Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.623
Ramin Ghiasi, M. Ghasemi, T. Chan
Structural Health Monitoring (SHM) is rapidly developing as a multi-disciplinary technology solution for condition assessment and performance evaluation of civil infrastructures. It consists of three parts: data collection, data processing (feature extraction/selection), and decision-making (feature classification). In this research, for effectively reducing a dimension of SHM data, various methods are proposed such as advanced feature extraction, feature subset selection using optimization algorithm, and effective surrogate model based on artificial intelligence methods. These frameworks enhance the capability of the SHM process to tackle with uncertainties and big data problem. To reach such goals, a framework based on three main blocks are proposed here: feature extraction block using wavelet pocket relative energy (WPRE), feature selection block using improved version of binary harmony search algorithm and finally feature classification block using wavelet weighted least square support vector machine (WWLS-SVM). The capability of the proposed framework is compared with various well known methods for each block. Results will be presented using metrics of precision, recall, accuracy and feature-reduction. Furthermore, to show the robustness of the proposed methods, six well-known benchmark datasets of SHM domain are studied. The results validate the suitability of the proposed methods in providing data reduction and accelerating damage detection process.
{"title":"Optimum feature selection for SHM of benchmark structures using efficient AI mechanism","authors":"Ramin Ghiasi, M. Ghasemi, T. Chan","doi":"10.12989/SSS.2021.27.4.623","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.623","url":null,"abstract":"Structural Health Monitoring (SHM) is rapidly developing as a multi-disciplinary technology solution for condition assessment and performance evaluation of civil infrastructures. It consists of three parts: data collection, data processing (feature extraction/selection), and decision-making (feature classification). In this research, for effectively reducing a dimension of SHM data, various methods are proposed such as advanced feature extraction, feature subset selection using optimization algorithm, and effective surrogate model based on artificial intelligence methods. These frameworks enhance the capability of the SHM process to tackle with uncertainties and big data problem. To reach such goals, a framework based on three main blocks are proposed here: feature extraction block using wavelet pocket relative energy (WPRE), feature selection block using improved version of binary harmony search algorithm and finally feature classification block using wavelet weighted least square support vector machine (WWLS-SVM). The capability of the proposed framework is compared with various well known methods for each block. Results will be presented using metrics of precision, recall, accuracy and feature-reduction. Furthermore, to show the robustness of the proposed methods, six well-known benchmark datasets of SHM domain are studied. The results validate the suitability of the proposed methods in providing data reduction and accelerating damage detection process.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"623"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46183257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.669
A. Alnujaie, Ş. Akbaş, M. A. Eltaher, A. Assie
The following article presents the damped forced vibration of layered functionally graded thick beams including material porosities. In case of very thick beams, beam theories fail to satisfy boundary conditions and to predict the mechanical response accurately. So, the two-dimensional (2D) plane continuum model is exploited to model a thick functionally graded layered beam. The beam is composed from three- layers with functionally graded porous materials. The porosity is described by three different distribution models through the layer thickness. Applied forces to the functionally graded beam are assumed to be sinusoidal harmonic point load in time domain. The KelvinVoigt viscoelastic constitutive model is used to simulate damping effect. The governing equations are obtained by using Lagrange's equations. In frame of finite element analysis, twelve .node 2D plane element is exploited to discretize the space domain of thick beam. In the solution of the dynamic problem, the Newmark average acceleration method is used. Numerical studies illustrate effects of porosity distribution, stacking sequence, and graduation constant on the dynamic responses of layered functionally graded porous thick beams. The results show that the porosity function, stacking sequences and the damping ratio have a vital role in dynamic response of functionally graded beams. The proposed model can be used in nuclear, marine, and aerospace technologies.
{"title":"Damped forced vibration analysis of layered functionally graded thick beams with porosity","authors":"A. Alnujaie, Ş. Akbaş, M. A. Eltaher, A. Assie","doi":"10.12989/SSS.2021.27.4.669","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.669","url":null,"abstract":"The following article presents the damped forced vibration of layered functionally graded thick beams including material porosities. In case of very thick beams, beam theories fail to satisfy boundary conditions and to predict the mechanical response accurately. So, the two-dimensional (2D) plane continuum model is exploited to model a thick functionally graded layered beam. The beam is composed from three- layers with functionally graded porous materials. The porosity is described by three different distribution models through the layer thickness. Applied forces to the functionally graded beam are assumed to be sinusoidal harmonic point load in time domain. The KelvinVoigt viscoelastic constitutive model is used to simulate damping effect. The governing equations are obtained by using Lagrange's equations. In frame of finite element analysis, twelve .node 2D plane element is exploited to discretize the space domain of thick beam. In the solution of the dynamic problem, the Newmark average acceleration method is used. Numerical studies illustrate effects of porosity distribution, stacking sequence, and graduation constant on the dynamic responses of layered functionally graded porous thick beams. The results show that the porosity function, stacking sequences and the damping ratio have a vital role in dynamic response of functionally graded beams. The proposed model can be used in nuclear, marine, and aerospace technologies.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"669"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49177362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.559
H. Haeri, V. Sarfarazi, M. F. Marji, M. Yavari, Amin Zahedi-khameneh
The direct tensile strength of a typical hard rock like granite is measured by a novel apparatus known as compression-to-tensile load transfer (CTLT) device. The rock specimen is prepared in form of a slab containing a central hole and placed in the universal testing machine where the direct tensile stress can be applied to this specimen by implementing a special type of load transferring device which converts the applied compressive load to that of the tensile during the test. In the present work, some typical hard rock specimens of granite are specially prepared and tested in the laboratory to measure their direct tensile strengths. Then, a new load converting device implemented in the universal tensile testing machine is used to cause the rock specimen to be subjected to a direct tensile loading during the test. The compressive load was applied to the transferring device at the rate of 0.02 MPa/s. Numerical modeling of the tested specimens were accomplished using the discrete element method (DEM) and the higher order displacement discontinuity method (HODDM). The tensile failure of granite rock mainly occurs along the horizontal axis. The experimental results were in a good accordance with DEM results and HODDM outputs.
{"title":"Direct tensile strength measurement of granite by the universal tensile testing machine","authors":"H. Haeri, V. Sarfarazi, M. F. Marji, M. Yavari, Amin Zahedi-khameneh","doi":"10.12989/SSS.2021.27.4.559","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.559","url":null,"abstract":"The direct tensile strength of a typical hard rock like granite is measured by a novel apparatus known as compression-to-tensile load transfer (CTLT) device. The rock specimen is prepared in form of a slab containing a central hole and placed in the universal testing machine where the direct tensile stress can be applied to this specimen by implementing a special type of load transferring device which converts the applied compressive load to that of the tensile during the test. In the present work, some typical hard rock specimens of granite are specially prepared and tested in the laboratory to measure their direct tensile strengths. Then, a new load converting device implemented in the universal tensile testing machine is used to cause the rock specimen to be subjected to a direct tensile loading during the test. The compressive load was applied to the transferring device at the rate of 0.02 MPa/s. Numerical modeling of the tested specimens were accomplished using the discrete element method (DEM) and the higher order displacement discontinuity method (HODDM). The tensile failure of granite rock mainly occurs along the horizontal axis. The experimental results were in a good accordance with DEM results and HODDM outputs.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"559"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47371799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.691
Afshin Bahrami Rad, M. Nouri, J. Katebi, S. Ghasemi
Model predictive control (MPC) is an optimal control algorithm in which the current control action is obtained by solving an optimization problem in the presence of hard and soft constraints in the finite time horizons sequentially. In most cases, neglecting the effects of the external loads in predicting the future responses of the structures lead to inaccurate control action. Therefore, it could be beneficial to consider the effects of external loads in the future within the MPC to improve its accuracy. In this paper, a developed model predictive control (DMPC) scheme is introduced. For this purpose, a forecasting seismic excitation model is formulated by two sequential autoregressive (AR) models. One of those estimates the future output of the seismic excitation and the second one enhances the estimation accuracy. Then, the efficiency of the presented approach is demonstrated by the numerical study of two benchmark buildings equipped with an active tuned mass damper (ATMD). The performance of the proposed MPC is finally compared with the conventional and ideal MPCs. The numerical outputs prove the competency and higher conformity of the proposed MPC with the ideal one almost in all of the cases. Twelve benchmark performance indices are also utilized for determining the superiority of the method. The average conformity values for all of the performance indices for the proposed method in the three- and nine-story buildings are by up to 17.75% and 9% more than the values in conventional one, respectively.
{"title":"A developed model predictive control scheme for vibration attenuation of building structures","authors":"Afshin Bahrami Rad, M. Nouri, J. Katebi, S. Ghasemi","doi":"10.12989/SSS.2021.27.4.691","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.691","url":null,"abstract":"Model predictive control (MPC) is an optimal control algorithm in which the current control action is obtained by solving an optimization problem in the presence of hard and soft constraints in the finite time horizons sequentially. In most cases, neglecting the effects of the external loads in predicting the future responses of the structures lead to inaccurate control action. Therefore, it could be beneficial to consider the effects of external loads in the future within the MPC to improve its accuracy. In this paper, a developed model predictive control (DMPC) scheme is introduced. For this purpose, a forecasting seismic excitation model is formulated by two sequential autoregressive (AR) models. One of those estimates the future output of the seismic excitation and the second one enhances the estimation accuracy. Then, the efficiency of the presented approach is demonstrated by the numerical study of two benchmark buildings equipped with an active tuned mass damper (ATMD). The performance of the proposed MPC is finally compared with the conventional and ideal MPCs. The numerical outputs prove the competency and higher conformity of the proposed MPC with the ideal one almost in all of the cases. Twelve benchmark performance indices are also utilized for determining the superiority of the method. The average conformity values for all of the performance indices for the proposed method in the three- and nine-story buildings are by up to 17.75% and 9% more than the values in conventional one, respectively.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"691"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48378695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.607
Jiecheng Xiong, Jun Chen
To mathematically represent crowd jumping loads, the features of the jumping load of each person, including pulse curve patterns, pulse interval sequences, and pulse energy sequences are considered. These features are essentially highdimensional random variables. However, they have to be represented in a practically simplified model due to the lack of mathematical tools. The recently emerged generative adversarial networks (GANs) can model high-dimensional random variables well, as demonstrated in image synthesis and text generation. Therefore, this study adopts GANs as a new method for modelling crowd jumping loads. Conditional GANs (CGANs) combined with Wasserstein GANs with gradient penalty (WGANs*GP) are used in pulse curve pattern modelling, where a multi-layer perceptron and convolutional neural network are selected as the discriminator and generator, respectively. For the pulse energy sequence and pulse interval sequence modelling, similar GANs are used, where recurrent neural networks are selected as both the generator and discriminator. Finally, crowd jumping loads can be simulated by connected the pulse samples based on the pulse energy sequence samples and interval sequence samples, generated by the three proposed GANs. The experimental individual and crowd jumping load records are utilized in training GANs to ensure their output can simulate real load records well. Finally, the feasibility of the proposed GANs was verified by comparing the measured structural responses of an existing floor to the predicted structural responses.
{"title":"Crowd jumping load simulation with generative adversarial networks","authors":"Jiecheng Xiong, Jun Chen","doi":"10.12989/SSS.2021.27.4.607","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.607","url":null,"abstract":"To mathematically represent crowd jumping loads, the features of the jumping load of each person, including pulse curve patterns, pulse interval sequences, and pulse energy sequences are considered. These features are essentially highdimensional random variables. However, they have to be represented in a practically simplified model due to the lack of mathematical tools. The recently emerged generative adversarial networks (GANs) can model high-dimensional random variables well, as demonstrated in image synthesis and text generation. Therefore, this study adopts GANs as a new method for modelling crowd jumping loads. Conditional GANs (CGANs) combined with Wasserstein GANs with gradient penalty (WGANs*GP) are used in pulse curve pattern modelling, where a multi-layer perceptron and convolutional neural network are selected as the discriminator and generator, respectively. For the pulse energy sequence and pulse interval sequence modelling, similar GANs are used, where recurrent neural networks are selected as both the generator and discriminator. Finally, crowd jumping loads can be simulated by connected the pulse samples based on the pulse energy sequence samples and interval sequence samples, generated by the three proposed GANs. The experimental individual and crowd jumping load records are utilized in training GANs to ensure their output can simulate real load records well. Finally, the feasibility of the proposed GANs was verified by comparing the measured structural responses of an existing floor to the predicted structural responses.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"607"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44191817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.651
M. Kaloop, Omar M M Yousry, P. Samui, M. Elshikh, J. Hu
The compressive strength is an important mechanical feature of concrete that is needed in construction design. Thus, a lot of investigations were carried out to predict the compressive strength of various concretes. However, the prediction models for the compressive strength of cement mortar or paste that include magnetic water (MW) and granulated blast-furnace slag (GBFS) are still limited. The current study has developed hybrid algorithms based on adaptive neuro-fuzzy inference system (ANFIS) for modeling the compressive strength of cement mortar and paste that made with MW and GBFS as a novel mixture content. A total of 144 experimental sets of concrete-compressive strength tests for each cement mortar and paste were collected to train and validate the proposed methods, in which the cycles number of water magnetization, cement, GBFS, superplasticizer contents and curing time are set as the input data while the compressive strength value is set as the output. The developed hybrid algorithms of ANFIS optimized by firefly algorithm (FA), Improved Particle Swarm Optimization (IPSO) and biogeographybased optimization (BBO) algorithms for predicting the compressive strength of the mortar and paste. The proposed models and relevance vector machine (RVM) approach were evaluated and compared. The results showed that the ANFIS-FA outperforms other models for modeling the compressive strength of cement mortar and paste. The adjusted-coefficient of determination and root mean square error values of cement mortar models (96.20%, 92.33%, 92.36% and 89.41%) and (2.17 MPa, 3.10 MPa, 3.18 MPa and 3.06 MPa) and of cement paste models (96.92%, 80.91%, 92.19% and 88.18%) and (2.45 MPa, 5.80 MPa, 4.39 MPa and 5.20 MPa) were determined for ANFIS-FA, ANFIS-IPSO, ANFIS-BBO and RVM models, respectively, which indicate that the ANFIS-FA is a suitable model for estimating the compressive strength of cement mortar and paste that include MW. Moreover, the sensitivity of MW and GBFS is shown high for modeling the compressive strength of cement mortar.
{"title":"Hybrid-ANFIS approaches for compressive strength prediction of cementitious mortar and paste employing magnetic water","authors":"M. Kaloop, Omar M M Yousry, P. Samui, M. Elshikh, J. Hu","doi":"10.12989/SSS.2021.27.4.651","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.651","url":null,"abstract":"The compressive strength is an important mechanical feature of concrete that is needed in construction design. Thus, a lot of investigations were carried out to predict the compressive strength of various concretes. However, the prediction models for the compressive strength of cement mortar or paste that include magnetic water (MW) and granulated blast-furnace slag (GBFS) are still limited. The current study has developed hybrid algorithms based on adaptive neuro-fuzzy inference system (ANFIS) for modeling the compressive strength of cement mortar and paste that made with MW and GBFS as a novel mixture content. A total of 144 experimental sets of concrete-compressive strength tests for each cement mortar and paste were collected to train and validate the proposed methods, in which the cycles number of water magnetization, cement, GBFS, superplasticizer contents and curing time are set as the input data while the compressive strength value is set as the output. The developed hybrid algorithms of ANFIS optimized by firefly algorithm (FA), Improved Particle Swarm Optimization (IPSO) and biogeographybased optimization (BBO) algorithms for predicting the compressive strength of the mortar and paste. The proposed models and relevance vector machine (RVM) approach were evaluated and compared. The results showed that the ANFIS-FA outperforms other models for modeling the compressive strength of cement mortar and paste. The adjusted-coefficient of determination and root mean square error values of cement mortar models (96.20%, 92.33%, 92.36% and 89.41%) and (2.17 MPa, 3.10 MPa, 3.18 MPa and 3.06 MPa) and of cement paste models (96.92%, 80.91%, 92.19% and 88.18%) and (2.45 MPa, 5.80 MPa, 4.39 MPa and 5.20 MPa) were determined for ANFIS-FA, ANFIS-IPSO, ANFIS-BBO and RVM models, respectively, which indicate that the ANFIS-FA is a suitable model for estimating the compressive strength of cement mortar and paste that include MW. Moreover, the sensitivity of MW and GBFS is shown high for modeling the compressive strength of cement mortar.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"651"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45365025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.593
Linlin Wang, B. Spencer, Junjie Li, Pan Hu
Visual inspection of concrete cracks has been widely used in structural health monitoring (SHM). Capturing highresolution images is an effective method to visualize a complete crack, but it is difficult to show a whole crack from a single high-resolution image. One feasible method is using image stitching technique to stitch several images into a complete crack map. However, the current image stitching method is a computationally intensive process. Numerous images are required to cover large-scale structures with sufficient resolution, this can be computationally prohibitive. To address this problem, an improved image stitching method for crack damage evaluation is proposed, which can quickly stitch the crack images without affecting the quality of the stitching or the resulting images. Rather than first stitching the images together and then determining the crack maps, we propose to first develop the crack maps for the individual images and then stitch them together. The proposed method reduces the number of redundant matching points between the original images by combining their characteristics during image stitching, so it can reduce the calculation time without affecting the quality. Also, the results will not be influenced by the image stitching seam, which can reduce the complexity of the algorithm. Several experimental results are provided in this article to demonstrate that the proposed method can reduce the calculation time without affecting the quality of image stitching and have better robustness than the current method in use.
{"title":"A fast image-stitching algorithm for characterization of cracks in large-scale structures","authors":"Linlin Wang, B. Spencer, Junjie Li, Pan Hu","doi":"10.12989/SSS.2021.27.4.593","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.593","url":null,"abstract":"Visual inspection of concrete cracks has been widely used in structural health monitoring (SHM). Capturing highresolution images is an effective method to visualize a complete crack, but it is difficult to show a whole crack from a single high-resolution image. One feasible method is using image stitching technique to stitch several images into a complete crack map. However, the current image stitching method is a computationally intensive process. Numerous images are required to cover large-scale structures with sufficient resolution, this can be computationally prohibitive. To address this problem, an improved image stitching method for crack damage evaluation is proposed, which can quickly stitch the crack images without affecting the quality of the stitching or the resulting images. Rather than first stitching the images together and then determining the crack maps, we propose to first develop the crack maps for the individual images and then stitch them together. The proposed method reduces the number of redundant matching points between the original images by combining their characteristics during image stitching, so it can reduce the calculation time without affecting the quality. Also, the results will not be influenced by the image stitching seam, which can reduce the complexity of the algorithm. Several experimental results are provided in this article to demonstrate that the proposed method can reduce the calculation time without affecting the quality of image stitching and have better robustness than the current method in use.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"593"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45737891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.12989/SSS.2021.27.4.641
A. G. Arani, Ashkan Farazin, M. Mohammadimehr, S. Lenjannejadian
In the present study, the generation of electrical energy from induced vibrations in a composite beam with piezoelectric layer are studied. Accordingly, using Euler-Bernoulli beam theory and considering two types of air damping (external damping) and structural damping (internal damping), the equations of motion for sandwich beam are obtained and then using the Kantorovich method, the output voltage relations for a composite beam with a piezoelectric layer are extracted. After validating the analytical results with the results in the literature, the effect of various parameters such as external fluid flow rate, fiber angle, and how the piezoelectric layer composite beams are arranged on energy harvesting. Also, the maximum oscillation amplitude are investigated. The results show that by using composite materials and with proper layer design and fiber angle in each layer, a different equivalent modulus of elasticity can be created in the composite beam, which will change the normal frequency of the system and the output voltage range of the circuit. The results show that the angle of the fibers has a significant effect on the damping coefficient of the structure, flexural stiffness, natural frequency and finally energy harvesting. According to the results, it can be seen that the minimum value of voltage per use of fibers with an angle of 50 degrees and the maximum amount of voltage per use of fibers with an angle of zero degrees are occurred.
{"title":"Energy harvesting of sandwich beam with laminated composite core and piezoelectric face sheets under external fluid flow","authors":"A. G. Arani, Ashkan Farazin, M. Mohammadimehr, S. Lenjannejadian","doi":"10.12989/SSS.2021.27.4.641","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.4.641","url":null,"abstract":"In the present study, the generation of electrical energy from induced vibrations in a composite beam with piezoelectric layer are studied. Accordingly, using Euler-Bernoulli beam theory and considering two types of air damping (external damping) and structural damping (internal damping), the equations of motion for sandwich beam are obtained and then using the Kantorovich method, the output voltage relations for a composite beam with a piezoelectric layer are extracted. After validating the analytical results with the results in the literature, the effect of various parameters such as external fluid flow rate, fiber angle, and how the piezoelectric layer composite beams are arranged on energy harvesting. Also, the maximum oscillation amplitude are investigated. The results show that by using composite materials and with proper layer design and fiber angle in each layer, a different equivalent modulus of elasticity can be created in the composite beam, which will change the normal frequency of the system and the output voltage range of the circuit. The results show that the angle of the fibers has a significant effect on the damping coefficient of the structure, flexural stiffness, natural frequency and finally energy harvesting. According to the results, it can be seen that the minimum value of voltage per use of fibers with an angle of 50 degrees and the maximum amount of voltage per use of fibers with an angle of zero degrees are occurred.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"641"},"PeriodicalIF":3.5,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42976434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.12989/SSS.2021.27.3.467
Mohsen Zare Golmoghany, S. M. Zahrai
To improve seismic behavior of structures, a two-level control system is proposed in this paper where by combining two vertical shear panels in series in a chevron bracing configuration, Double-Vertical Shear Panel, D-VSP is introduced. Utilizing two-levels of energy absorption for two different earthquake intensity levels, D-VSP is expected to beneficially change dynamic behavior parameters like strength, stiffness and damping ratio through increasing ductility. To validate research, a VSP is modeled in ABAQUS and related numerical results are compared to those of a previous experimental work. Pushover, quasistatic cyclic and seismic analyses are conducted on two models. The hysteresis curves show symmetric two-level behavior with stable strength and stiffness leading to increase ductility ratio up to 29.4%. Maximum displacement and maximum base shear under seismic loading decrease 5.91 and 11.18% respectively under moderate earthquakes when D-VSP system uses only first fuse, saving second fuse for severe earthquakes. However, in a strong earthquake, both of the shear panels absorb seismic energy and can control vibration better than conventional systems with one level control mechanism. The proposed system using a weaker panel can better control an extensive range of earthquakes as well as the earthquake with foreshocks.
{"title":"Seismic behavior of a two-level control system with double vertical shear links in series","authors":"Mohsen Zare Golmoghany, S. M. Zahrai","doi":"10.12989/SSS.2021.27.3.467","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.3.467","url":null,"abstract":"To improve seismic behavior of structures, a two-level control system is proposed in this paper where by combining two vertical shear panels in series in a chevron bracing configuration, Double-Vertical Shear Panel, D-VSP is introduced. Utilizing two-levels of energy absorption for two different earthquake intensity levels, D-VSP is expected to beneficially change dynamic behavior parameters like strength, stiffness and damping ratio through increasing ductility. To validate research, a VSP is modeled in ABAQUS and related numerical results are compared to those of a previous experimental work. Pushover, quasistatic cyclic and seismic analyses are conducted on two models. The hysteresis curves show symmetric two-level behavior with stable strength and stiffness leading to increase ductility ratio up to 29.4%. Maximum displacement and maximum base shear under seismic loading decrease 5.91 and 11.18% respectively under moderate earthquakes when D-VSP system uses only first fuse, saving second fuse for severe earthquakes. However, in a strong earthquake, both of the shear panels absorb seismic energy and can control vibration better than conventional systems with one level control mechanism. The proposed system using a weaker panel can better control an extensive range of earthquakes as well as the earthquake with foreshocks.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"467"},"PeriodicalIF":3.5,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41737249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-01DOI: 10.12989/SSS.2021.27.3.493
Jingliang Liu, Chengxu Lin, Xinlin Ye, Wenting Zheng, Yong-peng Luo
Since the complex continuous wavelet transform (CCWT) based pile damage detection method is empirical and subjective, an improved algorithm for pile damage localization based on CCWT is proposed by introducing K-means clustering and fast Fourier transform (FFT). In this method, the K-means clustering algorithm is used to accurately calculate the time coordinates of two energy concentrating points caused by the incident and reflected waves, respectively. Meanwhile, FFT is employed to estimate the concerned frequency band of the response signal. Therefore, a specific region in the time frequency plane is defined objectively and it can be used to search the phase angle turning points and localize pile damage. The proposed method is verified by numerical examples of piles with single and multiple damage positions. A parameter analysis is also conducted to investigate how damage depth and damage degree in piles affect the accuracy and effectiveness of the proposed method. The results demonstrate that the proposed method is able to localize a pile with a damage at least 2.5 m away from the pile head when the damage degree is as less as 5%. After that, dynamic tests of an actual square reinforced concrete pile and an actual circular reinforced concrete pile are investigated to verify the application of the proposed method on practical engineering. Although the proposed method is capable of localizing actual piles more accurately than the CCWT method, the problem of interference points needs to be addressed by mutual verification with other pile damage localization methods.
{"title":"An improved algorithm for pile damage localization based on complex continuous wavelet transform","authors":"Jingliang Liu, Chengxu Lin, Xinlin Ye, Wenting Zheng, Yong-peng Luo","doi":"10.12989/SSS.2021.27.3.493","DOIUrl":"https://doi.org/10.12989/SSS.2021.27.3.493","url":null,"abstract":"Since the complex continuous wavelet transform (CCWT) based pile damage detection method is empirical and subjective, an improved algorithm for pile damage localization based on CCWT is proposed by introducing K-means clustering and fast Fourier transform (FFT). In this method, the K-means clustering algorithm is used to accurately calculate the time coordinates of two energy concentrating points caused by the incident and reflected waves, respectively. Meanwhile, FFT is employed to estimate the concerned frequency band of the response signal. Therefore, a specific region in the time frequency plane is defined objectively and it can be used to search the phase angle turning points and localize pile damage. The proposed method is verified by numerical examples of piles with single and multiple damage positions. A parameter analysis is also conducted to investigate how damage depth and damage degree in piles affect the accuracy and effectiveness of the proposed method. The results demonstrate that the proposed method is able to localize a pile with a damage at least 2.5 m away from the pile head when the damage degree is as less as 5%. After that, dynamic tests of an actual square reinforced concrete pile and an actual circular reinforced concrete pile are investigated to verify the application of the proposed method on practical engineering. Although the proposed method is capable of localizing actual piles more accurately than the CCWT method, the problem of interference points needs to be addressed by mutual verification with other pile damage localization methods.","PeriodicalId":51155,"journal":{"name":"Smart Structures and Systems","volume":"27 1","pages":"493"},"PeriodicalIF":3.5,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42099769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：