Hot carrier effects of p MOSFETs with different oxide thicknesses are studied in low gate voltage range.All electrical parameters follow a power law relationship with stress time,but degradation slope is dependent ...Hot carrier effects of p MOSFETs with different oxide thicknesses are studied in low gate voltage range.All electrical parameters follow a power law relationship with stress time,but degradation slope is dependent on gate voltage.For the devices with thicker oxides,saturated drain current degradation has a close relationship with the product of gate current and electron fluence.For small dimensional devices,saturated drain current degradation has a close relationship with the electron fluence.This degradation model is valid for p MOSFETs with 0 25μm channel length and different gate oxide thicknesses.展开更多
A degradation model with a random failure threshold is presented for the assessment of reliability by the Bayesian approach. This model is different from others in that the degradation process is proceeding under pre-...A degradation model with a random failure threshold is presented for the assessment of reliability by the Bayesian approach. This model is different from others in that the degradation process is proceeding under pre-specified periodical calibrations. And here a random threshold distribution instead of a constant threshold which is difficult to determine in practice is used. The system reliability is defined as the probability that the degradation signals do not exceed the random threshold. Based on the posterior distribution estimates of degradation performance, two models for Bayesian reliability assessments are presented in terms of the degradation performance and the distribution of random failure threshold. The methods proposed in this paper are very useful and practical for multi-stage system with uncertain failure threshold. This study perfects the degradation modeling approaches and plays an important role in the remaining useful life estimation and maintenance decision making.展开更多
The major concern of this article is to address the shortcoming and outgoing effects of the human activities on the landscape patterns and their consequences in the Sefidrood River watershed in Iran. A flow of data in...The major concern of this article is to address the shortcoming and outgoing effects of the human activities on the landscape patterns and their consequences in the Sefidrood River watershed in Iran. A flow of data includes three inputs; each of them belongs to one part of three zones of a fluvial system. The three parts of the Sefidrood River fluvial system include Zone 1,a sub-watershed as degradation modeling site,Zone 2,Sefidrood Dam as dam site,and Zone 3,17km away from the Sefidrood River path to the Caspian Sea as ending point site. The degradation model in the Zone 1 provides a suitable mean for decision support system to decrease the human impacts on each small district. The maximum number for degradation coefficient belongs to the small district with the highest physiographic density,relatively cumulative activities,and a lower figure for the habitat vulnerability. The human degradation impact were not limited to the upstream. The investigation to the Sefidrood Dam and ending point of the Sefidrood River depicts that sedimentation continues as a significant visual impact in the Sefidrood Dam reservoir and the estuary.展开更多
Distribution-based degradation models （or graphical approach in some literature） occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideratio...Distribution-based degradation models （or graphical approach in some literature） occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideration. A validation methodology for distribution-based models is proposed in this paper. Since the model can be expressed as consisting of assumptions of model structures and embedded model parameters, the proposed methodology carries out the validation from these two aspects. By using appropriate statistical techniques, the rationality of degradation distributions, suitability of fitted models and validity of degradation models are validated respectively. A new statistical technique based on control limits is also proposed, which can be implemented in the validation of degradation models＇ validity. The case study on degradation modeling of an actual accelerometer shows that the proposed methodology is an effective solution to the validation problem of distribution-based de qradation models.展开更多
A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images.Some ETM+panchromatic and multispectral images are used to assess the new method.Its ...A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images.Some ETM+panchromatic and multispectral images are used to assess the new method.Its spatial and spectral effects are evaluated by qualitative and quantitative measures and the results are compared with those of IHS,PCA,Brovey,OWT(Orthogonal Wavelet Transform)and RWT(Redundant Wavelet Transform).The results show that the new method can keep almost the same spatial resolution as the panchromatic images,and the spectral effect of the new method is as good as those of wavelet-based methods.展开更多
Modern highly reliable products may have two or more quality characteristics(QCs) because of their complex structures and abundant functions. Relations between the QCs should be considered when assessing the reliabili...Modern highly reliable products may have two or more quality characteristics(QCs) because of their complex structures and abundant functions. Relations between the QCs should be considered when assessing the reliability of these products. This paper conducts a Bayesian analysis for a bivariate constant-stress accelerated degradation model based on the inverse Gaussian(IG) process. We assume that the product considered has two QCs and each of the QCs is governed by an IG process. The relationship between the QCs is described by a Frank copula function. We also assume that the stress on the products affects not only the parameters of the IG processes, but also the parameter of the Frank copula function. The Bayesian MCMC method is developed to calculate the maximum likelihood estimators(MLE) of the model parameters. The reliability function and the mean-time-to-failure(MTTF) are estimated through the calculation of the posterior samples. Finally, a simulation example is presented to illustrate the proposed bivariate constant-stress accelerated degradation model.展开更多
With more and more attention on degradation process, we need the degradation model to be accurate all over the time rather than only at some specific moments. However, the traditional validation metric only estimates ...With more and more attention on degradation process, we need the degradation model to be accurate all over the time rather than only at some specific moments. However, the traditional validation metric only estimates difference of static features. A validation method proposed in this paper uses hypothesis testing to identify whether the distributions of experimental measurements and simulation results are consistent. Then, based on the deviation between sample means, a global validation metric which reflects the difference of degradation process between computational model and physical system all over the service time is derived from the statistics of deviation between sample means. Furthermore, curve fit method for discrete experimental measurements is introduced. The case of electro-hydraulic servo valve is studied, and the results show that the proposed validation metric is appropriate for the validation of degradation model with dynamic performance output.展开更多
In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testin...In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testing of a blade.A novel non-linear fatigue damage accumulation model is proposed using the damage assessment theories of composite laminates for the first time.Then,a stiffness degradation model is established based on the correlation of fatigue damage and residual stiffness of the composite laminates.Finally,a stiffness degradation model for the blade is presented based on the full-scale fatigue testing.The scientific rationale of the proposed stiffness model of blade is verified by using full-scale fatigue test data of blade with a total length of 52.5 m.The results indicate that the proposed stiffness degradation model of the blade agrees well with the fatigue testing results of this blade.This work provides a basis for evaluating the fatigue damage and lifetime of blade under cyclic fatigue loading.展开更多
Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to in...Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to inherent fluctuations,limited data and imperfect measurements resulting in aleatory,epistemic and measurement uncertainties of the degradation process.This paper proposes a degradation model and remaining useful life(RUL)prediction method under triple uncertainties for a category of complex equipment with multi-phase degradation and jumps.First,a multi-phase degradation model with random jumps and measurement errors is constructed based on uncertain random processes.Afterward,the analytic expression of RUL prediction considering the heterogeneity is derived by modeling the uncertainty of degradation states at change points under the concept of first hitting time.A stochastic uncertain approach is utilized for the proposed multi-phase degradation model to identify model parameters based on historical data.Furthermore,the implied degradation features are adaptively updated in online stage using similarity-based weighted stochastic uncertain maximum likelihood estimation and Kalman filtering.Finally,the effectiveness of the method is verified by simulation example and practical case.展开更多
Electrolysis is expected to play an essential role in future energy systems that rely on renewable energy sources,especially in achieving climate neutrality in sectors that are challenging to electrify directly.The ec...Electrolysis is expected to play an essential role in future energy systems that rely on renewable energy sources,especially in achieving climate neutrality in sectors that are challenging to electrify directly.The economic success of this technology is largely dependent on effective predictive maintenance,which requires a clear understanding of the systems’current and future state-of-health to ensure adequate replacement planning with decreasing efficiency and prevent undesired aging-related failures.Given the incomplete physical understanding and mathematical description of degradation processes,while more and more data is becoming available,data-driven machine learning models are increasingly moving into focus.These models can learn underlying relationships from data without necessitating prior knowledge.Therefore,this study concentrates on predicting the degradation trend of a proton exchange membrane water electrolysis cell using a data-driven machine learning approach.To this end,a comprehensive data-driven modeling matrix is proposed and evaluated through selected practically relevant modeling concepts,which are characterized by different combinations of available training data and desired model outputs.Experimentally,this is facilitated by a targeted accelerated stress test consisting of operating and characterization phases.The applied machine learning pipeline,covering the hierarchical sequence of necessary data preprocessing and modeling steps,is presented in detail to ensure the traceability and reproducibility of the methodology from data collection to model testing and evaluation.As a major finding,it was demonstrated that the degradation trend prediction for the entire polarization curve can be realized using only typical operating data.This represents an initial step toward predicting the complete cell characteristic without interrupting ongoing operation for corresponding measurements.展开更多
This paper proposes an objective Bayesian method to study the degradation model with respect to a Wiener process.The Jeffreys prior and reference prior for the parameters are derived,and the propriety of the posterior...This paper proposes an objective Bayesian method to study the degradation model with respect to a Wiener process.The Jeffreys prior and reference prior for the parameters are derived,and the propriety of the posteriors under these priors is validated.Two sampling algorithms are introduced to compute the posteriors.A simulation study is conducted to investigate the performance of the objective Bayesian procedure.Finally,the authors apply the approach to a degradation data.展开更多
Planting trees was used as one of cost-effective measures for desertification control in add and semi-add areas of China. Woodland degradation, however, is becoming an inevitable issue in these areas. In this paper, a...Planting trees was used as one of cost-effective measures for desertification control in add and semi-add areas of China. Woodland degradation, however, is becoming an inevitable issue in these areas. In this paper, a typical county, Ejin Holo County, Inner Mongolia, China was selected for its assessment of artificial woodland degradation. A conceptual model for woodland degradation was delineated qualitatively based on field sampling survey, and four model-based indicators as humidity index （HI）, vegetation index （NDVI）, soil type （ST） and soil erosion modulus （EM） were screened out and used to a GIS-based method for artificial woodland degradation assessment in this semi-add agro-pastoral transitional area. All the indicator layers were overlaid and desertification assessed using simplified equation with equal weights for each indicators. The assessment results showed that in 336. 09 km^2 of total woodland area, 311.35 km^2 woodland were under degradation, and the area for slight, medium, severe degradation was 78.97, 119.73 and 112.65 km^2, respectively. It was suggested that much attention should be paid on woodland improvement and plant species selection, especially shrub species, before revegetation in similar areas.展开更多
The Wiener process as a degradation model plays an important role in the degradation analysis.In this paper, we propose an objective Bayesian analysis for an acceleration degradation Wienermodel which is subjected to ...The Wiener process as a degradation model plays an important role in the degradation analysis.In this paper, we propose an objective Bayesian analysis for an acceleration degradation Wienermodel which is subjected to measurement errors. The Jeffreys prior and reference priors underdifferent group orderings are first derived, the propriety of the posteriors is then validated. It isshown that two of the reference priors can yield proper posteriors while the others cannot. A simulation study is carried out to investigate the frequentist performance of the approach comparedto the maximum likelihood method. Finally, the approach is applied to analyse a real data.展开更多
Biomimetic scaffolds provide a suitable growth environment for tissue engineering and demonstrate good potential for application in biomedical fields.Different-sized copolymerized biomimetic scaffolds degrade differen...Biomimetic scaffolds provide a suitable growth environment for tissue engineering and demonstrate good potential for application in biomedical fields.Different-sized copolymerized biomimetic scaffolds degrade differently,and the degradation rate is affected by the copolymerization ratio.The study of the degradation property is the foundational research necessary for realizing individualized biomimetic scaffold design.The degradation performance of polyesters with different copolymerization ratios has been widely reported;however,the modeling of this performance has been rarely reported.In this research,the degradation of copolymers was studied with multi-scale modeling,in which the copolymers were dispersed in a cellular manner,the chain break time was simulated,and the chain selection was based on the Monte Carlo(MC)algorithm.The probability model of the copolymer's chain break position was established as a//roulette,/model,whose probability values were estimated by the calculation of the potential energy difference at different chain break positions by molecular dynamics that determined the position of chain shear,thereby fully realizing the simulation of the chain micro-break process.The diffusion of the oligomers was then calculated using the macro diffusion equation,and the degradation process of the copolymer was simulated by three-scale coupling calculations.The calculation results were in good agreement with the experimental data,demonstrating the effectiveness of the proposed method.展开更多
Background:Mg alloys have attractive properties,including biocompatibility,biodegradability,and ideal mechanical properties.Moreover,Mg alloys are regarded as one of the promising candidates for manufacturing ureteral...Background:Mg alloys have attractive properties,including biocompatibility,biodegradability,and ideal mechanical properties.Moreover,Mg alloys are regarded as one of the promising candidates for manufacturing ureteral stents.This study proposed a multi-objective optimization method based on the Kriging surrogate model,NSGA-III,and finite element analysis to improve the degradation performance of Mg alloy ureteral stents.Methods:The finite element model for the degradation of Mg alloy ureteral stents has been established to compare the degradation performance of the stents under different parameters.Latin hypercube sampling was adopted to generate train sample points in the design space.Meanwhile,the Kriging surrogate model was constructed between strut parameters and stent degradation behavior.The NSGA-III was utilized to determine the optimal solution in the global design space.Results:The optimized stent achieved 5.52degradation uniformity(M),10degradation time(DT),and 4work time(FT).The errors between the Kriging surrogate model and the finite element calculation results were less than 6%.Conclusion:The optimized stent achieved better degradation performance.The degradation behavior of stents was dependent on the design parameters.The multi-objective optimization method based on the Kriging surrogate model and finite element analysis was effective in stent design optimization problems.展开更多
An improved hot carrier injection （HCI） degradation model was proposed based on interface trap generation and oxide charge injection theory. It was evident that the degradation behavior of electric parameters such a...An improved hot carrier injection （HCI） degradation model was proposed based on interface trap generation and oxide charge injection theory. It was evident that the degradation behavior of electric parameters such as Idlin, Idsat, Gm and Vt fitted well with this model. Devices were prepared with 0.35μm technology and different LDD processes. Idlin and Idsat after HCI stress were analyzed with the improved model. The effects of interface trap generation and oxide charge injection on device degradation were extracted, and the charge injection site could be obtained by this method. The work provides important information to device designers and process engineers.展开更多
This paper presents a multi-scale experimental investigation of the weathering degradation of red mudstone.Natural rocks were extracted from the surface ground to 120 m,inwhich three sets of samples were selected to c...This paper presents a multi-scale experimental investigation of the weathering degradation of red mudstone.Natural rocks were extracted from the surface ground to 120 m,inwhich three sets of samples were selected to consider the different initial rock fabrics.The long-term relative humidity(RH)cycles under two amplitudes were imposed on red mudstone to simulate the weathering process.After RH cycles,a series of uniaxial compression tests,Brazilian splitting tests and bender-extender element tests were carried out to examine the reduction in strength and stiffness.The objective of this study is to develop an extended stress-volume framework characterizing the degradation of natural red mudstone both at microscale and macroscale.Accompanied by the irreversible swelling of the rock specimen is the progressive degradation of strength,stiffness and Poisson's ratio.A unified exponential degradation model in terms of the irreversible volumetric strain was thus proposed to capture such a degradation pattern.The effect of the initial rock fabric was evident.The highest degradation rate and potential were identified in slightly weathered specimens.Significant slaking of aggregates and crack propagation were confirmed by scanning electron microscope(SEM)micrographs,which were considered as the main consequence of structure damage leading to degradation of mechanical properties.The structure damage during RH cycles denoted the hysteresis nature in the response to the cycling hydraulic reaction,in turn causing the increase in volumetric strain.Thus,the stress-volume relation rather than the suction relation was found in more reasonable agreement with the experimental results.展开更多
Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferome...Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferometric imaging faces the impact of multi-stage degradation. Most exsiting interferometric spectrum reconstruction methods are based on tradition model-based framework with multiple steps, showing poor efficiency and restricted performance. Thus, we propose an interferometric spectrum reconstruction method based on degradation synthesis and deep learning.Firstly, based on imaging mechanism, we proposed an mathematical model of interferometric imaging to analyse the degradation components as noises and trends during imaging. The model consists of three stages, namely instrument degradation, sensing degradation, and signal-independent degradation process. Then, we designed calibration-based method to estimate parameters in the model, of which the results are used for synthesizing realistic dataset for learning-based algorithms.In addition, we proposed a dual-stage interferogram spectrum reconstruction framework, which supports pre-training and integration of denoising DNNs. Experiments exhibits the reliability of our degradation model and synthesized data, and the effectiveness of the proposed reconstruction method.展开更多
The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain deg...The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.展开更多
The redistribution of three-dimensional(3D)geostress during underground tunnel excavation can easily induce to shear failure along rockmass structural plane,potentially resulting in engineering disasters.However,the c...The redistribution of three-dimensional(3D)geostress during underground tunnel excavation can easily induce to shear failure along rockmass structural plane,potentially resulting in engineering disasters.However,the current understanding of rockmass shear behavior is mainly based on shear tests under2D stress without lateral stress,the shear fracture under 3D stress is unclear,and the relevant 3D shear fracture theory research is deficient.Therefore,this study conducted true triaxial cyclic loading and unloading shear tests on intact and bedded limestone under different normal stress σ_(n) and lateral stressσ_(p)to investigate the shear strength,deformation,and failure characteristics.The results indicate that under differentσ_(n)and σ_(p),the stress–strain hysteresis loop area gradually increases from nearly zero in the pre-peak stage,becomes most significant in the post-peak stage,and then becomes very small in the residual stage as the number of shear test cycles increases.The shear peak strength and failure surface roughness almost linearly increase with the increase inσ_(n),while they first increase and then gradually decrease asσ_(p)increases,with the maximum increases of 12.9%for strength and 15.1%for roughness.The shear residual strength almost linearly increases withσ_(n),but shows no significant change withσ_(p).Based on the acoustic emission characteristic parameters during the test process,the shear fracture process and microscopic failure mechanism were analyzed.As the shear stressτincreases,the acoustic emission activity,main frequency,and amplitude gradually increase,showing a significant rise during the cycle near the peak strength,while remaining almost unchanged in the residual stage.The true triaxial shear fracture process presents tensile-shear mixture failure characteristics dominated by microscopic tensile failure.Based on the test results,a 3D shear strength criterion considering the lateral stress effect was proposed,and the determination methods and evolution of the shear modulus G,cohesion c_(jp),friction angleφ_(jp),and dilation angleψjpduring rockmass shear fracture process were studied.Under differentσ_(n)andσ_(p),G first rapidly decreases and then tends to stabilize;cjp,φ_(jp),andψjpfirst increase rapidly to the maximum value,then decrease slowly,and finally remain basically unchanged.A 3D shear mechanics model considering the effects of lateral stress and shear parameter degradation was further established,and a corresponding numerical calculation program was developed based on3D discrete element software.The proposed model effectively simulates the shear failure evolution process of rockmass under true triaxial shear test,and is further applied to successfully reveal the failure characteristics of surrounding rocks with structural planes under different combinations of tunnel axis and geostress direction.展开更多
文摘Hot carrier effects of p MOSFETs with different oxide thicknesses are studied in low gate voltage range.All electrical parameters follow a power law relationship with stress time,but degradation slope is dependent on gate voltage.For the devices with thicker oxides,saturated drain current degradation has a close relationship with the product of gate current and electron fluence.For small dimensional devices,saturated drain current degradation has a close relationship with the electron fluence.This degradation model is valid for p MOSFETs with 0 25μm channel length and different gate oxide thicknesses.
基金the National Natural Science Foundation of China(No.71371031)
文摘A degradation model with a random failure threshold is presented for the assessment of reliability by the Bayesian approach. This model is different from others in that the degradation process is proceeding under pre-specified periodical calibrations. And here a random threshold distribution instead of a constant threshold which is difficult to determine in practice is used. The system reliability is defined as the probability that the degradation signals do not exceed the random threshold. Based on the posterior distribution estimates of degradation performance, two models for Bayesian reliability assessments are presented in terms of the degradation performance and the distribution of random failure threshold. The methods proposed in this paper are very useful and practical for multi-stage system with uncertain failure threshold. This study perfects the degradation modeling approaches and plays an important role in the remaining useful life estimation and maintenance decision making.
文摘The major concern of this article is to address the shortcoming and outgoing effects of the human activities on the landscape patterns and their consequences in the Sefidrood River watershed in Iran. A flow of data includes three inputs; each of them belongs to one part of three zones of a fluvial system. The three parts of the Sefidrood River fluvial system include Zone 1,a sub-watershed as degradation modeling site,Zone 2,Sefidrood Dam as dam site,and Zone 3,17km away from the Sefidrood River path to the Caspian Sea as ending point site. The degradation model in the Zone 1 provides a suitable mean for decision support system to decrease the human impacts on each small district. The maximum number for degradation coefficient belongs to the small district with the highest physiographic density,relatively cumulative activities,and a lower figure for the habitat vulnerability. The human degradation impact were not limited to the upstream. The investigation to the Sefidrood Dam and ending point of the Sefidrood River depicts that sedimentation continues as a significant visual impact in the Sefidrood Dam reservoir and the estuary.
文摘Distribution-based degradation models （or graphical approach in some literature） occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideration. A validation methodology for distribution-based models is proposed in this paper. Since the model can be expressed as consisting of assumptions of model structures and embedded model parameters, the proposed methodology carries out the validation from these two aspects. By using appropriate statistical techniques, the rationality of degradation distributions, suitability of fitted models and validity of degradation models are validated respectively. A new statistical technique based on control limits is also proposed, which can be implemented in the validation of degradation models＇ validity. The case study on degradation modeling of an actual accelerometer shows that the proposed methodology is an effective solution to the validation problem of distribution-based de qradation models.
文摘A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images.Some ETM+panchromatic and multispectral images are used to assess the new method.Its spatial and spectral effects are evaluated by qualitative and quantitative measures and the results are compared with those of IHS,PCA,Brovey,OWT(Orthogonal Wavelet Transform)and RWT(Redundant Wavelet Transform).The results show that the new method can keep almost the same spatial resolution as the panchromatic images,and the spectral effect of the new method is as good as those of wavelet-based methods.
基金the National Natural Science Foundation of China(No.11671080)the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence(No.BM2017002)
文摘Modern highly reliable products may have two or more quality characteristics(QCs) because of their complex structures and abundant functions. Relations between the QCs should be considered when assessing the reliability of these products. This paper conducts a Bayesian analysis for a bivariate constant-stress accelerated degradation model based on the inverse Gaussian(IG) process. We assume that the product considered has two QCs and each of the QCs is governed by an IG process. The relationship between the QCs is described by a Frank copula function. We also assume that the stress on the products affects not only the parameters of the IG processes, but also the parameter of the Frank copula function. The Bayesian MCMC method is developed to calculate the maximum likelihood estimators(MLE) of the model parameters. The reliability function and the mean-time-to-failure(MTTF) are estimated through the calculation of the posterior samples. Finally, a simulation example is presented to illustrate the proposed bivariate constant-stress accelerated degradation model.
基金the National Natural Science Foundation of China(No.61304218)the Beijing Higher Education Young Elite Teacher Project(No.YETP1123)
文摘With more and more attention on degradation process, we need the degradation model to be accurate all over the time rather than only at some specific moments. However, the traditional validation metric only estimates difference of static features. A validation method proposed in this paper uses hypothesis testing to identify whether the distributions of experimental measurements and simulation results are consistent. Then, based on the deviation between sample means, a global validation metric which reflects the difference of degradation process between computational model and physical system all over the service time is derived from the statistics of deviation between sample means. Furthermore, curve fit method for discrete experimental measurements is introduced. The case of electro-hydraulic servo valve is studied, and the results show that the proposed validation metric is appropriate for the validation of degradation model with dynamic performance output.
基金supported by the Science and Technology Programs of Gansu Province,China(Nos.21JR1RA248,20JR10RA264)the Young Scholars Science Foundation of Lanzhou Jiaotong University,China(Nos.2020039,2020017)the Special Funds for Guiding Local Scientific and Technological Development by the Central Government,China(No.22ZY1QA005)。
文摘In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testing of a blade.A novel non-linear fatigue damage accumulation model is proposed using the damage assessment theories of composite laminates for the first time.Then,a stiffness degradation model is established based on the correlation of fatigue damage and residual stiffness of the composite laminates.Finally,a stiffness degradation model for the blade is presented based on the full-scale fatigue testing.The scientific rationale of the proposed stiffness model of blade is verified by using full-scale fatigue test data of blade with a total length of 52.5 m.The results indicate that the proposed stiffness degradation model of the blade agrees well with the fatigue testing results of this blade.This work provides a basis for evaluating the fatigue damage and lifetime of blade under cyclic fatigue loading.
基金supported by the National Key Research and Development Program of China(2021YFB3301200)the National Natural Science Foundation of China(NSFC)(U21A20483,62373040,62203042).
文摘Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to inherent fluctuations,limited data and imperfect measurements resulting in aleatory,epistemic and measurement uncertainties of the degradation process.This paper proposes a degradation model and remaining useful life(RUL)prediction method under triple uncertainties for a category of complex equipment with multi-phase degradation and jumps.First,a multi-phase degradation model with random jumps and measurement errors is constructed based on uncertain random processes.Afterward,the analytic expression of RUL prediction considering the heterogeneity is derived by modeling the uncertainty of degradation states at change points under the concept of first hitting time.A stochastic uncertain approach is utilized for the proposed multi-phase degradation model to identify model parameters based on historical data.Furthermore,the implied degradation features are adaptively updated in online stage using similarity-based weighted stochastic uncertain maximum likelihood estimation and Kalman filtering.Finally,the effectiveness of the method is verified by simulation example and practical case.
基金financial support by the Federal Ministry of Education and Research of Germany in the frame-work of SEGIWA(grant no.03HY121G)HyThroughGen(grant no.3HY108C)as part of the hydrogen flagship project H2Giga.
文摘Electrolysis is expected to play an essential role in future energy systems that rely on renewable energy sources,especially in achieving climate neutrality in sectors that are challenging to electrify directly.The economic success of this technology is largely dependent on effective predictive maintenance,which requires a clear understanding of the systems’current and future state-of-health to ensure adequate replacement planning with decreasing efficiency and prevent undesired aging-related failures.Given the incomplete physical understanding and mathematical description of degradation processes,while more and more data is becoming available,data-driven machine learning models are increasingly moving into focus.These models can learn underlying relationships from data without necessitating prior knowledge.Therefore,this study concentrates on predicting the degradation trend of a proton exchange membrane water electrolysis cell using a data-driven machine learning approach.To this end,a comprehensive data-driven modeling matrix is proposed and evaluated through selected practically relevant modeling concepts,which are characterized by different combinations of available training data and desired model outputs.Experimentally,this is facilitated by a targeted accelerated stress test consisting of operating and characterization phases.The applied machine learning pipeline,covering the hierarchical sequence of necessary data preprocessing and modeling steps,is presented in detail to ensure the traceability and reproducibility of the methodology from data collection to model testing and evaluation.As a major finding,it was demonstrated that the degradation trend prediction for the entire polarization curve can be realized using only typical operating data.This represents an initial step toward predicting the complete cell characteristic without interrupting ongoing operation for corresponding measurements.
基金supported by the National Natural Science Foundation of China under Grant Nos.11201005,11526070 and 11601008the Project of National Bureau of Statistics under Grant No.2013LZ17+1 种基金the Project of Anhui Educational Committee under Grant No.gxfx ZD2016015the Natural Science Foundation of Anhui Province under Grant No.1408085MA07
文摘This paper proposes an objective Bayesian method to study the degradation model with respect to a Wiener process.The Jeffreys prior and reference prior for the parameters are derived,and the propriety of the posteriors under these priors is validated.Two sampling algorithms are introduced to compute the posteriors.A simulation study is conducted to investigate the performance of the objective Bayesian procedure.Finally,the authors apply the approach to a degradation data.
基金This paper is funded by National Natural Science Fund (30171205) and National Tenth-year-plan Key Sci&tech Project (2005BA517A04)
文摘Planting trees was used as one of cost-effective measures for desertification control in add and semi-add areas of China. Woodland degradation, however, is becoming an inevitable issue in these areas. In this paper, a typical county, Ejin Holo County, Inner Mongolia, China was selected for its assessment of artificial woodland degradation. A conceptual model for woodland degradation was delineated qualitatively based on field sampling survey, and four model-based indicators as humidity index （HI）, vegetation index （NDVI）, soil type （ST） and soil erosion modulus （EM） were screened out and used to a GIS-based method for artificial woodland degradation assessment in this semi-add agro-pastoral transitional area. All the indicator layers were overlaid and desertification assessed using simplified equation with equal weights for each indicators. The assessment results showed that in 336. 09 km^2 of total woodland area, 311.35 km^2 woodland were under degradation, and the area for slight, medium, severe degradation was 78.97, 119.73 and 112.65 km^2, respectively. It was suggested that much attention should be paid on woodland improvement and plant species selection, especially shrub species, before revegetation in similar areas.
基金The work is supported by the Humanities and Social Sciences Foundation of Ministry of Education,China(Grant No.17YJC910003).
文摘The Wiener process as a degradation model plays an important role in the degradation analysis.In this paper, we propose an objective Bayesian analysis for an acceleration degradation Wienermodel which is subjected to measurement errors. The Jeffreys prior and reference priors underdifferent group orderings are first derived, the propriety of the posteriors is then validated. It isshown that two of the reference priors can yield proper posteriors while the others cannot. A simulation study is carried out to investigate the frequentist performance of the approach comparedto the maximum likelihood method. Finally, the approach is applied to analyse a real data.
基金This paper is sponsored by the National Study Abroad Fund of China and supported by The National Key Research and Development Program of China(2017YFB1002304).
文摘Biomimetic scaffolds provide a suitable growth environment for tissue engineering and demonstrate good potential for application in biomedical fields.Different-sized copolymerized biomimetic scaffolds degrade differently,and the degradation rate is affected by the copolymerization ratio.The study of the degradation property is the foundational research necessary for realizing individualized biomimetic scaffold design.The degradation performance of polyesters with different copolymerization ratios has been widely reported;however,the modeling of this performance has been rarely reported.In this research,the degradation of copolymers was studied with multi-scale modeling,in which the copolymers were dispersed in a cellular manner,the chain break time was simulated,and the chain selection was based on the Monte Carlo(MC)algorithm.The probability model of the copolymer's chain break position was established as a//roulette,/model,whose probability values were estimated by the calculation of the potential energy difference at different chain break positions by molecular dynamics that determined the position of chain shear,thereby fully realizing the simulation of the chain micro-break process.The diffusion of the oligomers was then calculated using the macro diffusion equation,and the degradation process of the copolymer was simulated by three-scale coupling calculations.The calculation results were in good agreement with the experimental data,demonstrating the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(12172034,U20A20390,and 11827803)Beijing Municipal Natural Science Foundation(7212205)+1 种基金the 111 project(B13003)the Fundamental Research Funds for the Central Universities.
文摘Background:Mg alloys have attractive properties,including biocompatibility,biodegradability,and ideal mechanical properties.Moreover,Mg alloys are regarded as one of the promising candidates for manufacturing ureteral stents.This study proposed a multi-objective optimization method based on the Kriging surrogate model,NSGA-III,and finite element analysis to improve the degradation performance of Mg alloy ureteral stents.Methods:The finite element model for the degradation of Mg alloy ureteral stents has been established to compare the degradation performance of the stents under different parameters.Latin hypercube sampling was adopted to generate train sample points in the design space.Meanwhile,the Kriging surrogate model was constructed between strut parameters and stent degradation behavior.The NSGA-III was utilized to determine the optimal solution in the global design space.Results:The optimized stent achieved 5.52degradation uniformity(M),10degradation time(DT),and 4work time(FT).The errors between the Kriging surrogate model and the finite element calculation results were less than 6%.Conclusion:The optimized stent achieved better degradation performance.The degradation behavior of stents was dependent on the design parameters.The multi-objective optimization method based on the Kriging surrogate model and finite element analysis was effective in stent design optimization problems.
基金supported by the Shanghai Rising-Star Program(No.07QB14018)
文摘An improved hot carrier injection （HCI） degradation model was proposed based on interface trap generation and oxide charge injection theory. It was evident that the degradation behavior of electric parameters such as Idlin, Idsat, Gm and Vt fitted well with this model. Devices were prepared with 0.35μm technology and different LDD processes. Idlin and Idsat after HCI stress were analyzed with the improved model. The effects of interface trap generation and oxide charge injection on device degradation were extracted, and the charge injection site could be obtained by this method. The work provides important information to device designers and process engineers.
基金The financial support from Project(Grant Nos.52278432,and 52168066)of National Natural Science Foundation of China and Project(Grant No.K2023G033)of the Science and Technology Research and Development Plan of China National Railway Group Co.,Ltd.were greatly appreciated.
文摘This paper presents a multi-scale experimental investigation of the weathering degradation of red mudstone.Natural rocks were extracted from the surface ground to 120 m,inwhich three sets of samples were selected to consider the different initial rock fabrics.The long-term relative humidity(RH)cycles under two amplitudes were imposed on red mudstone to simulate the weathering process.After RH cycles,a series of uniaxial compression tests,Brazilian splitting tests and bender-extender element tests were carried out to examine the reduction in strength and stiffness.The objective of this study is to develop an extended stress-volume framework characterizing the degradation of natural red mudstone both at microscale and macroscale.Accompanied by the irreversible swelling of the rock specimen is the progressive degradation of strength,stiffness and Poisson's ratio.A unified exponential degradation model in terms of the irreversible volumetric strain was thus proposed to capture such a degradation pattern.The effect of the initial rock fabric was evident.The highest degradation rate and potential were identified in slightly weathered specimens.Significant slaking of aggregates and crack propagation were confirmed by scanning electron microscope(SEM)micrographs,which were considered as the main consequence of structure damage leading to degradation of mechanical properties.The structure damage during RH cycles denoted the hysteresis nature in the response to the cycling hydraulic reaction,in turn causing the increase in volumetric strain.Thus,the stress-volume relation rather than the suction relation was found in more reasonable agreement with the experimental results.
文摘Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferometric imaging faces the impact of multi-stage degradation. Most exsiting interferometric spectrum reconstruction methods are based on tradition model-based framework with multiple steps, showing poor efficiency and restricted performance. Thus, we propose an interferometric spectrum reconstruction method based on degradation synthesis and deep learning.Firstly, based on imaging mechanism, we proposed an mathematical model of interferometric imaging to analyse the degradation components as noises and trends during imaging. The model consists of three stages, namely instrument degradation, sensing degradation, and signal-independent degradation process. Then, we designed calibration-based method to estimate parameters in the model, of which the results are used for synthesizing realistic dataset for learning-based algorithms.In addition, we proposed a dual-stage interferogram spectrum reconstruction framework, which supports pre-training and integration of denoising DNNs. Experiments exhibits the reliability of our degradation model and synthesized data, and the effectiveness of the proposed reconstruction method.
基金Financial support was provided by the State Grid Sichuan Electric Power Company Science and Technology Project“Key Research on Development Path Planning and Key Operation Technologies of New Rural Electrification Construction”under Grant No.52199623000G.
文摘The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.
基金the National Natural Science Foundation of China(Nos.52469019,52109119,and 52274145)the Chinese Postdoctoral Science Fund Project(No.2022M723408)+1 种基金the Major Project of Guangxi Science and Technology(No.AA23023016)the Technology Project of China Power Engineering Consulting Group Co.,Ltd.(No.DG2-T01-2023)。
文摘The redistribution of three-dimensional(3D)geostress during underground tunnel excavation can easily induce to shear failure along rockmass structural plane,potentially resulting in engineering disasters.However,the current understanding of rockmass shear behavior is mainly based on shear tests under2D stress without lateral stress,the shear fracture under 3D stress is unclear,and the relevant 3D shear fracture theory research is deficient.Therefore,this study conducted true triaxial cyclic loading and unloading shear tests on intact and bedded limestone under different normal stress σ_(n) and lateral stressσ_(p)to investigate the shear strength,deformation,and failure characteristics.The results indicate that under differentσ_(n)and σ_(p),the stress–strain hysteresis loop area gradually increases from nearly zero in the pre-peak stage,becomes most significant in the post-peak stage,and then becomes very small in the residual stage as the number of shear test cycles increases.The shear peak strength and failure surface roughness almost linearly increase with the increase inσ_(n),while they first increase and then gradually decrease asσ_(p)increases,with the maximum increases of 12.9%for strength and 15.1%for roughness.The shear residual strength almost linearly increases withσ_(n),but shows no significant change withσ_(p).Based on the acoustic emission characteristic parameters during the test process,the shear fracture process and microscopic failure mechanism were analyzed.As the shear stressτincreases,the acoustic emission activity,main frequency,and amplitude gradually increase,showing a significant rise during the cycle near the peak strength,while remaining almost unchanged in the residual stage.The true triaxial shear fracture process presents tensile-shear mixture failure characteristics dominated by microscopic tensile failure.Based on the test results,a 3D shear strength criterion considering the lateral stress effect was proposed,and the determination methods and evolution of the shear modulus G,cohesion c_(jp),friction angleφ_(jp),and dilation angleψjpduring rockmass shear fracture process were studied.Under differentσ_(n)andσ_(p),G first rapidly decreases and then tends to stabilize;cjp,φ_(jp),andψjpfirst increase rapidly to the maximum value,then decrease slowly,and finally remain basically unchanged.A 3D shear mechanics model considering the effects of lateral stress and shear parameter degradation was further established,and a corresponding numerical calculation program was developed based on3D discrete element software.The proposed model effectively simulates the shear failure evolution process of rockmass under true triaxial shear test,and is further applied to successfully reveal the failure characteristics of surrounding rocks with structural planes under different combinations of tunnel axis and geostress direction.
