Structural Control & Health Monitoring最新文献

{"title":"Application of Acoustic Emission and Baseline-Based Approach for Early Fatigue-Damage Detection","authors":"Lu Cheng,&nbsp;Ze Chang,&nbsp;Roger Groves,&nbsp;Milan Veljkovic","doi":"10.1155/stc/3442236","DOIUrl":"https://doi.org/10.1155/stc/3442236","url":null,"abstract":"<div>\u0000 <p>Monitoring fatigue damage in mechanical connections is essential for maintaining the safety and structural integrity of offshore wind turbines (OWTs), particularly during the early stage of crack initiation. Recently, the C1 wedge connection (C1-WC) has emerged as a promising innovation for use in OWTs. Acoustic emission (AE) monitoring is a widely used real-time technique for detecting fatigue cracks. The space limitations of the lower segment holes in the C1-WC presents challenges for detecting surface cracks with conventional AE sensors. Thin Piezoelectric Wafer Active Sensors (PWAS), while small and lightweight, face limitations due to their poor signal-to-noise ratio. In this study, we propose a baseline-based approach to enhance the effectiveness of PWAS for accurate AE monitoring in confined spaces. A benchmark model correlating the damage state of specimens is created by breaking pencil leads. Multivariate feature vectors are extracted and then mapped to the Mahalanobis distance for damage identification. The proposed method is validated through testing on compact specimens and C1-WC specimens. To enhance the AE detection results, supplementary monitoring techniques, including digital image correlation, crack propagation gauges, and distributed optical fiber sensors, are employed. The experimental setup, signal acquisition, and detection efficiency of these techniques are briefly outlined. This study demonstrates that the proposed approach is highly effective in detecting early damage in C1-WC specimens using AE monitoring with PWAS.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/3442236","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antiwhip Measures for High-Energy Piping in Nuclear Power Plants Using Lead Extrusion Impact Damping Devices: Tests and Simulations","authors":"Luwei Shi,&nbsp;Yiqian Lu,&nbsp;Lingyun Peng,&nbsp;Jingsheng Qiao,&nbsp;Ruhan Zhang,&nbsp;Tianwei Sun","doi":"10.1155/stc/8829452","DOIUrl":"https://doi.org/10.1155/stc/8829452","url":null,"abstract":"<div>\u0000 <p>In this study, the antiwhip capability of high-energy piping in nuclear power plants was investigated based on the basement structure of a conventional island in a nuclear power engineering project. A lead extrusion impact damping device was developed, and its mechanical performance was validated through uniaxial static loading tests. A 1:4 scaled-down test model was designed and fabricated using traditional energy-dissipating steel beams, lead extrusion impact damping, and concrete blocks as three types of antiwhip restraining devices. Impact test studies were conducted supplemented by destructive impact tests without antiwhip restraining devices. Finite element models were established using Ansys LS-DYNA simulation software, and simulations were conducted for these four scenarios. The antiwhip performances of different antiwhip measures were evaluated by comparing the test and finite element simulation results and considering factors such as the impact force, wall displacement, wall acceleration, and crack distribution and development. The results indicate that while traditional energy-dissipating steel beams continue to provide some antiwhip effectiveness, the lead extrusion impact damping solution exhibits a significantly improved performance with better control of the structural dynamic response. In contrast, the concrete block solution demonstrated a poorer performance, leading to severe damage in structures like those without antiwhip restraining devices.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/8829452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Study on the Damping Ratio Evaluation of a Cable-Stayed Bridge Based on Damping Dissipation Function","authors":"Fengzong Gong,&nbsp;Cheng Pan,&nbsp;Ye Xia","doi":"10.1155/stc/5810450","DOIUrl":"https://doi.org/10.1155/stc/5810450","url":null,"abstract":"<div>\u0000 <p>Damping ratio is a fundamental dynamic parameter of the structure. Recent monitoring of cable-stayed bridges has shown that the damping ratio changes under different operating conditions. In general, the damping ratio of a structure can only be evaluated after the structure is built, and it is still challenging to theoretically calculate the damping ratio of a structure beforehand. To further understand the mechanism of the bridge damping ratio, this paper proposes an evaluation method based on the damping dissipation function. The effects of the initial and modal strain energy of the structure on the damping dissipation are considered. The damping dissipation function of substructures of a laboratory cable-stayed bridge model was tested, and the structural system damping ratio was evaluated. Furthermore, the theoretical discussion and experimental verification of the effect of support friction on the damping ratio were conducted. The results indicate that the damping ratio of the substructure varies with both the vibration amplitude and the initial stress level. Consideration of the initial strain energy during testing the substructure damping dissipation function can lead to more accurate results in the evaluation of the damping ratio of the structural system. In addition, support friction also significantly influences the damping ratio of the longitudinal drift and vertical bending modes of the structure.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/5810450","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Validation of New Methodology for Automated Operational Modal Analysis Using Modal Domain Range","authors":"Fatih Yesevi Okur,&nbsp;Ahmet Can Altunişik,&nbsp;Ebru Kalkan Okur","doi":"10.1155/stc/6267884","DOIUrl":"https://doi.org/10.1155/stc/6267884","url":null,"abstract":"<div>\u0000 <p>The ability to conduct automated operational modal analysis is essential for enabling real-time structural health monitoring without human intervention. Such automation remains a significant challenge due to the complexity of processing large datasets and the necessity of setting multiple user-defined thresholds. This study introduces a novel methodology for automated modal identification that leverages the enhanced frequency domain decomposition method. The key innovation of the proposed approach is the concept of the modal domain range, a parameter calculated for each frequency of the structure to distinguish physical modes from noise and false modes. The modal domain range is derived using the correlation of mode shapes, assessed through the modal assurance criterion method. High values within this range indicate dominant structural frequencies, enabling the autonomous identification of the structure’s dynamic characteristics. To validate the proposed methodology, experimental data from the Z24 Bridge, a prestressed concrete structure, were analyzed. The dynamic parameters, including natural frequencies and mode shapes, were identified using the developed approach and compared with reference data from the literature. The results demonstrated that the methodology achieves remarkable precision. Moreover, the proposed method effectively reduces the impact of noise and environmental variations through a systematic filtering and grouping process. The findings highlight the robustness and adaptability of the methodology, demonstrating its capability for automated and accurate identification of modal parameters in civil engineering structures.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/6267884","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Approach for Anomaly Detection in Vibration-Based Structural Health Monitoring Using Autoencoders in Deep Learning","authors":"Fatih Yesevi Okur,&nbsp;Ahmet Can Altunişik,&nbsp;Ebru Kalkan Okur","doi":"10.1155/stc/5602604","DOIUrl":"https://doi.org/10.1155/stc/5602604","url":null,"abstract":"<div>\u0000 <p>Structural health monitoring (SHM) has been widely employed in civil infrastructures for a number of years. Real-time monitoring of civil projects involves the utilization of diverse sensors. Nevertheless, accurately assessing the actual condition of a structure can pose challenges due to the existence of anomalies in the collected data. Abnormalities in this context often arise from a variety of factors, including extreme weather conditions, malfunctioning sensors, and structural impairments. The existing condition of anomaly detection is significantly impeded by this disparity. Online detection of anomalies in SHM data plays a crucial role in promptly assessing the status of structures and making informed decisions. In vibration-based SHM, enhanced frequency domain decomposition (EFDD) is one of the most used methods in the frequency domain. The signal output obtained from EFDD also includes the frequencies of the structures, which is a holistic evaluation. The findings of frequency measurements are influenced by the presence of structural damages. Extracting damage-sensitive characteristics from structural response has emerged as a complex task. Deep learning approaches have garnered growing interest due to their capacity to efficiently extract high-level abstract features from raw data. Within the scope of the study, a novel approach based on anomaly detection of changes in the signal output obtained using the EFDD was developed with autoencoders in deep learning. The performance of the novel approach was examined depending on different noise ratios (0%, 0.5%, 1%, 1.5%, and 2.0%) using the Z24 Bridge dataset. In the autoencoder training model, an autoencoder model containing a 4 Conv1D layer encoder–decoder as 128 × 64 × 64 × 128 was designed. By using the signal data of the first singular values obtained with the EFDD method, grouping was made with the labels “training data (1260 pieces),” “undamaged new data (250 pieces),” and “damaged new data (320 pieces).” In addition, the upper limit of the reconstruction error was calculated as 810 using the training data in the autoencoder model. The filtered reconstruction error values obtained were compared under different noise levels. At the end of the study, it was concluded that the novel approach works effectively under different noises and can be used in anomaly detection.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/5602604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging-Based Instance Segmentation of Pavement Cracks Using an Improved YOLOv8 Network","authors":"Fei Yu,&nbsp;Guanting Ye,&nbsp;Qing Jiang,&nbsp;Ka-Veng Yuen,&nbsp;Xun Chong,&nbsp;Qiang Jin","doi":"10.1155/stc/1660649","DOIUrl":"https://doi.org/10.1155/stc/1660649","url":null,"abstract":"<div>\u0000 <p>An improved YOLOv8 model, YOLOv8-NETC, is proposed in this study for fine-grained crack recognition through instance segmentation. YOLOv8-NETC is designed and enhanced with four self-developed modules. First, ablation studies were conducted to assess the effectiveness of each module. The model’s accuracy and speed were evaluated based on parameters such as mean average precision (mAP50) and model weight (MW). The experimental results show significant improvements in accuracy, storage efficiency, and processing speed. Compared to the original network, YOLOv8-NETC achieved a 6.5% increase in mAP50, a 6.1% average reduction in MW and parameters, and an 8.5% improvement in FPS. Subsequently, YOLOv8-NETC was compared with other state-of-the-art models across three datasets, including the crack type dataset, crack trueness dataset, and the public Crack500 dataset. The experimental results demonstrate that the proposed model achieved the best recognition performance on all datasets. Furthermore, YOLOv8-NETC showed superior robustness against interference and computational efficiency compared to other benchmark models.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/1660649","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143595141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Cycle Fatigue Assessment Method for Composite Bridges Based on Predamage Mechanics Model","authors":"Yongtao Bai,&nbsp;Qingyu Gong,&nbsp;Dixiao Tan,&nbsp;Zhongxiang Liu,&nbsp;Chunxu Qu","doi":"10.1155/stc/9959484","DOIUrl":"https://doi.org/10.1155/stc/9959484","url":null,"abstract":"<div>\u0000 <p>Long-span bridges face the significant challenge of deteriorating life cycles under fatigue loads. A new macroscopic damage mechanics model for rod hinge elements has been proposed to quantify the predamage of bridge beams subjected to high-cycle fatigue. This model introduces predamage variables to evaluate the damage evolution process prior to fatigue crack initiation, enabling the prediction of moderate deterioration in bridges that cannot be monitored during their service life. By comparing the fatigue test results and predamage simulation results of simply supported composite beams and continuous composite beams, it was found that the error between the model predictions and the test results is relatively small. This result confirms the reliability of the model. The predamage model has been implemented as a self-programming subroutine for numerical analysis. Taking the Daxi River Bridge as the engineering background, this predamage model was applied to practical engineering. Combined with typical traffic loads, a predamage assessment was conducted on its dangerous points. The dangerous beam segments of the bridge were taken and the damage values were calculated using a predamage subroutine model. The results obtained had a small error compared to the damage values of the corresponding beam segments in the full bridge simulation. The proposed high-cycle fatigue predamage subroutine model offers a valuable reference for predicting fatigue damage in bridges.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/9959484","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143581448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable Artificial Intelligence–Based Search Space Reduction for Optimal Sensor Placement in the Pipeline Systems of Naval Ships","authors":"Chungeon Kim,&nbsp;Hyunseok Oh,&nbsp;Byung Chang Jung,&nbsp;Seok Jun Moon,&nbsp;Bongtae Han","doi":"10.1155/stc/8462004","DOIUrl":"https://doi.org/10.1155/stc/8462004","url":null,"abstract":"<div>\u0000 <p>Pipeline damage in mission-critical systems, such as pipelines within naval ships, can result in substantial consequences. Compared to manual inspection of pipeline damage by crew members onboard, structural health monitoring of pipeline systems offers prompt identification of damage sites, enabling efficient damage mitigation. However, one challenge of this approach is deriving an optimal sensor placement (OSP) strategy, given the large and complex pipelines found in real-scale naval vessels. To address this issue, a search space reduction method is proposed for OSP suitable for the large and complex pipeline systems found in naval ships. In the proposed method, the original search space for sensor placement is reduced to a manageable scale using an explainable artificial intelligence (XAI) technique, namely, a gradient-weighted class activation map (Grad-CAM). Grad-CAM enables quantification and visualization of the contribution of individual pipeline nodes to classify damage scenarios. Noncritical sensor locations can be excluded from the candidate search space. Furthermore, a peak-finding algorithm is devised to select only a limited number of nodes with the highest Grad-CAM values; in this research, the algorithm is proven effective in reconstructing the search space. As a result, the original OSP problem—which has an extremely large search space—is reconstructed into a new OSP problem with a computationally manageable search space. The new OSP problem can be solved using either meta-heuristic methods or exhaustive search methods. The effectiveness of the proposed method is validated through a case study on a real-scale naval combat vessel, measuring 102 m in length and carrying a full load of 2300 tons. The results show that the proposed XAI-based search space reduction approach efficiently designs an optimal pipeline sensor network in real-scale naval combat vessels.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/8462004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an Advanced Online Adaptive FOPID Controller Using the Interval Type 2 Fuzzy Neural Network Optimized With the Levenberg–Marquardt Algorithm for a 20-Story Benchmark Building","authors":"Rasoul Sabetahd,&nbsp;Ommegolsoum Jafarzadeh","doi":"10.1155/stc/6676388","DOIUrl":"https://doi.org/10.1155/stc/6676388","url":null,"abstract":"<div>\u0000 <p>This paper proposes an innovative control method to reduce the seismic responses of nonlinear structures under the uncertainties of near- and far-field earthquakes. This method is crucial for controlling the seismic response and ensuring structural stability. For this purpose, the robust adaptive FOPID controller is combined with the interval Type 2 fuzzy neural network, whose parameters are optimized through the Levenberg–Marquardt algorithm. An MLP neural network trained using an error backpropagation algorithm is considered for structural system identification and plant estimation. The Jacobian of the estimated model is applied online to the controller. Also, an adaptive compensator, interval Type 2 fuzzy neural networks, is considered to increase the stability and robustness of the proposed controller against estimation error, seismic disturbances, and some unknown nonlinear functions. The extended Kalman filter with feedback error learning strategy is used to maintain the acceptable performance level in the compensator. The performance effectiveness of the proposed controller equipped with a compensator in reducing seismic responses was investigated on a 20-story benchmark building equipped with an active cable damper, and the evaluation criteria were compared with previous works. The results indicate that the IT2FNN-FOPID controller performs better than other controllers in mitigating the seismic responses of the structure during an earthquake and achieving the control objectives. Thus, the <i>J</i>₁ criterion in the El Centro earthquake with an intensity of 1.5 times has improved by about 70% of the ratio of the LQG controller, which is about 60% in the case of the Kobe earthquake.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/6676388","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic Static Model Updating of Bridge Using Homotopy Method and Pre-Estimated Solution Domain","authors":"Bin Huang,&nbsp;Kaiyi Xue,&nbsp;Hui Chen,&nbsp;Ming Sun,&nbsp;Zhifeng Wu","doi":"10.1155/stc/4714219","DOIUrl":"https://doi.org/10.1155/stc/4714219","url":null,"abstract":"<div>\u0000 <p>When implementing structural model updating, whether the model is stochastic or deterministic, the ill-posed issue is a challenging problem. To effectively address this problem, this paper proposes a new static stochastic model updating method, which combines the homotopy method with the pre-estimation technique of solution domains of the updating quantities. Firstly, considering the uncertain static measurement displacements, the solution domains of updating factors in structural models such as bridges are derived in terms of the sensitivity of static strain energy. Then the homotopy method is used to transfer the stochastic static model updating equation into a series of deterministic recursive equations about the expansion coefficients of updating factors. Within the pre-estimated solution domains, the expansion coefficients of the updating factors can be solved by the L-curve method and the convex optimization. When the measurement positions do not contain the loading points, a model expansion strategy is provided. Two numerical examples demonstrate that the proposed method can offer stable updating results, which coincide very well with those assumed real values, in the cases of high-dimension and limited measurement points. And when the displacements at the loading points are not directly measured, compared with the Bayesian method with the finite element samples, the proposed method has higher computational efficiency with the equivalent accuracy. When updating a practical continuous box-girder bridge, the proposed method can efficiently update a large finite element model, and the statistics of updating results agree very well with those of the static measurement data.</p>\u0000 </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2025 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/stc/4714219","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143522007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}