Nonlinear boundary parameter identification of bridges based on temperature-induced strains

Zuo-Cai Wang,Guo-Peng Zha,Wei-Xin Ren,Ke Hu,Hao Yang 국제구조공학회 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.68 No.5

Temperature-induced responses, such as strains and displacements, are related to the boundary conditions. Therefore, it is required to determine the boundary conditions to establish a reliable bridge model for temperature-induced responses analysis. Particularly, bridge bearings usually present nonlinear behavior with an increase in load, and the nonlinear boundary conditions cause significant effect on temperature-induced responses. In this paper, the bridge nonlinear boundary conditions were simulated as bilinear translational or rotational springs, and the boundary parameters of the bilinear springs were identified based on the measured temperature-induced responses. First of all, the temperature-induced responses of a simply support beam with nonlinear translational and rotational springs subjected to various temperature loads were analyzed. The simulated temperature-induced strains and displacements were assumed as measured data. To identify the nonlinear translational and rotational boundary parameters of the bridge, the objective function based on the temperature-induced responses is then created, and the nonlinear boundary parameters were further identified by using the nonlinear least squares optimization algorithm. Then, a beam structure with nonlinear translational and rotational springs was simulated as a numerical example, and the nonlinear boundary parameters were identified based on the proposed method. The numerical results show that the proposed method can effectively identify the parameters of the nonlinear boundary conditions. Finally, the boundary parameters of a real arch bridge were identified based on the measured strain data and the proposed method. Since the bearings of the real bridge do not perform nonlinear behavior, only the linear boundary parameters of the bridge model were identified. Based on the bridge model and the identified boundary conditions, the temperature-induced strains were recalculated to compare with the measured strain data. The recalculated temperature-induced strains are in a good agreement with the real measured data.

Damage detection of nonlinear structures with analytical mode decomposition and Hilbert transform

Zuo-Cai Wang,Dong Geng,Wei-Xin Ren,Guang-Feng Zhang,Gen-Da Chen 국제구조공학회 2015 Smart Structures and Systems, An International Jou Vol.15 No.1

This paper proposes an analytical mode decomposition (AMD) and Hilbert transform method for structural nonlinearity quantification and damage detection under earthquake loads. The measured structural response is first decomposed into several intrinsic mode functions (IMF) using the proposed AMD method. Each IMF is an amplitude modulated-frequency modulated signal with narrow frequency bandwidth. Then, the instantaneous frequencies of the decomposed IMF can be defined with Hilbert transform. However, for a nonlinear structure, the defined instantaneous frequencies from the decomposed IMF are not equal to the instantaneous frequencies of the structure itself. The theoretical derivation in this paper indicates that the instantaneous frequency of the decomposed measured response includes a slowly-varying part which represents the instantaneous frequency of the structure and rapidly-varying part for a nonlinear structure subjected to earthquake excitations. To eliminate the rapidly-varying part effects, the instantaneous frequency is integrated over time duration. Then the degree of nonlinearity index, which represents the damage severity of structure, is defined based on the integrated instantaneous frequency in this paper. A one-story hysteretic nonlinear structure with various earthquake excitations are simulated as numerical examples and the degree of nonlinearity index is obtained. Finally, the degree of nonlinearity index is estimated from the experimental data of a seven-story building under four earthquake excitations. The index values for the building subjected to a low intensity earthquake excitation, two medium intensity earthquake excitations, and a large intensity earthquake excitation are calculated as 12.8%, 23.0%, 23.2%, and 39.5%, respectively.

A data fusion method for bridge displacement reconstruction based on LSTM networks

Zuo-Cai Wang,Da-You Duan,Xiao-Tong Sun,Yu Xin 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.4

Bridge displacement contains vital information for bridge condition and performance. Due to the limits of direct displacement measurement methods, the indirect displacement reconstruction methods based on the strain or acceleration data are also developed in engineering applications. There are still some deficiencies of the displacement reconstruction methods based on strain or acceleration in practice. This paper proposed a novel method based on long short-term memory (LSTM) networks to reconstruct the bridge dynamic displacements with the strain and acceleration data source. The LSTM networks with three hidden layers are utilized to map the relationships between the measured responses and the bridge displacement. To achieve the data fusion, the input strain and acceleration data need to be preprocessed by normalization and then the corresponding dynamic displacement responses can be reconstructed by the LSTM networks. In the numerical simulation, the errors of the displacement reconstruction are below 9% for different load cases, and the proposed method is robust when the input strain and acceleration data contains additive noise. The hyper-parameter effect is analyzed and the displacement reconstruction accuracies of different machine learning methods are compared. For experimental verification, the errors are below 6% for the simply supported beam and continuous beam cases. Both the numerical and experimental results indicate that the proposed data fusion method can accurately reconstruct the displacement.

Damage detection of nonlinear structures with analytical mode decomposition and Hilbert transform

Wang, Zuo-Cai,Geng, Dong,Ren, Wei-Xin,Chen, Gen-Da,Zhang, Guang-Feng Techno-Press 2015 Smart Structures and Systems, An International Jou Vol.15 No.1

This paper proposes an analytical mode decomposition (AMD) and Hilbert transform method for structural nonlinearity quantification and damage detection under earthquake loads. The measured structural response is first decomposed into several intrinsic mode functions (IMF) using the proposed AMD method. Each IMF is an amplitude modulated-frequency modulated signal with narrow frequency bandwidth. Then, the instantaneous frequencies of the decomposed IMF can be defined with Hilbert transform. However, for a nonlinear structure, the defined instantaneous frequencies from the decomposed IMF are not equal to the instantaneous frequencies of the structure itself. The theoretical derivation in this paper indicates that the instantaneous frequency of the decomposed measured response includes a slowly-varying part which represents the instantaneous frequency of the structure and rapidly-varying part for a nonlinear structure subjected to earthquake excitations. To eliminate the rapidly-varying part effects, the instantaneous frequency is integrated over time duration. Then the degree of nonlinearity index, which represents the damage severity of structure, is defined based on the integrated instantaneous frequency in this paper. A one-story hysteretic nonlinear structure with various earthquake excitations are simulated as numerical examples and the degree of nonlinearity index is obtained. Finally, the degree of nonlinearity index is estimated from the experimental data of a seven-story building under four earthquake excitations. The index values for the building subjected to a low intensity earthquake excitation, two medium intensity earthquake excitations, and a large intensity earthquake excitation are calculated as 12.8%, 23.0%, 23.2%, and 39.5%, respectively.

Latin Hypercube Sampling Based Probabilistic Small Signal Stability Analysis Considering Load Correlation

Zuo, Jian,Li, Yinhong,Cai, Defu,Shi, Dongyuan The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.6

A novel probabilistic small signal stability analysis (PSSSA) method considering load correlation is proposed in this paper. The superiority Latin hypercube sampling (LHS) technique combined with Monte Carlo simulation (MCS) is utilized to investigate the probabilistic small signal stability of power system in presence of load correlation. LHS helps to reduce the sampling size, meanwhile guarantees the accuracy and robustness of the solutions. The correlation coefficient matrix is adopted to represent the correlations between loads. Simulation results of the two-area, four-machine system prove that the proposed method is an efficient and robust sampling method. Simulation results of the 16-machine, 68-bus test system indicate that load correlation has a significant impact on the probabilistic analysis result of the critical oscillation mode under a certain degree of load uncertainty.

Optimization of the microemulsion formulation of curcuma oil and evaluation of its acaricidal efficacy against Tetranychus cinnabarinus (Boisduval) (Acari: Tetranychidae)

Cheng Zuo-Hui,Fan Fang-Fang,Zhao Jin-Zhong,Li Rui,Li Sheng-Cai,Zhang En-Jia,Liu Yu-Kun,Wang Jue-Ying,Zhu Xiang-Run,Tian Yong-Ming 한국응용곤충학회 2020 Journal of Asia-Pacific Entomology Vol.23 No.4

The microemulsion formulation (hereafter formulation) of curcuma oil and its acaricidal efficacy against Tetranychus cinnabarinus Boisduval (Acari: Tetranychidae) were optimized in the laboratory to evaluate their spray effectiveness of oviposition inhibition and repellence. Ethovision XT6 was used to analyse the effects of the sublethal concentrations (LC 20 ) of curcuma oil and the formulation on the behaviors of T. cinnabarinus. The results showed that Tween-80 was the best surfactant, Isopropanol was the best co-surfactant and K m = 2:1 was the best condition for the formulation. The prepared microemulsions are stable under conditions of centrifugation and incubation for extended periods. The results showed that the effect of the spray bioassays of the formulation against T. cinnabarinus continuously increased during the experiment, but for curcuma oil almost no longer increase observed when the exposure time went beyond 24 h. Moreover, compared with curcuma oil (LC 50 = 0.716%), the spray bioassay of the formulation (LC 50 = 0.035%) was stronger against T. cinnabarinus. The repellency of the formulation to T. cinnabarinus was stronger with increasing exposure time, but that of curcuma oil declined after 12 h of exposure. The mobile distance of T. cinnabarinus treated with the formulation continuously declined during the experiment but that due to the curcuma oil almost no longer declined when the treatment time reached 12 h. The maximum mobile frequency of T. cinnabarinus treated by curcuma oil and the formulation was recorded at 6 h and 12 h, respectively. Thus, the formulation is a promising candidate as a botanical acaricide of green vegetables.

Latin Hypercube Sampling Based Probabilistic Small Signal Stability Analysis Considering Load Correlation

Jian Zuo,Yinhong Li,Defu Cai,Dongyuan Shi 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.6

A novel probabilistic small signal stability analysis (PSSSA) method considering load correlation is proposed in this paper. The superiority Latin hypercube sampling (LHS) technique combined with Monte Carlo simulation (MCS) is utilized to investigate the probabilistic small signal stability of power system in presence of load correlation. LHS helps to reduce the sampling size, meanwhile guarantees the accuracy and robustness of the solutions. The correlation coefficient matrix is adopted to represent the correlations between loads. Simulation results of the two-area, four-machine system prove that the proposed method is an efficient and robust sampling method. Simulation results of the 16-machine, 68-bus test system indicate that load correlation has a significant impact on the probabilistic analysis result of the critical oscillation mode under a certain degree of load uncertainty.

BMB : Reports ; An inhibitory role of NEK6 in TGFβ/Smad signaling pathway

( Jie Zuo ),( Haijie Ma ),( Hao Cai ),( Yanhua Wu ),( Wei Jiang ),( Long Yu ) 생화학분자생물학회(구 한국생화학분자생물학회) 2015 BMB Reports Vol.48 No.8

The NEK6 (NIMA-related kinases 6) is reported to play po-tential roles in tumorigenesis. Although it is suggested to function in several cellular pathways, the underlying mechanism in tumorigenesis is still largely unknown. In the present study, we discovered interaction of NEK6 with Smad4, a key member of transforming growth factor beta (TGFβ) pathway. Over-expression of NEK6 in hepatocellular carcinoma (HCC) cell lines suppresses TGFβ- mediated transcription activity in a kinase activity-dependent manner. In addition, NEK6 suppresses the cell growth arrest induced by TGFβ. Mechanically, NEK6 blocks nuclear translocation of Smad4, which is essential for TGF β function. Moreover, we identified that NEK6 could be regulated by TGFβ and hypoxia. Our study sheds new light on the roles of NEK6 in canonical TGFβ/Smad pathway and tum-origenesis. [BMB Reports 2015; 48(8): 473-478]

Nonlinear structural model updating based on the Deep Belief Network

Ye Mo,Zuo-Cai Wang,Genda Chen,Ya-Jie Ding,Bi Ge 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.5

In this paper, a nonlinear structural model updating methodology based on the Deep Belief Network (DBN) is proposed. Firstly, the instantaneous parameters of the vibration responses are obtained by the discrete analytical mode decomposition (DAMD) method and the Hilbert transform (HT). The instantaneous parameters are regarded as the independent variables, and the nonlinear model parameters are considered as the dependent variables. Then the DBN is utilized for approximating the nonlinear mapping relationship between them. At last, the instantaneous parameters of the measured vibration responses are fed into the well-trained DBN. Owing to the strong learning and generalization abilities of the DBN, the updated nonlinear model parameters can be directly estimated. Two nonlinear shear-type structure models under two types of excitation and various noise levels are adopted as numerical simulations to validate the effectiveness of the proposed approach. The nonlinear properties of the structure model are simulated via the hysteretic parameters of a Bouc-Wen model and a Giuffré- Menegotto-Pinto model, respectively. Besides, the proposed approach is verified by a three-story shear-type frame with a piezoelectric friction damper (PFD). Simulated and experimental results suggest that the nonlinear model updating approach has high computational efficiency and precision.

Glial and Vascular Cell Regulation of the Blood-Brain Barrier in Diabetes

Xiaolong Li,Yan Cai,Zuo Zhang,Jiyin Zhou 대한당뇨병학회 2022 Diabetes and Metabolism Journal Vol.46 No.2

As a structural barrier, the blood-brain barrier (BBB) is located at the interface between the brain parenchyma and blood, and modulates communication between the brain and blood microenvironment to maintain homeostasis. The BBB is composed of endothelial cells, basement membrane, pericytes, and astrocytic end feet. BBB impairment is a distinguishing and pathogenic factor in diabetic encephalopathy. Diabetes causes leakage of the BBB through downregulation of tight junction proteins, resulting in impaired functioning of endothelial cells, pericytes, astrocytes, microglia, nerve/glial antigen 2-glia, and oligodendrocytes. However, the temporal regulation, mechanisms of molecular and signaling pathways, and consequences of BBB impairment in diabetes are not well understood. Consequently, the efficacy of therapies diabetes targeting BBB leakage still lags behind the requirements. This review summarizes the recent research on the effects of diabetes on BBB composition and the potential roles of glial and vascular cells as therapeutic targets for BBB disruption in diabetic encephalopathy.