Journal of Nondestructive Evaluation最新文献

{"title":"Air-coupled Impact-echo Actuation Applied on Concrete Sleepers for Crack Detection","authors":"Christoph Strangfeld,&nbsp;David Ringeloth","doi":"10.1007/s10921-026-01404-z","DOIUrl":"10.1007/s10921-026-01404-z","url":null,"abstract":"<div><p>Worldwide, about one billion prestressed concrete sleepers degenerate due to loads, chemical reactions, moisture or climatic conditions. Corrosion of the reinforcement or damage to the material structure can occur in the sleeper without any visible external signs. Therefore, non-destructive testing methods are required to reliably assess the condition. In this work, six prestressed concrete sleepers of type B70 are examined using the impact-echo method. Three different actuation methods are applied: a manually operated impact-hammer, an electromechanically mounted impact-cylinder and an air-coupled supersonic jet flow. All three actuation types show similar and consistent spectrograms. In intact rail sleepers, a dominant frequency above 10 kHz is always visible. In contrast, damaged sleepers show a dominant frequency significantly below 10 kHz. This simple threshold analysis can already be used for a condition assessment of the sleepers. Since the supersonic jet flow is continuous, an air-coupled inspection during travel at up to 80 km/h is theoretically possible. Since the nozzles are inexpensive, robust and virtually maintenance-free, a multi-channel actuation could be realised with little effort. In the future, the entire sleeper could be inspected non-destructively in a single high-speed pass, including a real-time condition assessment.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10921-026-01404-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Numerical Approach to Evaluate Frequency Shifts in Composite Laminates After Impact: Facilitating Machine Learning-Based Non-Destructive Assessment of Impact Damage","authors":"Zhihong Liang,&nbsp;Zhifang Zhang,&nbsp;Jiyang Fu,&nbsp;Karthik Ram Ramakrishnan","doi":"10.1007/s10921-026-01406-x","DOIUrl":"10.1007/s10921-026-01406-x","url":null,"abstract":"<div><p>Fibre-reinforced polymer (FRP) composites are susceptible to impact damage during their service life. Vibration-based structural health monitoring (SHM) has emerged as a promising technique for reliably detecting and assessing such damage. This approach leverages the principle that damage induces local stiffness discontinuities, altering vibrational parameters such as natural frequencies, mode shapes, and damping. Research in this area has focused on using frequency shifts across multiple modes and applying inverse algorithms like Artificial Neural Networks (ANN) or Genetic Algorithms (GA) to predict the location and extent of damage. Training these machine learning algorithms (MLAs) requires extensive databases of frequency shifts corresponding to various damage parameters. To address the computational demands of database generation, numerical models offer an economical alternative. This study introduces a novel numerical methodology for evaluating frequency shifts in FRP composite laminates subjected to impact damage, facilitating machine learning-based non-destructive evaluation. The approach employs finite element modelling with restart analysis to efficiently simulate multiple damage scenarios without the need for complex parametric mappings. Simulations of composite plates under various impact energies demonstrate the method's effectiveness in characterizing cumulative damage through frequency shifts, particularly at higher energy levels, where it outperforms conventional techniques. The study also examines the influence of different damage criteria, including two-dimensional and three-dimensional Hashin models, on frequency shifts and mode shapes, showcasing the versatility of the proposed method. By streamlining the generation of extensive frequency shift databases, this approach significantly enhances the training of MLAs for inverse damage identification. The methodology has the potential to advance SHM techniques for composite structures across aerospace, automotive, and wind energy applications.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148466216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PLB-Based Acoustic Emission Damage Index for Quantifying Barely Visible Impact Damage in Aluminum-Lined CFRP Laminates with Nonlinear Ultrasonics","authors":"Lu Zhang,&nbsp;Xiang Li,&nbsp;Daojun Feng,&nbsp;Lianxin Chen,&nbsp;Bin Tang,&nbsp;Feifei Long","doi":"10.1007/s10921-026-01411-0","DOIUrl":"10.1007/s10921-026-01411-0","url":null,"abstract":"<div><p>Barely visible impact damage (BVID) in carbon fiber-reinforced polymer (CFRP) laminates is difficult to assess reliably using a single nondestructive testing (NDT) technique. Therefore, this study proposes an in situ measurement strategy that combines pencil lead break acoustic emission (PLB-AE) with nonlinear ultrasonics to quantitatively assess impact damage in aluminum-lined CFRP laminates. Low-velocity impact tests were conducted at energies of 10, 20, 30, 45, and 60 J to induce BVID of different severity. After verifying waveform consistency using the skewness and kurtosis of the PLB-AE signals before and after impact, the damage index (DI) was developed using Mahalanobis distance (MD) based on PLB-AE characteristics (amplitude, energy, count, and rise time amplitude (RA)). The DI derived from PLB-AE characteristics can be correlated with damage and used to identify the transition in damage mode. Likewise, the acoustic nonlinearity coefficient obtained from nonlinear ultrasonic testing (NLUT) shows higher sensitivity to impact damage and reflects changes in damage modes. A pronounced shift in the trends of both the DI and the nonlinearity coefficient occurs around 30 J, indicating that a transition in damage mechanisms takes place near this impact energy in the tested laminated structures. The proposed PLB-NLUT method provides a reliable and practical strategy for evaluating BVID in composite structures.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148466132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on In-Situ Measurement Method of Permanent Volumetric Expansion of Large Capacity Gas Cylinders Based on 3D Point Cloud Modeling","authors":"Kun Shi,&nbsp;Yunyi Zhou,&nbsp;Kangjian Cai,&nbsp;Yu He,&nbsp;Xiaolan Wang,&nbsp;Maohua Zhong","doi":"10.1007/s10921-026-01408-9","DOIUrl":"10.1007/s10921-026-01408-9","url":null,"abstract":"<div><p>Gas cylinders are typical pressure vessels used for transporting and storing gases (including liquefied gases) and serve as essential infrastructure supporting a country’s economic and social development. Repeated filling and discharging in use may cause material fatigue, leading to plastic deformation and eventual failure. Permanent volumetric expansion is a key safety and quality indicator for cylinders. Traditional methods, whether direct expansion method or water jacket method, require dedicated equipment and sites, cannot realize in-situ inspection, and cannot capture localized plastic deformation. They are also inefficient and costly. To enable accurate in-situ measurement of permanent volumetric expansion, this paper proposes a method based on 3D point cloud modeling, combining laser scanning with theoretical analysis and experimental comparison. Using 3D laser scanning, point cloud data of five cylinders were collected before and after hydraulic testing. Triangular mesh models were constructed from the data, and permanent volumetric expansion was derived from volume change calculations. Experimental results compared with the water jacket method show that the proposed method uses fewer devices, is simple to operate, and yields small errors, confirming its feasibility. More importantly, unlike existing methods that only reflect overall deformation, this method accurately and intuitively reveals deformation at each local section of the cylinder. This is significant for precisely assessing cylinder safety. The method demonstrates clear advantages over similar techniques and offers engineering practicality. Future work may establish corresponding measurement and evaluation standards based on this method’s technical features.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparative Study of Convolutional Neural Networks for Classification of Low Velocity Impact Damages in CFRP from Ultrasonic C-Scans","authors":"Johannes Wolfrum,&nbsp;Julia Meyer,&nbsp;Christoph Petroll,&nbsp;Sebastian Johannes Lorenz,&nbsp;Sami Hamza","doi":"10.1007/s10921-026-01393-z","DOIUrl":"10.1007/s10921-026-01393-z","url":null,"abstract":"<div><p>Carbon fiber-reinforced polymers (CFRP) are particularly vulnerable to low-velocity impact loads that can lead to material degradation like cracks and delaminations. Due to the difficult visual detectability of these damages, ultrasonic testing has been established for many decades as the standard test method. Usually, the interpretation of the ultrasonic C-Scans is performed manually which requires a high level of operator qualification and experience. Therefore, this study compares different convolutional neural networks (CNN) for the classification of damaged and undamaged ultrasonic C-Scans of CFRP-specimen. For the required dataset, in-house ultrasonic C-Scans were compiled and categorized into three different classes: low-velocity impact damage, “non-impact” damage and undamaged CFRP-material. Before use in a CNN, the dataset was edited with an automated image processing to reduce inhomogeneities. The final dataset was first attached to various pretrained networks. Further it was used for the training of a self-generated model. The adapted and pretrained models outperformed the self-generated one with an accuracy of up to 92,5%. Due to the fact, that the self-generated model offers more possibilities for fitting the architecture and the extracted features exactly to the given classification task it is still preferred.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10921-026-01393-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pattern Recognition of Crack Extension in Oil and Gas Pipelines Based on Acoustic Emission Signals","authors":"Jianhua Pan,&nbsp;Zaoxiang Kuang","doi":"10.1007/s10921-026-01409-8","DOIUrl":"10.1007/s10921-026-01409-8","url":null,"abstract":"<div><p>To address the insufficient real-time capability and strong noise interference associated with conventional crack detection methods for oil and gas pipelines, this paper proposes a crack propagation pattern recognition method that integrates acoustic emission (AE) signals with intelligent algorithms. An improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is introduced to denoise AE signals. Wavelet packet energy spectrum analysis and kernel principal component analysis (KPCA) are then combined to extract the principal components of frequency-band energy, and multi-channel data are fused by a feature serial fusion strategy to construct comprehensive feature vectors. Furthermore, a convolutional neural network optimized by the sparrow search algorithm (SSA-CNN) is developed to accurately classify three stages of crack propagation: crack initiation, stable propagation, and unstable propagation. The experimental results show that the proposed method can effectively identify crack propagation patterns under both sufficient-sample and small-sample conditions. Compared with the conventional SVM and unoptimized CNN models, the recognition accuracy is significantly improved, reaching a maximum of 98.67%, which verifies the robustness and engineering applicability of the proposed method. This study provides a new technical approach for real-time safety monitoring of oil and gas pipelines and is of great significance for improving pipeline operation and maintenance efficiency as well as accident early-warning capability.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shear Deformation Identification of Laminated High Damping Rubber Bearings using Electro-Mechanical Coupled Model of Bonded PZT Transducers: Modeling, Simulation and Experimentation","authors":"Demi Ai,&nbsp;Aoqiu Zhou,&nbsp;Hedong Li","doi":"10.1007/s10921-026-01405-y","DOIUrl":"10.1007/s10921-026-01405-y","url":null,"abstract":"<div><p>In-situ deformation detection in laminated high damping rubber bearings (HDRBs) is a challenging experimental mechanics task particularly when using a non-intrusive approach. One potential application of such task is the management of the in-service HDRBs in base-isolated civil infrastructures. This article examined the potential of the Electro-Mechanical Admittance (EMA) method to provide an identification of shear deformation levels in HDRBs by using piezoelectric ceramic (PZT). A novel electro-mechanical coupling model that integrated structural mechanical impedance with two-spring model theory was proposed to analytically resolve the correlation between the EMA spectrums and vertical stiffness/damping associated to shear deformations in the HDRB, which was further validated by generating a full-scaled three-dimensional finite element (FE) model and performing experimental tests on an identical HDRB subjected to different shear deformations from 0% to 60% and constant compressive stress of 12 MPa. Theoretical, numerical and experimental investigations consistently revealed that the resonant peaks in the EMA signatures of PZT transducers bonded on the rubber layer exhibited gradual reduction of the resonance frequency accompanied with magnitude increase with increasing shear deformations, while that of the transducers bonded on steel end plate behaved inverse characteristics. Extraction of the resonance parameters favorably confirmed the EMA signatures as a linear function of the shear deformations in the HDRB, thus providing quantifiable estimation. Comparing to traditional disassembly, acoustic emission and wave-based methods, the developed model offered an accurate, low-costive and non-invasive tool for assessing the deformative levels of in-situ HDRBs in base-isolated structures.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GLCA-Net: Global-Local Contextual Attention Network for Real-Time Insulated Gate Bipolar Transistor Void Defect Segmentation Based on Computed Laminography System","authors":"Yan Li,&nbsp;Shuangquan Liu,&nbsp;Cunfeng Wei,&nbsp;Chao Fan","doi":"10.1007/s10921-026-01402-1","DOIUrl":"10.1007/s10921-026-01402-1","url":null,"abstract":"<div><p>Insulated gate bipolar transistor (IGBT) modules are core components of power electronic systems, and void defect in their welding layers severely compromise system reliability and service life. Accurate void segmentation is critical for quality control yet remains challenging due to complex morphological variations and low contrast. Moreover, highly accurate, real-time, and robust methods are crucial for industrial applications. To address these issues, we propose the global-local contextual attention network (GLCA-Net), a lightweight encoder-decoder architecture for real-time void segmentation in IGBT welding layers. In the encoder, to capture both global contextual information and fine-grained local details across multiple scales, we propose a global-local multi-scale attention (GLMSA) module. In the decoder, inspired by the skip connection of DeepLabV3+, we devise a scale-aware channel spatial attention (SCSA) module to take full advantage of the multi-scale features from the encoder. Validated on two in-house IGBT welding void defect datasets (IGBT-WVD-Chip and IGBT-WVD-DBC), GLCA-Net outperforms UNet, DeepLabV3+, TransUNet, SwinUNet and BiSeNet. It achieves 71.49% Dice and 56.07% IoU on the Chip dataset, and 66.43% Dice and 54.29% IoU on the DBC dataset, with merely 0.244 M parameters and 182 FPS inference speed. This work provides a technical reference for the automatic void detection of IGBT welding layers, thus facilitating the improvement of their manufacturing quality.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity Crossover and Generalized Scaling Laws in Resonant Eddy Current Testing of Cylindrical Conductors","authors":"Yukinaga Shimoguchiya,&nbsp;Shigeharu Sugawara","doi":"10.1007/s10921-026-01400-3","DOIUrl":"10.1007/s10921-026-01400-3","url":null,"abstract":"<div><p>Non-contact inspection of cylindrical conductors, such as pipes and rods, is crucial in industrial applications. While traditional Eddy Current Testing (ECT) theory predominantly relies on flat-plate models, the specific geometric effects inherent to cylindrical geometries remain underexplored. This study investigates the relationship between eddy current behavior and sensor sensitivity, specifically frequency shift, using the Finite Element Method (FEM) and theoretical analysis. We identify a \"Sensitivity Crossover\" phenomenon in the intermediate frequency range, where thin-walled pipes exhibit a stronger sensor response than solid rods, despite their smaller conductor volume. Detailed analysis of current density distributions reveals that this counterintuitive behavior stems from an \"Interference Boost\" caused by electromagnetic wave reflection at the pipe's inner wall, which suppresses energy diffusion into the depths and enhances the effective magnetic coupling through current confinement near the surface. Furthermore, we construct a \"Generalized Sensitivity Curve\" correlating resistivity with sensitivity, establishing design guidelines to exploit the \"Transition Region\" where this crossover occurs. Finally, deriving scaling rules based on electromagnetic similarity, we present theoretical engineering solutions applicable to the inspection of cylindrical components of arbitrary dimensions.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of the Impact Resistance of RC Slabs using Acoustic Emission Information Entropy: A Multi-Parameter Fusion Approach","authors":"Alipujiang Jierula,&nbsp;Weicheng Wang,&nbsp;Cungen Wang,&nbsp;Shuhong Wang,&nbsp;Tae-Min Oh","doi":"10.1007/s10921-026-01403-0","DOIUrl":"10.1007/s10921-026-01403-0","url":null,"abstract":"<div><p>Reinforced concrete (RC) slabs are the core horizontal load-bearing members in civil and protective engineering. Under extreme loads such as explosive impacts and falling object impacts, they are prone to sudden structural collapse due to the continuous accumulation of internal damage. However, traditional detection methods can only obtain macroscopic mechanical responses and cannot realize real-time dynamic monitoring of the entire process of damage initiation and propagation. As a passive dynamic non-destructive testing method, acoustic emission (AE) technology can achieve real-time characterization of internal damage by capturing elastic wave signals released by material damage. Nevertheless, its application under impact load conditions still suffers from the lack of a systematic correlation mechanism between damage and parameters. This paper proposes a multi-parameter fusion analysis method based on AE information entropy CV. By conducting increasing-amplitude drop weight impact tests on RC slabs with three thicknesses (80, 100 and 120 mm), the mechanical responses, stiffness degradation and AE characteristics were systematically investigated. The results show that the cumulative displacement-stiffness degradation model proposed in this paper can effectively quantify the degradation rate through the attenuation index α after component failure, and this parameter decreases with increasing slab thickness. This corresponds to different failure modes: the 80 mm slab exhibits rapid stiffness degradation and damage-accumulative punching shear failure, the 120 mm thick slab undergoes a more ductile punching shear failure, and the 100 mm thick slab presents a transitional response. In addition, AE information entropy CV can serve as an early warning indicator for component damage and failure. The evaluation system constructed by combining multi-dimensional signal characteristics including AE activity analysis, AE information entropy CV, RA-AF distribution and b-value with macroscopic data such as displacement can accurately characterize damage stages, crack modes and failure precursors, providing a quantitative basis for damage identification and health monitoring of RC structures under impact loads. Unlike single-parameter methods, which may fail when damage becomes complex, the proposed multi-parameter fusion strategy overcomes this limitation, and simultaneous anomalies across multiple parameters provide stronger evidence of impending failure.</p></div>","PeriodicalId":655,"journal":{"name":"Journal of Nondestructive Evaluation","volume":"45 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148465118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}