Journal of Manufacturing Processes最新文献

{"title":"Formation and mechanical performance of the pre-counter bore resistance rivet welded joints for thick cast aluminum and ultra-high strength steel","authors":"Zixuan Chen ,&nbsp;Ming Lou ,&nbsp;Han Yu ,&nbsp;Bowen Zhang ,&nbsp;Cheng Liu ,&nbsp;Sizhe Niu ,&nbsp;Yongbing Li","doi":"10.1016/j.jmapro.2025.03.002","DOIUrl":"10.1016/j.jmapro.2025.03.002","url":null,"abstract":"<div><div>Al/steel dissimilar joining represents a crucial strategy for vehicle body lightweighting. However, the increasing adoption of integrated die-casting with thick aluminum components in automotive manufacturing has introduced unprecedented challenges for Al/steel joining technologies. A novel approach to address thick cast Al to steel joining was developed through an innovative modification of resistance rivet welding (RRW). By incorporating a presetting counter bore prior to the traditional RRW process, high-performance flat surface joining between thick cast aluminum and press hardened steel (PHS) was successfully achieved, as demonstrated with 3.0 mm and 1.5 mm thickness specimens respectively. Through systematic investigation of process parameters, a comprehensive process window was established and detailed analyses of joint geometry characteristics were conducted. Microstructural characterization revealed that Al elements were uniformly distributed throughout the Al/steel mixed nugget. Under low heat input conditions, the nugget consisted of ferrite with an average grain size of 135.9 μm, while under high heat input conditions, it was composed of martensite with an average grain size of 3.9 μm. The joints exhibited mechanical performance, with a peak microhardness of 580 HV, tensile-shear strength of 10,691 N and cross-tension strength of 4057 N achieved. This study provides an effective solution for joining thick cast aluminum to steel and expanding the capabilities of dissimilar metal joining technology.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 431-444"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development on shape and performance control of aeronautical parts in additive manufacturing","authors":"Guofu Gao,&nbsp;Yan Wang,&nbsp;Yi Wang,&nbsp;Kuan Zhang,&nbsp;Daohui Xiang,&nbsp;Junjin Ma","doi":"10.1016/j.jmapro.2025.03.015","DOIUrl":"10.1016/j.jmapro.2025.03.015","url":null,"abstract":"<div><div>The strong thermal-solidification-mechanical coupling in the additive manufacturing process makes it technically difficult to establish a reliable shape accuracy and performance control method in aerospace applications. Most of the existing shape and performance control methods are aimed at improving shape accuracy and mechanical performance separately. To understand the development trend of shape accuracy and performance control, this study reviews the progress covering mechanism analysis of shape and performance defects, prediction and compensation methods, process control, different assisted machining methods, application effects, heat-treat. The shape and surface defects are mainly caused by the design method and the instability of the molten pool and the high cooling rate during manufacturing process, and the mechanical performance defects are mainly formed by the special microstructure and internal defects formed during the manufacturing process. Before manufacturing, the shape and surface defects are predicted and compensated mainly by simulation and preheating. In the processing stage, key process parameters are controlled to ensure constant heat input and stability of the molten pool. Auxiliary technology and post-processing are important methods to optimize surface quality and microstructure to enhance shape accuracy and performance. The current deficiencies and future challenges of shape and performance collaborative control are summarized to lay the foundation for the further development of shape accuracy and performance control in AM.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 351-374"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Easily creating slant microwall arrays by tailoring melt redistribution for directional liquid transportation","authors":"Chenxi Jia ,&nbsp;Pingmei Ming ,&nbsp;Yunyan Zhang ,&nbsp;Jianshu Wang ,&nbsp;Jinlong Song","doi":"10.1016/j.jmapro.2025.03.010","DOIUrl":"10.1016/j.jmapro.2025.03.010","url":null,"abstract":"<div><div>Driving directional liquid transportation on structured surfaces has garnered significant attention. Laser texturing technology is favored for its efficiency and flexibility in creating functional surfaces. However, existing laser texturing processes often struggle to form the complex structures required for customized functional surfaces. In this study, we propose a novel strategy called vertically incident high-frequency pulsed laser tailored melt redistribution (viHPLTMR) to rapidly fabricate slant microwall arrays. This strategy employs nanosecond (ns) pulsed laser direct writing (DLW) with repeated line-by-line unidirectional scanning to control the flow patterns of the melt microfluidics. Specifically, the redistribution direction of melt microfluidics aligns with the advancing direction of the laser and is regulated by thermal effects from multi-pulse and periodic energy input. Proper selection of machining parameters allows for the adjustment of microstructure unit sizes and the transformation of microwall slant angles from 34° to 65°. Additionally, based on the multi-process analysis of microstructure characterization, a mechanism model of melt redistribution driven by high-frequency pulsed laser is established. This model reveals the formation process of array structures and the reasons behind their regular behavior. It was found that the constructed surface exhibits excellent superhydrophobicity and anisotropy, with droplets (6.4 μL) achieving a maximum horizontal bounce distance of 1.92 mm and up to 22 consecutive jumps, demonstrating significantly favorable long-distance directional liquid transmission ability. Unlike traditional heterogeneous gradient surfaces, these structured surfaces are free from regional limitations, offering greater flexibility and higher transmission speeds (10.4 mm/s). Furthermore, the viHPLTMR strategy can similarly control melt microfluidic motion and surface wetting performance on different metallic materials such as titanium alloy, stainless steel, magnesium alloy, and aluminum alloy, offering the advantages of low cost, high flexibility, and suitability for large-scale manufacturing.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 389-402"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive review of twin-wire directed energy deposition-arc (TW-DED-arc) process: An in-situ alloying based additive manufacturing approach for intermetallics","authors":"Chen Shen ,&nbsp;Yan Ma ,&nbsp;Zengxi Pan ,&nbsp;Fang Li ,&nbsp;Yuelong Zhang ,&nbsp;Lin Wang ,&nbsp;Yuchen Li ,&nbsp;Huijun Li ,&nbsp;Xueming Hua","doi":"10.1016/j.jmapro.2025.03.007","DOIUrl":"10.1016/j.jmapro.2025.03.007","url":null,"abstract":"<div><div>Twin-wire directed energy deposition-arc (TW-DED-arc) is a metal additive manufacturing (AM) technique that involves in-situ alloying. This approach has been under development since 2014. During this procedure, two dissimilar wires are independently introduced into a single molten arc pool to create the material according to a predetermined design by adjusting the feeding ratios of the wires. In contrast to conventional AM methods that utilize pre-alloyed powder or wire as filler materials, TW-DED-arc demonstrates enhanced applicability for producing intermetallic components attributed to its in-situ alloying and arc-deposition characteristics. To date, TW-DED-arc method has demonstrated feasibility in the fabrication of a wide range of application-valuable intermetallic alloys, including titanium aluminide, iron aluminide, and nitinol. The flexible TW feeding feature also enables the easy achievement of composition functional graded materials. In 2023, the initial titanium aluminide low-pressure turbine (LPT) blade produced from TiAl-4822 alloy using TW-DED-arc fabrication method was documented. This event marks a significant milestone for this distinctive AM technology as it transitions from laboratory settings to industrial applications. The emergence of this process not only advances research on AM of intermetallics but also provides a novel approach for the flexible fabrication of intermetallics. While further efforts are required to standardize TW-DED-arc process for producing intermetallic alloys, the ongoing research on this method has already demonstrated its validity and competitiveness. This review provides a summary of the research progress on TW-DED-arc over the past decade and identifies the current challenges to serve as a roadmap for future technical advancements.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 296-318"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards the automation of woven fabric draping via reinforcement learning and Extended Position Based Dynamics","authors":"Patrick M. Blies ,&nbsp;Sophia Keller ,&nbsp;Ulrich Kuenzer ,&nbsp;Yassine El Manyari ,&nbsp;Franz Maier ,&nbsp;Markus G.R. Sause ,&nbsp;Marcel Wasserer ,&nbsp;Roland M. Hinterhölzl","doi":"10.1016/j.jmapro.2025.02.063","DOIUrl":"10.1016/j.jmapro.2025.02.063","url":null,"abstract":"<div><div>The draping process in the preforming stage of composite manufacturing is very cost- and time-expensive and requires substantial manual labor. One strategy towards automation is the use of collaborative robots. Recent advances in AI have made it possible to train robots on difficult real-world tasks with reinforcement learning. However, training a robot using reinforcement learning is practically challenging and leveraging simulation is often the only option to use reinforcement learning in real-world settings at all. Existing FE models, which are commonly used for optimization of preforming processes, are too slow for reinforcement learning training. We addressed this issue by developing an XPBD-based surrogate model, drastically reducing simulation times compared to a classic FE model. With the achieved speedup, the training of a reinforcement learning agent became feasible and a draping trajectory could successfully be transferred to a real-world cobot, demonstrating the potential and capabilities of this innovative approach.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 336-350"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Model based adaptive process control along intercompany process chain for sheet metal forming of steel","authors":"Nilesh Thakare ,&nbsp;Jannik Gerlach ,&nbsp;Nikita Fjodorovs ,&nbsp;David Bailly ,&nbsp;Emad Scharifi","doi":"10.1016/j.jmapro.2025.02.082","DOIUrl":"10.1016/j.jmapro.2025.02.082","url":null,"abstract":"<div><div>A typical metallic product manufacturing process chain involving several companies faces challenges in promptly responding to the deviations in material properties, thereby impacting its economic efficiency. This can be attributed to the lack of knowledge about the exact condition of each product in a batch, as suppliers can only perform quality inspections randomly. This study introduces a novel approach utilizing simulation models to calculate the mechanical properties of products and design of experiments based process design using the calculated product properties shared by suppliers with their customers over a secure and reliable intercompany data management platform. The proposed approach is implemented in a laboratory scale process chain consisting of cold rolling and deep drawing using DC04 steel to demonstrate adaptive process control via intercompany exchange of yield and tensile strength of the cold strip. The benefits of adaptive process control are demonstrated by 50 % reduction in deviations in the minimum sheet thickness in cross die, thus showcasing the reproducibility of the end product with improved quality and by avoiding scrap generation, thereby allowing a sustainable manufacturing.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 403-415"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Machine learning-driven ultrasonic monitoring for quality assurance in additive manufacturing employing 2D phononic coupons","authors":"Avijit Chakrobarty,&nbsp;Tipu Sultan,&nbsp;Cetin Cetinkaya","doi":"10.1016/j.jmapro.2025.02.083","DOIUrl":"10.1016/j.jmapro.2025.02.083","url":null,"abstract":"<div><div>Additive Manufacturing/3D Printing (AM/3DP) is a critical fabrication technology, especially for manufacturing high-value, high-performance, complex parts and components requiring unprecedented degrees of morphological (shape) complexities, material combinations, and internal geometrical intricacies. However, in AM/3DP, quality assurance remains a persistent problem. AM/3DP processes are known to be volatile and involve coupled fields with strong nonlinearities; as a result, traditional first-principles-based approaches often struggle with accurate process modeling and predictions. Ultrasound is a promising Non-destructive Evaluation (NDE) technique, but its direct use has limitations in evaluating compact parts with intricate internal structures due to the complex diffraction and reflection fields that its interfaces cause in the near-field, leading to challenges in building principles-based mathematical models. The current proof-of-concept study introduces a Machine Learning (ML)-driven ultrasonic monitoring framework using Phononic Test Coupons (PTCs) for real-time quality assurance in AM/3DP. PTCs are specially designed lattice-based coupons with periodic internal structures that mimic the actual build's critical geometric and structural attributes. In the presented model PTC designs, each layer consists of 20 closely packed parallel lines (bundles) printed in a Fused Filament Fabrication (FFF) process from PLA material, stacked in a six-layer structure totaling 120 bundles. Each bundle is labeled with a unique global bundle index. A Deep Neural Network (DNN) model that detects and localizes defects in real-time by analyzing the experimental ultrasonic elastic waves acquired during printing is developed and used. The effectiveness of the resulting DNN model is tested with previously unseen experimental data, demonstrating an accuracy of over 86 % in predicting the global bundle index from the ultrasonic waveform. The proposed framework could provide real-time feedback to the closed-loop control system of the machine or proactively halt defective prints, allowing for necessary adjustments in the process.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 416-430"},"PeriodicalIF":6.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In situ tailoring microstructure of martensitic stainless steel during wire-arc directed energy deposition via intrinsic heat treatment","authors":"Zhiwei Lyu ,&nbsp;Su Li ,&nbsp;Yutaka S. Sato ,&nbsp;Yue Zhao ,&nbsp;Xi He ,&nbsp;Zhifang Shi ,&nbsp;Yifeng Xiao ,&nbsp;Qiang Zhu","doi":"10.1016/j.jmapro.2025.03.005","DOIUrl":"10.1016/j.jmapro.2025.03.005","url":null,"abstract":"<div><div>Additive manufacturing enables precise control over process parameters during fabrication, thereby influencing the resulting microstructure. In this study, the microstructure of AISI 420 martensitic stainless steel was tailored during wire-arc directed energy deposition by strategically manipulating intrinsic heat treatment, i.e., rapid reheating from subsequent depositions. By reducing the interpass dwell time and maintaining the interpass temperature above the martensite start (M_s) temperature, the martensitic transformation in the deposited layer was inhibited, preserving the austenite phase. The austenite remained largely unaffected by intrinsic heat treatment and primarily transformed into martensite after the final pass, yielding high hardness (∼410 HV) and ultimate tensile strength (∼1090 MPa), albeit with reduced elongation (∼5 %). In contrast, increasing the interpass dwell time and keeping the interpass temperature below the martensite finish (M_f) temperature led to predominant martensitic transformation upon solidification and cooling. Subsequent intrinsic heat treatment facilitated in situ tempering of martensite, promoting Cr-rich M₇C₃ carbide precipitation, reducing dislocation density, and increasing the effective grain size. This microstructure exhibited lower hardness (∼290 HV) and ultimate tensile strength (∼760 MPa) but improved elongation (∼14 %). By dynamically adjusting the interpass temperature and controlling intrinsic heat treatment during wire-arc directed energy deposition, locally tailored microstructures with tunable mechanical properties were successfully achieved.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 282-295"},"PeriodicalIF":6.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image-based wear state evolution and in-process recognition method for abrasive belt grinding of GH4169","authors":"Bing Chen ,&nbsp;Ran Chen ,&nbsp;Yujia Ding ,&nbsp;Junde Qi ,&nbsp;Rong Wang","doi":"10.1016/j.jmapro.2025.02.078","DOIUrl":"10.1016/j.jmapro.2025.02.078","url":null,"abstract":"<div><div>Abrasive belt wear is one of the most important factors affecting grinding quality, especially on difficult-to-machine materials such as GH4169, where belt wear is even greater. Currently, there is no unified method for quantitatively characterizing the wear state of abrasive belts. Moreover, due to the absence of a correlation between the wear degree and machining quality, it is challenging to quantitatively categorize the wear stages and offer process - oriented guidance for parameter optimization. Aiming at addressing the aforementioned issues, the image-based methodology for the evolution and in-process recognition method of the wearing status is proposed for abrasive belts grinding. First, based on the industrial robot grinding platform, the abrasive belt wear experiment is carried out, and the evolutionary process of the abrasive belt wear state of GH4169 as well as the influence law of wear on machining quality are obtained. And then, the influence of abrasive belt wear on the material removal depth has been studied. A wear area coefficient-material removal depth model is established from the perspective of microscopic abrasive particles, and the evolutionary law of grinding material removal depth with different wear area coefficients is revealed. A wear state characterization method based on material removal depth is put forward. And then, an image-based on-machine calculation method for abrasive belt wear area coefficient has been established. Finally, an image-based abrasive belt wear state recognition method for the GH4169 robotic abrasive belt grinding is achieved, and the effectiveness of the method is verified through experiments.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 237-249"},"PeriodicalIF":6.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing ultrahigh-strength aluminum alloys via TiC nanoparticle-pinning effect in friction rolling additive manufacturing","authors":"Haibin Liu ,&nbsp;Chunyang Yang ,&nbsp;Ruishan Xie ,&nbsp;Ying Chen ,&nbsp;Shujun Chen","doi":"10.1016/j.jmapro.2025.03.003","DOIUrl":"10.1016/j.jmapro.2025.03.003","url":null,"abstract":"<div><div>Friction rolling additive manufacturing (FRAM) is offers an effective approach for producing high-performance aluminum alloy parts. However, achieving ultrahigh-strength aluminum alloys is difficult owing to the softening behavior of materials during solid-phase deposition and abnormal grain growth during heat treatment. In this study, a strategy for improving the microstructure and preparing ultrahigh-strength aluminum alloys using the pinning effect of TiC nanoparticles on grain boundaries is proposed. The results show that compared with 7075‑aluminum alloy, TiC nanoparticles enhanced dynamic recrystallization during friction roll additive manufacturing, thereby reducing the deposited grain size from 3.13 to 2.60 μm and inhibiting the abnormal grain growth during heat treatment, thereby reducing the grain size from 6.05 to 3.53 μm. In addition, the addition of TiC nanoparticles promoted the precipitation and refinement of the η’-MgZn₂ phase during heat treatment. A 7075-TiC alloy prepared using this method exhibited excellent mechanical properties. After heat treatment, the tensile strength (UTS), yield strength (YS), and elongation (EL) were 626 ± 15.0 MPa, 546 ± 5.2 MPa, and 15.5 ± 0.5 %, respectively, achieving a good synergistic effect on strength and plasticity. Precipitation strengthening played a key role in enhancing the mechanical properties of the 7075-TiC alloy.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 263-281"},"PeriodicalIF":6.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}