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
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
In this work,we demonstrated the InSnO(ITO)TFTs passivated with SiO_(2)via the PECVD process compatible with large-area production for the first time.The passivated ITO TFTs with various channel thicknesses(t_(ch)=4,5...In this work,we demonstrated the InSnO(ITO)TFTs passivated with SiO_(2)via the PECVD process compatible with large-area production for the first time.The passivated ITO TFTs with various channel thicknesses(t_(ch)=4,5,6 nm)exhibit excellent electrical performance and superior uniformity.The reliability properties of ITO TFTs were evaluated in detail under positive bias stress(PBS)conditions before and after passivation.Compared to the devices without passivation,the passivated devices have only 50%threshold voltage degradation(ΔV_(th))and 50%newly generated traps due to excellent isolation of the ambient atmosphere.The negligible performance degradation of ITO TFTs with passivation during negative bias stress(NBS)and negative bias temperature stress(NBTS)verifies the outstanding immunity to the water vapor of the SiO_(2)passivation layer.Overall,the ITO TFT with the t_(ch)of 6 nm and with SiO_(2)passivation exhibits the best performance in terms of electrical properties,uniformity,and reliability,which is promising in large-area production.展开更多
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
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
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
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
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
The advancement of imaging resolution has made the impact of multi-frequency composite jitter in satellite platforms on non-collinear time delay and integration(TDI)charge-coupled device(CCD)imaging systems increasing...The advancement of imaging resolution has made the impact of multi-frequency composite jitter in satellite platforms on non-collinear time delay and integration(TDI)charge-coupled device(CCD)imaging systems increasingly critical.Moreover,the accuracy of jitter detection is constrained by the limited inter-chip overlap region inherent to non-collinear TDI CCDs.To address these challenges,a multi-frequency jitter detection method is proposed,achieving sub-pixel level error extraction.Furthermore,a multi-frequency jitter fitting approach utilizing a scale-adjustable sliding window is introduced.For composite multi-frequency jitter,spectral analysis decomposes the relative jitter error curve,while the scale-adjustable sliding window enables frequency-division fitting and modeling.Validation experiments using Gaofen-8(GF-8)remote sensing satellite imagery detected jitter at 0.65,20,and 100 Hz in the cross-track direction and at 0.5,100,and 120 Hz in the along-track direction,demonstrating the method’s precision in detecting platform jitter at sub-pixel accuracy(<0.2 pixels)and its efficacy in fitting and modeling for non-collinear TDI CCD imaging systems subject to multi-frequency jitter.展开更多
Autonomous Underwater Vehicles(AUVs)are pivotal for deep-sea exploration and resource exploitation,yet their reliability in extreme underwater environments remains a critical barrier to widespread deployment.Through s...Autonomous Underwater Vehicles(AUVs)are pivotal for deep-sea exploration and resource exploitation,yet their reliability in extreme underwater environments remains a critical barrier to widespread deployment.Through systematic analysis of 150 peer-reviewed studies employing mixed-methods research,this review yields three principal advancements to the reliability analysis of AUVs.First,based on the hierarchical functional division of AUVs into six subsystems(propulsion system,navigation system,communication system,power system,environmental detection system,and emergency system),this study systematically identifies the primary failure modes and potential failure causes of each subsystem,providing theoretical support for fault diagnosis and reliability optimization.Subsequently,a comprehensive review of AUV reliability analysis methods is conducted from three perspectives:analytical methods,simulated methods,and surrogate model methods.The applicability and limitations of each method are critically analyzed to offer insights into their suitability for engineering applications.Finally,the study highlights key challenges and research hotpots in AUV reliability analysis,including reliability analysis under limited data,AI-driven reliability analysis,and human reliability analysis.Furthermore,the potential of multi-sensor data fusion,edge computing,and advanced materials in enhancing AUV environmental adaptability and reliability is explored.展开更多
Laser frequency microcombs provide a series of equidistant,coherent frequency markers across a broad spectrum,enabling advancements in laser spectroscopy,dense optical communications,precision distance metrology,and a...Laser frequency microcombs provide a series of equidistant,coherent frequency markers across a broad spectrum,enabling advancements in laser spectroscopy,dense optical communications,precision distance metrology,and astronomy.Here,we design and fabricate silicon nitride,dispersion-managed microresonators that effectively suppress avoided-mode crossings and achieve close-to-zero averaged dispersion.Both the stochastic noise and mode-locking dynamics of the resonator are numerically and experimentally investigated.First,we experimentally demonstrate thermally stabilized microcomb formation in the microresonator across different mode-locked states,showing negligible center frequency shifts and a broad frequency bandwidth.Next,we characterize the femtosecond timing jitter of the microcombs,supported by precise metrology of the timing phase and relative intensity noise.For the single-soliton state,we report a relative intensity noise of−153.2 dB∕Hz,close to the shot-noise limit,and a quantum-noise–limited timing jitter power spectral density of 0.4 as 2∕Hz at a 100 kHz offset frequency,measured using a self-heterodyne linear interferometer.In addition,we achieve an integrated timing jitter of 1.7 fs±0.07 fs,measured from 10 kHz to 1 MHz.Measuring and understanding these fundamental noise parameters in high clock rate frequency microcombs is critical for advancing soliton physics and enabling new applications in precision metrology.展开更多
Measurement precision of laser displacement sensor is subject to various factors,among which laser jitter and target tilt will directly lead to the position movement and shape variation of the laser spot,resulting in ...Measurement precision of laser displacement sensor is subject to various factors,among which laser jitter and target tilt will directly lead to the position movement and shape variation of the laser spot,resulting in displacement measurement errors,so that researchers have to do a lot of research on the spot centering algorithm to weaken the above effects,which can treat the symptoms but not the root cause.Starting from the source of the problem,this paper proposes a double focus double peak solution,which uses a reflector to change the direction of the optical path,so that the imaging spots of the designed two optical paths focus on the same CMOS,forming a double peak structure.When laser jitter or target tilt occurs,the center of the two laser spots is shifted,but they move in the same direction,while their relative position remains unchanged.Therefore,the displacement can be characterized by the relative position of the two laser spots,so that laser jitter and target tilt are suppressed from the source.However,the two spots imaged on CMOS form a non-Gaussian distributed double peak structure,so the conventional laser spot centering algorithms are no longer applicable.To this end,a double peak adaptive threshold waveform extraction method combined with grayscale gravity method is proposed for spot centering algorithm,which combines the suppression of laser jitter and target tilt from the source and the improvement of spot positioning precision which represents the displacement measurement precision,and is experimentally verified.展开更多
Quantum key distribution(QKD)achieves information-theoretic security based on quantum mechanics principles,where single-photon detectors(SPDs)serve as critical components.This study focuses on the sinusoidal gated SPD...Quantum key distribution(QKD)achieves information-theoretic security based on quantum mechanics principles,where single-photon detectors(SPDs)serve as critical components.This study focuses on the sinusoidal gated SPDs widely used in high-speed QKD systems.We investigate the mechanisms underlying the rising-edge jitter in detection signals,identifying contributions from factors such as the temporal width of injected optical pulses,avalanche generation processes,avalanche signal extraction,and pulse discrimination.To address the issue of excessive jitter-induced bit errors,we propose a retiming scheme that utilizes coincidence signals synchronized with the sinusoidal gating signal.This approach effectively suppresses detection signal jitter and reduces the after-pulse probability of the detector.Experimental validation using a high-precision time-to-digital converter(TDC)demonstrates a significant reduction in the rising-edge jitter distribution after applying the suppression scheme.The proposed method features clear principles and straightforward engineering implementation,avoiding direct interference with the detector’s operational processes.The designed high-speed sinusoidal gated InGaAs/InP SPD operates at 1.25 GHz,achieving a remarkable reduction in after-pulse probability from 10.7%(without jitter suppression)to 0.72%,thereby enhancing the overall performance of QKD systems.展开更多
Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative char...Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative characterization of interface debonding mechanisms and the challenge of identifying key factors have made precise control of process variables difficult,resulting in unpredictable failure risks.This paper presents an improved fuzzy failure probability evaluation method that combines fuzzy fault tree analysis with expert knowledge,transforming process data into fuzzy failure probability to accurately assess debonding probabilities.The predictive model is constructed through a general regression neural network and optimized using the particle swarm optimization algorithm.Sensitivity analysis is conducted to identify key decision variables,including normal force,grain rotation speed,and adhesive weight,which are verified experimentally.Compared with classical models,the maximum error margin of the constructed reliability prediction model is only 0.02%,and it has high stability.The experimental results indicate that the main factors affecting debonding are processing roughness and coating uniformity.Controlling the key decision variable as the median resulted in a maximum increase of 200.7%in bonding strength.The feasibility of the improved method has been verified,confirming that identifying key decision variables has the ability to improve bonding reliability.The proposed method simplifies the evaluation of propellant interface bonding reliability under complex conditions by quantifying the relationship between process parameters and failure risk,enabling targeted management of key decision variables.展开更多
Fractional-N phase-locked loops(PLLs)are widely deployed in high-speed communication systems to generate local oscillator(LO)or clock signals with precise frequency.To support sophisticated modulations for increasing ...Fractional-N phase-locked loops(PLLs)are widely deployed in high-speed communication systems to generate local oscillator(LO)or clock signals with precise frequency.To support sophisticated modulations for increasing the data rate,the PLL needs to generate low-jitter output[1].展开更多
Amorphous microwires(AMWs)are well known for their high strength and elastic limit,making them excellent candidates for various engineering applications.However,one of the key challenges in utilizing AMWs is their inh...Amorphous microwires(AMWs)are well known for their high strength and elastic limit,making them excellent candidates for various engineering applications.However,one of the key challenges in utilizing AMWs is their inherent variability in mechanical performance,particularly in achieving stable fracture strength across different compositions.This study provides critical insights into the relationship between microstructure and mechanical behavior by investigating CuZr-based AMWs with varying compositions during quasi-static tensile fracture.Specifically,uniaxial tensile tests on Cu_(48)Zr_(48)Al_(4),Cu_(45)Zr_(45)Co_(10),and Cu_(48)Zr_(47.2)Al_(4)Nb_(0.8) AMWs,combined with log-normal and Weibull statistical analysis,revealed that Cu_(48)Zr_(47.2)Al4Nb_(0.8) exhibits the highest fracture reliability(mTr=3.97)and fracture threshold(σμTr=1307 MPa),while Cu_(48)Zr_(48)Al_(4) showed the lowest performance(m_(Tr)=3.08,σ_(μTr)=1085 MPa).Moreover,a standard power-law relationship exists between the characteristic size L of the fracture surface and the degree of order O was established,linking atomic mixing enthalpy and atomic radius to structural homogeneity and fracture behavior.This study provides an important perspective for optimizing AMW compositions to achieve higher fracture strength and improve the reliability for engineering applications.展开更多
In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a ...In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a distributed data source trust assessment management framework,a trust quantification model,and a dynamic adjustment mechanism are proposed.Themodel integrates the Analytic Hierarchy Process(AHP)and Dempster-Shafer(D-S)evidence theory to determine attribute weights and calculate direct trust values,while the PageRank algorithm is employed to derive indirect trust values.Thedirect and indirect trust values are then combined to compute the comprehensive trust value of the data source.Furthermore,a dynamic adjustment mechanism is introduced to continuously update the comprehensive trust value based on historical assessment data.By leveraging the collaborative efforts of multiple nodes in the distributed network,the proposed framework enables a comprehensive,dynamic,and objective evaluation of data source trustworthiness.Extensive experimental analyses demonstrate that the trust quantification model effectively handles large-scale data source trust assessments,exhibiting both strong trust differentiation capability and high robustness.展开更多
The novel structural reliability methodology presented in this study is especially well suited for multidimensional structural dynamics that are physically measured or numerically simulated over a representative timel...The novel structural reliability methodology presented in this study is especially well suited for multidimensional structural dynamics that are physically measured or numerically simulated over a representative timelapse.The Gaidai multivariate reliability method is applied to an operational offshore Jacket platform that operates in Bohai Bay.This study demonstrates the feasibility of this method to accurately estimate collapse risks in dynamic systems under in situ environmental stressors.Modern reliability approaches do not cope easily with the high dimensionality of real engineering dynamic systems,as well as nonlinear intercorrelations between various structural components.The Jacket offshore platform is chosen as the case study for this reliability analysis because of the presence of various hotspot stresses that synchronously arise in its structural parts.The authors provide a straightforward,precise method for estimating overall risks of operational failure,damage,or hazard for nonlinear multidimensional dynamic systems.The latter tool is important for offshore engineers during the design stage.展开更多
Nodal pricing is a critical mechanism in electricity markets,utilized to determine the cost of power transmission to various nodes within a distribution network.As power systems evolve to incorporate higher levels of ...Nodal pricing is a critical mechanism in electricity markets,utilized to determine the cost of power transmission to various nodes within a distribution network.As power systems evolve to incorporate higher levels of renewable energy and face increasing demand fluctuations,traditional nodal pricing models often fall short to meet these new challenges.This research introduces a novel enhanced nodal pricing mechanism for distribution networks,integrating advanced optimization techniques and hybrid models to overcome these limitations.The primary objective is to develop a model that not only improves pricing accuracy but also enhances operational efficiency and system reliability.This study leverages cutting-edge hybrid algorithms,combining elements of machine learning with conventional optimization methods,to achieve superior performance.Key findings demonstrate that the proposed hybrid nodal pricing model significantly reduces pricing errors and operational costs compared to conventional methods.Through extensive simulations and comparative analysis,the model exhibits enhanced performance under varying load conditions and increased levels of renewable energy integration.The results indicate a substantial improvement in pricing precision and network stability.This study contributes to the ongoing discourse on optimizing electricity market mechanisms and provides actionable insights for policymakers and utility operators.By addressing the complexities of modern power distribution systems,our research offers a robust solution that enhances the efficiency and reliability of power distribution networks,marking a significant advancement in the field.展开更多
文摘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.
基金Project supported by the National Natural Science Foundation of China(Grant No.12472033)。
文摘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.
基金supported in part by the National Natural Science Foundation of China(62404110,62274033)Natural Science Foundation of Jiangsu Province(BK20221453)+1 种基金Fundamental Research Funds for the Central UniversitiesNatural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(NY223159)。
文摘In this work,we demonstrated the InSnO(ITO)TFTs passivated with SiO_(2)via the PECVD process compatible with large-area production for the first time.The passivated ITO TFTs with various channel thicknesses(t_(ch)=4,5,6 nm)exhibit excellent electrical performance and superior uniformity.The reliability properties of ITO TFTs were evaluated in detail under positive bias stress(PBS)conditions before and after passivation.Compared to the devices without passivation,the passivated devices have only 50%threshold voltage degradation(ΔV_(th))and 50%newly generated traps due to excellent isolation of the ambient atmosphere.The negligible performance degradation of ITO TFTs with passivation during negative bias stress(NBS)and negative bias temperature stress(NBTS)verifies the outstanding immunity to the water vapor of the SiO_(2)passivation layer.Overall,the ITO TFT with the t_(ch)of 6 nm and with SiO_(2)passivation exhibits the best performance in terms of electrical properties,uniformity,and reliability,which is promising in large-area production.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘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.
基金Funded by the National Natural Science Foundation of China(No.52178216)the Research on the Durability and Application of High-performance Concrete for Highway Engineering in the Cold and Arid Salt Areas of Northwest China(No.2022-24)the Construction Project of the Scientific Research Platform of Provincial Enterprises Supported by the Capital Operating Budget of Gansu Province(No.2023GZ018)。
文摘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.
基金Supported by National Natural Science Foundation of China(Grant No.U2141246)Key Laboratory of Artillery Launch and Control Technology of China(Grant No.2021-001)Basic Research of State Administration of Science Technology and Industry for National Defense of China(Grant No.JXJL202208A001).
文摘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.
基金supported by the Major Program of National Natural Science Foundation of China(Grant No.42090055)the National Key ScientificInstruments and Equipment Development Projects of China(Grant No.41827808)the National Nature Science Foundation of China(Grant No.42207216).
文摘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.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
文摘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.
文摘The advancement of imaging resolution has made the impact of multi-frequency composite jitter in satellite platforms on non-collinear time delay and integration(TDI)charge-coupled device(CCD)imaging systems increasingly critical.Moreover,the accuracy of jitter detection is constrained by the limited inter-chip overlap region inherent to non-collinear TDI CCDs.To address these challenges,a multi-frequency jitter detection method is proposed,achieving sub-pixel level error extraction.Furthermore,a multi-frequency jitter fitting approach utilizing a scale-adjustable sliding window is introduced.For composite multi-frequency jitter,spectral analysis decomposes the relative jitter error curve,while the scale-adjustable sliding window enables frequency-division fitting and modeling.Validation experiments using Gaofen-8(GF-8)remote sensing satellite imagery detected jitter at 0.65,20,and 100 Hz in the cross-track direction and at 0.5,100,and 120 Hz in the along-track direction,demonstrating the method’s precision in detecting platform jitter at sub-pixel accuracy(<0.2 pixels)and its efficacy in fitting and modeling for non-collinear TDI CCD imaging systems subject to multi-frequency jitter.
基金The National Key R&D Program Projects(Grant No.2022YFC2803601)the Natural Science Foundation of Shandong Province(Grant No.ZR2021YQ29)+1 种基金the Natural Science Foundation of Heilongjiang Province(Grant No.YQ2024E036)the Taishan Scholars Project(Grant No.tsqn202312317).
文摘Autonomous Underwater Vehicles(AUVs)are pivotal for deep-sea exploration and resource exploitation,yet their reliability in extreme underwater environments remains a critical barrier to widespread deployment.Through systematic analysis of 150 peer-reviewed studies employing mixed-methods research,this review yields three principal advancements to the reliability analysis of AUVs.First,based on the hierarchical functional division of AUVs into six subsystems(propulsion system,navigation system,communication system,power system,environmental detection system,and emergency system),this study systematically identifies the primary failure modes and potential failure causes of each subsystem,providing theoretical support for fault diagnosis and reliability optimization.Subsequently,a comprehensive review of AUV reliability analysis methods is conducted from three perspectives:analytical methods,simulated methods,and surrogate model methods.The applicability and limitations of each method are critically analyzed to offer insights into their suitability for engineering applications.Finally,the study highlights key challenges and research hotpots in AUV reliability analysis,including reliability analysis under limited data,AI-driven reliability analysis,and human reliability analysis.Furthermore,the potential of multi-sensor data fusion,edge computing,and advanced materials in enhancing AUV environmental adaptability and reliability is explored.
基金support from the Lawrence Livermore National Laboratory(Grant No.B622827)the National Science Foundation(Grant Nos.1824568,1810506,1741707,and 1829071)the Office of Naval Research(Grant No.N00014-16-1-2094).
文摘Laser frequency microcombs provide a series of equidistant,coherent frequency markers across a broad spectrum,enabling advancements in laser spectroscopy,dense optical communications,precision distance metrology,and astronomy.Here,we design and fabricate silicon nitride,dispersion-managed microresonators that effectively suppress avoided-mode crossings and achieve close-to-zero averaged dispersion.Both the stochastic noise and mode-locking dynamics of the resonator are numerically and experimentally investigated.First,we experimentally demonstrate thermally stabilized microcomb formation in the microresonator across different mode-locked states,showing negligible center frequency shifts and a broad frequency bandwidth.Next,we characterize the femtosecond timing jitter of the microcombs,supported by precise metrology of the timing phase and relative intensity noise.For the single-soliton state,we report a relative intensity noise of−153.2 dB∕Hz,close to the shot-noise limit,and a quantum-noise–limited timing jitter power spectral density of 0.4 as 2∕Hz at a 100 kHz offset frequency,measured using a self-heterodyne linear interferometer.In addition,we achieve an integrated timing jitter of 1.7 fs±0.07 fs,measured from 10 kHz to 1 MHz.Measuring and understanding these fundamental noise parameters in high clock rate frequency microcombs is critical for advancing soliton physics and enabling new applications in precision metrology.
基金the Biomedical Science and Technology Support Special Project of Shanghai Science and Technology Committee(No.20S31908300)。
文摘Measurement precision of laser displacement sensor is subject to various factors,among which laser jitter and target tilt will directly lead to the position movement and shape variation of the laser spot,resulting in displacement measurement errors,so that researchers have to do a lot of research on the spot centering algorithm to weaken the above effects,which can treat the symptoms but not the root cause.Starting from the source of the problem,this paper proposes a double focus double peak solution,which uses a reflector to change the direction of the optical path,so that the imaging spots of the designed two optical paths focus on the same CMOS,forming a double peak structure.When laser jitter or target tilt occurs,the center of the two laser spots is shifted,but they move in the same direction,while their relative position remains unchanged.Therefore,the displacement can be characterized by the relative position of the two laser spots,so that laser jitter and target tilt are suppressed from the source.However,the two spots imaged on CMOS form a non-Gaussian distributed double peak structure,so the conventional laser spot centering algorithms are no longer applicable.To this end,a double peak adaptive threshold waveform extraction method combined with grayscale gravity method is proposed for spot centering algorithm,which combines the suppression of laser jitter and target tilt from the source and the improvement of spot positioning precision which represents the displacement measurement precision,and is experimentally verified.
基金supported by the Major Scientific and Technological Special Project of Anhui Province(202103a13010004)the Major Scientific and Technological Special Project of Hefei City(2021DX007)the Manufacturing Industry Project of Attracting Talents and Wisdom of Anhui Province(JB24179).
文摘Quantum key distribution(QKD)achieves information-theoretic security based on quantum mechanics principles,where single-photon detectors(SPDs)serve as critical components.This study focuses on the sinusoidal gated SPDs widely used in high-speed QKD systems.We investigate the mechanisms underlying the rising-edge jitter in detection signals,identifying contributions from factors such as the temporal width of injected optical pulses,avalanche generation processes,avalanche signal extraction,and pulse discrimination.To address the issue of excessive jitter-induced bit errors,we propose a retiming scheme that utilizes coincidence signals synchronized with the sinusoidal gating signal.This approach effectively suppresses detection signal jitter and reduces the after-pulse probability of the detector.Experimental validation using a high-precision time-to-digital converter(TDC)demonstrates a significant reduction in the rising-edge jitter distribution after applying the suppression scheme.The proposed method features clear principles and straightforward engineering implementation,avoiding direct interference with the detector’s operational processes.The designed high-speed sinusoidal gated InGaAs/InP SPD operates at 1.25 GHz,achieving a remarkable reduction in after-pulse probability from 10.7%(without jitter suppression)to 0.72%,thereby enhancing the overall performance of QKD systems.
基金supported in part by the Equipment Development Pre-research Project funded by Equipment Development Department,PRC under Grant No.50923010501Fundamental Research Program of Shenyang Institute of Automation(SIA),Chinese Academy of Sciencess under Grant No.355060201。
文摘Bonding quality at the interface of solid propellant grains is crucial for the reliability and safety of solid rocket motors.Although bonding reliability is influenced by numerous factors,the lack of quantitative characterization of interface debonding mechanisms and the challenge of identifying key factors have made precise control of process variables difficult,resulting in unpredictable failure risks.This paper presents an improved fuzzy failure probability evaluation method that combines fuzzy fault tree analysis with expert knowledge,transforming process data into fuzzy failure probability to accurately assess debonding probabilities.The predictive model is constructed through a general regression neural network and optimized using the particle swarm optimization algorithm.Sensitivity analysis is conducted to identify key decision variables,including normal force,grain rotation speed,and adhesive weight,which are verified experimentally.Compared with classical models,the maximum error margin of the constructed reliability prediction model is only 0.02%,and it has high stability.The experimental results indicate that the main factors affecting debonding are processing roughness and coating uniformity.Controlling the key decision variable as the median resulted in a maximum increase of 200.7%in bonding strength.The feasibility of the improved method has been verified,confirming that identifying key decision variables has the ability to improve bonding reliability.The proposed method simplifies the evaluation of propellant interface bonding reliability under complex conditions by quantifying the relationship between process parameters and failure risk,enabling targeted management of key decision variables.
基金supported by the University of Macao Research Fund under Grant MYRG-GRG2024-00298-IMEby the Macao Science and Technology Development Fund(FDCT)under Grant 0103/2022/AFJ.
文摘Fractional-N phase-locked loops(PLLs)are widely deployed in high-speed communication systems to generate local oscillator(LO)or clock signals with precise frequency.To support sophisticated modulations for increasing the data rate,the PLL needs to generate low-jitter output[1].
基金supported by the National Natural Science Foundation of China(Nos.52071118,52371025,and 52171154)。
文摘Amorphous microwires(AMWs)are well known for their high strength and elastic limit,making them excellent candidates for various engineering applications.However,one of the key challenges in utilizing AMWs is their inherent variability in mechanical performance,particularly in achieving stable fracture strength across different compositions.This study provides critical insights into the relationship between microstructure and mechanical behavior by investigating CuZr-based AMWs with varying compositions during quasi-static tensile fracture.Specifically,uniaxial tensile tests on Cu_(48)Zr_(48)Al_(4),Cu_(45)Zr_(45)Co_(10),and Cu_(48)Zr_(47.2)Al_(4)Nb_(0.8) AMWs,combined with log-normal and Weibull statistical analysis,revealed that Cu_(48)Zr_(47.2)Al4Nb_(0.8) exhibits the highest fracture reliability(mTr=3.97)and fracture threshold(σμTr=1307 MPa),while Cu_(48)Zr_(48)Al_(4) showed the lowest performance(m_(Tr)=3.08,σ_(μTr)=1085 MPa).Moreover,a standard power-law relationship exists between the characteristic size L of the fracture surface and the degree of order O was established,linking atomic mixing enthalpy and atomic radius to structural homogeneity and fracture behavior.This study provides an important perspective for optimizing AMW compositions to achieve higher fracture strength and improve the reliability for engineering applications.
基金funded by Haikou Science and Technology Plan Project(2022-007),in part by key Laboratory of PK System Technologies Research of Hainan,China.
文摘In the data transaction process within a data asset trading platform,quantifying the trustworthiness of data source nodes is challenging due to their numerous attributes and complex structures.To address this issue,a distributed data source trust assessment management framework,a trust quantification model,and a dynamic adjustment mechanism are proposed.Themodel integrates the Analytic Hierarchy Process(AHP)and Dempster-Shafer(D-S)evidence theory to determine attribute weights and calculate direct trust values,while the PageRank algorithm is employed to derive indirect trust values.Thedirect and indirect trust values are then combined to compute the comprehensive trust value of the data source.Furthermore,a dynamic adjustment mechanism is introduced to continuously update the comprehensive trust value based on historical assessment data.By leveraging the collaborative efforts of multiple nodes in the distributed network,the proposed framework enables a comprehensive,dynamic,and objective evaluation of data source trustworthiness.Extensive experimental analyses demonstrate that the trust quantification model effectively handles large-scale data source trust assessments,exhibiting both strong trust differentiation capability and high robustness.
文摘The novel structural reliability methodology presented in this study is especially well suited for multidimensional structural dynamics that are physically measured or numerically simulated over a representative timelapse.The Gaidai multivariate reliability method is applied to an operational offshore Jacket platform that operates in Bohai Bay.This study demonstrates the feasibility of this method to accurately estimate collapse risks in dynamic systems under in situ environmental stressors.Modern reliability approaches do not cope easily with the high dimensionality of real engineering dynamic systems,as well as nonlinear intercorrelations between various structural components.The Jacket offshore platform is chosen as the case study for this reliability analysis because of the presence of various hotspot stresses that synchronously arise in its structural parts.The authors provide a straightforward,precise method for estimating overall risks of operational failure,damage,or hazard for nonlinear multidimensional dynamic systems.The latter tool is important for offshore engineers during the design stage.
文摘Nodal pricing is a critical mechanism in electricity markets,utilized to determine the cost of power transmission to various nodes within a distribution network.As power systems evolve to incorporate higher levels of renewable energy and face increasing demand fluctuations,traditional nodal pricing models often fall short to meet these new challenges.This research introduces a novel enhanced nodal pricing mechanism for distribution networks,integrating advanced optimization techniques and hybrid models to overcome these limitations.The primary objective is to develop a model that not only improves pricing accuracy but also enhances operational efficiency and system reliability.This study leverages cutting-edge hybrid algorithms,combining elements of machine learning with conventional optimization methods,to achieve superior performance.Key findings demonstrate that the proposed hybrid nodal pricing model significantly reduces pricing errors and operational costs compared to conventional methods.Through extensive simulations and comparative analysis,the model exhibits enhanced performance under varying load conditions and increased levels of renewable energy integration.The results indicate a substantial improvement in pricing precision and network stability.This study contributes to the ongoing discourse on optimizing electricity market mechanisms and provides actionable insights for policymakers and utility operators.By addressing the complexities of modern power distribution systems,our research offers a robust solution that enhances the efficiency and reliability of power distribution networks,marking a significant advancement in the field.
