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Acoustic emission assessment of interface cracking in thermal barrier coatings

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Acta Mechanica Sinica 2016年第2期32卷 342-348页

作者： Li Yang Zhi-chun Zhong Yi-chun Zhou Wang Zhu Zhi-Biao Zhang Can-Ying Cai chun-sheng lu Key Laboratory of Key Film Materials & Application for Equipment (Hunan Province) School of Materials Science and EngineeringXiangtan University Key Laboratory of Low Dimensional Materials & Application Technology (Ministry of Education) School of Materials Science and EngineeringXiangtan University Department of Mechanical Engineering Curtin University

In this paper,acoustic emission（AE） and digital image correlation methods were applied to monitor interface cracking in thermal barrier coatings under *** interface failure process can be identifie via its AE features,including buckling,delamination incubation and *** to the Fourier transformation of AE signals,there arefourdifferentfailuremodes：surfaceverticalcracks,opening and sliding interface cracks,and substrate *** characteristic frequency of AE signals from surface vertical cracks is 0.21 MHz,whilst that of the two types of interface cracks are 0.43 and 0.29 MHz,*** energy released of the two types of interface cracks are 0.43 and 0.29 MHz,*** on the energy released from cracking and the AE signals,a relationship is established between the interface crack length and AE parameters,which is in good agreement with experimental results.

关键词： Thermal barrier coatings Acoustic emission Interface cracking Crack type Quantitative analysis

Reliability assessment on interfacial failure of thermal barrier coatings

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Acta Mechanica Sinica 2016年第5期32卷 915-924页

作者： Jin-Wei Guo Li Yang Yi-chun Zhou Li-Min He Wang Zhu Can-Ying Cai chun-sheng lu Key Laboratory of Key Film Materials & Application for Equipment (Hunan Province) School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105China Key Laboratory of Low Dimensional Materials & Application Technology (Ministry of Education) School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105China Beijing Institute of Aeronautical Materials Beijing 100095China Department of Mechanical Engineering Curtin UniversityPerthWestern Australia 6845Australia

Thermal barrier coatings（TBCs） usually exhibit an uncertain lifetime owing to their scattering mechanical properties and severe service conditions. To consider these uncertainties, a reliability assessment method is proposed based on failure probability analysis. First, a limit state equation is established to demarcate the boundary between failure and safe regions, and then the failure probability is calculated by the integration of a probability density function in the failure area according to the first- or second-order *** is shown that the parameters related to interfacial failure follow a Weibull distribution in two types of TBC. The interfacial failure of TBCs is significantly affected by the thermal mismatch of material properties and the temperature drop in service.

关键词： Reliability assessment Thermal barrier coatings Interfacial failure

Effects of oxygen vacancies on polarization stability of barium titanate

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Science China(Physics,Mechanics & Astronomy) 2016年第3期59卷 96-99页

作者： Jun Wang Yao Gen Shen Fan Song Fu Jiu Ke Yi Long Bai chun sheng lu State Key Laboratory of Nonlinear Mechanics (LNM) Institute of Mechanics Chinese Academy of Sciences Department of Mechanical and Biomedical Engineering City University of Hong Kong School of Physics and Nuclear Energy Engineering Beihang University Department of Mechanical Engineering Curtin University

Oxygen vacancy, a kind of native point defects in ferroelectric ceramics, usually causes an increase of the dielectric loss. Based on experimental observations, it is believed that all of the oxygen vacancies are an unfavorable factor for energy saving. By using molecular dynamics simulations, we show that the increase of coercive and saturated electric fields is due to the difficulty to switch local polarization near an oxygen vacancy, and so that a ferroelectric device has to sustain the rising consumption of energy. The simulation results also uncover how oxygen vacancies influence ferroelectric properties.

关键词： ferroelectricity hysteresis oxygen vacancy molecular dynamics simulation

Determination of interfacial adhesive properties for polymeric film by blister test

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Transactions of Nonferrous Metals Society of China 2013年第10期23卷 3033-3039页

作者：王子菡马增胜周益春卢春生湘潭大学低维材料及其应用技术教育部重点实验室湘潭411105 湘潭大学材料与光电物理学院湘潭411105 科廷大学机械工程系

The interfacial adhesive properties ofpolypropylene/stainless steel were studied by the blister test. The polypropylene film with a squared free-standing window was pressured by oil from one side of film. The corresponding deformation field was observed by a digital speckle correlation method. The experimental results show that the squared film deforms and debonds from stainless steel with the increase of pressure. The debonding of the squared film in initiates from the center of edge and extends to the comer, and then the deformation of film evolves from square to circle shape. The interfacial adhesive energy of polypropylene/stainless steel is （22.60±1.55） J/m2, which is in agreement with that measured by film with a circular window.

关键词： blister test polymeric film interracial adhesive properties debonding whole-filed deformation

综合考虑尺寸和应变速率的单晶Ni_(3)Al屈服强度的理论模型

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Transactions of Nonferrous Metals Society of China 2023年第3期33卷 816-823页

作者：张志伟蔡微王军杨荣肖攀柯孚久卢春生中国科学院力学研究所非线性力学国家重点实验室北京100190 中国科学院大学工程科学学院北京100049 北京航空航天大学物理学院北京100191 School of Civil and Mechanical Engineering Curtin UniversityPerthWA 6845Australia

为了综合考虑尺寸和应变率效应对单晶延性材料屈服强度的影响,建立基于位错形核机制的理论模型。以Ni_(3)Al为例,首先,通过分子动力学模拟结果拟合出材料参数;然后,通过材料参数构建屈服强度的理论曲面;最后,用现有实验数据检验该理论... 详细信息

为了综合考虑尺寸和应变率效应对单晶延性材料屈服强度的影响,建立基于位错形核机制的理论模型。以Ni_(3)Al为例,首先,通过分子动力学模拟结果拟合出材料参数;然后,通过材料参数构建屈服强度的理论曲面;最后,用现有实验数据检验该理论模型。通过现有第三方单晶铜和金的分子动力学和实验数据对该模型进行检验。结果表明,该模型可以跨越分子动力学和实验条件之间巨大的空间和时间差异,从而得到单晶Ni_(3)Al、铜和金的可靠力学性能。

关键词：屈服强度尺寸应变速率单晶Ni_(3)Al

Single-cell transcriptomic profiling reveals ZEB1-mediated regulation in microglial subtypes and the impact of exercise on neuroinflammatory responses

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Traditional Medicine Research 2025年第2期10卷 55-64页

作者： Jin-Fang Wu Yi-sheng Chen Yu-chun Xie Department of Rehabilitation Medicine Jiangsu Province Geriatric HospitalNanjing 210024China Fujian Key Laboratory of Toxicant and Drug Toxicology Medical CollegeNingde Normal UniversityNingde 352100China Central Laboratory Jiangsu Province Geriatric HospitalNanjing 210024China

Background:This study aims to identify distinct cellular subtypes within brain tissue using single-cell transcriptomic analysis,focusing on specific biomarkers that differentiate cell types and the effects of traditional and exercise ***:Four samples were analyzed:older control(OC),older exercise(OE),younger control(YC),and younger exercise(YE).Single-cell RNA sequencing was used to distinguish cellular subtypes through their biomarker *** visualization included violin and t-SNE plots to illustrate biomarker expression across cell clusters such as oligodendrocytes,microglia,and ***,BV2 cells were exposed to amyloid-beta fragments to simulate Alzheimer’s disease,assessing the impact of exercise-induced cellular ***:Distinct cellular subtypes were identified:oligodendrocytes(MBP,St18),microglia(Dock8),and astrocytes(Aqp4,Gpc5).Sample OE was predominantly oligodendrocytes,while YE had more astrocytes,inhibitory neurons,and Canal-Retzius *** showed a significant presence of Olfm3+ganglion ***1 gene knockout revealed changes in SMAD family gene expression,which regulate *** stress levels were also ***:This profiling enhances our understanding of brain cellular functions and interactions,potentially informing targeted therapies in neurological *** may influence brain cell immune responses and cell death pathways by regulating specific gene expressions,offering new insights for treating neuroinflammation and degeneration.

关键词： single-cell transcriptomics brain tissue cellular subtypes biomarker expression neuronal diversity

The Citron homology domain of MAP4Ks improves outcomes of traumatic brain injury

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Neural Regeneration Research 2025年第11期20卷 3233-3244页

作者： Xiaoling Zhong Wenjiao Tai Meng-lu Liu Shuaipeng Ma Tianjin Shen Yuhua Zou chun-Li Zhang Department of Molecular Biology University of Texas Southwestern Medical CenterDallasTXUSA Hamon Center for Regenerative Science and Medicine University of Texas Southwestern Medical CenterDallasTXUSA Peter O’Donnell Jr.Brain Institute University of Texas Southwestern Medical CenterDallasTXUSA

The mitogen-activated protein kinase kinase kinase kinases(MAP4Ks)signaling pathway plays a pivotal role in axonal regrowth and neuronal degeneration following *** targeting this pathway is beneficial to brain injury remains *** this study,we showed that adeno-associated virus-delivery of the Citron homology domain of MAP4Ks effectively reduces traumatic brain injury-induced reactive gliosis,tauopathy,lesion size,and behavioral *** inhibition of MAP4Ks replicated the ameliorative effects observed with expression of the Citron homology ***,the Citron homology domain acted as a dominant-negative mutant,impeding MAP4K-mediated phosphorylation of the dishevelled proteins and thereby controlling the Wnt/β-catenin *** findings implicate a therapeutic potential of targeting MAP4Ks to alleviate the detrimental effects of traumatic brain injury.

关键词： adeno-associated virus Citron homology Citron homology domain gene therapy mitogen-activated protein kinase kinase kinase kinases traumatic brain injury

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城市污染土壤中磁性物质对重金属的富集作用

土壤通报 2009年第6期40卷 1421-1425页

作者：郭军玲张春梅卢升高浙江大学环境与资源学院浙江杭州310029

应用环境磁学方法监测土壤重金属污染是土壤污染研究的新途径。本研究以杭州和洛阳城市污染土壤为对象,应用磁分离技术分离污染土壤中的磁性物质。结果表明,杭州和洛阳城市土壤的磁性物质含量分别是0.20～2.75(平均值0.75%)和0.47%～3.6... 详细信息

应用环境磁学方法监测土壤重金属污染是土壤污染研究的新途径。本研究以杭州和洛阳城市污染土壤为对象,应用磁分离技术分离污染土壤中的磁性物质。结果表明,杭州和洛阳城市土壤的磁性物质含量分别是0.20～2.75(平均值0.75%)和0.47%～3.67%(平均值1.36%),土壤中磁性物质数量取决于土壤的磁化率大小和重金属污染程度。统计分析表明土壤磁性物质含量与重金属综合污染负荷指数(PLI)呈极显著相关(R2=0.531),土壤磁性物质的含量可大致反映城市土壤的重金属污染状况。城市土壤的重金属富集系数表明磁性物质对重金属有显著的富集作用,杭州和洛阳城市土壤中Fe的平均富集系数分别为20.1和15.8,土壤磁性物质对重金属的富集系数大小为Fe>Cr>Cu>Mn>Pb>Zn。土壤重金属在磁性物质中的富集作用解释了土壤磁测反映重金属污染状况的环境磁学机理。

关键词：城市土壤磁性颗粒磁分离重金属富集系数

A method to predict the peak shear strength of rock joints based on machine learning

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Journal of Mountain Science 2023年第12期20卷 3718-3731页

作者： BAN Li-ren ZHU chun HOU Yu-hang DU Wei-sheng QI Cheng-zhi lu chun-sheng School of Civil and Transportation Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China Key Laboratory of Construction and Safety of Water Engineering of the Ministry of Water Resources China Institute of Water Resources and Hydropower ResearchBeijing 100038China School of Earth Sciences and Engineering Hohai UniversityNanjing 210098China Anhui Province Key Laboratory of Building Structure and Underground Engineering Anhui Jianzhu UniversityHefei 230601China Deep Mining and Rock Burst Research Institute China Coal Research InstituteBeijing 100013China School of Civil and Mechanical Engineering Curtin UniversityWestern Australia 6845Australia

In geotechnical and tunneling engineering,accurately determining the mechanical properties of jointed rock holds great significance for project safety *** shear strength(PSS),being the paramount mechanical property of joints,has been a focal point in the research *** are limitations in the current peak shear strength(PSS)prediction models for jointed rock:(i)the models do not comprehensively consider various influencing factors,and a PSS prediction model covering seven factors has not been established,including the sampling interval of the joints,the surface roughness of the joints,the normal stress,the basic friction angle,the uniaxial tensile strength,the uniaxial compressive strength,and the joint size for coupled joints;(ii)the datasets used to train the models are relatively limited;and(iii)there is a controversy regarding whether compressive or tensile strength should be used as the strength term among the influencing *** overcome these limitations,we developed four machine learning models covering these seven influencing factors,three relying on Support Vector Regression(SVR)with different kernel functions(linear,polynomial,and Radial Basis Function(RBF))and one using deep learning(DL).Based on these seven influencing factors,we compiled a dataset comprising the outcomes of 493 published direct shear tests for the training and validation of these four *** compared the prediction performance of these four machine learning models with Tang’s and Tatone’s *** prediction errors of Tang’s and Tatone’s models are 21.8%and 17.7%,respectively,while SVR_linear is at 16.6%,SVR_poly is at 14.0%,and SVR_RBF is at 12.1%.DL outperforms the two existing models with only an 8.5%***,we performed shear tests on granite joints to validate the predictive capability of the DL-based *** the DL approach,the results suggest that uniaxial tensile strength is recommended as the material strength term in the PSS model for m

关键词： Peak shear strength Rock joints Prediction model Machine learning Deep learning