i.e., ductility, strength, energy dissipation, stiffness – were assessed. Also, to calculate the values of effective stiffness and yield and ultimate strengths, a number of analytical relationships have been formulated. Finally, contour plots have been obtained which can be used to calculate the stiffness of the proposed LYD. Comparing results showed that the damper can, to an acceptable level, improve the seismic parameters of the structure. Also, if the stiffness and yield strength of all of the LYDs added to the frame are, respectively, 3.25 and 0.13 times those of the bare frame, the frame will have its best performance.
{"title":"Investigating the Effect of Low-Yield Yielding Dampers on the Seismic Behavior of Steel Frames","authors":"Kambiz Cheraghi, M. H. Tavana, R. Aghayari","doi":"10.3311/ppci.21804","DOIUrl":"https://doi.org/10.3311/ppci.21804","url":null,"abstract":"Yielding dampers operate based on plastic deformations and energy dissipation. Given its low yield stress point and high ductility, low-yield steel is a suitable choice to build yielding dampers. In the present study, using the ABAQUS software, a number of pushover analyses have been carried out on a steel frame equipped with low-yield yielding dampers (LYDs). Therefore, using 40 pushover analyses, the effects of the number of the LYDs and the column’s axial force have been evaluated. All of the models were analyzed and their force-displacement curves were obtained. Using the obtained, different seismic aspects of the frame – i.e., ductility, strength, energy dissipation, stiffness – were assessed. Also, to calculate the values of effective stiffness and yield and ultimate strengths, a number of analytical relationships have been formulated. Finally, contour plots have been obtained which can be used to calculate the stiffness of the proposed LYD. Comparing results showed that the damper can, to an acceptable level, improve the seismic parameters of the structure. Also, if the stiffness and yield strength of all of the LYDs added to the frame are, respectively, 3.25 and 0.13 times those of the bare frame, the frame will have its best performance.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81282830","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}
The nonlinearity of the soil may considerably affect the response of structures subjected to seismic events. This paper aims to show under which circumstances geometry, soil, and earthquake-type; the nonlinearity is important. A simple model based on a 1D shear column was developed to calculate the maximum shear strain (γ) in the soil subjected to earthquake excitation. It was found that γ is a function of peak ground acceleration PGA and the maximum horizontal ground displacement (∆). EC8 provides an expression for calculating ∆ that is independent of the soil thickness. It was found that this expression is conservative for shallow layers and underestimates γ for thick ones, as a result, improvements have been suggested. By performing several time history analyses, simple formulas are developed which enable the designer to assess when nonlinearity must be taken into account. Four curves based on soil thickness and peak ground acceleration have been introduced for different soil types (A, B, C, and D) using a limit value of γ = 10–4. These curves show that depending on the soil depth, the threshold acceleration of nonlinear soil behavior is around 0.48, 0.36, 0.29, and 0.10 m/s2 for soil types A, B, C, and D, respectively. Obviously, nonlinear analysis must be performed for shallow soil layers under moderate seismicity.
{"title":"Role of Nonlinearity in the Soil in Earthquake-Resistant Design of Structures","authors":"Yaseen Shayah, L. Kollár","doi":"10.3311/ppci.21641","DOIUrl":"https://doi.org/10.3311/ppci.21641","url":null,"abstract":"The nonlinearity of the soil may considerably affect the response of structures subjected to seismic events. This paper aims to show under which circumstances geometry, soil, and earthquake-type; the nonlinearity is important. A simple model based on a 1D shear column was developed to calculate the maximum shear strain (γ) in the soil subjected to earthquake excitation. It was found that γ is a function of peak ground acceleration PGA and the maximum horizontal ground displacement (∆). EC8 provides an expression for calculating ∆ that is independent of the soil thickness. It was found that this expression is conservative for shallow layers and underestimates γ for thick ones, as a result, improvements have been suggested. By performing several time history analyses, simple formulas are developed which enable the designer to assess when nonlinearity must be taken into account. Four curves based on soil thickness and peak ground acceleration have been introduced for different soil types (A, B, C, and D) using a limit value of γ = 10–4. These curves show that depending on the soil depth, the threshold acceleration of nonlinear soil behavior is around 0.48, 0.36, 0.29, and 0.10 m/s2 for soil types A, B, C, and D, respectively. Obviously, nonlinear analysis must be performed for shallow soil layers under moderate seismicity.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85443952","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}
Jinhuo Zheng, Minglong Shen, M. Motahari, M. Khajehzadeh
The tensile strength of the rocks is one of the effective factors in the rupture of structure foundations and underground spaces, the stability of rocky slopes, and the ability to drill and explode in rocks. This research was conducted to estimate tensile strength using methods such as simple regression (SR), multivariate linear regression (MVLR), support vector regression (SVR) with radial basis kernel function, multilayer feed-forward artificial neural network (MFF-ANN), Gaussian process regression (GPR) using squared exponential kernel (SEK) function, and adaptive neuro-fuzzy inference system (ANFIS) based on Gaussian membership function. For this purpose, petrography, and engineering features of the limestone, sandstone, and argillaceous limestone samples in the south of Iran, were assessed. The results obtained from this study were compared with those of previous research, revealing a strong correlation (R2=0.95 to 1.00) between our findings and the published works. To estimate Brazilian tensile strength (BTS), the index properties including water absorption by weight, point load index (PLI), porosity%, P-wave velocity (Vp), and density were considered as inputs. Methods were compared using various criteria. The SVR precision (R=0.96) was higher than MFF-ANN (R=0.92), ANFIS (R=0.95), GPR (R=0.945), and MVLR (R=0.89) to estimate the tensile strength. The average BTS measured in the laboratory and predicted by all 5 methods is 6.62 and 6.71 MPa, respectively, which shows the very high precision of the investigated methods. Analysis of model criteria using statistical analysis for developed relationships revealed that there is sufficient accuracy to use the empirical equations.
{"title":"Prediction of Rock Tensile Strength Using Soft Computing and Statistical Methods","authors":"Jinhuo Zheng, Minglong Shen, M. Motahari, M. Khajehzadeh","doi":"10.3311/ppci.22179","DOIUrl":"https://doi.org/10.3311/ppci.22179","url":null,"abstract":"The tensile strength of the rocks is one of the effective factors in the rupture of structure foundations and underground spaces, the stability of rocky slopes, and the ability to drill and explode in rocks. This research was conducted to estimate tensile strength using methods such as simple regression (SR), multivariate linear regression (MVLR), support vector regression (SVR) with radial basis kernel function, multilayer feed-forward artificial neural network (MFF-ANN), Gaussian process regression (GPR) using squared exponential kernel (SEK) function, and adaptive neuro-fuzzy inference system (ANFIS) based on Gaussian membership function. For this purpose, petrography, and engineering features of the limestone, sandstone, and argillaceous limestone samples in the south of Iran, were assessed. The results obtained from this study were compared with those of previous research, revealing a strong correlation (R2=0.95 to 1.00) between our findings and the published works. To estimate Brazilian tensile strength (BTS), the index properties including water absorption by weight, point load index (PLI), porosity%, P-wave velocity (Vp), and density were considered as inputs. Methods were compared using various criteria. The SVR precision (R=0.96) was higher than MFF-ANN (R=0.92), ANFIS (R=0.95), GPR (R=0.945), and MVLR (R=0.89) to estimate the tensile strength. The average BTS measured in the laboratory and predicted by all 5 methods is 6.62 and 6.71 MPa, respectively, which shows the very high precision of the investigated methods. Analysis of model criteria using statistical analysis for developed relationships revealed that there is sufficient accuracy to use the empirical equations.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87351401","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}
Using ultrasonic detection, microhardness test, scanning electron microscope test, mercury intrusion method and X-ray diffraction, the parameters of sonic time, microhardness, pore size distribution, cumulative pumping of high strength concrete under low cycle compression loading are tested after exposure to 200 °C, 400 °C and 600 °C. Experimental study showed that with the increasing loading times, the rangeability of sonic time, the microhardness, and total pore volume shows an overall trend of fast-slow-fast. Furthermore, the sonic time and microhardness are linearly related to the longitudinal fatigue strain. The research results provided references for nondestructive testing, fatigue damage analysis and structural evaluation of concrete structures subjected to fire or other high temperature processes.
{"title":"Microstructural Changes of High Strength Concrete during Low Cycle Compression Fatigue Test after Exposure to High Temperature","authors":"D. Zhao, Wenbo He, Peiyuan Hao","doi":"10.3311/ppci.21506","DOIUrl":"https://doi.org/10.3311/ppci.21506","url":null,"abstract":"Using ultrasonic detection, microhardness test, scanning electron microscope test, mercury intrusion method and X-ray diffraction, the parameters of sonic time, microhardness, pore size distribution, cumulative pumping of high strength concrete under low cycle compression loading are tested after exposure to 200 °C, 400 °C and 600 °C. Experimental study showed that with the increasing loading times, the rangeability of sonic time, the microhardness, and total pore volume shows an overall trend of fast-slow-fast. Furthermore, the sonic time and microhardness are linearly related to the longitudinal fatigue strain. The research results provided references for nondestructive testing, fatigue damage analysis and structural evaluation of concrete structures subjected to fire or other high temperature processes.\u0000\u0000\u0000 \u0000\u0000","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72888263","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}
Vibration-based structural damage detection is one of the most promising venues for building smart and automated structural health monitoring applications; however, its applicability is impeded by a large amount of collected vibration data, and the performance could be undermined by degraded data. Therefore, this study develops a robust framework, dubbed AutoBoost-SDD, that can effectively handle contaminated vibration data and provide reliable monitoring results within reasonable computational resources. The proposed method consists of three key components. Firstly, multi-domain feature extraction techniques are utilized to convert high-dimensional raw data into informative feature vectors. Secondly, the auto-encoder deep learning architecture is leveraged to refine feature vectors of contaminated data. Finally, a tree-based boosting machine learning algorithm, namely LightGBM, is employed to assess the structures’ operational states using learned output from the second step. The viability and performance of the proposed framework are illustrated via three case studies involving numerical data of a 5-degree of freedom system, a 2D frame structure, and experimental data of a large-scale 18-story frame structure from the literature. The results show that the AutoBoost-SDD framework is able to provide reasonable detection results despite the presence of various contaminations, including noisy, missing, and anomalous data.
{"title":"Development of Structural Damage Detection Method Working with Contaminated Vibration Data via Autoencoder and Gradient Boosting","authors":"V. Dang","doi":"10.3311/ppci.22373","DOIUrl":"https://doi.org/10.3311/ppci.22373","url":null,"abstract":"Vibration-based structural damage detection is one of the most promising venues for building smart and automated structural health monitoring applications; however, its applicability is impeded by a large amount of collected vibration data, and the performance could be undermined by degraded data. Therefore, this study develops a robust framework, dubbed AutoBoost-SDD, that can effectively handle contaminated vibration data and provide reliable monitoring results within reasonable computational resources. The proposed method consists of three key components. Firstly, multi-domain feature extraction techniques are utilized to convert high-dimensional raw data into informative feature vectors. Secondly, the auto-encoder deep learning architecture is leveraged to refine feature vectors of contaminated data. Finally, a tree-based boosting machine learning algorithm, namely LightGBM, is employed to assess the structures’ operational states using learned output from the second step. The viability and performance of the proposed framework are illustrated via three case studies involving numerical data of a 5-degree of freedom system, a 2D frame structure, and experimental data of a large-scale 18-story frame structure from the literature. The results show that the AutoBoost-SDD framework is able to provide reasonable detection results despite the presence of various contaminations, including noisy, missing, and anomalous data.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73606480","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}
Highly efficient materials and structures are becoming increasingly common in military, aeronautical, aerospace, mechanical, and civil engineering applications. Composite materials have been developed to address the need to combine two or more materials to achieve superior properties. Many structural elements, such as laminated beams, use composite materials, but an accurate mathematical model of the bending behavior is required due to the abrupt changes in material properties in the interlaminar zones. This accurate model can be achieved using zigzag theory. This theory is one of the most commonly used formulations for modeling laminated beams. This theory is an improvement of the equivalent single-layer theory as an additional term called the “zigzag function” is used to represent the variation in the axial displacement along the cross section. This paper proposes a novel high-order zigzag function in a sinusoidal format. Several higher-order beam theories are combined with the proposed functions, and their performances are compared with those of other functions in the literature. The results reveal excellent agreement between the proposed formulation and the reference solution as well as a more effective combination of zigzag functions and beam theory.
{"title":"A Novel Higher-Order Zigzag Function Applied to Refined Unified Beam Theory for the Analysis of Composite Laminated Materials","authors":"Leonardo Fellipe Prado Leite, F. C. Da Rocha","doi":"10.3311/ppci.21784","DOIUrl":"https://doi.org/10.3311/ppci.21784","url":null,"abstract":"Highly efficient materials and structures are becoming increasingly common in military, aeronautical, aerospace, mechanical, and civil engineering applications. Composite materials have been developed to address the need to combine two or more materials to achieve superior properties. Many structural elements, such as laminated beams, use composite materials, but an accurate mathematical model of the bending behavior is required due to the abrupt changes in material properties in the interlaminar zones. This accurate model can be achieved using zigzag theory. This theory is one of the most commonly used formulations for modeling laminated beams. This theory is an improvement of the equivalent single-layer theory as an additional term called the “zigzag function” is used to represent the variation in the axial displacement along the cross section. This paper proposes a novel high-order zigzag function in a sinusoidal format. Several higher-order beam theories are combined with the proposed functions, and their performances are compared with those of other functions in the literature. The results reveal excellent agreement between the proposed formulation and the reference solution as well as a more effective combination of zigzag functions and beam theory.","PeriodicalId":49705,"journal":{"name":"Periodica Polytechnica-Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90304540","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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