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
Reliability analysis of soil slopes under rainfall is an important task for landslide risk assessment.Previous studies rarely contribute to the probabilistic analysis of slope stability under rainfall with reinforceme...Reliability analysis of soil slopes under rainfall is an important task for landslide risk assessment.Previous studies rarely contribute to the probabilistic analysis of slope stability under rainfall with reinforcement.A new method is suggested for reliability analysis of soil slopes stabilized with piles under rainfall.First,an efficient numerical model is exploited for slope stability analysis,where two types of slope failure modes,i.e.,plastic flow and local failure are considered.To address the blocking effect of piles during seepage analysis,the equivalent hydraulic conductivity of the pile area is estimated according to the effective medium theory.The stabilizing force of piles is investigated by an analytical approach.For saving computational effort,the response surface is established based on a multi-class classification model to predict two types of slope failure modes.Finally,uncertainties in soil parameters and rainfall events are both modelled,and the failure probability of soil slopes within a given time period is assessed through Monte Carlo simulation.An illustrative example is used to demonstrate the performance of the suggested method.It is found that the slope is mainly controlled by local failure.As the pile spacing increases,the likelihood of plastic flow significantly increases.As the piles are located near the slope crest,plastic flow is effectively prevented and the slope is better stabilized against rainfall.If rainfall uncertainties are not considered,the slope failure probability is significantly overestimated.Overall,this study can provide a useful guidance for the design of pile-stabilized slopes against rainfall infiltration.展开更多
Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status...Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status.Each of these methods contributes unique diagnostic insights,enhancing the overall assessment of patient condition.Nevertheless,the amalgamation of data from multiple modalities presents difficulties due to disparities in resolution,data collection methods,and noise levels.While traditional models like Convolutional Neural Networks(CNNs)excel in single-modality tasks,they struggle to handle multi-modal complexities,lacking the capacity to model global relationships.This research presents a novel approach for examining multi-modal medical imagery using a transformer-based system.The framework employs self-attention and cross-attention mechanisms to synchronize and integrate features across various modalities.Additionally,it shows resilience to variations in noise and image quality,making it adaptable for real-time clinical use.To address the computational hurdles linked to transformer models,particularly in real-time clinical applications in resource-constrained environments,several optimization techniques have been integrated to boost scalability and efficiency.Initially,a streamlined transformer architecture was adopted to minimize the computational load while maintaining model effectiveness.Methods such as model pruning,quantization,and knowledge distillation have been applied to reduce the parameter count and enhance the inference speed.Furthermore,efficient attention mechanisms such as linear or sparse attention were employed to alleviate the substantial memory and processing requirements of traditional self-attention operations.For further deployment optimization,researchers have implemented hardware-aware acceleration strategies,including the use of TensorRT and ONNX-based model compression,to ensure efficient execution on edge devices.These optimizations allow the approach to function effectively in real-time clinical settings,ensuring viability even in environments with limited resources.Future research directions include integrating non-imaging data to facilitate personalized treatment and enhancing computational efficiency for implementation in resource-limited environments.This study highlights the transformative potential of transformer models in multi-modal medical imaging,offering improvements in diagnostic accuracy and patient care outcomes.展开更多
The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a mult...The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.展开更多
Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence spee...Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence speed of structural reliability analysis,an improved coati optimization algorithm(COA)is proposed in this paper.In this study,the social learning strategy is used to improve the coati optimization algorithm(SL-COA),which improves the convergence speed and robustness of the newheuristic optimization algorithm.Then,the SL-COAis comparedwith the latest heuristic optimization algorithms such as the original COA,whale optimization algorithm(WOA),and osprey optimization algorithm(OOA)in the CEC2005 and CEC2017 test function sets and two engineering optimization design examples.The optimization results show that the proposed SL-COA algorithm has a high competitiveness.Secondly,this study introduces the SL-COA algorithm into the MPP(Most Probable Point)search process based on FORM and constructs a new reliability analysis method.Finally,the proposed reliability analysis method is verified by four mathematical examples and two engineering examples.The results show that the proposed SL-COA-assisted FORM exhibits fast convergence and avoids premature convergence to local optima as demonstrated by its successful application to problems such as composite cylinder design and support bracket analysis.展开更多
The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum S...The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum State,Sudan.It also aims to examine whether test’s factor structure in this sample replicated that of the original WPPSI-III.The study sample consisted of 384 kindergarten and primary school children in Khartoum State(females=50%mean age=4.14,SD=1.37),selected using stratified random sampling across its seven localities:Khartoum,Jebel Awliya,Khartoum Bahri,East Nile,Omdurman,Ombada,Karari.For concurrent validation,the children additionally completed the Goodenough Draw-a-Man Test,and the Colored Progressive Matrices.WPPSI-III scores demonstrated high internal consistency across the subtest items.Confirmatory factor analysis indicators for total,verbal,and performance intelligence were all excellent.The scale also showed weak to strong score stability ranging from 0.25(weak)to 0.88(strong)based on the Spearman-Brown equation,0.25 to 0.75 based on the Guttman split-half method.The Cronbach’s alpha coefficient scores ranged from 0.54 to 0.93.The WPPSI-III and Goodenough Draw-a-Man Test scores concurrent validity scores were poor(0.05)to modest(0.31),and while those with the Colored Progressive Matrices test were poor(r=0.04–0.18).Thesefindings provide evidence to suggest that the WPPSI-III is appropriate for research use with kindergarten and lower primary school students in Khartoum State,Sudan.展开更多
In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher ac...In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher accuracy,the additional computation of the Hessian matrix leads to lower computational efficiency.Additionally,when the dimensionality of the random variables is high,the approximation formula of SORM can result in larger errors.To address these issues,a structural reliability analysis method based on Kriging and spherical cap area integral is proposed.Firstly,this method integrates FORM with the quasi-Newton algorithm Broyden-Fletcher-Goldfarb-Shanno(BFGS),trains the Kriging model by using sample points from the algorithm’s iteration process,and combines the Kriging model with gradient information to approximate the Hessian matrix.Then,the failure surface is approximated as a rotating paraboloid,utilizing the spherical cap to replace the complex surface.For the n-dimensional case,the hyperspherical cap area expression is combined with the integral method to calculate the failure probability.Finally,the method is validated through three examples,demonstrating improved computational accuracy and efficiency compared to traditional methods.展开更多
It is important to determine the safety lifetime of Multi-mode Time-Dependent Structural System(MTDSS). However, there is still a lack of corresponding analysis methods.Therefore, this paper establishes MTDSS safety l...It is important to determine the safety lifetime of Multi-mode Time-Dependent Structural System(MTDSS). However, there is still a lack of corresponding analysis methods.Therefore, this paper establishes MTDSS safety lifetime model firstly, and then proposes a Kriging surrogate model based method to estimate safety lifetime. The first step of proposed method is to construct the Kriging model of MTDSS performance function by using extremum learning function. By identifying possible extremum mode of MTDSS, the performance function of MTDSS can be equivalently transformed into the one of Single-mode Time-Dependent Structure(STDS).The second step is to use the Advanced First Failure Instant Learning Function(AFFILF) to train the Kriging model constructed in the first step, so that the convergent Kriging model can identify the possible First Failure Instant(FFI) of STDS. Then safety lifetime can be searched quickly by dichotomy search. By using AFFILF, the minimum instant that the state is not accurately identified by the current Kriging model is selected as the training point, which avoids the unnecessary calculation which may be introduced into the existing First Failure Instant Learning Function(FFILF).In addition, the Candidate Sample Pool(CSP) reduction strategy is also adopted. By adaptively deleting the random candidate sample points whose FFI have been accurately identified by the current Kriging model, the training efficiency is further improved. Three cases show that the proposed method is accurate and efficient.展开更多
Response surface method is used to study the reliability analysis of laterally loaded piles in sloping ground. A development load-displacement （p-y） curve for laterally loaded pile response in sloping ground is used...Response surface method is used to study the reliability analysis of laterally loaded piles in sloping ground. A development load-displacement （p-y） curve for laterally loaded pile response in sloping ground is used to model the pile-soil system, both the pile head displacement and the maximum bending moment of the piles are used as the performance criteria in this study. The reliability analysis method of the laterally loaded pile in sloping ground under the pile head displacement and the maximum bending moment failure modes is proposed, which is in good agreement with the Monte Carlo method. The influences on the probability index of failure by a number of parameters are discussed. It is shown that the variability of pile head displacement increases with the increase in the coefficients of variation of ultimate bearing capacity factor （Npu）, secant elastic modulus at 50%（E50） and level load （H）. A negative correlation between Npu and non-dimensional factor （λ） leads to less spread out probability density function （PDF） of the pile head displacement;in contrast, a positive correlation between Npu andλgives a great variation in the PDF of pile head displacement. As for bearing capacity factor on ground surface （Npo） and λ, both negative and positive correlations between them give a great variation in the PDF of pile head displacement, and a negative correlation will obviously increase the variability of the response.展开更多
Aim To define a mixed redundant model(MRM), improving the reliability of C 3I system. Methods The model combined the technology characters of two? unit system with one warm stand by unit and function substitute s...Aim To define a mixed redundant model(MRM), improving the reliability of C 3I system. Methods The model combined the technology characters of two? unit system with one warm stand by unit and function substitute system. The reliability and availability equations of MRM were deduced. Results and Conclusion Compared with several other reliability models, it has obvious effect upon improving the system reliability. The effect? cost rate is very high among these models. The model can be used in reliability design, evaluation and check of C 3I system. Only a little attached cost is needed to improve C 3I system reliability effectively.展开更多
The reliability analysis, based on the reliability index method, of two dimensional slopes is generalized by taking Sarma′s acceleration as the performance function. That is to say, a general expression of the perfo...The reliability analysis, based on the reliability index method, of two dimensional slopes is generalized by taking Sarma′s acceleration as the performance function. That is to say, a general expression of the performance function is given under various kinds of slice methods, even under various shapes of slice partition, beyond the traditional vertical slice method. A simple example shows explicitly the relationship of four commonly used slice methods in the slope reliability analysis. It is also found that the results of the reliability analysis are basically consistent with those of the stability analysis based on Sarma′s method.展开更多
This article presents two new kinds of artificial neural network （ANN） response surface methods （RSMs）： the ANN RSM based on early stopping technique （ANNRSM-1）, and the ANN RSM based on regularization theory ...This article presents two new kinds of artificial neural network （ANN） response surface methods （RSMs）： the ANN RSM based on early stopping technique （ANNRSM-1）, and the ANN RSM based on regularization theory （ANNRSM-2）. The following improvements are made to the conventional ANN RSM （ANNRSM-0）： 1） by monitoring the validation error during the training process, ANNRSM-1 determines the early stopping point and the training stopping point, and the weight vector at the early stopping point, which corresponds to the ANN model with the optimal generalization, is finally returned as the training result; 2） according to the regularization theory, ANNRSM-2 modifies the conventional training performance function by adding to it the sum of squares of the network weights, so the network weights are forced to have smaller values while the training error decreases. Tests show that the performance of ANN RSM becomes much better due to the above-mentioned improvements： first, ANNRSM-1 and ANNRSM-2 approximate to the limit state function （LSF） more accurately than ANNRSM-0; second, the estimated failure probabilities given by ANNRSM-1 and ANNRSM-2 have smaller errors than that obtained by ANNRSM-0; third, compared with ANNRSM-0, ANNRSM-1 and ANNRSM-2 require much fewer data samples to achieve stable failure probability results.展开更多
A Bayesian approach is proposed for the inference of the geotechnical parameters used in slope design.The methodology involves the construction of posterior probability distributions that combine prior information on ...A Bayesian approach is proposed for the inference of the geotechnical parameters used in slope design.The methodology involves the construction of posterior probability distributions that combine prior information on the parameter values with typical data from laboratory tests and site investigations used in design.The posterior distributions are often complex,multidimensional functions whose analysis requires the use of Markov chain Monte Carlo(MCMC)methods.These procedures are used to draw representative samples of the parameters investigated,providing information on their best estimate values,variability and correlations.The paper describes the methodology to define the posterior distributions of the input parameters for slope design and the use of these results for evaluation of the reliability of a slope with the first order reliability method(FORM).The reliability analysis corresponds to a forward stability analysis of the slope where the factor of safety(FS)is calculated with a surrogate model from the more likely values of the input parameters.The Bayesian model is also used to update the estimation of the input parameters based on the back analysis of slope failure.In this case,the condition FS?1 is treated as a data point that is compared with the model prediction of FS.The analysis requires a sufficient number of observations of failure to outbalance the effect of the initial input parameters.The parameters are updated according to their uncertainty,which is determined by the amount of data supporting them.The methodology is illustrated with an example of a rock slope characterised with a Hoek-Brown rock mass strength.The example is used to highlight the advantages of using Bayesian methods for the slope reliability analysis and to show the effects of data support on the results of the updating process from back analysis of failure.展开更多
With the uncertainties related to operating conditions,in-service non-destructive testing（NDT） measurements and material properties considered in the structural integrity assessment,probabilistic analysis based on t...With the uncertainties related to operating conditions,in-service non-destructive testing（NDT） measurements and material properties considered in the structural integrity assessment,probabilistic analysis based on the failure assessment diagram（FAD） approach has recently become an important concern.However,the point density revealing the probabilistic distribution characteristics of the assessment points is usually ignored.To obtain more detailed and direct knowledge from the reliability analysis,an improved probabilistic fracture mechanics（PFM） assessment method is proposed.By integrating 2D kernel density estimation（KDE） technology into the traditional probabilistic assessment,the probabilistic density of the randomly distributed assessment points is visualized in the assessment diagram.Moreover,a modified interval sensitivity analysis is implemented and compared with probabilistic sensitivity analysis.The improved reliability analysis method is applied to the assessment of a high pressure pipe containing an axial internal semi-elliptical surface crack.The results indicate that these two methods can give consistent sensitivities of input parameters,but the interval sensitivity analysis is computationally more efficient.Meanwhile,the point density distribution and its contour are plotted in the FAD,thereby better revealing the characteristics of PFM assessment.This study provides a powerful tool for the reliability analysis of critical structures.展开更多
Redundant actuator is the key component of Fly-By-Wire （FBW） system in which exists the inherent force fighting among different redundant channels at colligation point, This paper establishes the mathematical model ...Redundant actuator is the key component of Fly-By-Wire （FBW） system in which exists the inherent force fighting among different redundant channels at colligation point, This paper establishes the mathematical model of quad redundant actuator （QRA）, investigates the force equalization algorithm and carries out the performance degradation simulation and reliability analysis under the first failure and the second failure. The results indicate that the optimal equalization algorithm can solve the force fighting effectively, and the QRA can operate at degradation performance continuously under the first failure and the second failure. With the dynamic fault tree analysis, this paper calculates the reliability based on the performance of QRA and proves that the redundant actuator has very high reliability and safety.展开更多
Electromagnetic relay in aerospace is one of the main electronic components in aerospace electronic systems for information transfer, control and power distribution, and its reliability will influence the reliability ...Electromagnetic relay in aerospace is one of the main electronic components in aerospace electronic systems for information transfer, control and power distribution, and its reliability will influence the reliability of the whole aerospace electronic systems. Reliability design is the key technique of electromagnetic relay reliability engineering. This paper synthetically analyzes the present reliability design methods, and presents the reliability tolerance analyzing mathematic models of electromagnetic force basing on orthogonal design, mechanical spring force basing on probability statistics theory, and matching characteristics of electromagnetic force and mechanical spring force basing on method of stressstrength interference. Some instructive conclusions are draw by researching on the reliability tolerance of some type electromagnetic relay in aerospace.展开更多
To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method (AMRSM) was proposed for...To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method (AMRSM) was proposed for multi-failure mode sensitivity analysis for reliability. The mathematical model of AMRSM was established and the basic principle of multi-failure mode sensitivity analysis for reliability with AMRSM was given. The important parameters of turbine blisk failures are obtained by the multi-failure mode sensitivity analysis of turbine blisk. Through the reliability sensitivity analyses of multiple failure modes (deformation, stress and strain) with the proposed method considering fluid-thermal-solid interaction, it is shown that the comprehensive reliability of turbine blisk is 0.9931 when the allowable deformation, stress and strain are 3.7 x 10(-3) m, 1.0023 x 10(9) Pa and 1.05 x 10(-2) m/m, respectively; the main impact factors of turbine blisk failure are gas velocity, gas temperature and rotational speed. As demonstrated in the comparison of methods (Monte Carlo (MC) method, traditional response surface method (RSM), multiple response surface method (MRSM) and AMRSM), the proposed AMRSM improves computational efficiency with acceptable computational accuracy. The efforts of this study provide the AMRSM with high precision and efficiency for multi-failure mode reliability analysis, and offer a useful insight for the reliability optimization design of multi-failure mode structure. (C) 2016 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.展开更多
According to the demand of high reliability of the primary cylinder of the hydraulic press, the reliability model of the primary cylinder is built after its reliability analysis. The stress of the primary cylinder is...According to the demand of high reliability of the primary cylinder of the hydraulic press, the reliability model of the primary cylinder is built after its reliability analysis. The stress of the primary cylinder is analyzed by finite element software—MARC, and the structure reliability of the cylinder based on stress strength model is predicted, which would provide the reference to the design.展开更多
Components of electromechanical systems usually contain multiple performance parameters and degrade over time. In previous studies, the reliability of these electromechanical systems was analyzed by the traditional me...Components of electromechanical systems usually contain multiple performance parameters and degrade over time. In previous studies, the reliability of these electromechanical systems was analyzed by the traditional method, and the system reliability was estimated based on the reliability of components and the structures of the systems. The system reliability estimated by the traditional method could not reflect the performance of the systems. A new method is proposed in this paper to analyze the system reliability according to the data of multiple performance degraded processes of components. The performance distribution of a degraded component is obtained by the performance degradation analysis, and then states of the component are defined and corresponding state probabilities are estimated. The universal generating function method is proposed and extended to compute the performance distribution and reliability of the system based on the performances of components. A numerical example illustrates the proposed method. The results of the example show that the proposed method can relate the performance of the system to the performances of components and absolutely reflect the relationship between reliability and performance. Compared with the exact values of the system reliability, the results obtained by the proposed method is almost the same with the exact values, and the results obtained by the traditional method are conservative. The proposed method overcomes the shortcomings of the traditional method and provides a new approach to analyze the reliability of electromechanical systems with degraded components containing multiple performance parameters.展开更多
Based on nonlinear failure criterion,a three-dimensional failure mechanism of the possible collapse of deep tunnel is presented with limit analysis theory.Support pressure is taken into consideration in the virtual wo...Based on nonlinear failure criterion,a three-dimensional failure mechanism of the possible collapse of deep tunnel is presented with limit analysis theory.Support pressure is taken into consideration in the virtual work equation performed under the upper bound theorem.It is necessary to point out that the properties of surrounding rock mass plays a vital role in the shape of collapsing rock mass.The first order reliability method and Monte Carlo simulation method are then employed to analyze the stability of presented mechanism.Different rock parameters are considered random variables to value the corresponding reliability index with an increasing applied support pressure.The reliability indexes calculated by two methods are in good agreement.Sensitivity analysis was performed and the influence of coefficient variation of rock parameters was discussed.It is shown that the tensile strength plays a much more important role in reliability index than dimensionless parameter,and that small changes occurring in the coefficient of variation would make great influence of reliability index.Thus,significant attention should be paid to the properties of surrounding rock mass and the applied support pressure to maintain the stability of tunnel can be determined for a given reliability index.展开更多
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supported by the National Key Research and Development Program of China(Grant No.2021YFB2600504)the National Natural Science Foundation of China(Grant No.42072302)the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240533).
文摘Reliability analysis of soil slopes under rainfall is an important task for landslide risk assessment.Previous studies rarely contribute to the probabilistic analysis of slope stability under rainfall with reinforcement.A new method is suggested for reliability analysis of soil slopes stabilized with piles under rainfall.First,an efficient numerical model is exploited for slope stability analysis,where two types of slope failure modes,i.e.,plastic flow and local failure are considered.To address the blocking effect of piles during seepage analysis,the equivalent hydraulic conductivity of the pile area is estimated according to the effective medium theory.The stabilizing force of piles is investigated by an analytical approach.For saving computational effort,the response surface is established based on a multi-class classification model to predict two types of slope failure modes.Finally,uncertainties in soil parameters and rainfall events are both modelled,and the failure probability of soil slopes within a given time period is assessed through Monte Carlo simulation.An illustrative example is used to demonstrate the performance of the suggested method.It is found that the slope is mainly controlled by local failure.As the pile spacing increases,the likelihood of plastic flow significantly increases.As the piles are located near the slope crest,plastic flow is effectively prevented and the slope is better stabilized against rainfall.If rainfall uncertainties are not considered,the slope failure probability is significantly overestimated.Overall,this study can provide a useful guidance for the design of pile-stabilized slopes against rainfall infiltration.
基金supported by the Deanship of Research and Graduate Studies at King Khalid University under Small Research Project grant number RGP1/139/45.
文摘Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status.Each of these methods contributes unique diagnostic insights,enhancing the overall assessment of patient condition.Nevertheless,the amalgamation of data from multiple modalities presents difficulties due to disparities in resolution,data collection methods,and noise levels.While traditional models like Convolutional Neural Networks(CNNs)excel in single-modality tasks,they struggle to handle multi-modal complexities,lacking the capacity to model global relationships.This research presents a novel approach for examining multi-modal medical imagery using a transformer-based system.The framework employs self-attention and cross-attention mechanisms to synchronize and integrate features across various modalities.Additionally,it shows resilience to variations in noise and image quality,making it adaptable for real-time clinical use.To address the computational hurdles linked to transformer models,particularly in real-time clinical applications in resource-constrained environments,several optimization techniques have been integrated to boost scalability and efficiency.Initially,a streamlined transformer architecture was adopted to minimize the computational load while maintaining model effectiveness.Methods such as model pruning,quantization,and knowledge distillation have been applied to reduce the parameter count and enhance the inference speed.Furthermore,efficient attention mechanisms such as linear or sparse attention were employed to alleviate the substantial memory and processing requirements of traditional self-attention operations.For further deployment optimization,researchers have implemented hardware-aware acceleration strategies,including the use of TensorRT and ONNX-based model compression,to ensure efficient execution on edge devices.These optimizations allow the approach to function effectively in real-time clinical settings,ensuring viability even in environments with limited resources.Future research directions include integrating non-imaging data to facilitate personalized treatment and enhancing computational efficiency for implementation in resource-limited environments.This study highlights the transformative potential of transformer models in multi-modal medical imaging,offering improvements in diagnostic accuracy and patient care outcomes.
文摘The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.
基金funded by the National Key Research and Development Program(Grant No.2022YFB3706904).
文摘Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence speed of structural reliability analysis,an improved coati optimization algorithm(COA)is proposed in this paper.In this study,the social learning strategy is used to improve the coati optimization algorithm(SL-COA),which improves the convergence speed and robustness of the newheuristic optimization algorithm.Then,the SL-COAis comparedwith the latest heuristic optimization algorithms such as the original COA,whale optimization algorithm(WOA),and osprey optimization algorithm(OOA)in the CEC2005 and CEC2017 test function sets and two engineering optimization design examples.The optimization results show that the proposed SL-COA algorithm has a high competitiveness.Secondly,this study introduces the SL-COA algorithm into the MPP(Most Probable Point)search process based on FORM and constructs a new reliability analysis method.Finally,the proposed reliability analysis method is verified by four mathematical examples and two engineering examples.The results show that the proposed SL-COA-assisted FORM exhibits fast convergence and avoids premature convergence to local optima as demonstrated by its successful application to problems such as composite cylinder design and support bracket analysis.
基金The authors extend their appreciation to the Ongoing Research Funding Program,number(ORF2025R705),King Saud University,Riyadh,Saudi Arabia,for funding this work.
文摘The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum State,Sudan.It also aims to examine whether test’s factor structure in this sample replicated that of the original WPPSI-III.The study sample consisted of 384 kindergarten and primary school children in Khartoum State(females=50%mean age=4.14,SD=1.37),selected using stratified random sampling across its seven localities:Khartoum,Jebel Awliya,Khartoum Bahri,East Nile,Omdurman,Ombada,Karari.For concurrent validation,the children additionally completed the Goodenough Draw-a-Man Test,and the Colored Progressive Matrices.WPPSI-III scores demonstrated high internal consistency across the subtest items.Confirmatory factor analysis indicators for total,verbal,and performance intelligence were all excellent.The scale also showed weak to strong score stability ranging from 0.25(weak)to 0.88(strong)based on the Spearman-Brown equation,0.25 to 0.75 based on the Guttman split-half method.The Cronbach’s alpha coefficient scores ranged from 0.54 to 0.93.The WPPSI-III and Goodenough Draw-a-Man Test scores concurrent validity scores were poor(0.05)to modest(0.31),and while those with the Colored Progressive Matrices test were poor(r=0.04–0.18).Thesefindings provide evidence to suggest that the WPPSI-III is appropriate for research use with kindergarten and lower primary school students in Khartoum State,Sudan.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities,China(No.23D110316)。
文摘In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher accuracy,the additional computation of the Hessian matrix leads to lower computational efficiency.Additionally,when the dimensionality of the random variables is high,the approximation formula of SORM can result in larger errors.To address these issues,a structural reliability analysis method based on Kriging and spherical cap area integral is proposed.Firstly,this method integrates FORM with the quasi-Newton algorithm Broyden-Fletcher-Goldfarb-Shanno(BFGS),trains the Kriging model by using sample points from the algorithm’s iteration process,and combines the Kriging model with gradient information to approximate the Hessian matrix.Then,the failure surface is approximated as a rotating paraboloid,utilizing the spherical cap to replace the complex surface.For the n-dimensional case,the hyperspherical cap area expression is combined with the integral method to calculate the failure probability.Finally,the method is validated through three examples,demonstrating improved computational accuracy and efficiency compared to traditional methods.
基金supported by the National Natural Science Foundation of China(No.52075442)the National Science and Technology Major Project(2017-Ⅳ-0009-0046)the National Natural Science Foundation of China(No.51975476)。
文摘It is important to determine the safety lifetime of Multi-mode Time-Dependent Structural System(MTDSS). However, there is still a lack of corresponding analysis methods.Therefore, this paper establishes MTDSS safety lifetime model firstly, and then proposes a Kriging surrogate model based method to estimate safety lifetime. The first step of proposed method is to construct the Kriging model of MTDSS performance function by using extremum learning function. By identifying possible extremum mode of MTDSS, the performance function of MTDSS can be equivalently transformed into the one of Single-mode Time-Dependent Structure(STDS).The second step is to use the Advanced First Failure Instant Learning Function(AFFILF) to train the Kriging model constructed in the first step, so that the convergent Kriging model can identify the possible First Failure Instant(FFI) of STDS. Then safety lifetime can be searched quickly by dichotomy search. By using AFFILF, the minimum instant that the state is not accurately identified by the current Kriging model is selected as the training point, which avoids the unnecessary calculation which may be introduced into the existing First Failure Instant Learning Function(FFILF).In addition, the Candidate Sample Pool(CSP) reduction strategy is also adopted. By adaptively deleting the random candidate sample points whose FFI have been accurately identified by the current Kriging model, the training efficiency is further improved. Three cases show that the proposed method is accurate and efficient.
基金Projects(5147847951322403)supported by the National Natural Science Foundation of China+3 种基金Project(2015CX005)supported by Innovation Driven Plan of Central South University,ChinaProject(14JJ4003)supported by Hunan Provincial Natural Science Foundation,ChinaProject(SKLGP2014K008)supported by Opening Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology,ChinaProject(2015CB060200)supported by the National Basic Research Program of China
文摘Response surface method is used to study the reliability analysis of laterally loaded piles in sloping ground. A development load-displacement （p-y） curve for laterally loaded pile response in sloping ground is used to model the pile-soil system, both the pile head displacement and the maximum bending moment of the piles are used as the performance criteria in this study. The reliability analysis method of the laterally loaded pile in sloping ground under the pile head displacement and the maximum bending moment failure modes is proposed, which is in good agreement with the Monte Carlo method. The influences on the probability index of failure by a number of parameters are discussed. It is shown that the variability of pile head displacement increases with the increase in the coefficients of variation of ultimate bearing capacity factor （Npu）, secant elastic modulus at 50%（E50） and level load （H）. A negative correlation between Npu and non-dimensional factor （λ） leads to less spread out probability density function （PDF） of the pile head displacement;in contrast, a positive correlation between Npu andλgives a great variation in the PDF of pile head displacement. As for bearing capacity factor on ground surface （Npo） and λ, both negative and positive correlations between them give a great variation in the PDF of pile head displacement, and a negative correlation will obviously increase the variability of the response.
文摘Aim To define a mixed redundant model(MRM), improving the reliability of C 3I system. Methods The model combined the technology characters of two? unit system with one warm stand by unit and function substitute system. The reliability and availability equations of MRM were deduced. Results and Conclusion Compared with several other reliability models, it has obvious effect upon improving the system reliability. The effect? cost rate is very high among these models. The model can be used in reliability design, evaluation and check of C 3I system. Only a little attached cost is needed to improve C 3I system reliability effectively.
文摘The reliability analysis, based on the reliability index method, of two dimensional slopes is generalized by taking Sarma′s acceleration as the performance function. That is to say, a general expression of the performance function is given under various kinds of slice methods, even under various shapes of slice partition, beyond the traditional vertical slice method. A simple example shows explicitly the relationship of four commonly used slice methods in the slope reliability analysis. It is also found that the results of the reliability analysis are basically consistent with those of the stability analysis based on Sarma′s method.
基金National High-tech Research and Development Program of China (2006AA04Z405)
文摘This article presents two new kinds of artificial neural network （ANN） response surface methods （RSMs）： the ANN RSM based on early stopping technique （ANNRSM-1）, and the ANN RSM based on regularization theory （ANNRSM-2）. The following improvements are made to the conventional ANN RSM （ANNRSM-0）： 1） by monitoring the validation error during the training process, ANNRSM-1 determines the early stopping point and the training stopping point, and the weight vector at the early stopping point, which corresponds to the ANN model with the optimal generalization, is finally returned as the training result; 2） according to the regularization theory, ANNRSM-2 modifies the conventional training performance function by adding to it the sum of squares of the network weights, so the network weights are forced to have smaller values while the training error decreases. Tests show that the performance of ANN RSM becomes much better due to the above-mentioned improvements： first, ANNRSM-1 and ANNRSM-2 approximate to the limit state function （LSF） more accurately than ANNRSM-0; second, the estimated failure probabilities given by ANNRSM-1 and ANNRSM-2 have smaller errors than that obtained by ANNRSM-0; third, compared with ANNRSM-0, ANNRSM-1 and ANNRSM-2 require much fewer data samples to achieve stable failure probability results.
基金supported by the Large Open Pit Ⅱ project through contract No.019799 with the Geotechnical Research Centre of The University of Queensland,Australia and by SRK Consulting South Africa
文摘A Bayesian approach is proposed for the inference of the geotechnical parameters used in slope design.The methodology involves the construction of posterior probability distributions that combine prior information on the parameter values with typical data from laboratory tests and site investigations used in design.The posterior distributions are often complex,multidimensional functions whose analysis requires the use of Markov chain Monte Carlo(MCMC)methods.These procedures are used to draw representative samples of the parameters investigated,providing information on their best estimate values,variability and correlations.The paper describes the methodology to define the posterior distributions of the input parameters for slope design and the use of these results for evaluation of the reliability of a slope with the first order reliability method(FORM).The reliability analysis corresponds to a forward stability analysis of the slope where the factor of safety(FS)is calculated with a surrogate model from the more likely values of the input parameters.The Bayesian model is also used to update the estimation of the input parameters based on the back analysis of slope failure.In this case,the condition FS?1 is treated as a data point that is compared with the model prediction of FS.The analysis requires a sufficient number of observations of failure to outbalance the effect of the initial input parameters.The parameters are updated according to their uncertainty,which is determined by the amount of data supporting them.The methodology is illustrated with an example of a rock slope characterised with a Hoek-Brown rock mass strength.The example is used to highlight the advantages of using Bayesian methods for the slope reliability analysis and to show the effects of data support on the results of the updating process from back analysis of failure.
基金supported by National Department Public Benefit Research Foundation of China (Grant No. 200810411)
文摘With the uncertainties related to operating conditions,in-service non-destructive testing（NDT） measurements and material properties considered in the structural integrity assessment,probabilistic analysis based on the failure assessment diagram（FAD） approach has recently become an important concern.However,the point density revealing the probabilistic distribution characteristics of the assessment points is usually ignored.To obtain more detailed and direct knowledge from the reliability analysis,an improved probabilistic fracture mechanics（PFM） assessment method is proposed.By integrating 2D kernel density estimation（KDE） technology into the traditional probabilistic assessment,the probabilistic density of the randomly distributed assessment points is visualized in the assessment diagram.Moreover,a modified interval sensitivity analysis is implemented and compared with probabilistic sensitivity analysis.The improved reliability analysis method is applied to the assessment of a high pressure pipe containing an axial internal semi-elliptical surface crack.The results indicate that these two methods can give consistent sensitivities of input parameters,but the interval sensitivity analysis is computationally more efficient.Meanwhile,the point density distribution and its contour are plotted in the FAD,thereby better revealing the characteristics of PFM assessment.This study provides a powerful tool for the reliability analysis of critical structures.
文摘Redundant actuator is the key component of Fly-By-Wire （FBW） system in which exists the inherent force fighting among different redundant channels at colligation point, This paper establishes the mathematical model of quad redundant actuator （QRA）, investigates the force equalization algorithm and carries out the performance degradation simulation and reliability analysis under the first failure and the second failure. The results indicate that the optimal equalization algorithm can solve the force fighting effectively, and the QRA can operate at degradation performance continuously under the first failure and the second failure. With the dynamic fault tree analysis, this paper calculates the reliability based on the performance of QRA and proves that the redundant actuator has very high reliability and safety.
文摘Electromagnetic relay in aerospace is one of the main electronic components in aerospace electronic systems for information transfer, control and power distribution, and its reliability will influence the reliability of the whole aerospace electronic systems. Reliability design is the key technique of electromagnetic relay reliability engineering. This paper synthetically analyzes the present reliability design methods, and presents the reliability tolerance analyzing mathematic models of electromagnetic force basing on orthogonal design, mechanical spring force basing on probability statistics theory, and matching characteristics of electromagnetic force and mechanical spring force basing on method of stressstrength interference. Some instructive conclusions are draw by researching on the reliability tolerance of some type electromagnetic relay in aerospace.
基金co-supported by the National Natural Science Foundation of China (No. 51275138)the Science Foundation of Heilongjiang Provincial Department of Education (No. 12531109)+1 种基金the funding of Hong Kong Scholars Programs (Nos. XJ2015002 and G-YZ90)China’s Postdoctoral Science Funding (No. 2015M580037)
文摘To reasonably implement the reliability analysis and describe the significance of influencing parameters for the multi-failure modes of turbine blisk, advanced multiple response surface method (AMRSM) was proposed for multi-failure mode sensitivity analysis for reliability. The mathematical model of AMRSM was established and the basic principle of multi-failure mode sensitivity analysis for reliability with AMRSM was given. The important parameters of turbine blisk failures are obtained by the multi-failure mode sensitivity analysis of turbine blisk. Through the reliability sensitivity analyses of multiple failure modes (deformation, stress and strain) with the proposed method considering fluid-thermal-solid interaction, it is shown that the comprehensive reliability of turbine blisk is 0.9931 when the allowable deformation, stress and strain are 3.7 x 10(-3) m, 1.0023 x 10(9) Pa and 1.05 x 10(-2) m/m, respectively; the main impact factors of turbine blisk failure are gas velocity, gas temperature and rotational speed. As demonstrated in the comparison of methods (Monte Carlo (MC) method, traditional response surface method (RSM), multiple response surface method (MRSM) and AMRSM), the proposed AMRSM improves computational efficiency with acceptable computational accuracy. The efforts of this study provide the AMRSM with high precision and efficiency for multi-failure mode reliability analysis, and offer a useful insight for the reliability optimization design of multi-failure mode structure. (C) 2016 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
基金This project is supported by Science and Technology Foundation of the Mechanical Ministry! (98250541)
文摘According to the demand of high reliability of the primary cylinder of the hydraulic press, the reliability model of the primary cylinder is built after its reliability analysis. The stress of the primary cylinder is analyzed by finite element software—MARC, and the structure reliability of the cylinder based on stress strength model is predicted, which would provide the reference to the design.
基金supported by Graduate School of National University of Defense Technology, China
文摘Components of electromechanical systems usually contain multiple performance parameters and degrade over time. In previous studies, the reliability of these electromechanical systems was analyzed by the traditional method, and the system reliability was estimated based on the reliability of components and the structures of the systems. The system reliability estimated by the traditional method could not reflect the performance of the systems. A new method is proposed in this paper to analyze the system reliability according to the data of multiple performance degraded processes of components. The performance distribution of a degraded component is obtained by the performance degradation analysis, and then states of the component are defined and corresponding state probabilities are estimated. The universal generating function method is proposed and extended to compute the performance distribution and reliability of the system based on the performances of components. A numerical example illustrates the proposed method. The results of the example show that the proposed method can relate the performance of the system to the performances of components and absolutely reflect the relationship between reliability and performance. Compared with the exact values of the system reliability, the results obtained by the proposed method is almost the same with the exact values, and the results obtained by the traditional method are conservative. The proposed method overcomes the shortcomings of the traditional method and provides a new approach to analyze the reliability of electromechanical systems with degraded components containing multiple performance parameters.
基金Project (2013CB036004) supported by National Basic Research Program of China
文摘Based on nonlinear failure criterion,a three-dimensional failure mechanism of the possible collapse of deep tunnel is presented with limit analysis theory.Support pressure is taken into consideration in the virtual work equation performed under the upper bound theorem.It is necessary to point out that the properties of surrounding rock mass plays a vital role in the shape of collapsing rock mass.The first order reliability method and Monte Carlo simulation method are then employed to analyze the stability of presented mechanism.Different rock parameters are considered random variables to value the corresponding reliability index with an increasing applied support pressure.The reliability indexes calculated by two methods are in good agreement.Sensitivity analysis was performed and the influence of coefficient variation of rock parameters was discussed.It is shown that the tensile strength plays a much more important role in reliability index than dimensionless parameter,and that small changes occurring in the coefficient of variation would make great influence of reliability index.Thus,significant attention should be paid to the properties of surrounding rock mass and the applied support pressure to maintain the stability of tunnel can be determined for a given reliability index.
