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A condition control-based dual-reliability evaluation for structural health monitoring 认领 引用
1
作者 Qiuhui XU Shenfang YUAN +1 位作者 Jian CHEN Hutao JING 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期247-262,共16页
It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typica... It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty. 展开更多
关键词 Crack detection and sizing Dual-reliability evaluation Evaluation condition control Guided wave-based monitoring Reliability evaluation Structural health monitoring
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Fatigue reliability modeling using an energy-based parameter by loading cycle-failure life interference:Validation and application 认领 引用
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作者 Hanghang Gu Runzi Wang +5 位作者 Kun Zhang Ji Wang Li Sun Kaishang Li Xiancheng Zhang Shantung Tu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第3期68-79,共12页
Several probabilistic fatigue evaluation models have been proposed,but the effectiveness and accuracy of current models have not yet been examined.In this work,probabilistic fatigue life is linked to an energy-based d... Several probabilistic fatigue evaluation models have been proposed,but the effectiveness and accuracy of current models have not yet been examined.In this work,probabilistic fatigue life is linked to an energy-based damage parameter,where the statistic of logarithmic fatigue life is represented by this parameter.Taking into account the variability in loading amplitudes and material properties,a novel fatigue reliability assessment method for structural system is proposed,based on the probabilistic fatigue model and loading cycle-failure life interference principle.A series of strain-controlled fatigue tests of Inconel 718 alloy are conducted for model development and fatigue data with different strain ratios are collected from open literature to verify the model applicability.The results show that the proposed model aligns most closely with experimental data when compared to traditional probability-strain-life models,Xie's modified model,Castillo's model,and Correia's model.Furthermore,a turbine fir-tree attachment is taken as an instance to illustrate the implementation procedure for fatigue reliability analysis.It is evident that the proposed method mitigates the overly con-servative estimates typically provided by independent treatments in structural system reliability assessments.This research proposes a method for accurate evaluations of material-level fatigue life and system-level relia-bility supports reliability-centered design and life management of crucial structures. 展开更多
关键词 Fatigue reliability Energy-based parameter System-level Turbine fir-tree attachment
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System reliability analysis of jointed bedding rock slopes under seismic loading:Integrating multiple failure modes 认领 引用
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作者 ZHANG Yingbin CHEN Haiping +3 位作者 FU Junwen LI Dejian LI Hekai YU Qiangshan 《Journal of Mountain Science》 SCIE CSCD 2026年第5期2074-2087,I0007-I0010,共14页
Jointed bedding rock slopes are susceptible to multiple failure modes under seismic loading,yet conventional stability assessments relying on a single mode are insufficient and may introduce significant errors,potenti... Jointed bedding rock slopes are susceptible to multiple failure modes under seismic loading,yet conventional stability assessments relying on a single mode are insufficient and may introduce significant errors,potentially underestimating slope instability risk.This study established a novel system reliability framework,integrating four key failure modes—translational(TM),rotational(RM),upper rotationallower translational(URLTM),and upper translationallower rotational(UTLRM)—for seismic stability assessment.Utilizing Monte Carlo simulation,the framework explicitly accounted for inherent randomness and uncertainty in the strength parameters of joint surfaces and rock bridges.System reliability was evaluated using the minimum safety factor(FS)to identify the dominant failure mode.The analysis reveals that using only a single failure model can introduce maximum errors in Fs exceeding 10%;with increasing cr(cohesion)andφr(internal friction angle),the dominant failure mode changes from RM(not affected by the joint surface)to UTLRM/TM(controlled by the joint surface);as Kc(cohesion weakening coefficient)and Kφ(friction coefficient(tanφr)weakening coefficient)increase,failure is more likely atδ/β(joint surface angle/slope angle)=0.40~0.65;seismic action further increases the likelihood of joint-surface-controlled failure,increasing seismic action shifts the dominant failure mode from UTLRM to TM.These results offer direct support for the efficient determination of the dominant failure mode and sliding surface position in stability assessments of jointed bedding rock slopes. 展开更多
关键词 Jointed bedding rock slopes Multiple failure modes System reliability Monte Carlo Dominant failure mode
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Research on the reliability of motion accuracy for ammunition conveyor in artillery automatic loading system 认领 引用
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作者 Guangsong Chen Junhua Chen +1 位作者 Jinsong Tang Yongji Liu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第1期102-114,共13页
The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the e... The automatic loading systems of artillery are critical for the accurate,efficient,and reliable delivery of pro-jectiles and propellants into the gun chamber.In modern artillery,the ammunition conveyor serves as the end effector of the automatic loading system,and its motion state significantly impacts the accuracy of projectiles.Therefore,it is of immense importance to precisely and effectively evaluate the reliability of the motion accuracy of the ammunition conveyor.This paper aims to propose a practical and efficient analysis method for evaluating the reliability of the motion accuracy of the ammunition conveyor.The proposed approach involves the use of a deep learning network to approximate the physical model and the extremum method to obtain a single cycle sequence decoupling strategy for solving the time-varying reliability issue of complex systems.Employing this strategy,the time-varying reliability of the ammunition conveyor is transformed into a static reliability problem.The proposed method includes the use of a deep feedforward neural network,second-order saddle point ap-proximation(SPA)method,extremum method,and efficient global optimization(EGO)technology.The results reveal that the reliability of the motion accuracy of the ammunition conveyor is 93.42%,with the maximum failure probability occurring at 0.21 s.These results serve as an important reference for the structural optimi-zation design of the ammunition conveyor based on reliability and the maintenance of the operational process. 展开更多
关键词 Automatic loading system Ammunition conveyor Motion accuracy Reliability Second-order saddle point approximation
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Gradient Optimization Assisted Bubble Sampling Method for Structural Reliability Analysis 认领 引用
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作者 Zeng Meng LiwenjieShen +2 位作者 Changquan Li Jiaxiang Yi Gang Dong 《Acta Mechanica Solida Sinica》 SCIE EI CSCD 2026年第6期891-904,共14页
The sampling method is an important numerical technique for solving reliability problems in engineering systems.However,the evaluation of the failure probability using classical sampling methods is time-consuming for ... The sampling method is an important numerical technique for solving reliability problems in engineering systems.However,the evaluation of the failure probability using classical sampling methods is time-consuming for complex engineering structure.To address this issue,this paper proposes a gradient optimization assisted bubble sampling method(GOBSM)to reduce the computational costs,which enhances the coverage range of bubbles,thereby improving the computational efficiency without sacrificing the accuracy.Furthermore,the bubble gradient iterative algorithm is developed to efficiently construct bubbles.Eight complex numerical examples are tested for assessing the failure probability,and the results demonstrate the performance of GOBSM. 展开更多
关键词 Reliability analysis Bubble sampling method Bubble gradient iterative algorithm Failure probability
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Transmission patterns of progressive damage and reliability analysis of reservoir-induced landslides considering local tensile failure 认领 引用
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作者 Minghao Miao Huiming Tang +5 位作者 Yinlong Jiang Kun Fang Changdong Li Cheng He Peng Cao Sha Lu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第2期913-931,共19页
Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the ten... Reservoir-induced landslides in China's Three Gorges Reservoir area are prone to tensile cracks due to the influenceof their own weight and fluctuationsin water levels.The presence of cracks indicates that the tensile stress in the area has exceeded the tensile strength of the soil,leading to local instability.To explore the impact of tensile failure behavior on the stability and failure modes of reservoir landslides,the Huangtupo Riverside Slump#1 is taken as a case study.By considering local tensile failure,potential tensile cracks are incorporated into the analysis via the limit equilibrium method and reliability theory.The reliability of landslides under different tensile failure scenarios is quantified.Strain-softening characteristics of the soil are combined to further analyze the failure transmission path of the landslide.Finally,these potential failure modes were validated through physical model tests.The results show that cracks developing at rear positions reduce the stability of the slope and increase the probability of instability.During the destruction process,retrogressive failures with multiple sliding surfaces are likely to occur.However,tensile failure at the forefront reduces the likelihood of an individual slide mass descending.Progressive failure results in both regular and skip transmission patterns.Additionally,cracks and water level changes can also lead to shifts in the positions of the most dangerous blocks.Therefore,in practical landslide analysis and prevention,it is necessary to consider local tensile damage and identify potential tensile crack locations in advance to optimize prevention measures and accurately evaluate landslide risk. 展开更多
关键词 Reliability analysis Tensile failure Reservoir landslide Progressive damage Failure mode Tensile crack
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Impact of sidewall passivation on reliability in InGaN-based micro-LEDs 认领 引用
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作者 Tae Kyoung Kim Abu Bashar Mohammad Hamidul Islam +8 位作者 Jongil Kim Hyeondong Lee Minji Kim Joohan Bae June-O Song Dong-Soo Shin Jong-In Shim Sang Ho Oh Joon Seop Kwak 《Advanced Photonics Nexus》 CSCD 2026年第1期186-201,共16页
The performance degradation of micro light-emitting diodes(micro-LEDs)is closely associated with the deterioration of sidewall passivation layers under prolonged electrical bias.We investigate reliability improvements... The performance degradation of micro light-emitting diodes(micro-LEDs)is closely associated with the deterioration of sidewall passivation layers under prolonged electrical bias.We investigate reliability improvements in 20μm×20μm InGaN/GaN blue micro-LEDs by suppressing the formation of an unstable interfacial layer during sidewall passivation.SiO2is deposited on the etched mesa sidewalls using either Sputtering or plasma-enhanced chemical vapor deposition(PECVD).Comparative analysis reveals that PECVD-passivated devices experience more severe performance degradation,primarily due to the increased leakage current.After 100 h of accelerated aging,external quantum efficiency decreases by 44%in PECVD-passivated samples,whereas Sputter-passivated devices exhibit only an11%reduction.This discrepancy is attributed to the formation of a thicker and chemically unstable gallium oxynitride(Ga-OX-N1-X)interfacial layer at the SiO2∕GaN-based interface,which facilitates the generation of sidewall defects.Suppressing the formation of this interlayer enhances the crystallinity and structural stability of the passivation layer,thereby mitigating the activation of point defects.Notably,Sputter deposition is more effective in minimizing the formation of Ga-O-N interlayer.These findings emphasize the critical role of achieving low-defect-density sidewall passivation to improve the reliability of micro-LEDs for next-generation high-resolution display applications. 展开更多
关键词 micro light-emitting diode sputter plasma-enhanced chemical vapor deposition passivation external quantum efficiency point defect reliability interfacial layer
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Dynamic balance and reliability of a stochastic ecosystem with Markov switching 认领 引用
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作者 Ya-Nan Sun Xin-Zhi Liu You-Ming Lei 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第1期381-390,共10页
A stochastic predator-prey system with Markov switching is explored.We have developed a new chasing technique to efficiently solve the Fokker-Planck-Kolmogorov and backward Kolmogorov equations.Dynamic balance and rel... A stochastic predator-prey system with Markov switching is explored.We have developed a new chasing technique to efficiently solve the Fokker-Planck-Kolmogorov and backward Kolmogorov equations.Dynamic balance and reliability of the switching system are evaluated via stationary probability density function and first-passage failure theory,taking into account factors such as switching frequencies,noise intensities,and initial conditions.Results reveal that Markov switching leads to stochastic P-bifurcation,enhancing dynamic balance and reducing white-noise-induced oscillations.But frequent switching can heighten initial value dependence,harming reliability.Further,the influence of the subsystem on the switching system is not proportional to its action probabilities.Monte Carlo simulations validate the findings,offering an in-depth exploration of these dynamics. 展开更多
关键词 stochastic ecosystem Markov switching first-passage failure reliability
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Bi-Objective Optimization of Distribution Network Reliability Enhancement Using Quantitative Decomposition 认领 引用
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作者 Chenying Yi Yangjun Zhou +8 位作者 Wei Zhang Like Gao Hongwen Wu Yuanchao Zhou Ke Zhou Weixiang Huang Juntao Pan Shan Li Bin Feng 《Energy Engineering》 EI 2026年第8期262-276,共15页
Ensuring reliability in distribution networks is essential under increasing operational and economic constraints.Traditional planning models rely on power flow calculations,leading to high computational costs and poor... Ensuring reliability in distribution networks is essential under increasing operational and economic constraints.Traditional planning models rely on power flow calculations,leading to high computational costs and poor scalability.This study proposes a quantitative decomposition framework that establishes a direct linkage among reliability improvement measures,reliability parameters,and reliability indices,enabling fast and analytical reliability evaluation without power flow analysis.A bi-objective optimization model is developed to minimize both reliability indices(SAIDI)and investment costs,solved using Pareto-based multi-objective PSO combined with the TOPSIS method.Case studies on a 519-node distribution network demonstrate that the proposed approach achieves significant reliability improvement with superior computational efficiency,offering a practical and scalable tool for reliabilityoriented distribution planning. 展开更多
关键词 Distribution network reliability improvement measures quantitative analysis optimization decision
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Efficient Structural Reliability Analysis via Adaptive Hidden Neuron Screening in Extreme Learning Machines 认领 引用
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作者 Yunlong Teng Ying Liu +1 位作者 Jianhong Liang Jinshang Luo 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第6期274-300,共27页
Over the past decades,surrogate model-aided reliability analysis approaches grounded in active learning have undergone extensive development.However,Gaussian process models like Kriging suffer from severe computationa... Over the past decades,surrogate model-aided reliability analysis approaches grounded in active learning have undergone extensive development.However,Gaussian process models like Kriging suffer from severe computational burdens when handling high-dimensional problems or large samples.Conversely,machine learning algorithms such as extreme learning machines exhibit high computational efficiency but lack variance output and stability,making them difficult to employ for adaptive active learning strategies.To address these limitations,this study proposes a population Monte Carlo method based on an adaptive closed neuron extreme learning machine.First,a closed neuron strategy uses a consistency metric to screen and retain neurons containing the most informative features.This preserves the fast analytical solution advantage of extreme learning machines while significantly improving the reconstruction accuracy and stability of the true limit state surface.Second,to overcome the lack of variance in the output,an ensemble model is constructed.By calculating predictive mean and standard deviation,a learning function is formulated for efficient adaptive sample enrichment.Finally,utilizing the adaptive importance sampling mechanism of the population Monte Carlo framework,the auxiliary density function is optimized to progressively shift the sampling center toward high contribution failure regions.Four engineering examples confirm that the proposed method achieves exceptional computational efficiency and high accuracy for complex reliability analysis involving extremely small failure probabilities. 展开更多
关键词 Structural reliability analysis machine learning models enhanced learning framework population Monte Carlo feature screening
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Exploring the Reliability and Validity of AI Scoring in the Continuation Writing Task 认领 引用
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作者 Jie Zhang Chunhua Ma 《Chinese Journal of Applied Linguistics》 2026年第1期133-150,161,共18页
This study examines the reliability and validity of AI-generated scoring for continuation writing tasks.By comparing GPT-4 with eight experienced human raters across 21 student responses,it evaluates AI’s consistency... This study examines the reliability and validity of AI-generated scoring for continuation writing tasks.By comparing GPT-4 with eight experienced human raters across 21 student responses,it evaluates AI’s consistency,severity,and alignment with human scoring criteria.Results show that AI exhibits high self-consistency and adapts effectively to different scoring roles(e.g.,teacher vs.highstakes rater).However,AI scores were more lenient than human raters and demonstrated divergent evaluation focuses—prioritizing narrative coherence and emotional depth,while teachers emphasized linguistic accuracy and richness of detail.The findings suggest AI’s potential as a supplementary assessment tool,offering rapid,holistic feedback,but highlight the need for further calibration to align with educational standards.Implications include exploring hybrid evaluation models that leverage the strengths of both AI and human raters to achieve more equitable,efficient,and pedagogically meaningful writing assessments. 展开更多
关键词 continuation writing AI scoring human raters reliability validity
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Structural Reliability Analysis Based on Differential Evolution Algorithm and Hypersphere Integration 认领 引用
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作者 CHEN Zhenzhong HAN Zhuo +4 位作者 WANG Peiyu PAN Qianghua LI Xiaoke GAN Xuehui CHEN Ge 《Journal of Donghua University(English Edition)》 CAS 2026年第1期118-130,共13页
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia... In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision. 展开更多
关键词 reliability analysis design point positioning differential evolution algorithm hypersphere integration
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A Stochastic Multi-Objective Framework for Wind DG Allocation and Dynamic Reconfiguration:Minimizing Losses and Enhancing Reliability with an Improved Grey Wolf Optimizer 认领 引用
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作者 Ali S.Alghamdi 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期704-744,共41页
The integration of wind-based DG introduces significant variability and uncertainty into the operation of distribution networks,which complicates the planning and decision-making process.This paper presents a dualobje... The integration of wind-based DG introduces significant variability and uncertainty into the operation of distribution networks,which complicates the planning and decision-making process.This paper presents a dualobjective stochastic optimization framework for the optimal allocation of wind DG,considering dynamic network reconfiguration across multiple loading conditions.Probabilistic modeling of wind speed is integrated using the Weibull distribution and the associated wind power uncertainty is discretized through a scenario-based point estimation method.Variability in load is accounted for by considering multiple loading levels,and the integrated uncertainty space is constructed as the Cartesian product of wind scenarios and load profiles.The optimization seeks to minimize the total energy losses together with the enhancement of reliability,quantified through the expected energy not supplied.For the solution of the complex,nonlinear,multi-objective problem,the Improved Multi-Objective Grey Wolf Optimizer(I-MGWO)is developed,including quasi-oppositional population seeding,adaptive stochastic coeficient strategy,and dynamic convex combination position update.Simulation results on the IEEE 33-bus system demonstrate that the proposed integrated strategy of simultaneous wind DG allocation and network reconfiguration gives synergistic improvements,yielding up to 55.7%reduction in energy losses,and a reduction of up to 61.4%in EENS over the base case.In both convergence speed and solution quality,I-MGWO consistently outperforms conventional algorithms and gives a robust and computationally efficient tool for distribution system planning under uncertainty. 展开更多
关键词 Wind power generation distributed generation allocation active distribution network network reconfiguration uncertainty modeling stochastic optimization multi-objective optimization reliability assessment Grey Wolf Optimizer
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Combined Fault Tree Analysis and Bayesian Network for Reliability Assessment of Marine Internal Combustion Engine 认领 引用 被引量：1
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作者 Ivana Jovanović Çağlar Karatuğ +1 位作者 Maja Perčić Nikola Vladimir 《哈尔滨工程大学学报（英文版）》 CSCD 2026年第1期239-258,共20页
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ... This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels. 展开更多
关键词 Fault tree analysis Bayesian network Reliability Redundancy Internal combustion engine
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Review on reliability technology for high-end CNC machine tools:Overview and prospect 认领 引用
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作者 Zhijie Li Zhaojun Yang +3 位作者 Zhifeng Liu Chuanhai Chen Jinyan Guo Hailong Tian 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第3期1-18,共18页
After several years of research on the reliability of CNC machine tools,many theories and technologies have been developed,which have improved the reliability level of economical CNC machine tools produced in China.Ho... After several years of research on the reliability of CNC machine tools,many theories and technologies have been developed,which have improved the reliability level of economical CNC machine tools produced in China.However,the relevant methods have not significantly promoted the reliability of high-end CNC machine tools,and there are limitations and deficiencies that need to be solved urgently.This paper analyzes the unique challenges posed by the inherent characteristics of high-end CNC machine tools to reliability research and systematically reviews the research trends in this field in recent years.It focuses on analyzing the research progress in the development of accelerated degradation testing,failure mechanism analysis,reliability modeling for small sample datasets,and fault diagnosis/intelligent maintenance technologies integrated with deep learning to adapt to the aforementioned characteristics.It also points out the current research deficiencies in design principles,load spectra for new components,and maintenance support.Finally,it provides forward-looking suggestions for the future development of CNC machine tool reliability research,serving as a reference for researchers and practitioners. 展开更多
关键词 High-end CNC machine tools Reliability Accelerated degradation test Small sample modeling Fault diagnosis
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Evaluation of Deterioration Law and Reliability of Concrete after Durability Improvement Based on Wiener Theory 认领 引用
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作者 SHI Hongzhuang SU Fuyun +3 位作者 QIAO Hongxia ZHANG Lei FU Yong YANG Xiaosen 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS CSCD 2026年第1期147-161,共15页
To study the durability of concrete in harsh environments in Northwest China,concrete was prepared with various durability-improving materials such as concrete anti-erosion inhibitor(SBT-TIA),acrylate polymer(AP),supe... To study the durability of concrete in harsh environments in Northwest China,concrete was prepared with various durability-improving materials such as concrete anti-erosion inhibitor(SBT-TIA),acrylate polymer(AP),super absorbent resin(SAP).The erosion mode and internal deterioration mechanism under salt freeze-thaw cycle and dry-wet cycle were explored.The results show that the addition of enhancing materials can effectively improve the resistance of concrete to salt freezing and sulfate erosion:the relevant indexes of concrete added with X-AP and T-AP are improved after salt freeze-thaw cycles;concrete added with SBTTIA shows optimal sulfate corrosion resistance;and concrete added with AP displays the best resistance to salt freezing.Microanalysis shows that the increase in the number of cycles decreases the generation of internal hydration products and defects in concrete mixed with enhancing materials and improves the related indexes.Based on the Wiener model analysis,the reliability of concrete with different lithologies and enhancing materials is improved,which may provide a reference for the application of manufactured sand concrete and enhancing materials in Northwest China,especially for the study of the improvement effects and mechanism of enhancing materials on the performance of concrete. 展开更多
关键词 manufactured sand concrete durability enhancement enhancing materials reliability analysis
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Investigation of a gate-series-diode structure for improving Schottky-type p-GaN gate reliability 认领 引用
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作者 Xuejing Sun Shenglei Zhao +13 位作者 Yinhe Wu Longyang Yu Juan Gui Ga Zhang Xiufeng Song Shuzhen You Song Yang Hui Sun Bin Hu Huantao Duan Jin Rao Zhen Chen Yue Hao Jincheng Zhang 《Journal of Semiconductors》 EI CAS CSCD 2026年第5期97-106,共10页
In this paper,a novel gate-series-diode structure for the Schottky-type p-GaN HEMTs is proposed,and the impact of the proposed structure on gate-source voltage oscillation is investigated when the device is turned on.... In this paper,a novel gate-series-diode structure for the Schottky-type p-GaN HEMTs is proposed,and the impact of the proposed structure on gate-source voltage oscillation is investigated when the device is turned on.The proposed structure is capable of effectively mitigating the gate-source voltage overshoot problem of GaN device,and has little effect on the switching characteristics.The gate voltage oscillations can be greatly stabilized at the steady-state turn-on voltage level when the turn-on voltage is 5 V.Compared with the conventional structure,the overshoots of the proposed structure reduce by31.4%-71.4%and 40.6%-80.4%respectively under the two pulses,as drain-source voltage rises.The proposed structure is proved to be a potential method on improving gate reliability of the most GaN power devices. 展开更多
关键词 p-GaN high-electron-mobility transistors(p-GaN HEMTs) schottky-type contact gate-series-diode gate reliability
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Machine learning-driven reliability assessment of liquefaction probability based on state parameter analysis 认领 引用
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作者 Kishan Kumar Pijush Samui +1 位作者 S.S.Choudhary Hong-Hu Zhu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第4期2960-2979,共20页
The state parameter(ψ)utilising the concept of critical state soil mechanics integrates the effect of relative density and effective stress and offers notable advantages for liquefaction assessment.This study present... The state parameter(ψ)utilising the concept of critical state soil mechanics integrates the effect of relative density and effective stress and offers notable advantages for liquefaction assessment.This study presents aψ-based liquefaction analysis using the first-order reliability method(FORM)and second-order reliability method(SORM)to evaluate the liquefaction probability of failure(PL)considering the parametric uncertainty.Four machine learning(ML)models,which include long short-term memory(LSTM),bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and Bayesian non-parametric general regression(BNGR),were developed to predict PL.The reliability analysis confirmed the robustness of the results,with PL values consistent with those obtained by established methodologies.A mapping function relating the safety factor(SF)to the PL was developed using the cone penetration test(CPT)database.Performance evaluation using 15 statistical indices,alongside sensitivity and uncertainty analysis,demonstrates the relative significance of input parameters and prediction reliability.The GRU model outperformed other ML models in terms of overall performance.The BiLSTM model achieved the highest R² values of 0.976 in training,and the GRU model(0.961)in testing,with comparable root mean square error(RMSE)values of 0.046 and 0.065,respectively.Additionally,the BNGR model showed promising results in accuracy and model complexity with the lowest Akaike information criterion(AIC)value of 11.62.Williams plots were used to illustrate the models’applicability domain,while sensitivity analysis underscores the significance of input parameters,with ψ emerging as the most influential parameter.This research provides a comprehensive framework for enhancing the accuracy and reliability of liquefaction evaluation in engineering and infrastructure design. 展开更多
关键词 Liquefaction State parameter Machine learning(ML) Reliability analysis Deep learning Bayesian modelling
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A reliability-based framework using Markov chain Monte Carlo simulation for estimating the strength of intact rock 认领 引用
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作者 Md Shayan Sabri Amit Kumar Verma +1 位作者 Krzysztof Sternik T.N.Singh 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第7期5091-5108,共18页
Uniaxial Compressive Strength(UCS)is a critical parameter in geotechnical and rock engineering applications,yet its direct measurement is time-consuming and resource demanding.This study proposes a probabilistic appro... Uniaxial Compressive Strength(UCS)is a critical parameter in geotechnical and rock engineering applications,yet its direct measurement is time-consuming and resource demanding.This study proposes a probabilistic approach to UCS estimation using three key input parameters:Schmidt hammer rebound number(SRn),P-wave velocity(VP),and Point Load Index(IS50).Regression models,including Multiple Linear Regression(MLR)and Non-Linear Multiple Regression(NLMR),were developed and validated using an independent dataset of 222 samples.Although MLR provided high predictive accuracy,it occasionally yielded unrealistic negative UCS values,necessitating the adoption of NLMR.Pearson correlation analysis revealed moderate to strong positive correlations between UCS and SRn(0.69),VP(0.64),and IS50(0.42).The most accurate predictive model,M-7,exhibited the highest correlation coefficient(R=0.7861)and lowest RMSE(27.59).To enhance reliability,stochastic simulations using Monte Carlo Simulation(MCS)and Markov Chain Monte Carlo(MCMC)were incorporated,effectively accounting for input parameter uncertainties.The mean UCS values predicted by MCS(76.21 MPa)and MCMC(75.08 MPa)closely aligned with experimental data(75.05 MPa),with MCMC demonstrating superior consistency while requiring fewer simulations(5000 vs.10,000).Hypothesis testing indicated that VP had the most significantinfluenceon UCS uncertainty(ZH=19.63),followed by SRn(-6.55)and IS50(0.61).The integration of the NLMR model with MCS and MCMC provides a robust framework for accurate UCS estimation,minimizing errors and enhancing predictive reliability for practical engineering applications. 展开更多
关键词 Regression Unconfined compressive strength K-S test Monte Carlo simulation Markov chain Monte Carlo Reliability
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Time-varying reliability analysis of a reservoir bank slope considering creep behavior and sequential Bayesian updating 认领 引用
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作者 Wenyu Zhuang Qingchao Lyu +4 位作者 Yaoru Liu Kai Zhang Ting Liu Junlei Bai Qun Zhang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第3期2104-2121,共18页
The probabilistic stability evolution analysis of reservoir bank slopes is a crucial aspect of risk assessment,with core challenges including the consideration of deformation mechanisms and accurate determination of m... The probabilistic stability evolution analysis of reservoir bank slopes is a crucial aspect of risk assessment,with core challenges including the consideration of deformation mechanisms and accurate determination of mechanical parameters.In this study,a novel time-varying reliability analysis framework based on sequential Bayesian updating of mechanical parameters is proposed.The inverse parameters account for damage time-dependent behavior,incorporating water effect and a strain-driven softening-hardening process that depends on sliding states.The likelihood function is enhanced to simultaneously consider observation error,surrogate model prediction error,and model structural error,with the introduction of physical penalty.Exploration of the high-dimensional parameter space is achieved via the Hamiltonian Monte Carlo(HMC)method and the physics knowledge-based time-dependent deformation surrogate model.The time-varying reliability analysis of the slope is performed using the multi-grid method.Taking a reservoir bank slope as a case study,the sequential updating of 12 mechanical parameters is conducted based on deformation time series from 16 monitoring points,thereby validating the proposed framework.The results indicate that the proposed framework effectively captures the posterior distribution of mechanical parameters,with the case slope remaining in a critically stable state after overall sliding,showing a high failure probability.Introducing model structural error can reduce parameter compensation,and a reasonable sequential updating step size can improve inversion accuracy. 展开更多
关键词 Sequential Bayesian updating Probabilistic back analysis Time-varying reliability Reservoir bank slope Model structural error Surrogate model prediction error Markov chain Monte Carlo(MCMC)method Multi-grid method
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