International Journal of Plasticity最新文献

{"title":"A chemo–mechanical–damage framework with finite-rate hydrogen trapping: Geometry- and rate-controlled relevance of lattice–trap kinetics","authors":"Geonjin Shin,Sang Yoon Song,Kijung Kim,Seung Chae Yoon,Seok Su Sohn,Jinheung Park,Myoung-Gyu Lee","doi":"10.1016/j.ijplas.2026.104801","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104801","url":null,"abstract":"","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"9 1","pages":"104801"},"PeriodicalIF":9.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148896050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasticity driven elemental redistribution in microstructural evolution of multicomponent Ni-based superalloys: A thermodynamic-driven multicomponent crystal plasticity phase field modeling","authors":"Zexin Wang, Chuanxin Liang, Dong Wang, Yihui Jiang, Xiangdong Ding","doi":"10.1016/j.ijplas.2026.104813","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104813","url":null,"abstract":"Elemental partitioning in multicomponent Ni-based superalloys is fundamentally governed by thermodynamic driving forces and in turn controls the kinetics of precipitate growth, coarsening and rafting under service conditions. Among these forces, elastic strain energy plays a key role in altering elemental partitioning and thus feeding back on microstructural evolution, but the contribution of plastic deformation remains insufficiently understood. Here, we employ crystal plasticity coupled phase field simulations to thoroughly examine the elemental partitioning and microstructural evolution in multicomponent Ni–Al–Cr–Mo superalloy under applied strain conditions. The results reveal a pronounced tensile-compressive asymmetry in elemental partitioning under plasticity conditions, arising from the combined effects of γ/γʹ lattice mismatch and applied strain. In addition, the partitioning behavior of Mo is reversed under compressive strain conditions due to a reduction in the elastic potential difference. Furthermore, the γʹ coarsening rate displays contrasting trends under tensile and compressive strains due to variations in the γ/γʹ lattice mismatch. These findings underscore the importance of plasticity in regulating elemental partitioning and microstructural stability in Ni-based superalloys, providing new insights for future research on creep processes and stress-assisted aging heat treatment.","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"177 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phenomenological-prior-based few-shot transfer learning for TA15 alloy constitutive modeling at high temperatures","authors":"Chengjie Guo, Dian Xu, Jinbao Li, Bo Wang, Rui Li","doi":"10.1016/j.ijplas.2026.104814","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104814","url":null,"abstract":"Accurate constitutive modeling of high-temperature alloys—represented by the TA15 alloy—is critical yet challenging due to complex thermomechanical behaviors, particularly the non-monotonic transition from strain hardening to dynamic softening. While classical phenomenological models often struggle to capture these complex evolutions, purely data-driven approaches (e.g., deep neural networks) are hindered by the expensive cost of acquiring large-scale experimental data across diverse loading conditions. To bridge this gap, this study proposes a phenomenological-prior-based transfer learning approach tailored for data-scarce environments. Instead of learning from scratch, a deep neural network is pre-trained on a synthetic dataset generated by the Johnson-Cook (JC) constitutive model to capture the priors of the plastic flow behavior by strain hardening parameters (<ce:italic>A, B, n</ce:italic>). Subsequently, the network is fine-tuned using a few-shot experimental dataset to capture the dynamic softening of TA15 alloy. To validate this approach, we conduct a series of high-temperature tensile experiments on the TA15 alloy between 450 and 800°C using high-temperature extensometers, full-field high-temperature digital image correlation measurements, and scanning electron microscopes, revealing the microstructural evolution driving the softening. We demonstrate that while the simplified JC constitutive model is incapable of describing softening, the “full model pretrain” strategy enables the network to adaptively relax rigid hardening constraints, effectively capturing the non-monotonic transition from hardening to dynamic softening. Crucially, using condition-specific hardening descriptors extracted from the early pre-peak plastic-strain interval, the learned model predicts the subsequent softening or steady-state portions at additional temperatures and under compression-type conditions. Finite element implementation via UMAT material subroutine further confirms its capability to accurately reproduce macroscopic strain localization. Results demonstrate that phenomenological-prior pretraining improves predictive fidelity and model robustness with few-shot experimental data, establishing a scalable paradigm for complex constitutive modeling.","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"52 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural Network-Based Distortional Hardening Inferred from Experiments via FE-Coupled Backpropagation: Application to Ti-6Al-4V and Third-Generation AHSS","authors":"Xueyang Li, Dirk Mohr","doi":"10.1016/j.ijplas.2026.104812","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104812","url":null,"abstract":"To learn the elasto-plastic constitutive response of metals from experiments with heterogeneous mechanical fields, we developed a finite element-coupled backpropagation algorithm that trains neural network-based plasticity models using force-displacement curves from notched tension and central-hole tension specimens. This approach enables training deep into the post-necking regime, well beyond the strain ranges accessible to standard uniaxial tests. Building on this framework, a neural network-based distortional hardening model is proposed in which a single network simultaneously predicts the flow resistance, anisotropic yield parameters, and yield function exponent of the YLD2000-3D yield locus as functions of equivalent plastic strain. This unified formulation enables continuous transition of the yield locus between sharp-cornered shapes and smooth shapes with high flexibility during deformation. The model is first pre-trained using uniaxial tension stress-strain data, after which the finite element-coupled training substantially improves predictions at large deformations. Ti-6Al-4V exhibits strong plastic anisotropy together with an unusual reversal in the orientation ranking of force-displacement responses between notched and central-hole tension specimens. The investigated third-generation advanced high-strength steel (AHSS) exhibits a hardening response that transitions from convex to concave curvature. For both materials, the proposed model accurately reproduces the large-deformation and post-necking behavior of all training experiments and successfully predicts unseen validation experiment results, including local strains and the evolution of Lankford coefficients. The proposed framework is computationally stable, efficient, and readily implementable in commercial finite element software. Moreover, the methodology is general and can be extended to arbitrary phenomenological yield functions and experimental training configurations.","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"7 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-cycle Fatigue Life Prediction of LPBF GH4169 via Crystal Plasticity: The Dominant Role of Porosity Defects","authors":"Minyang Wang, Xuewei Fang, Shahid Ghafoor, Yuan Zhou, Haonan Wu, Xuefan Guo, Naiyuan Xi, Xiaopeng Li, Ke Huang","doi":"10.1016/j.ijplas.2026.104811","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104811","url":null,"abstract":"Most GH4169 components serve in harsh environments where low-cycle fatigue (LCF) performance is critical. However, accurate LCF life prediction for laser powder bed fusion (LPBF) components remains challenging due to the complex coupling of heterogeneous microstructures and process-induced porosity defects. Existing studies routinely idealize porosity defects as simplified geometric primitives, overlooking the decisive role of its realistic morphology in damage evolution. To address this issue, the present work fabricated samples with different defect distribution patterns (lack-of-fusion (LoF) dominated and gas pore dominated) via manipulating the process parameters of LPBF. An orthogonal numerical experiment was performed to decouple the effects of defect size and morphology via crystal plasticity finite element (CPFE) method. Building on this mechanistic insight, a CPFE framework incorporating high-fidelity defect geometries was established, with stored energy density (SED) as the fatigue indicator parameter. The framework delivered accurate LCF life predictions for high-density samples across the full strain amplitude range (0.4%–1.2%). For low-density samples, prediction accuracy was maintained at low strain amplitudes (≤ 0.6%), whereas deviations occurred at high strain amplitudes (≥ 0.6%). Incorporating the actual largest defect into the RVE confirmed that insufficient sampling of extreme defects was a major cause of the observed prediction deviations. Additionally, specific continuously distributed porosity defects were found to form interconnected damage bands that accelerate microcrack coalescence. This work establishes a robust pathway for reliable LCF life prediction in LPBF GH4169 components with diverse porosity defect distribution patterns.","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"13 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 strain-gradient elastoplastic model: formulation, mixed finite element implementation and applications","authors":"Lidiia Nazarenko, Aleksandr Yu. Chirkov, Holm Altenbach","doi":"10.1016/j.ijplas.2026.104810","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104810","url":null,"abstract":"A simplified strain-gradient elastoplastic model is developed within the framework of small-strain kinematics to describe size-dependent mechanical behaviour at the micro- and sub-micrometre scales. The formulation extends classical J<ce:inf loc=\"post\">2</ce:inf> plasticity by incorporating both elastic and plastic strain gradients together with an intrinsic material length-scale parameter.","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"9 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2026-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dislocation-mediated three-directional ε-lath network enabled excellent cryogenic strain hardening in a warm-rolled Fe49.8Mn30Co10Cr10C0.2 medium-entropy alloy","authors":"Jiehua Chen, Xianya Tang, Binjun Wang, Xiaoshuai Jia, Yi Luo, Yu Li","doi":"10.1016/j.ijplas.2026.104809","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104809","url":null,"abstract":"Metastable ferrous medium/high-entropy alloys (MEAs/HEAs) suffer from a strength-ductility trade-off, especially at cryogenic temperatures. To address this, the study tailored dislocation substructures in a Fe<ce:inf loc=\"post\">49.8</ce:inf>Mn<ce:inf loc=\"post\">30</ce:inf>Co<ce:inf loc=\"post\">10</ce:inf>Cr<ce:inf loc=\"post\">10</ce:inf>C<ce:inf loc=\"post\">0.2</ce:inf> MEA via warm rolling (WR) at 600°C with reductions of 30%, 50% and 70% (designated as WR30, WR50 and WR70). Experimental and molecular dynamics (MD) simulations revealed that WR induced a strain-dependent evolution: incidental dislocation boundaries (IDBs) formed via Lomer-Cottrell-like reactions of Shockley partial dislocations, which transitioned to dense IDB/low-angle grain boundary (LAGB) mixtures with increasing deformation. The ε-phase fraction changed as 25.6% (WR30) → 33.8% (WR50) → 24.1% (WR70), with WR70 exhibiting a bimodal morphology. Although the enhancement of tensile properties at room temperature (RT) was limited with increasing WR reduction, both strength and ductility improved simultaneously and significantly at liquid nitrogen temperature (LNT): WR30 showed inferior performance (yield strength YS ∼482 MPa, ultimate tensile strength UTS ∼1300 MPa, low total elongation TEL, ∼25%) due to sparse IDBs and early transformation saturation of single-orientation coarse ε-phases, leading to severe strain concentration. WR50 represented an intermediate state, with a moderate strength-ductility combination and the emergence of ε-laths along two distinct orientations. Notably, WR70 exhibited an exceptional combination of YS (∼640 MPa), UTS (∼2000 MPa), strain hardening rate (SHR, ∼5 GPa) and TEL (∼60%)—outperforming most reported Fe-based MEAs/HEAs. This synergy originates from: (1) IDB/LAGB-mediated forest hardening; (2) sustained transformation-induced plasticity (TRIP) via continuous and abundant nucleation of three-directional ε-laths; (3) strain dispersion by the three-dimensional network of ε-laths. This work highlights the role of dislocation engineering in designing high-performance cryogenic structural alloys.","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"9 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148885550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequential reorientation-to-twinning plasticity for sustained work hardening in high-strength dual-phase α′/α titanium alloys","authors":"Tao Chen, Duhua Yang, Yujing Liu, Yusi Li, Qizhi Hou, Dong Qiu, Chao Yang, Shuzhi Zhang, Junsong Zhang, Xinyu Zhang","doi":"10.1016/j.ijplas.2026.104805","DOIUrl":"https://doi.org/10.1016/j.ijplas.2026.104805","url":null,"abstract":"Titanium alloys face a persistent strength–hardening trade-off: alloys exhibiting substantial work hardening (&gt;2 GPa) typically yield below 800 MPa, whereas alloys with yield strengths above 1 GPa commonly show limited hardening (&lt;2 GPa). Here, we demonstrate that this dilemma can be overcome in a dual-phase α′/α titanium alloy by activating sequential reorientation-to-twinning plasticity in metastable α′ martensite. In the Ti-6Al-7Nb-20Zr alloy containing 17 vol.% metastable HCP α′ martensite, a peak work hardening rate of approximately 8 GPa and a large work hardening ability of 384 MPa were achieved together with a high yield strength of 1063 MPa, placing it among the top-performing titanium alloys in terms of strength–hardening synergy. Strain dependent microstructure analyses suggested that the initial multivariant α′ martensite first underwent stress-induced variant reorientation, producing reoriented near-single-variant α′ domains. These domains then continue to accommodate plasticity through post-reorientation {10<mml:math altimg=\"si1.svg\"><mml:mover accent=\"true\"><mml:mn>1</mml:mn><mml:mo>¯</mml:mo></mml:mover></mml:math>1} twinning, twin/dislocation co-deformation, and secondary twinning within primary twins. The twinning-related stages were associated with a major hardening contribution beyond the initial reorientation stage. Meanwhile, the continuous α<ce:inf loc=\"post\">p</ce:inf> served as the primary load-bearing constituent, while the different behaviors of deformation between α<ce:inf loc=\"post\">p</ce:inf> and α′ promotes interfacial dislocation accumulation and back-stress strengthening. First-principles calculations supported the metastability of α′ and its propensity for reorientation-to-twinning plasticity. These results identify reorientation-to-twinning plasticity as a novel mechanism for achieving gigapascal-level yield strength together with sustained work hardening in α′/α titanium alloys.","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"3 1","pages":""},"PeriodicalIF":9.8,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148852746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microstructural origins of enhanced creep resistance in laser printed Ti-6Al-4V","authors":"Zhun Liang ,&nbsp;Mingyang Zhang ,&nbsp;Zheng Guo ,&nbsp;Zongchang Guo ,&nbsp;Yinan Cui","doi":"10.1016/j.ijplas.2026.104637","DOIUrl":"10.1016/j.ijplas.2026.104637","url":null,"abstract":"<div><div>Creep resistance is critical for the reliability of engineering structures at high temperatures. In this study, <em>in situ</em> scanning electron microscope (SEM) creep experiments show that laser powder bed fusion fabricated Ti-6Al-4V (LPBF Ti-6Al-4V) exhibits a creep lifetime about three to five times longer than that of forged Ti-6Al-4V. Distinct creep failure mechanisms were identified, with grain boundary sliding dominating in the forged Ti-6Al-4V, while void-induced grain boundary separation controlled the LPBF Ti-6Al-4V. By integrating experiments with a multiphysics coupled microscale creep model that simultaneously captures diffusion creep, dislocation glide and climb, grain boundary sliding, and void evolution, the results suggest that the elongated grain morphology and lower dislocation density in LPBF Ti-6Al-4V contribute to its enhanced creep performance. A physics-informed neural network (PINN)-driven multiscale creep framework is developed to bridge the gap between the mechanistic microscale creep model and macroscale creep life prediction. This work provides new insights into the creep resistance of additively manufactured titanium alloys and presents a promising approach for multiscale creep life assessment.</div></div>","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"199 ","pages":"Article 104637"},"PeriodicalIF":12.8,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146116217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microstructure-induced fatigue scatter of additively manufactured inconel 718: Insight from multilevel simulations and dislocation-based strain gradient crystal plasticity","authors":"Xian-Chen Kuang ,&nbsp;Wu-Gui Jiang ,&nbsp;Long-Hui Mao ,&nbsp;Zhi-Kai Wu ,&nbsp;Fen-Cheng Liu ,&nbsp;Xiang Zhou ,&nbsp;Peng-Hang Ling ,&nbsp;Yang-Cheng Zhang ,&nbsp;Min Yi","doi":"10.1016/j.ijplas.2026.104632","DOIUrl":"10.1016/j.ijplas.2026.104632","url":null,"abstract":"<div><div>The fatigue performance of additively manufactured (AM) Inconel 718 is intrinsically governed by its grain morphology, necessitating a predictive understanding of the underlying plasticity-dominated mechanisms. To address this challenge, this study applies an integrated multilevel computational framework that explicitly bridges the process–structure–property–performance chain by coupling finite-element and cellular-automata (FE–CA) simulations of grain growth during laser powder bed fusion (LPBF), a deep neural network (DNN) for efficient material parameter calibration, and a strain-gradient crystal plasticity finite element (CPFE) model for fatigue life prediction. This unified framework enables, for the first time, a rigorous like-for-like comparison of three characteristic AM microstructures—equiaxed, columnar, and mixed grains—under a consistent computational and experimental calibration protocol, and thereby reveals new micromechanical insights into potential fatigue damage initiation from the plasticity perspective. Our simulations indicate that fatigue resistance is predominantly controlled by grain morphology and further modulated by morphology-induced anisotropy. Among them, equiaxed grains exhibit superior fatigue resistance to columnar and mixed grain morphologies, which is attributed to the activation of multiple slip systems and the resulting homogeneous deformation. In contrast, the strong texture in columnar grains gives rise to a pronounced “channeling effect”, leading to highly localized slip and a mismatch between regions of elevated plastic strain and actual damage accumulation. In terms of loading direction, the fatigue resistance under loading along the building direction (BD) is higher than that under loading along the transverse direction (TD). Crack initiation is predominantly predicted at high-angle grain boundaries and triple junctions, with the specific patterns highly sensitive to both grain morphology and loading direction. A key finding is the identification of a critical fatigue indicator parameter (FIP) threshold, beyond which fatigue life scatter intensifies significantly. While the CPFE model provides accurate predictions at intermediate strain amplitudes, its efficacy diminishes at higher strains due to the activation of alternative failure mechanisms. Overall, by integrating established computational methods, this work provides microstructure-sensitive insights and a practical framework for fatigue life prediction of AM materials, offering a potential pathway for AM process and microstructure optimization to achieve superior fatigue performance.</div></div>","PeriodicalId":340,"journal":{"name":"International Journal of Plasticity","volume":"198 ","pages":"Article 104632"},"PeriodicalIF":12.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146101602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}