This paper presents a new finite element model updating method for estimating structural parameters and detecting structural damage location and severity based on the structural responses(output-only data).The method ...This paper presents a new finite element model updating method for estimating structural parameters and detecting structural damage location and severity based on the structural responses(output-only data).The method uses the sensitivity relation of transmissibility data through a least-squares algorithm and appropriate normalization of the extracted equations.The proposed transmissibility-based sensitivity equation produces a more significant number of equations than the sensitivity equations based on the frequency response function(FRF),which can estimate the structural parameters with higher accuracy.The abilities of the proposed method are assessed by using numerical data of a two-story two-bay frame model and a plate structure model.In evaluating different damage cases,the number,location,and stiffness reduction of the damaged elements and the severity of the simulated damage have been accurately identified.The reliability and stability of the presented method against measurement and modeling errors are examined using error-contaminated data.The parameter estimation results prove the method’s capabilities as an accurate model updating algorithm.展开更多
Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction me...Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.展开更多
With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that consid...With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.展开更多
Analytical models prepared from field drawings do not generally provide results that match with experimental results.The error may be due to uncertainties in the property of materials,size of members and errors in the...Analytical models prepared from field drawings do not generally provide results that match with experimental results.The error may be due to uncertainties in the property of materials,size of members and errors in the modelling process.It is important to improve analytical models using experimentally obtained data.For the past several years,data obtained from ambient vibration testing have been successfully used in many cases to update and match dynamic behaviors of analytical models with real structures.This paper presents a comparison between artificial neural network(ANN) and eigensensitivity based model updating of an existing multi-story building.A simple spring-mass analytical model,developed from the structural drawings of the building,is considered and the corresponding spring stiffness and lumped mass of all floors are chosen as updating parameters.The advantages and disadvantages of these updating methods are discussed.The advantage is that both methods ensure a physically meaningful model which canbe further employed in determining structural response and health monitoring.展开更多
Combining the advantages of numerical simulation with experimental testing,real-time dynamic substructure(RTDS)testing provides a new experimental method for the investigation of engineered structures.However,not all ...Combining the advantages of numerical simulation with experimental testing,real-time dynamic substructure(RTDS)testing provides a new experimental method for the investigation of engineered structures.However,not all unmodeled parts can be physically tested,as testing is often limited by the capacity of the test facility.Model updating is a good option to improve the modeling accuracy for numerical substructures in RTDS.In this study,a model updating method is introduced,which has great performance in describing this nonlinearity.In order to determine the optimal parameters in this model,an Unscented Kalman Filter(UKF)-based algorithm was applied to extract the knowledge contained in the sensors data.All the parameters that need to be identified are listed as the extended state variables,and the identification was achieved via the step-by-step state prediction and state update process.Effectiveness of the proposed method was verified through a group of experimental data,and results showed good agreement.Furthermore,the proposed method was compared with the Extended Kalman Filter(EKF)-based method,and better accuracy was easily found.The proposed parameter identification method has great applicability for structural objects with nonlinear behaviors and could be extended to research in other engineering fields.展开更多
Model updating issues with high-dimensional and strong-nonlinear optimization processes are still unsolved by most optimization methods.In this study,a hybrid methodology that combines the Gaussian-white-noise-mutatio...Model updating issues with high-dimensional and strong-nonlinear optimization processes are still unsolved by most optimization methods.In this study,a hybrid methodology that combines the Gaussian-white-noise-mutation particle swarm optimization(GMPSO),back-propagation neural network(BPNN)and Latin hypercube sampling(LHS)technique is proposed.In this approach,as a meta-heuristic algorithm with the least modification to the standard PSO,GMPSO simultaneously offers convenient programming and good performance in optimization.The BPNN with LHS establishes the meta-models for FEM to accelerate efficiency during the updating process.A case study of the model updating of an actual bridge with no distribution but bounded parameters was carried out using this methodology with two different objective functions.One considers only the frequencies of the main girder and the other considers both the frequencies and vertical displacements of typical points.The updating results show that the methodology is a sound approach to solve an actual complex bridge structure and offers good agreement in the frequencies and mode shapes of the updated model and test data.Based on the shape comparison of the main girder at the finished state with different objective functions,it is emphasized that both the dynamic and static responses should be taken into consideration during the model updating process.展开更多
This paper aims to establish an intelligent procedure that combines the observational method with the existing deep learning technique for updating deformation of braced excavation in clay.The gated recurrent unit(GRU...This paper aims to establish an intelligent procedure that combines the observational method with the existing deep learning technique for updating deformation of braced excavation in clay.The gated recurrent unit(GRU) neural network is adopted to formulate the forecast model and learn the potential rules in the field observations using the Nesterov-accelerated Adam(Nadam) algorithm.In the proposed procedure,the GRU-based forecast model is first trained based on the field data of previous and current stages.Then,the field data of the current stage are used as input to predict the deformation response of the next stage via the previously trained GRU-based forecast model.This updating process will loop up till the end of the excavation.This procedure has the advantage of directly predicting the deformation response of unexcavated stages based on the monitoring data.The proposed intelligent procedure is verified on two well-documented cases in terms of accuracy and reliability.The results indicate that both wall deflection and ground settlement are accurately predicted as the excavation proceeds.Furthermore,the advantages of the proposed intelligent procedure compared with the Bayesian/o ptimization updating are illustrated.展开更多
A model based damage identification was proposed by facilitating parameter sensitivity analysis and applied to a general overhead travelling crane.As updating reference data,experimental modal frequency was obtained b...A model based damage identification was proposed by facilitating parameter sensitivity analysis and applied to a general overhead travelling crane.As updating reference data,experimental modal frequency was obtained by operational modal analysis(OMA)under ambient excitation.One dimensional damage function was defined to identify the damage by bending stiffness.The results showed that the model updating method could locate the damage and quantitatively describe the structure.The average error of eigenvalues between updated model analysis and the experimental results was less than 4% which proved the accuracy reliable.The comparison of finite element analysis and the test results of the deflection under the capacity load further verified the feasibility of this method.展开更多
Model updating for aircraft in a high temperature environment(HTE)is proposed based on the hierarchical method.With this method,the problem can be decomposed into temperature field updating and dynamic structural upda...Model updating for aircraft in a high temperature environment(HTE)is proposed based on the hierarchical method.With this method,the problem can be decomposed into temperature field updating and dynamic structural updating.In order to improve the estimation accuracy,the model updating problem is turned into a multi-objective optimization problem by constructing the objective function which combined with residues of modal frequency and effective modal mass.Then the metamodeling,support vector regression(SVR)is introduced to improve the optimization efficiency,and the solution can be determined by adaptive weighted-sum method(AWS).Finally,the proposed method is tested on a finite element(FE)model of a reentry vehicle model.The results show that the multi-objective model updating method in HTE can identify the input parameters of the temperature field and structure with good accuracy.展开更多
To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail....To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.展开更多
We study cooperative spectrum sensing in cognitive radio (CR) networks using the hidden Markov model (HMM) for opportunistic spectrum access (OSA). We assume that the primary channel operates in a time division multip...We study cooperative spectrum sensing in cognitive radio (CR) networks using the hidden Markov model (HMM) for opportunistic spectrum access (OSA). We assume that the primary channel operates in a time division multiple address (TDMA) manner. Thus, spectrum sensing is operating in a slot-by-slot basis. In contrast to the conventional Bayesian updating using only one observation, in this work, we propose to perform the update in a concatenated fashion with all the observations available from the secondary users (SUs). In the proposed scheme, a predefined threshold on the belief is used for determining the channel activity. With the threshold, the proposed scheme is more flexible in the system operation than the simple majority vote scheme, in which no such threshold is available. We compare, by simulations, the performance of the proposed concatenated update scheme with that of the majority vote scheme and show that the probabilities of correctly detecting a busy state and an idle state are about 1 as the number of SUs is as large as 15, so the effects of the further increase in the number of SUs are limited.展开更多
A finite element model updating technique for complicated beam-type structures is presented in this study.Firstly, a complicated beam-type structure is reduced to a reduced super beam model with a much smaller degree ...A finite element model updating technique for complicated beam-type structures is presented in this study.Firstly, a complicated beam-type structure is reduced to a reduced super beam model with a much smaller degree of freedom by using the reduced super beam method, which is based on the classic plane cross-section assumption and displacement interpolation function of beam theory.Then based on the reduced super beam, the analysis of eigensolutions and eigensensitivities from the reduced eigenequation are processed for model updating, which will greatly reduce the computational effort when compared to the traditional model updating methods performed on the global model.Optimization techniques are adopted for updating the difference of modal dynamic properties, resulting in optimal values of the structural parameters.Finally, a complicated stiffened cylindrical shell model and a practical missile structure, served as the illustrative examples, are employed for model updating application, which demonstrate that the reduced super beam-based method is both effective and highly efficient.展开更多
The load transfer characteristics of a tensile anchor in the rock mass with weak interlayers were investigated,considering the nonuniform stress of the horizontally layered rock mass along anchors.An improved shear-sl...The load transfer characteristics of a tensile anchor in the rock mass with weak interlayers were investigated,considering the nonuniform stress of the horizontally layered rock mass along anchors.An improved shear-slipping model was proposed to describe the stress evolution characteristics of the bolt-rock interface.Based on the improved model,analytical solutions of the axial force,shear stress distribution and load-displacement relationship considering the residual stress stage were established.The effects of the stratigraphic sequence,pulling force and bolt diameter on the stress distribution of the anchorage interface were evaluated by using analytical solutions.The results were verified by applying the finite difference numerical simulation method.The sensitivity of each parameter to the axial force and shear stress of the rock bolt was determined based on calculation of the sensitivity coefficient.The study results show that the axial force and shear stress tend to decrease nonuniformly along the rock bolt towards the anchorage depth.Due to the existence of weak interlayers,the shear stress mutates at the weak and hard rock interface,and the axial force appears to“rebound”at the bottom of the anchored section.Lithology has more significant effects on the axial force and shear stress at the bottom of the anchor than at the top of the anchor.The pulling force is more sensitive to the anchor stress than stratigraphic sequence when the bolt diameter is determined.This study provides a theoretical framework for the fundamental problem of tensile bolts in horizontally or vertically laminated rock masses,providing a theoretical basis for anchor design.展开更多
Let ∑, Г be two n-by-n diagonal matrices with σi,γi as their diagonals. For the inverse eigenvalue problem: look for y∈Rn such that Г + yyT is similar to ∑, we prove thatu also the sufficient condition for the ...Let ∑, Г be two n-by-n diagonal matrices with σi,γi as their diagonals. For the inverse eigenvalue problem: look for y∈Rn such that Г + yyT is similar to ∑, we prove thatu also the sufficient condition for the solvability of this inverse problem. Its solution (set) is given explicitly. In some case, the problem is unstable. But we prove that the sums of the square of some contigious components keep stable, i.e., small sum keeps small, large sum has a small relative perturbation, see Theorem 3.展开更多
A new approach to modifying the stiffness and mass matrices of finite element models is presented to improve the calculation precision.By measuring the mode frequencies and shapes of both of the original and the new s...A new approach to modifying the stiffness and mass matrices of finite element models is presented to improve the calculation precision.By measuring the mode frequencies and shapes of both of the original and the new structures with changed stiffness and mass,the stiffness and mass matrices of the finite element model can be updated through matrices calculation and solving algebra equations.Taking a multi-freedom model as an example,the relation between the number of the modes and the correction precision of stiffness and mass matrix elements is researched.The facility and precision of the method are totally confirmed especially when the modeling error is known limited to a definite local range.The feasibility of the approach is proven by an effective engineering application to the model updating of a wing piece used in flutter test.展开更多
Internet of Things (IoT) has emerged as one of the new use cases in the 5th Generation wireless networks. However, the transient nature of the data generated in IoT networks brings great challenges for content caching...Internet of Things (IoT) has emerged as one of the new use cases in the 5th Generation wireless networks. However, the transient nature of the data generated in IoT networks brings great challenges for content caching. In this paper, we study a joint content caching and updating strategy in IoT networks, taking both the energy consumption of the sensors and the freshness loss of the contents into account. In particular, we decide whether or not to cache the transient data and, if so, how often the servers should update their contents. We formulate this content caching and updating problem as a mixed 0–1 integer non-convex optimization programming, and devise a Harmony Search based content Caching and Updating (HSCU) algorithm, which is self-learning and derivativefree and hence stipulates no requirement on the relationship between the objective and variables. Finally, extensive simulation results verify the effectiveness of our proposed algorithm in terms of the achieved satisfaction ratio for content delivery, normalized energy consumption, and overall network utility, by comparing it with some baseline algorithms.展开更多
Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will resul...Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will result in the decline of positioning accuracy.The widespread extension of Bluetooth positioning is limited by the need of manual effort to collect the fingerprints with position labels for fingerprint database construction and updating.To address this problem,this paper presents an adaptive fingerprint database updating approach.First,the crowdsourced data including the Bluetooth Received Signal Strength(RSS)sequences and the speed and heading of the pedestrian were recorded.Second,the recorded crowdsourced data were fused by the Kalman Filtering(KF),and then fed into the trajectory validity analysis model with the purpose of assigning the unlabeled RSS data with position labels to generate candidate fingerprints.Third,after enough candidate fingerprints were obtained at each Reference Point(RP),the Density⁃based Spatial Clustering of Applications with Noise(DBSCAN)approach was conducted on both the original and the candidate fingerprints to filter out the fingerprints which had been identified as the noise,and then the mean of fingerprints in the cluster with the largest data volume was selected as the updated fingerprint of the corresponding RP.Finally,the extensive experimental results show that with the increase of the number of candidate fingerprints and update iterations,the fingerprint⁃based Bluetooth positioning accuracy can be effectively improved.展开更多
This paper provides a model updating approach to detect,locate,and char-acterize damage in structural and mechanical systems by examining changes in mea-sured vibration responses.Research in vibration-based damage ide...This paper provides a model updating approach to detect,locate,and char-acterize damage in structural and mechanical systems by examining changes in mea-sured vibration responses.Research in vibration-based damage identification has been rapidly expanding over the last few decades.The basic idea behind this technology is that modal parameters(notably frequencies,mode shapes,and modal damping)are functions of the physical properties of the structure(mass,damping,and sifies).Therefore,changes in the physical properties will cause changes in the modal proper-ties which could be obtained by structural health monitoring(SHM).Updating is a process fraught with numerical difficulties.These arise from inaccuracy in the model and imprecision and lack of information in the measurements,mainly taken place in joints and critical points.The motivation for the development of this technology is.presented,methods are categorized according to various criteria such as the level of damage detection provided from vibration testing,natural frequency and mode shape readings are then obtained by using modal analysis techniques,which are used for updating structural parameters of the associated finite element model The experi-mental studies for the laboratory tested bridge model show that the proposed model.updating using ME scope technique can provide reasonable model updating results.展开更多
This work focuses on the updating-based identification of the three-dimensional orthotropic elastic behavior of a thin carbon fiber reinforced plastic multilayer composite plate. This consists in identifying the engin...This work focuses on the updating-based identification of the three-dimensional orthotropic elastic behavior of a thin carbon fiber reinforced plastic multilayer composite plate. This consists in identifying the engineering constants that minimize the relative deviations between the first eight experimental and three-dimensional finite element frequencies of the vibrating free plate. For this purpose, a multi-objective optimization procedure is applied;it exploits a Particle Swarm Optimizer algorithm (PSO) that is coupled to a metamodeling by the new response surfaces method procedure (NRSMP);the latter is based on numerical design experiments. The conducted sensitivity analyses indicate that the four engineering constants of the two-dimensional elasticity are the most influent.展开更多
文摘This paper presents a new finite element model updating method for estimating structural parameters and detecting structural damage location and severity based on the structural responses(output-only data).The method uses the sensitivity relation of transmissibility data through a least-squares algorithm and appropriate normalization of the extracted equations.The proposed transmissibility-based sensitivity equation produces a more significant number of equations than the sensitivity equations based on the frequency response function(FRF),which can estimate the structural parameters with higher accuracy.The abilities of the proposed method are assessed by using numerical data of a two-story two-bay frame model and a plate structure model.In evaluating different damage cases,the number,location,and stiffness reduction of the damaged elements and the severity of the simulated damage have been accurately identified.The reliability and stability of the presented method against measurement and modeling errors are examined using error-contaminated data.The parameter estimation results prove the method’s capabilities as an accurate model updating algorithm.
基金Project supported by the National Natural Science Foundation of China(Nos.12272211,12072181,12121002)。
文摘Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.
基金The work was supported by Humanities and Social Sciences Fund of the Ministry of Education(No.22YJA630119)the National Natural Science Foundation of China(No.71971051)Natural Science Foundation of Hebei Province(No.G2021501004).
文摘With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.
文摘Analytical models prepared from field drawings do not generally provide results that match with experimental results.The error may be due to uncertainties in the property of materials,size of members and errors in the modelling process.It is important to improve analytical models using experimentally obtained data.For the past several years,data obtained from ambient vibration testing have been successfully used in many cases to update and match dynamic behaviors of analytical models with real structures.This paper presents a comparison between artificial neural network(ANN) and eigensensitivity based model updating of an existing multi-story building.A simple spring-mass analytical model,developed from the structural drawings of the building,is considered and the corresponding spring stiffness and lumped mass of all floors are chosen as updating parameters.The advantages and disadvantages of these updating methods are discussed.The advantage is that both methods ensure a physically meaningful model which canbe further employed in determining structural response and health monitoring.
基金National Natural Science Foundation of China under Grant Nos.61903009,51978016 and 61673002Beijing Municipal Education Commission under Grant No.KM201810011005。
文摘Combining the advantages of numerical simulation with experimental testing,real-time dynamic substructure(RTDS)testing provides a new experimental method for the investigation of engineered structures.However,not all unmodeled parts can be physically tested,as testing is often limited by the capacity of the test facility.Model updating is a good option to improve the modeling accuracy for numerical substructures in RTDS.In this study,a model updating method is introduced,which has great performance in describing this nonlinearity.In order to determine the optimal parameters in this model,an Unscented Kalman Filter(UKF)-based algorithm was applied to extract the knowledge contained in the sensors data.All the parameters that need to be identified are listed as the extended state variables,and the identification was achieved via the step-by-step state prediction and state update process.Effectiveness of the proposed method was verified through a group of experimental data,and results showed good agreement.Furthermore,the proposed method was compared with the Extended Kalman Filter(EKF)-based method,and better accuracy was easily found.The proposed parameter identification method has great applicability for structural objects with nonlinear behaviors and could be extended to research in other engineering fields.
基金National Natural Science Foundation of China under Grant No.51438002the research fund of Jiangsu Province Key Laboratory of Structure Engineering,China under Grant No.ZD1803+3 种基金Natural Science Foundation of Suzhou University of Science and Technology under Grant No.XKQ2018008Natural Science Foundation of Jiangsu Higher Education Institutions of China under Grant No.19KJB560021Science and Technology Project of Jiangsu Construction System under Grant No.2020ZD07Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Model updating issues with high-dimensional and strong-nonlinear optimization processes are still unsolved by most optimization methods.In this study,a hybrid methodology that combines the Gaussian-white-noise-mutation particle swarm optimization(GMPSO),back-propagation neural network(BPNN)and Latin hypercube sampling(LHS)technique is proposed.In this approach,as a meta-heuristic algorithm with the least modification to the standard PSO,GMPSO simultaneously offers convenient programming and good performance in optimization.The BPNN with LHS establishes the meta-models for FEM to accelerate efficiency during the updating process.A case study of the model updating of an actual bridge with no distribution but bounded parameters was carried out using this methodology with two different objective functions.One considers only the frequencies of the main girder and the other considers both the frequencies and vertical displacements of typical points.The updating results show that the methodology is a sound approach to solve an actual complex bridge structure and offers good agreement in the frequencies and mode shapes of the updated model and test data.Based on the shape comparison of the main girder at the finished state with different objective functions,it is emphasized that both the dynamic and static responses should be taken into consideration during the model updating process.
基金The financial supports provided by the Research Grants Council(RGC)of Hong Kong Special Administrative Region Government(HKSARG)of China(Grant Nos.15209119 and PolyU R5037-18F)Zhongtian Construction Group Co.Ltd.(Grant No.ZTCG-GDJTYJSJSFW-2020002)。
文摘This paper aims to establish an intelligent procedure that combines the observational method with the existing deep learning technique for updating deformation of braced excavation in clay.The gated recurrent unit(GRU) neural network is adopted to formulate the forecast model and learn the potential rules in the field observations using the Nesterov-accelerated Adam(Nadam) algorithm.In the proposed procedure,the GRU-based forecast model is first trained based on the field data of previous and current stages.Then,the field data of the current stage are used as input to predict the deformation response of the next stage via the previously trained GRU-based forecast model.This updating process will loop up till the end of the excavation.This procedure has the advantage of directly predicting the deformation response of unexcavated stages based on the monitoring data.The proposed intelligent procedure is verified on two well-documented cases in terms of accuracy and reliability.The results indicate that both wall deflection and ground settlement are accurately predicted as the excavation proceeds.Furthermore,the advantages of the proposed intelligent procedure compared with the Bayesian/o ptimization updating are illustrated.
基金supported by the Research Program of General Administration of Quality Supervision,Inspec-tion and Quarantine of the People's Republic of China(AQSIQ)(No.2014QK182)the Key Laboratory of Risk Identification and Structural Damage Detection Technology for Large Cranes of Jiangsu Province,Donghua Testing Technology Co.,Ltd
文摘A model based damage identification was proposed by facilitating parameter sensitivity analysis and applied to a general overhead travelling crane.As updating reference data,experimental modal frequency was obtained by operational modal analysis(OMA)under ambient excitation.One dimensional damage function was defined to identify the damage by bending stiffness.The results showed that the model updating method could locate the damage and quantitatively describe the structure.The average error of eigenvalues between updated model analysis and the experimental results was less than 4% which proved the accuracy reliable.The comparison of finite element analysis and the test results of the deflection under the capacity load further verified the feasibility of this method.
基金supported by the National Natural Science Foundation of China(No.11472132)the Fundamental Research Funds for Central University (No. NJ20160050)the Fundamental Research Funds for Central University(No.NJ2016098)
文摘Model updating for aircraft in a high temperature environment(HTE)is proposed based on the hierarchical method.With this method,the problem can be decomposed into temperature field updating and dynamic structural updating.In order to improve the estimation accuracy,the model updating problem is turned into a multi-objective optimization problem by constructing the objective function which combined with residues of modal frequency and effective modal mass.Then the metamodeling,support vector regression(SVR)is introduced to improve the optimization efficiency,and the solution can be determined by adaptive weighted-sum method(AWS).Finally,the proposed method is tested on a finite element(FE)model of a reentry vehicle model.The results show that the multi-objective model updating method in HTE can identify the input parameters of the temperature field and structure with good accuracy.
基金Sponsored by the National Key Technology Research and Development Program of China(Grant No.2011BAK02B02)
文摘To investigate the application of meta-model for finite element( FE) model updating of structures,the performance of two popular meta-model,i. e.,Kriging model and response surface model( RSM),were compared in detail. Firstly,above two kinds of meta-model were introduced briefly. Secondly,some key issues of the application of meta-model to FE model updating of structures were proposed and discussed,and then some advices were presented in order to select a reasonable meta-model for the purpose of updating the FE model of structures. Finally,the procedure of FE model updating based on meta-model was implemented by updating the FE model of a truss bridge model with the measured modal parameters. The results showed that the Kriging model was more proper for FE model updating of complex structures.
文摘We study cooperative spectrum sensing in cognitive radio (CR) networks using the hidden Markov model (HMM) for opportunistic spectrum access (OSA). We assume that the primary channel operates in a time division multiple address (TDMA) manner. Thus, spectrum sensing is operating in a slot-by-slot basis. In contrast to the conventional Bayesian updating using only one observation, in this work, we propose to perform the update in a concatenated fashion with all the observations available from the secondary users (SUs). In the proposed scheme, a predefined threshold on the belief is used for determining the channel activity. With the threshold, the proposed scheme is more flexible in the system operation than the simple majority vote scheme, in which no such threshold is available. We compare, by simulations, the performance of the proposed concatenated update scheme with that of the majority vote scheme and show that the probabilities of correctly detecting a busy state and an idle state are about 1 as the number of SUs is as large as 15, so the effects of the further increase in the number of SUs are limited.
基金Sponsored by the National Natural Science Foundation of China(Grant No.11402077)
文摘A finite element model updating technique for complicated beam-type structures is presented in this study.Firstly, a complicated beam-type structure is reduced to a reduced super beam model with a much smaller degree of freedom by using the reduced super beam method, which is based on the classic plane cross-section assumption and displacement interpolation function of beam theory.Then based on the reduced super beam, the analysis of eigensolutions and eigensensitivities from the reduced eigenequation are processed for model updating, which will greatly reduce the computational effort when compared to the traditional model updating methods performed on the global model.Optimization techniques are adopted for updating the difference of modal dynamic properties, resulting in optimal values of the structural parameters.Finally, a complicated stiffened cylindrical shell model and a practical missile structure, served as the illustrative examples, are employed for model updating application, which demonstrate that the reduced super beam-based method is both effective and highly efficient.
基金supported by the National Key R&D Program of China(Nos.2018YFC1505300,2017YFC1501304)National Natural Science Foundation of China(Grout Nos.42090054,41922055 and 41931295)+2 种基金the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(No.CUGGC09)Research Project of China Three Gorges Corporation(No.2019073)the Zhejiang Huadong Construction Engineering Co.,Ltd.(No.KY2019-HDJS-07)。
文摘The load transfer characteristics of a tensile anchor in the rock mass with weak interlayers were investigated,considering the nonuniform stress of the horizontally layered rock mass along anchors.An improved shear-slipping model was proposed to describe the stress evolution characteristics of the bolt-rock interface.Based on the improved model,analytical solutions of the axial force,shear stress distribution and load-displacement relationship considering the residual stress stage were established.The effects of the stratigraphic sequence,pulling force and bolt diameter on the stress distribution of the anchorage interface were evaluated by using analytical solutions.The results were verified by applying the finite difference numerical simulation method.The sensitivity of each parameter to the axial force and shear stress of the rock bolt was determined based on calculation of the sensitivity coefficient.The study results show that the axial force and shear stress tend to decrease nonuniformly along the rock bolt towards the anchorage depth.Due to the existence of weak interlayers,the shear stress mutates at the weak and hard rock interface,and the axial force appears to“rebound”at the bottom of the anchored section.Lithology has more significant effects on the axial force and shear stress at the bottom of the anchor than at the top of the anchor.The pulling force is more sensitive to the anchor stress than stratigraphic sequence when the bolt diameter is determined.This study provides a theoretical framework for the fundamental problem of tensile bolts in horizontally or vertically laminated rock masses,providing a theoretical basis for anchor design.
文摘Let ∑, Г be two n-by-n diagonal matrices with σi,γi as their diagonals. For the inverse eigenvalue problem: look for y∈Rn such that Г + yyT is similar to ∑, we prove thatu also the sufficient condition for the solvability of this inverse problem. Its solution (set) is given explicitly. In some case, the problem is unstable. But we prove that the sums of the square of some contigious components keep stable, i.e., small sum keeps small, large sum has a small relative perturbation, see Theorem 3.
基金Supported by the National High Technology Research and Development Program of China(″863″Program)(2008AA12A205)the Aeronautical Science Foundation of China(2012ZA52001)
文摘A new approach to modifying the stiffness and mass matrices of finite element models is presented to improve the calculation precision.By measuring the mode frequencies and shapes of both of the original and the new structures with changed stiffness and mass,the stiffness and mass matrices of the finite element model can be updated through matrices calculation and solving algebra equations.Taking a multi-freedom model as an example,the relation between the number of the modes and the correction precision of stiffness and mass matrix elements is researched.The facility and precision of the method are totally confirmed especially when the modeling error is known limited to a definite local range.The feasibility of the approach is proven by an effective engineering application to the model updating of a wing piece used in flutter test.
基金National Natural Science Foundation of China(61701372)Talents Special Foundation of Northwest A&F University(Z111021801).
文摘Internet of Things (IoT) has emerged as one of the new use cases in the 5th Generation wireless networks. However, the transient nature of the data generated in IoT networks brings great challenges for content caching. In this paper, we study a joint content caching and updating strategy in IoT networks, taking both the energy consumption of the sensors and the freshness loss of the contents into account. In particular, we decide whether or not to cache the transient data and, if so, how often the servers should update their contents. We formulate this content caching and updating problem as a mixed 0–1 integer non-convex optimization programming, and devise a Harmony Search based content Caching and Updating (HSCU) algorithm, which is self-learning and derivativefree and hence stipulates no requirement on the relationship between the objective and variables. Finally, extensive simulation results verify the effectiveness of our proposed algorithm in terms of the achieved satisfaction ratio for content delivery, normalized energy consumption, and overall network utility, by comparing it with some baseline algorithms.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61771083,61704015)the Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT1299)+3 种基金the Special Fund of Chongqing Key Laboratory(CSTC)Fundamental Science and Frontier Technology Research Project of Chongqing(Grant Nos.cstc2017jcyjAX0380,cstc2015jcyjBX0065)the Scientific and Technological Research Foundation of Chongqing Municipal Education Commission(Grant No.KJ1704083)the University Outstanding Achievement Transformation Project of Chongqing(Grant No.KJZH17117).
文摘Fingerprint⁃based Bluetooth positioning is a popular indoor positioning technology.However,the change of indoor environment and Bluetooth anchor locations has significant impact on signal distribution,which will result in the decline of positioning accuracy.The widespread extension of Bluetooth positioning is limited by the need of manual effort to collect the fingerprints with position labels for fingerprint database construction and updating.To address this problem,this paper presents an adaptive fingerprint database updating approach.First,the crowdsourced data including the Bluetooth Received Signal Strength(RSS)sequences and the speed and heading of the pedestrian were recorded.Second,the recorded crowdsourced data were fused by the Kalman Filtering(KF),and then fed into the trajectory validity analysis model with the purpose of assigning the unlabeled RSS data with position labels to generate candidate fingerprints.Third,after enough candidate fingerprints were obtained at each Reference Point(RP),the Density⁃based Spatial Clustering of Applications with Noise(DBSCAN)approach was conducted on both the original and the candidate fingerprints to filter out the fingerprints which had been identified as the noise,and then the mean of fingerprints in the cluster with the largest data volume was selected as the updated fingerprint of the corresponding RP.Finally,the extensive experimental results show that with the increase of the number of candidate fingerprints and update iterations,the fingerprint⁃based Bluetooth positioning accuracy can be effectively improved.
文摘This paper provides a model updating approach to detect,locate,and char-acterize damage in structural and mechanical systems by examining changes in mea-sured vibration responses.Research in vibration-based damage identification has been rapidly expanding over the last few decades.The basic idea behind this technology is that modal parameters(notably frequencies,mode shapes,and modal damping)are functions of the physical properties of the structure(mass,damping,and sifies).Therefore,changes in the physical properties will cause changes in the modal proper-ties which could be obtained by structural health monitoring(SHM).Updating is a process fraught with numerical difficulties.These arise from inaccuracy in the model and imprecision and lack of information in the measurements,mainly taken place in joints and critical points.The motivation for the development of this technology is.presented,methods are categorized according to various criteria such as the level of damage detection provided from vibration testing,natural frequency and mode shape readings are then obtained by using modal analysis techniques,which are used for updating structural parameters of the associated finite element model The experi-mental studies for the laboratory tested bridge model show that the proposed model.updating using ME scope technique can provide reasonable model updating results.
文摘This work focuses on the updating-based identification of the three-dimensional orthotropic elastic behavior of a thin carbon fiber reinforced plastic multilayer composite plate. This consists in identifying the engineering constants that minimize the relative deviations between the first eight experimental and three-dimensional finite element frequencies of the vibrating free plate. For this purpose, a multi-objective optimization procedure is applied;it exploits a Particle Swarm Optimizer algorithm (PSO) that is coupled to a metamodeling by the new response surfaces method procedure (NRSMP);the latter is based on numerical design experiments. The conducted sensitivity analyses indicate that the four engineering constants of the two-dimensional elasticity are the most influent.
