This paper presents the static and fatigue tests of hybrid(bonded/bolted)glass fiber reinforced polymer(GFRP)joints.Nine specimens of single-lap hybrid GFRP joints have been fabricated to study the static and fatigue ...This paper presents the static and fatigue tests of hybrid(bonded/bolted)glass fiber reinforced polymer(GFRP)joints.Nine specimens of single-lap hybrid GFRP joints have been fabricated to study the static and fatigue behaviors in the experimental campaign.The static tests of uniaxial tension loading are first conducted,from which the static ultimate bearing capacities of the joints are obtained.High-cycle fatigue tests are subsequently carried out so that the fatigue failure mode,fatigue life,and stiffness degradation of joints can be obtained.The measuring techniques including acoustic emission monitoring and three-dimensional digital image correlation have been employed in the tests to record the damage development process.The results revealed that the static strength and fatigue behavior of such thick hybrid GFRP joints were controlled by the bolted connections.The four stages of fatigue failure process are obtained from tests and acoustic emission signals analysis:cumulative damage of adhesive layer,damage of the adhesive layer,cumulative damage of GFRP plate,and damage of GFRP plate.The fatigue life and stiffness degradation can be improved by more bolts.The S-N(fatigue stress versus life)curves for the fatigue design of the single-lap hybrid GFRP joints under uniaxial tension loading are also proposed.展开更多
Accurately estimating the interfacial bond capacity of the near-surface mounted(NSM)carbon fiber-reinforced polymer(CFRP)to concrete joint is a fundamental task in the strengthening and retrofit of existing reinforced...Accurately estimating the interfacial bond capacity of the near-surface mounted(NSM)carbon fiber-reinforced polymer(CFRP)to concrete joint is a fundamental task in the strengthening and retrofit of existing reinforced concrete(RC)structures.The machine learning(ML)approach may provide an alternative to the commonly used semi-empirical or semi-analytical methods.Therefore,in this work we have developed a predictive model based on an artificial neural network(ANN)approach,i.e.using a back propagation neural network(BPNN),to map the complex data pattern obtained from an NSM CFRP to concrete joint.It involves a set of nine material and geometric input parameters and one output value.Moreover,by employing the neural interpretation diagram(NID)technique,the BPNN model becomes interpretable,as the influence of each input variable on the model can be tracked and quantified based on the connection weights of the neural network.An extensive database including 163 pull-out testing samples,collected from the authors’research group and from published results in the literature,is used to train and verify the ANN.Our results show that the prediction given by the BPNN model agrees well with the experimental data and yields a coefficient of determination of 0.957 on the whole database.After removing one non-significant feature,the BPNN becomes even more computationally efficient and accurate.In addition,compared with the existed semi-analytical model,the ANN-based approach demonstrates a more accurate estimation.Therefore,the proposed ML method may be a promising alternative for predicting the bond strength of NSM CFRP to concrete joint for structural engineers.展开更多
The column-to-beam flexural strength ratio(CBFSR)has been used in many seismic codes to achieve the strong column-weak beam(SCWB)failure mode in reinforced concrete(RC)frames,in which plastic hinges appear earlier in ...The column-to-beam flexural strength ratio(CBFSR)has been used in many seismic codes to achieve the strong column-weak beam(SCWB)failure mode in reinforced concrete(RC)frames,in which plastic hinges appear earlier in beams than in columns.However,seismic investigations show that the required limit of CBFSR in seismic codes usually cannot achieve the SCWB failure mode under strong earthquakes.This study investigates the failure modes of RC frames with different CBFSRs.Nine typical three-story RC frame models with different CBFSRs are designed in accordance with Chinese seismic codes.The seismic responses and failure modes of the frames are investigated through time-history analyses using 100 ground motion records.The results show that the required limit of the CBFSR that guarantees the SCWB failure mode depends on the beam-column connection type and the seismic intensity,and different types of beam-column connections exhibit different failure modes even though they are designed with the same CBFSR.Recommended CBFSRs are proposed for achieving the designed SCWB failure mode for different types of connections in RC frames under different seismic intensities.These results may provide some reference for further revisions of the SCWB design criterion in Chinese seismic codes.展开更多
The inter-story drift stiffness considered the semirigidity of beam and column joints connection, and P-Delta second order effect of steel frame parts in the mixed structure is presented in the paper. After considerin...The inter-story drift stiffness considered the semirigidity of beam and column joints connection, and P-Delta second order effect of steel frame parts in the mixed structure is presented in the paper. After considering on the influence of semirigidity between steel beams and steel columns, second order effect of beam-column members for steel frame and structural second order effect, the traditional continuum analytial method used in RC shear-frames wall structure is developed to steel frames-reinforced concrete shear wall mixed structure subject to horizontal load in this paper. A continuum approach, which is suitable for analyzing steel frames-reinforced concrete shear wall mixed structure subject to horizontal load, is presented. The method is relatively simple and more practical. It will be referred to structural design for steel frames-reinforced concrete shear wall mixed structure.展开更多
Finding out the most effective parameters relating to the resistance of reinforced concrete connections(RCCs)is an important topic in structural engineering.In this study,first,a finite element(FE)model is developed f...Finding out the most effective parameters relating to the resistance of reinforced concrete connections(RCCs)is an important topic in structural engineering.In this study,first,a finite element(FE)model is developed for simulating the performance of RCCs under post-earthquake fire(PEF).Then surrogate models,including multiple linear regression(MLR),multiple natural logarithm(Ln)equation regression(MLn ER),gene expression programming(GEP),and an ensemble model,are used to predict the remaining load-carrying capacity of an RCC under PEF.The statistical parameters,error terms,and a novel statistical table are used to evaluate and compare the accuracy of each surrogate model.According to the results,the ratio of the longitudinal reinforcement bars of the column(RLC)has a significant effect on the resistance of an RCC under PEF.Increasing the value of this parameter from 1%to 8%can increase the residual load-carrying capacity of an RCC under PEF by 492.2%when the RCC is exposed to fire at a temperature of 1000°C.Moreover,based on the results,the ensemble model can predict the residual load-carrying capacity with suitable accuracy.A safety factor of 1.55 should be applied to the results obtained from the ensemble model.展开更多
基金the National Natural Science Foundation of China(No.51978400)。
文摘This paper presents the static and fatigue tests of hybrid(bonded/bolted)glass fiber reinforced polymer(GFRP)joints.Nine specimens of single-lap hybrid GFRP joints have been fabricated to study the static and fatigue behaviors in the experimental campaign.The static tests of uniaxial tension loading are first conducted,from which the static ultimate bearing capacities of the joints are obtained.High-cycle fatigue tests are subsequently carried out so that the fatigue failure mode,fatigue life,and stiffness degradation of joints can be obtained.The measuring techniques including acoustic emission monitoring and three-dimensional digital image correlation have been employed in the tests to record the damage development process.The results revealed that the static strength and fatigue behavior of such thick hybrid GFRP joints were controlled by the bolted connections.The four stages of fatigue failure process are obtained from tests and acoustic emission signals analysis:cumulative damage of adhesive layer,damage of the adhesive layer,cumulative damage of GFRP plate,and damage of GFRP plate.The fatigue life and stiffness degradation can be improved by more bolts.The S-N(fatigue stress versus life)curves for the fatigue design of the single-lap hybrid GFRP joints under uniaxial tension loading are also proposed.
基金the National Natural Science Foundation of China(No.51808056)the Hunan Provincial Natural Science Foundation of China(No.2020JJ5583)+1 种基金the Research Foundation of Education Bureau of Hunan Province(No.19B012)the China Scholarship Council(No.201808430232)。
文摘Accurately estimating the interfacial bond capacity of the near-surface mounted(NSM)carbon fiber-reinforced polymer(CFRP)to concrete joint is a fundamental task in the strengthening and retrofit of existing reinforced concrete(RC)structures.The machine learning(ML)approach may provide an alternative to the commonly used semi-empirical or semi-analytical methods.Therefore,in this work we have developed a predictive model based on an artificial neural network(ANN)approach,i.e.using a back propagation neural network(BPNN),to map the complex data pattern obtained from an NSM CFRP to concrete joint.It involves a set of nine material and geometric input parameters and one output value.Moreover,by employing the neural interpretation diagram(NID)technique,the BPNN model becomes interpretable,as the influence of each input variable on the model can be tracked and quantified based on the connection weights of the neural network.An extensive database including 163 pull-out testing samples,collected from the authors’research group and from published results in the literature,is used to train and verify the ANN.Our results show that the prediction given by the BPNN model agrees well with the experimental data and yields a coefficient of determination of 0.957 on the whole database.After removing one non-significant feature,the BPNN becomes even more computationally efficient and accurate.In addition,compared with the existed semi-analytical model,the ANN-based approach demonstrates a more accurate estimation.Therefore,the proposed ML method may be a promising alternative for predicting the bond strength of NSM CFRP to concrete joint for structural engineers.
基金National Key R&D Program of China under Grant No.2017YFC1500601National Natural Science Foundation of China under Grant Nos.51678541 and 51708523Scientific Research Fund of the Institute of Engineering Mechanics,China Earthquake Administration under Grant No.2016A01。
文摘The column-to-beam flexural strength ratio(CBFSR)has been used in many seismic codes to achieve the strong column-weak beam(SCWB)failure mode in reinforced concrete(RC)frames,in which plastic hinges appear earlier in beams than in columns.However,seismic investigations show that the required limit of CBFSR in seismic codes usually cannot achieve the SCWB failure mode under strong earthquakes.This study investigates the failure modes of RC frames with different CBFSRs.Nine typical three-story RC frame models with different CBFSRs are designed in accordance with Chinese seismic codes.The seismic responses and failure modes of the frames are investigated through time-history analyses using 100 ground motion records.The results show that the required limit of the CBFSR that guarantees the SCWB failure mode depends on the beam-column connection type and the seismic intensity,and different types of beam-column connections exhibit different failure modes even though they are designed with the same CBFSR.Recommended CBFSRs are proposed for achieving the designed SCWB failure mode for different types of connections in RC frames under different seismic intensities.These results may provide some reference for further revisions of the SCWB design criterion in Chinese seismic codes.
文摘The inter-story drift stiffness considered the semirigidity of beam and column joints connection, and P-Delta second order effect of steel frame parts in the mixed structure is presented in the paper. After considering on the influence of semirigidity between steel beams and steel columns, second order effect of beam-column members for steel frame and structural second order effect, the traditional continuum analytial method used in RC shear-frames wall structure is developed to steel frames-reinforced concrete shear wall mixed structure subject to horizontal load in this paper. A continuum approach, which is suitable for analyzing steel frames-reinforced concrete shear wall mixed structure subject to horizontal load, is presented. The method is relatively simple and more practical. It will be referred to structural design for steel frames-reinforced concrete shear wall mixed structure.
文摘Finding out the most effective parameters relating to the resistance of reinforced concrete connections(RCCs)is an important topic in structural engineering.In this study,first,a finite element(FE)model is developed for simulating the performance of RCCs under post-earthquake fire(PEF).Then surrogate models,including multiple linear regression(MLR),multiple natural logarithm(Ln)equation regression(MLn ER),gene expression programming(GEP),and an ensemble model,are used to predict the remaining load-carrying capacity of an RCC under PEF.The statistical parameters,error terms,and a novel statistical table are used to evaluate and compare the accuracy of each surrogate model.According to the results,the ratio of the longitudinal reinforcement bars of the column(RLC)has a significant effect on the resistance of an RCC under PEF.Increasing the value of this parameter from 1%to 8%can increase the residual load-carrying capacity of an RCC under PEF by 492.2%when the RCC is exposed to fire at a temperature of 1000°C.Moreover,based on the results,the ensemble model can predict the residual load-carrying capacity with suitable accuracy.A safety factor of 1.55 should be applied to the results obtained from the ensemble model.
