System Reliability Analysis Method Based on T-S FTA and HE-BN

For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.

Transformation of long-period stacking ordered structures in Mg-Gd-Y-Zn alloys upon synergistic characterization of first-principles calculation and experiment and its effects on mechanical properties

Based on experiments and first-principles calculations,the microstructures and mechanical properties of as-cast and solution treated Mg-10Gd-4Y-xZn-0.6Zr(x=0,1,2,wt.%)alloys are investigated.The transformation process of long-period stacking ordered(LPSO)structure during solidification and heat treatment and its effect on the mechanical properties of experimental alloys are discussed.Results reveal that the stacking faults and 18R LPSO phases appear in the as-cast Mg-10Gd-4Y-1Zn-0.6Zr and Mg-10Gd-4Y-2Zn-0.6Zr alloys,respectively.After solution treatment,the stacking faults and 18R LPSO phase transform into 14H LPSO phase.The Enthalpies of formation and reaction energy of 14H and 18R LPSO are calculated based on first-principles.Results show that the alloying ability of 18R is stronger than that of 14H.The reaction energies show that the 14H LPSO phase is more stable than the 18R LPSO.The elastic properties of the 14H and 18R LPSO phases are also evaluated by first-principles calculations,and the results are in good agreement with the experimental results.The precipitation of LPSO phase improves the tensile strength,yield strength and elongation of the alloy.After solution treatment,the Mg-10Gd-4Y-2Zn-0.6Zr alloy has the best mechanical properties,and its ultimate tensile strength and yield strength are 278.7 MPa and 196.4 MPa,respectively.The elongation of Mg-10Gd-4Y-2Zn-0.6Zr reaches 15.1,which is higher than that of Mg-10Gd-4Y0.6Zr alloy.The improving mechanism of elastic modulus by the LPSO phases and the influence on the alloy mechanical properties are also analyzed.

Analysis of the Reform of Ideological and Political Education in College English Curriculum from the Perspective of“Cultural Confidence”

With the rapid development of the education industry,higher requirements have been put forward for college English education and teaching,accelerating the pace of college English reform.Issues such as how to integrate knowledge transmission,language expression skill improvement,cultural element extraction,and ideological and political education,and present the role of curriculum education function have attracted attention.In the era of informatization,college students’thinking has undergone certain changes and gradually developed towards diversification.Therefore,universities should start from the perspective of cultural confidence,extract valuable ideological and political elements,and explore effective tourism ideological and political teaching methods.While helping college students enhance their cultural confidence,it is also beneficial for them to better inherit traditional Chinese culture.This article conducts an in-depth exploration of ideological and political education in college English courses from the perspective of“cultural confidence”and uses scientific and effective measures to solve the problems encountered,aiming to provide valuable guidelines for relevant researchers.

GL-YOLOv5: An Improved Lightweight Non-Dimensional Attention Algorithm Based on YOLOv5

Craniocerebral injuries represent the primary cause of fatalities among riders involved in two-wheeler accidents;nevertheless,the prevalence of helmet usage among these riders remains alarmingly low.Consequently,the accurate identification of riders who are wearing safety helmets is of paramount importance.Current detection algorithms exhibit several limitations,including inadequate accuracy,substantial model size,and suboptimal performance in complex environments with small targets.To address these challenges,we propose a novel lightweight detection algorithm,termed GL-YOLOv5,which is an enhancement of the You Only Look Once version 5(YOLOv5)framework.This model incorporates a Global DualPooling NoReduction Blend Attention(GDPB)module,which optimizes the MobileNetV3 architecture by reducing the number of channels by half and implementing a parallelized channel and spatial attention mechanism without dimensionality reduction.Additionally,it replaces the conventional convolutional layer with a channel shuffle approach to overcome the constraints associated with the Squeeze-and-Excitation(SE)attention module,thereby significantly improving both the efficiency and accuracy of feature extraction and decreasing computational complexity.Furthermore,we have optimized the Variable Normalization and Attention Channel Spatial Partitioning(VNACSP)within the C3 module of YOLOv5,which enhances sensitivity to small targets through the application of a lightweight channel attention mechanism,substituting it for the standard convolution in the necking network.The Parameter-Free Spatial Adaptive Feature Fusion(PSAFF)module is designed to adaptively modify the weights of each spatial position through spatial pooling and activation functions,thereby effectively enhancing the model’s ability to perceive contextual information over distances.Ultimately,GL-YOLOv5 performs remarkably in the custom dataset,achieving a model parameter count of 922,895 M,a computational load of 2.9 GFLOPS,and a mean average precision(mAP)of 92.1%.These advancements significantly improve the model’s detection capabilities and underscore its potential for practical applications.

Research on Enhanced Contraband Dataset ACXray Based on ETL

To address the shortage of public datasets for customs X-ray images of contraband and the difficulties in deploying trained models in engineering applications,a method has been proposed that employs the Extract-Transform-Load(ETL)approach to create an X-ray dataset of contraband items.Initially,X-ray scatter image data is collected and cleaned.Using Kafka message queues and the Elasticsearch(ES)distributed search engine,the data is transmitted in real-time to cloud servers.Subsequently,contraband data is annotated using a combination of neural networks and manual methods to improve annotation efficiency and implemented mean hash algorithm for quick image retrieval.The method of integrating targets with backgrounds has enhanced the X-ray contraband image data,increasing the number of positive samples.Finally,an Airport Customs X-ray dataset(ACXray)compatible with customs business scenarios has been constructed,featuring an increased number of positive contraband samples.Experimental tests using three datasets to train the Mask Region-based Convolutional Neural Network(Mask R-CNN)algorithm and tested on 400 real customs images revealed that the recognition accuracy of algorithms trained with Security Inspection X-ray(SIXray)and Occluded Prohibited Items X-ray(OPIXray)decreased by 16.3%and 15.1%,respectively,while the ACXray dataset trained algorithm’s accuracy was almost unaffected.This indicates that the ACXray dataset-trained algorithm possesses strong generalization capabilities and is more suitable for customs detection scenarios.

Effect of high-energy Ne ions irradiation on mechanical properties difference between Zr_(63.5)Cu_(23)Al_(9)Fe_(4.5)metallic glass and crystalline W

In this paper,high-energy Ne ions were used to irradiate Zr_(63.5)Cu_(23)Al_(9)Fe_(4.5) metallic glass(MG)and crystalline W to investigate their difference in mechanical response after irradiation.The results showed that with the irradiation dose increased,the tensile micro-strain increased,nano-hardness increased from 7.11 GPa to 7.90 GPa and 8.62 GPa,Young’s modulus increased,and H3/E2 increased which indicating that the plastic deformability decreased in crystalline W.Under the same irradiation conditions,the Zr_(63.5)Cu_(23)Al_(9)Fe_(4.5) MG still maintained the amorphous structure and became more disordered despite the longer range and stronger displacement damage of Ne ions in Zr_(63.5)Cu_(23)Al_(9)Fe_(4.5) MG than in crystalline W.Unlike the irradiation hardening and embrittlement behavior of crystalline W,Zr_(63.5)Cu_(23)Al_(9)Fe_(4.5) MG showed the gradual decrease in hardness from 6.02 GPa to 5.89 GPa and 5.50 GPa,the decrease in modulus and the increase in plastic deformability with the increasing dose.Possibly,the irradiation softening and toughening phenomenon of Zr_(63.5)Cu_(23)Al_(9)Fe_(4.5) MG could provide new ideas for the design of nuclear materials.

Biomass-derived porous carbon with single-atomic cobalt toward high-performance aqueous zinc-sulfur batteries at room temperature

Aqueous zinc-sulfur batteries at room temperature hold great potential for next-generation energy storage technology due to their low cost,safety and high energy density.However,slow reaction kinetics and high activation energy at the sulfur cathode pose great challenges for the practical applications.Herein,biomass-derived carbon with single-atomic cobalt sites(MMPC-Co)is synthesized as the cathode in Zn-S batteries.The catalysis of single-atom Co sites greatly promotes the transform of cathode electrolyte interface(CEI)on the cathode surface,while offering accelerated charge transfer rate for high conversion reversibility and large electrochemical surface area(ECSA)for high electrocatalytic current.Furthermore,the rich pore structure not only physically limits sulfur loss,but also accelerates the transport of zinc ions.In addition,the large pore volume of MMPC-Co is able to relieve the stress effect caused by the volume expansion of Zn S during charge/discharge cycles,thereby maintaining the stability of electrode structure.Consequently,the sulfur cathode maintains a high specific capacity of 729.96 m A h g^(-1)after 500 cycles at4 A g^(-1),which is much better than most cathode materials reported in the literature.This work provides new insights into the design and development of room-temperature aqueous Zn-S batteries.

Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

Tailoring Ni based catalysts by indium for the dehydrogenative coupling of ethanol into ethyl acetate

Exploring stable and robust catalysts to replace the current toxic CuCr based catalysts for dehydrogenative coupling of ethanol to ethyl acetate is a challenging but promising task.Herein,novel NiIn based catalysts were developed by tailoring Ni catalysts with Indium(In)for this reaction.Over the optimal Ni0.1Zn0.7Al0.3InOx catalyst,the ethyl acetate selectivity reached 90.1%at 46.2%ethanol conversion under the conditions of 548 K and a weight hourly space velocity of 1.9 h^(-1)in the 370 h time on stream.Moreover,the ethyl acetate productivity surpassed 1.1 g_(ethyl acetate)g_(catalyst)^(-1)h^(-1),,one of the best performance in current works.According to catalyst characterizations and conditional experiments,the active sites for dehydrogenative coupling of ethanol to ethyl acetate were proved to be Ni4In alloys.The presence of In tailored the chemical properties of Ni,and subsequently inhibited the C-C cracking and/or condensation reactions during ethanol conversions.Over Ni4In alloy sites,ethanol was dehydrogenated into acetaldehyde,and then transformed into acetyl species with the removal of H atoms.Finally,the coupling between acetyl species and surface-abundant ethoxyde species into ethyl acetate was achieved,affording a high ethyl acetate selectivity and catalyst stability.

Decoupling of Rattling Mode and Superconductivity in Filled-Skutterudite Ba_(x)Ir_(4)Sb_(12)

The rattling mode,an anharmonic vibrational phonon,is widely recognized as a critical factor in the emergence of superconductivity in caged materials.Here,we present a counterexample in a filled-skutterudite superconductor Ba_(x)Ir_(4)Sb_(12)(x=0.8,0.9,1.0),synthesized via a high-pressure route.Transport measurements down to liquid 3He temperatures reveal a transition temperature(T_(c))of 1.2 K and an upper critical field(H_(c2))of 1.3 T.Unlike other superconductors with caged structures,the Ba_(x)Ir_(4)Sb_(12)(X=P,As,Sb)family exhibits a monotonic decreasing T_(c) with the enhancement of the rattling mode,as indicated by fitting the Bloch–Grüneisen formula.Theoretical analysis suggests that electron doping from Ba transforms the direct bandgap IrSb3 into a metal,with the Fermi surface dominated by the hybridization of Ir 5d and Sb 5p orbitals.Our findings of decoupled rattling modes and superconductivity distinguish the Ba_(x)Ir_(4)Sb_(12) family from other caged superconductors,warranting further exploration into the underlying mechanism.

Development of track geometry inspection equipment for high-speed comprehensive inspection train in China

Purpose–This study aims to analyze the development direction of track geometry inspection equipment for high-speed comprehensive inspection train in China.Design/methodology/approach–The development of track geometry inspection equipment for highspeed comprehensive inspection train in China in the past 20 years can be divided into 3 stages.Track geometry inspection equipment 1.0 is the stage of analog signal.At the stage 1.0,the first priority is to meet the China’s railways basic needs of pre-operation joint debugging,safety assessment and daily dynamic inspection,maintenance and repair after operation.Track geometry inspection equipment 2.0 is the stage of digital signal.At the stage 2.0,it is important to improve stability and reliability of track geometry inspection equipment by upgrading the hardware sensors and improving software architecture.Track geometry inspection equipment 3.0 is the stage of lightweight.At the stage 3.0,miniaturization,low power consumption,self-running and green economy are co-developing on demand.Findings–The ability of track geometry inspection equipment for high-speed comprehensive inspection train will be expanded.The dynamic inspection of track stiffness changes will be studied under loaded and unloaded conditions in response to the track local settlement,track plate detachment and cushion plate failure.The dynamic measurement method of rail surface slope and vertical curve radius will be proposed,to reveal the changes in railway profile parameters of high-speed railways and the relationship between railway profile,track irregularity and subsidence of subgrade and bridges.The 200 m cut-off wavelength of track regularity will be researched to adapt to the operating speed of 400 km/h.Originality/value–The research can provide new connotations and requirements of track geometry inspection equipment for high-speed comprehensive inspection train in the new railway stage.

Multi-objective optimization design of anti-roll torsion bar using improved beluga whale optimization algorithm

Purpose – This study aims to reduce the redundant weight of the anti-roll torsion bar brought by thetraditional empirical design and improving its strength and stiffness.Design/methodology/approach – Based on the finite element approach coupled with the improved belugawhale optimization (IBWO) algorithm, a collaborative optimization method is suggested to optimize the designof the anti-roll torsion bar structure and weight. The dimensions and material properties of the torsion bar weredefined as random variables, and the torsion bar’s mass and strength were investigated using finite elements.Then, chaotic mapping and differential evolution (DE) operators are introduced to improve the beluga whaleoptimization (BWO) algorithm and run case studies.Findings – The findings demonstrate that the IBWO has superior solution set distribution uniformity,convergence speed, solution correctness and stability than the BWO. The IBWO algorithm is used to optimizethe anti-roll torsion bar design. The error between the optimization and finite element simulation results wasless than 1%. The weight of the optimized anti-roll torsion bar was lessened by 4%, the maximum stress wasreduced by 35% and the stiffness was increased by 1.9%.Originality/value – The study provides a methodological reference for the simulation optimization process ofthe lateral anti-roll torsion bar.

Preparation of Corncob-Like WO3 Nanomaterials and Their Photocatalytic Treatment of Toluene

Corn rod-like WO3 nanomaterials were successfully synthesized by a simple hydrothermal method. The morphology, structure and optical absorption properties of the prepared samples were characterized by SEM, XRD, FTIR and UV-Vis-DRS. The WO3 materials were corn rod-like morphology with about 800 nm for length and 150 nm for diameter, especially there were plenty of corn particles (about 20 nm) on the surface of corn rods. The X-ray diffraction peaks of the products corresponded with WO3 standard card, and the characteristic peak of W-O bond was found in the infrared spectrum. The absorption band edge of the products was about 480 nm, indicating their potential visible-light-induced photocatalytic activity. In situ FTIR technology research showed that the prepared WO3 nanomaterials had visible photocatalytic activity to gas-phase toluene. After a photocatalytic reaction for 8 hours toluene was effectively degraded, and carboxylic acid and aldehyde could be regarded as the intermediate products, and CO2 was produced as the final product during the reaction process.

Research on the Application of Second Language Acquisition Theory in College English Speech Teaching

The teaching of English speeches in universities aims to enhance oral communication ability,improve English communication skills,and expand English knowledge,occupying a core position in English teaching in universities.This article takes the theory of second language acquisition as the background,analyzes the important role and value of this theory in English speech teaching in universities,and explores how to apply the theory of second language acquisition in English speech teaching in universities.It aims to strengthen the cultivation of English skilled talents and provide a brief reference for improving English speech teaching in universities.

The Two-level Management System of University and Schoo

With the development of our country’s higher education, the school also presents the great-leap-forward development trend. The previous denotative development has changed into the way of connotative development. The two-level management system of university and school is the most common management mode in many colleges. This paper introduces the advantage of this mode in the objective view, analyzes the problems existing in the practice operation, put forward countermeasures to improve the two-level management and proposes a method to build the two-level management system.

Influence of quick release valve on braking performance and coupler force of heavy haul train

We establish a simulation model based on the theory of air flow to analyze the accelerated release effect of the quick release valve inside the air brake control valve.In addition, the combined simulation system of train air brake system and longitudinal train dynamics is used to analyze how the parameters of the quick release valve in the 120/120–1 brake control valve affect the propagation characteristics of the train brake pipe pressure wave, the release action range of the accelerated brake, and the longitudinal coupler force for a 20,000-ton heavy haul train on the section of the Datong–Qinhuangdao Railway. The results show that the quick release valve can effectively accelerate the rising speed of the train brake pipe pressure during the initial release, as the accelerated release effect is evident before the train brake pipe pressure reaches582 k Pa. The quick release valve can effectively accelerate the release of the rear cars, reducing the longitudinal coupler force impact due to time delay of the release process. The quick release valve can effectively reduce the tensile coupler force in the train by as much as 20% in certain cases.

Adaptive Fault Estimation for Dynamics of High Speed Train Based on Robust UKF Algorithm

This paper proposes an adaptive unscented Kalman filter algorithm(ARUKF)to implement fault estimation for the dynamics of high⁃speed train(HST)with measurement uncertainty and time⁃varying noise with unknown statistics.Firstly,regarding the actuator and sensor fault as the auxiliary variables of the dynamics of HST,an augmented system is established,and the fault estimation problem for dynamics of HST is formulated as the state estimation of the augmented system.Then,considering the measurement uncertainties,a robust lower bound is proposed to modify the update of the UKF to decrease the influence of measurement uncertainty on the filtering accuracy.Further,considering the unknown time⁃varying noise of the dynamics of HST,an adaptive UKF algorithm based on moving window is proposed to estimate the time⁃varying noise so that accurate concurrent actuator and sensor fault estimations of dynamics of HST is implemented.Finally,a five-car model of HST is given to show the effectiveness of this method.

Effect of mixing temperature on microstructure of an Al-Si alloy prepared by controlled diffusion solidification

The effects of mixing temperature,i.e.,the temperatures of two precursor melts(pure Al and Al-12Si),on the temperature and solute fields of resultant mixture,the nucleation and growth,and the size and morphology of primary grains during controlled diffusion solidification(CDS) of Al-8Si alloy were investigated by using simulation and calculation.The results indicate that a lower mixing temperature is helpful for achieving more supercooled microscale Al-rich pockets in the mixture,and increasing the width and supercooling degree of supercooling zone in the Al-rich pockets,and thus,the nucleation rate.The nuclei grow up in nondendritic mode,resulting in spheroidal,at least,nondendritic grains.In a successful CDS,the superheat degrees of the two precursor melts should be limited within several degrees,and it is not necessary to extra stipulate the superheat degree of target alloy melt(Al-8Si) when the requirement about Gibbs energies of the three melts is matched.Subsequent observation on casting microstructures shows that the employed simulation and calculation processes are reasonable and the achieved results are reliable.

Predicting Reliability and Remaining Useful Life of Rolling Bearings Based on Optimized Neural Networks

In this study,an optimized long short-term memory(LSTM)network is proposed to predict the reliability and remaining useful life(RUL)of rolling bearings based on an improved whale-optimized algorithm(IWOA).The multi-domain features are extracted to construct the feature dataset because the single-domain features are difficult to characterize the performance degeneration of the rolling bearing.To provide covariates for reliability assessment,a kernel principal component analysis is used to reduce the dimensionality of the features.A Weibull distribution proportional hazard model(WPHM)is used for the reliability assessment of rolling bearing,and a beluga whale optimization(BWO)algorithm is combined with maximum likelihood estimation(MLE)to improve the estimation accuracy of the model parameters of the WPHM,which provides the data basis for predicting reliability.Considering the possible gradient explosion by training the rolling bearing lifetime data and the difficulties in selecting the key network parameters,an optimized LSTM network called the improved whale optimization algorithm-based long short-term memory(IWOA-LSTM)network is proposed.As IWOA better jumps out of the local optimization,the fitting and prediction accuracies of the network are correspondingly improved.The experimental results show that compared with the whale optimization algorithm-based long short-term memory(WOA-LSTM)network,the reliability prediction and RUL prediction accuracies of the rolling bearing are improved by the proposed IWOA-LSTM network.

Selection and modification of ground motion records using Newmark-Hall spectrum as target spectrum for long-period structures

Input ground motions have significant impacts on the uncertainty of structural responses in time-history analysis.In this study,records were selected and scaled for the evaluation of mean structural responses according to the target spectrum.The Newmark-Hall spectrum is closely related to seismic response of short,medium and long-period structures,so it was taken as the target spectrum here.The nonlinear time-history analyses of 9-story and 20-story steel moment-resisting frame structures were carried out as examples.They represent medium and long-period buildings,respectively.Three target spectra with risk of 50%,10%and 2%probabilities for exceedance in 50 years were calculated by the average Newmark-Hall spectrum method for three ground motion sets developed in the SAC Steel Project.The predicted structural mean responses of these Newmark-Hall spectra were compared with those calculated by the average spectral acceleration method for the same record set.It is found that both methods have similar accuracy for estimating the structural mean response.However,the method proposed herein is more effective in reducing the variability of the structural responses.Also,the proposed method is more advantageous for the time-history analysis of long-period structures or structures with more severe nonlinear responses under strong seismic excitations.