The characterization of track irregularities is crucial in railway dynamics,as track irregularities are the primary source of internal excitation in railway systems.In this paper,three mathematical models are proposed...The characterization of track irregularities is crucial in railway dynamics,as track irregularities are the primary source of internal excitation in railway systems.In this paper,three mathematical models are proposed to characterize the track irregularities under different circumstances.The first model is a novel explicit track spectrum function,which performs better in reflecting the inherent periodic components of track irregularities than the existing track spectra.On this foundation,the second model,a parameterized track spectrum random model,is proposed to represent the vast measured track irregularities from the probabilistic perspective.Finally,the third model,an imprecise track spectrum interval model based on a neighborhood uniform sampling Bootstrap method,is presented to identify the confidential interval of the track spectra when the track irregularity data are limited.Three examples are illustrated to demonstrate the feasibility of the three track irregularity models in characterizing the track irregularities in different conditions.This research can help capture the railway deformation status and optimize track maintenance strategies.展开更多
In the paper we obtain two infinite classes of p-groups, calculate the orders of their automorphism groups and correct a mistake（perhaps misprinted） of Rodney James＇ paper in 1980.
A p-group G is called a JC-group if the normal closure HG of every cyclic subgroup H satisfies｜G：HG｜≤p or｜HG：H｜≤p.In this paper, we classify the non-Dedekindian JC-groups for p 〉 2.
Let p be a prime number and f_2(G) be the number of factorizations G = AB of the group G, where A, B are subgroups of G. Let G be a class of finite p-groups as follows,G = a, b | a^(p^n)= b^(p^m)= 1, a^b= a^(p^(n-1)+1...Let p be a prime number and f_2(G) be the number of factorizations G = AB of the group G, where A, B are subgroups of G. Let G be a class of finite p-groups as follows,G = a, b | a^(p^n)= b^(p^m)= 1, a^b= a^(p^(n-1)+1), where n > m ≥ 1. In this article, the factorization number f_2(G) of G is computed, improving the results of Saeedi and Farrokhi in [5].展开更多
In this paper, we study the basis of augmentation ideals and the quotient groups of finite non-abelian p-group which has a cyclic subgroup of index p, where p is an odd prime, and k is greater than or equal to 3. A co...In this paper, we study the basis of augmentation ideals and the quotient groups of finite non-abelian p-group which has a cyclic subgroup of index p, where p is an odd prime, and k is greater than or equal to 3. A concrete basis for the augmentation ideal is obtained and then the structure of its quotient groups can be determined.展开更多
For any prime p, all finite noncyclic p-groups which contain a self-centralizing cyclic normal subgroup are determined by using cohomological techniques. Some applications are given, including a character theoretic de...For any prime p, all finite noncyclic p-groups which contain a self-centralizing cyclic normal subgroup are determined by using cohomological techniques. Some applications are given, including a character theoretic description for such groups.展开更多
Let G be a group and A and B be subgroups of G.If G=AB,then G is said to be factorized by A and B.Let p be a prime number.The factorization numbers of a 2-generators abelian p-group and a modular p-group have been det...Let G be a group and A and B be subgroups of G.If G=AB,then G is said to be factorized by A and B.Let p be a prime number.The factorization numbers of a 2-generators abelian p-group and a modular p-group have been determined.Further,suppose that G is a finite p-group as follows G=<a,b|a^(p)^(n)=b^(p)^(m)=1,a^(b)=a^(p^(n-1)+1)>,where n≥2,m≥1.In this paper,the factorization number of G is computed completely,which is a generalization of the result of Saeedi and Farrokhi.展开更多
Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed railways.They can cause significant wheel-rail dynamic interactions,leading to wheel-rail ...Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed railways.They can cause significant wheel-rail dynamic interactions,leading to wheel-rail noise,component damage,and deterioration.Few researchers have employed the vehicle-track interaction dynamic model to study the dynamic interactions between wheel and rail induced by rail weld geometry irregularities.However,the cosine wave model used to simulate rail weld irregularities mainly focuses on the maximum value and neglects the geometric shape.In this study,novel theoretical models were developed for three categories of rail weld irregularities,based on measurements of the high-speed railway from Beijing to Shanghai.The vertical dynamic forces in the time and frequency domains were compared under different running speeds.These forces generated by the rail weld irregularities that were measured and modeled,respectively,were compared to validate the accuracy of the proposed model.Finally,based on the numerical study,the impact force due to rail weld irrregularity is modeled using an Artificial Neural Network(ANN),and the optimum combination of parameters for this model is found.The results showed that the proposed model provided a more accurate wheel/rail dynamic evaluation caused by rail weld irregularities than that established in the literature.The ANN model used in this paper can effectively predict the impact force due to rail weld irrregularity while reducing the computation time.展开更多
Axle box bearings are critical components of high-speed trains.Localized defects,such as pitting and spalling,on raceways or rollers pose significant threats to the operational safety of railway vehicles.In this work,...Axle box bearings are critical components of high-speed trains.Localized defects,such as pitting and spalling,on raceways or rollers pose significant threats to the operational safety of railway vehicles.In this work,a novel bearing-flexible axle boxvehicle coupling model is established to explore the vibration characteristics of axle box bearings with irregular localized defects.First,based on the contact and kinematic relationship between rollers and raceways,the three-dimensional(3D)bearing force elements are analyzed and formulated.Second,the established model and a flexible axle box are integrated into the vehicle,and the responses of the normal and faulty bearings under the combined excitations of wheel roughness and track irregularities are simulated.Third,the simulation results are verified through a rolling-vibrating test bench for full-scale wheelsets of high-speed trains.The comparisons of the fault-induced repetitive transients in the time-domain and the fault characteristic frequencies in the envelope spectra demonstrate the efficiency of the proposed model.Finally,based on the flexible axle box model,a sensitivity analysis of the accelerometer placements to the bearing faults is carried out,and the optimal one is identified based on both the time-domain and frequency-domain signal-to-noise ratios(SNRs)for engineering applications.展开更多
As one of the major high-speed railway ballastless track structures in China,CRTSIII slab ballastless track has been laid for more than 6500 km.However,there are no detailed studies on its track irregularity deteriora...As one of the major high-speed railway ballastless track structures in China,CRTSIII slab ballastless track has been laid for more than 6500 km.However,there are no detailed studies on its track irregularity deterioration throughout extended service periods,which may threaten the safety and stability of high-speed vehicles(HSV).In this study,a long-term tracking detection of CRTSIII slab ballastless track irregularities has been conducted,revealing its annual evolution law.An HSV-track coupled dynamics model was established to investigate the HSV dynamic responses under annual evolution of track irregularities.Considering the potential deterioration of track irregularities to extremely bad condition,the recommended classified limits for irregularity are proposed by analyzing the limit-exceeding probability of the safety and stability indexes of HSV.The results show that:taking 10 m wavelength as a demarcation,longer-wavelength irregularities exhibit larger amplitudes,faster evolution rates and a linear increasing trend,primarily affecting the stability of HSV.Conversely,shorter-wavelength irregularities exhibit smaller amplitudes and an insignificant evolution trend,predominantly affecting the safety of HSV.Furthermore,the periodic irregularity induced by the arching of 32 m simply-supported beam bridge should be paid closer attention to,as their evolution rate significantly surpasses that of irregularities at other wavelengths.展开更多
The irregular porous structure,similar to human bone tissue,is more beneficial for bone ingrowth than the regular one.We proposed a new design method to create uniform and gradient irregular porous structures with por...The irregular porous structure,similar to human bone tissue,is more beneficial for bone ingrowth than the regular one.We proposed a new design method to create uniform and gradient irregular porous structures with porosities from 38 to 83%based on Voronoi tessellation.The models were fabricated using selective laser sintering,and micro-CT was used to assess their morphological features.Mechanical and fluid flow properties were evaluated through experiments and computational fluid dynamics simulations.Micro-CT scans confirmed that 3D printing can produce high-quality irregular structures.The Graded Irregular(GI)structure showed clear advantages in mechanical properties by reducing stress shielding and improving hydrodynamic performance with higher fluid flow velocity and lower permeability compared to the Uniform Irregular(UI)structure.Additionally,in vitro cell experiments indicated that the GI structure was better than the UI structure in promoting osteogenic differentiation,while in vivo animal studies showed that the GI structure was superior in terms of the ratio of Bone Volume to Total Volume(BV/TV)and Trabecular Number(Tb.N).Thus,the GI structure has greater application potential in bone tissue engineering.展开更多
Track irregularity from rail alternate side wear is manifested as uneven rail wear waveforms alternating in the left and right rails with equal intervals,which will cause carbody sway behaviour of railway vehicles and...Track irregularity from rail alternate side wear is manifested as uneven rail wear waveforms alternating in the left and right rails with equal intervals,which will cause carbody sway behaviour of railway vehicles and greatly influences the passenger comfort.In this work,the carbody sway behaviour and mechanism due to track irregularity from rail alternate side wear and possible solutions to this issue were studied by the field testing and numerical calculation approaches.First,the carbody sway of an urban rail transit train is introduced with full-scale field tests,through which the rail alternate side wear is characterized and the formatted track irregularity are presented.Then,multibody vehicle dynamic models are developed to reproduce the carbody sway behaviour induced by the track irregularity from the rail alternate side wear.The creep forces acting on the wheel and rail are preliminarily discussed to study the influence of the carbody sway on the wear of the wheel flange and the rail corner.Finally,some potential solutions,e.g.improving the damping ratio of carbody rigid mode and rail grinding,are proposed to relieve this issue.It is concluded that an increased damping ratio of the carbody mode can alleviate the carbody sway and wheel–rail interactions,while properly maintaining track conditions can improve the vehicle performance.展开更多
Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by co...Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by conducting large-scale(1:13)experiments to investigate the scour hole pattern and equilibrium scour depth around both slender and large monopiles under irregular waves.The experiments adopted KeuleganeCarpenter number(NKC)values from 1.01 to 8.89 and diffraction parameter(D/L,where D is the diameter of the monopile,and L is the wave length)values from 0.016 to 0.056.The results showed that changes in the maximum scour location and scour hole shape around a slender monopile were associated with NKC,with differences observed between irregular and regular waves.Improving the calculation of NKC enhanced the accuracy of existing scour formulae under irregular waves.The maximum scour locations around a large monopile were consistently found on both sides,regardless of NKC and D/L,but the scour hole topography was influenced by both parameters.Notably,the scour range around a large monopile was at least as large as the monopile diameter.展开更多
Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on co...Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.展开更多
With the continued expansion of oil and gas exploration,both in the eastern and western regions,the quality of seismic acquisition has become a key factor in oil and gas exploration in complex areas.However,convention...With the continued expansion of oil and gas exploration,both in the eastern and western regions,the quality of seismic acquisition has become a key factor in oil and gas exploration in complex areas.However,conventional seismic acquisition methods cannot efficiently avoid challenging acquisition locations and produce high-quality seismic data.In this regard,based on the curvelet transform,this paper proposes an irregular seismic acquisition method,which utilizes the high-precision characteristics of the curvelet transform and simulated annealing algorithm to establish a method for the evaluation of the coherence of irregular sampling matrices and design of observation systems.The method was verified using forward simulation and actual acquisition data.The results suggest the superior quality of seismic data gathered in complicated areas through this method over those acquired using traditional methods,which can provide technical guidance for the design of observation systems in complex areas.展开更多
Objective:To explore the clinical correlation between the detection of irregular antibodies in red blood cell blood groups and hemolytic disease of the newborn.Methods:This study selected newborns who underwent examin...Objective:To explore the clinical correlation between the detection of irregular antibodies in red blood cell blood groups and hemolytic disease of the newborn.Methods:This study selected newborns who underwent examinations and were diagnosed with hemolytic disease at our hospital from October 2024 to October 2025 as the research subjects.Based on the severity of their hemolytic disease,the infants were divided into a severe group and a mild group.All the infants underwent detection for irregular antibodies in their red blood cell blood groups.General information,blood types,and irregular antibody test results of the two groups were recorded.Univariate analysis was conducted,and variables with statistical significance from the univariate analysis were included in a multivariate logistic regression analysis to explore the clinical correlation between the detection of irregular antibodies in red blood cell blood groups and hemolytic disease of the newborn.Results:Through univariate analysis,it was found that IgG1 and IgG3 subclass antibodies,as well as ABO blood group incompatibility,were statistically significant(p<0.05).When these factors were included in a multivariate logistic regression analysis,it was discovered that IgG1(OR=2.461,95%CI:1.859-2.709),IgG3(OR=2.509,95%CI:1.918-2.893),and ABO blood group incompatibility(OR=2.998,95%CI:2.149-3.493)all exhibited a positive correlation with hemolytic disease of the newborn.Conclusion:As levels of IgG1,IgG3,and ABO blood group incompatibility increase,the incidence of hemolytic disease of the newborn also rises,warranting clinical attention.展开更多
Current research on rail vehicle system vibrations primarily relies on numerical methods,with vibration transfer functions commonly derived through data fitting.However,the physical mechanisms underlying these vibrati...Current research on rail vehicle system vibrations primarily relies on numerical methods,with vibration transfer functions commonly derived through data fitting.However,the physical mechanisms underlying these vibrations are not well understood.To clarify the vibration transfer function and its characteristics,four basic input vectors are defined,and an analytical method is proposed.The vibration transfer functions of the vehicle system are solved,and their spatial coherence is analyzed.The results show that there are two spatial scales and four coherent modes in the vehicle system.The track irregularity wavelengths are combined with two spatial scales to alter the proportions of basic input vectors and then show the characteristics of spatial coherence.Four coherent modes are involved in wheel-rail force and primary suspension force;two coherent modes are involved in bogie vertical motion;and their dominant modes vary with the input frequency.On the other hand,the coherent modes involved in the bogie pitching motion and vehicle body motion are single and fixed over the whole range of frequency.This study presents an analytical method for the rapid solution of dynamic responses in vehicle systems and systematically analyzes the coherence behavior of vibration transfer functions with respect to tracking irregularity wavelengths.展开更多
The finite-difference method(FDM)is an essential tool in exploration geophysics,particularly for simulating wave propagation in fluid-solid coupled media.Despite its widespread use,FDM faces significant challenges tha...The finite-difference method(FDM)is an essential tool in exploration geophysics,particularly for simulating wave propagation in fluid-solid coupled media.Despite its widespread use,FDM faces significant challenges that affect its accuracy and efficiency.Firstly,the implicit handling of fluid-solid boundary conditions through parameter averaging strategy often results in low simulation accuracy.Secondly,surface topography can introduce staircase diffraction noise when grid spacing is large.To address these issues,this paper presents a novel approach.We derive an implicit expression for fluidsolid boundary conditions based on average medium theory,translating explicit boundary conditions into model parameter modification.This enables implicit handling of fluid-solid boundaries by modifying the parameters near the boundary.Furthermore,to mitigate staircase diffraction noise,we employ multiple interface discretization based on the superposition method.This effectively suppresses staircase diffraction noise without requiring grid refinement.The efficacy of our method in accurately modeling wave propagation phenomena in fluid-solid coupled media is demonstrated by numerical examples.Results align well with those obtained using the spectral element method(SEM),with significant reduction in staircase diffraction noise.展开更多
Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaboratio...Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52208445,52478321,52378468)the Fundamental Research Funds for the Central Universities(Grant No.G2021KY05105)+7 种基金the Basic Research Program of Natural Science in Shaanxi Province(Grant No.2022JQ-369)the Open Foundation of National Engineering Laboratory for High Speed Railway Construction(No.HSR202001)the Youth Talent Support Program Project of Xi’an Association for Science and Technology(Grant No.959202413090)Science and Technology Research and Development Program Project of China railway group limited(Major Special Project,No.:2020-Special-022021-Special-082023-Special-07)Innovation-driven project of Central South University(2023CXQD072)the National Natural Science Foundation of Hunan Province(Grant No.:2022-JJ-20071).
文摘The characterization of track irregularities is crucial in railway dynamics,as track irregularities are the primary source of internal excitation in railway systems.In this paper,three mathematical models are proposed to characterize the track irregularities under different circumstances.The first model is a novel explicit track spectrum function,which performs better in reflecting the inherent periodic components of track irregularities than the existing track spectra.On this foundation,the second model,a parameterized track spectrum random model,is proposed to represent the vast measured track irregularities from the probabilistic perspective.Finally,the third model,an imprecise track spectrum interval model based on a neighborhood uniform sampling Bootstrap method,is presented to identify the confidential interval of the track spectra when the track irregularity data are limited.Three examples are illustrated to demonstrate the feasibility of the three track irregularity models in characterizing the track irregularities in different conditions.This research can help capture the railway deformation status and optimize track maintenance strategies.
基金Supported by the National Natural Science Foundation of China (Grant No. 11071150)the Natural Science Foundation of Shanxi Province (Grant No. 2012011001-3)Shanxi Scholarship Council of China (Grant No. [2011]8-59)
文摘We classify up to isomorphism those finite p-groups, for odd primes p, which contain a cyclic subgroup of index p3.
基金Supported by NNSF of China(60574052)Supported by NSF(05001820)Supported by PST of Guangdong(2005B33301008)
文摘In the paper we obtain two infinite classes of p-groups, calculate the orders of their automorphism groups and correct a mistake（perhaps misprinted） of Rodney James＇ paper in 1980.
基金Supported by the National Natural Science Foundation of China(Grant Nos.1152611411601245)+3 种基金the Natural Science Foundation of Guangdong Province(Grant No.2015A030313791)the Innovative Team Project of Guangdong Province(CHINA)(Grant No.2014KTSCX196)Guangdong Province Innovation Talent Project for Youths(Grant No.2015KQNCX107)the Appropriative Researching Fund for Doctors,Guangdong University of Education(Grant No.2013ARF07)
文摘A p-group G is called a JC-group if the normal closure HG of every cyclic subgroup H satisfies｜G：HG｜≤p or｜HG：H｜≤p.In this paper, we classify the non-Dedekindian JC-groups for p 〉 2.
基金Supported by National Natural Science Foundation of China(11601121)Henan Provincial Natural Science Foundation of China(162300410066)
文摘Let p be a prime number and f_2(G) be the number of factorizations G = AB of the group G, where A, B are subgroups of G. Let G be a class of finite p-groups as follows,G = a, b | a^(p^n)= b^(p^m)= 1, a^b= a^(p^(n-1)+1), where n > m ≥ 1. In this article, the factorization number f_2(G) of G is computed, improving the results of Saeedi and Farrokhi in [5].
文摘In this paper, we study the basis of augmentation ideals and the quotient groups of finite non-abelian p-group which has a cyclic subgroup of index p, where p is an odd prime, and k is greater than or equal to 3. A concrete basis for the augmentation ideal is obtained and then the structure of its quotient groups can be determined.
基金Supported by the NSF of China(11171194)by the NSF of Shanxi Province(2012011001-1)
文摘For any prime p, all finite noncyclic p-groups which contain a self-centralizing cyclic normal subgroup are determined by using cohomological techniques. Some applications are given, including a character theoretic description for such groups.
基金Supported by National Natural Science Foundation of China(Grant No.11601121,12171142).
文摘Let G be a group and A and B be subgroups of G.If G=AB,then G is said to be factorized by A and B.Let p be a prime number.The factorization numbers of a 2-generators abelian p-group and a modular p-group have been determined.Further,suppose that G is a finite p-group as follows G=<a,b|a^(p)^(n)=b^(p)^(m)=1,a^(b)=a^(p^(n-1)+1)>,where n≥2,m≥1.In this paper,the factorization number of G is computed completely,which is a generalization of the result of Saeedi and Farrokhi.
基金supported by Natural Science Foundation of China(52178441)the Scientific Research Projects of the China Academy of Railway Sciences Co.,Ltd.(Grant No.2022YJ043).
文摘Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed railways.They can cause significant wheel-rail dynamic interactions,leading to wheel-rail noise,component damage,and deterioration.Few researchers have employed the vehicle-track interaction dynamic model to study the dynamic interactions between wheel and rail induced by rail weld geometry irregularities.However,the cosine wave model used to simulate rail weld irregularities mainly focuses on the maximum value and neglects the geometric shape.In this study,novel theoretical models were developed for three categories of rail weld irregularities,based on measurements of the high-speed railway from Beijing to Shanghai.The vertical dynamic forces in the time and frequency domains were compared under different running speeds.These forces generated by the rail weld irregularities that were measured and modeled,respectively,were compared to validate the accuracy of the proposed model.Finally,based on the numerical study,the impact force due to rail weld irrregularity is modeled using an Artificial Neural Network(ANN),and the optimum combination of parameters for this model is found.The results showed that the proposed model provided a more accurate wheel/rail dynamic evaluation caused by rail weld irregularities than that established in the literature.The ANN model used in this paper can effectively predict the impact force due to rail weld irrregularity while reducing the computation time.
基金supported by the National Natural Science Foundation of China(Nos.12372056,12032017,12393783)the S&T Program of Hebei of China(No.24465001D)。
文摘Axle box bearings are critical components of high-speed trains.Localized defects,such as pitting and spalling,on raceways or rollers pose significant threats to the operational safety of railway vehicles.In this work,a novel bearing-flexible axle boxvehicle coupling model is established to explore the vibration characteristics of axle box bearings with irregular localized defects.First,based on the contact and kinematic relationship between rollers and raceways,the three-dimensional(3D)bearing force elements are analyzed and formulated.Second,the established model and a flexible axle box are integrated into the vehicle,and the responses of the normal and faulty bearings under the combined excitations of wheel roughness and track irregularities are simulated.Third,the simulation results are verified through a rolling-vibrating test bench for full-scale wheelsets of high-speed trains.The comparisons of the fault-induced repetitive transients in the time-domain and the fault characteristic frequencies in the envelope spectra demonstrate the efficiency of the proposed model.Finally,based on the flexible axle box model,a sensitivity analysis of the accelerometer placements to the bearing faults is carried out,and the optimal one is identified based on both the time-domain and frequency-domain signal-to-noise ratios(SNRs)for engineering applications.
基金Project(2022YFB2602900)supported by the National Key Research and Development Program of ChinaProject(K2022T002)supported by the Scientific Research Plan of China Railway。
文摘As one of the major high-speed railway ballastless track structures in China,CRTSIII slab ballastless track has been laid for more than 6500 km.However,there are no detailed studies on its track irregularity deterioration throughout extended service periods,which may threaten the safety and stability of high-speed vehicles(HSV).In this study,a long-term tracking detection of CRTSIII slab ballastless track irregularities has been conducted,revealing its annual evolution law.An HSV-track coupled dynamics model was established to investigate the HSV dynamic responses under annual evolution of track irregularities.Considering the potential deterioration of track irregularities to extremely bad condition,the recommended classified limits for irregularity are proposed by analyzing the limit-exceeding probability of the safety and stability indexes of HSV.The results show that:taking 10 m wavelength as a demarcation,longer-wavelength irregularities exhibit larger amplitudes,faster evolution rates and a linear increasing trend,primarily affecting the stability of HSV.Conversely,shorter-wavelength irregularities exhibit smaller amplitudes and an insignificant evolution trend,predominantly affecting the safety of HSV.Furthermore,the periodic irregularity induced by the arching of 32 m simply-supported beam bridge should be paid closer attention to,as their evolution rate significantly surpasses that of irregularities at other wavelengths.
基金supported by Medical Science and Technology Research of Guangdong Province(NO.B2024033)Medical Science and Technology Research of Guangdong Province(NO.A2024352)+1 种基金National Demonstration Pilot Project for the Inheritance and Innovative Development of Traditional Chinese Medicine-Research Project on Traditional Chinese Medicine at Zhongshan Hospital of Traditional Chinese Medicine(NO.YN2024B002)China Postdoctoral Science Foundation(NO.2024M750668).
文摘The irregular porous structure,similar to human bone tissue,is more beneficial for bone ingrowth than the regular one.We proposed a new design method to create uniform and gradient irregular porous structures with porosities from 38 to 83%based on Voronoi tessellation.The models were fabricated using selective laser sintering,and micro-CT was used to assess their morphological features.Mechanical and fluid flow properties were evaluated through experiments and computational fluid dynamics simulations.Micro-CT scans confirmed that 3D printing can produce high-quality irregular structures.The Graded Irregular(GI)structure showed clear advantages in mechanical properties by reducing stress shielding and improving hydrodynamic performance with higher fluid flow velocity and lower permeability compared to the Uniform Irregular(UI)structure.Additionally,in vitro cell experiments indicated that the GI structure was better than the UI structure in promoting osteogenic differentiation,while in vivo animal studies showed that the GI structure was superior in terms of the ratio of Bone Volume to Total Volume(BV/TV)and Trabecular Number(Tb.N).Thus,the GI structure has greater application potential in bone tissue engineering.
基金supported by the National Natural Science Foundation of China(Grant Nos.52002344,U2034210,and 61960206010)the Development Project of State Key Laboratory of Rail Transit Vehicle System(Grant No.2022TPL_T09)。
文摘Track irregularity from rail alternate side wear is manifested as uneven rail wear waveforms alternating in the left and right rails with equal intervals,which will cause carbody sway behaviour of railway vehicles and greatly influences the passenger comfort.In this work,the carbody sway behaviour and mechanism due to track irregularity from rail alternate side wear and possible solutions to this issue were studied by the field testing and numerical calculation approaches.First,the carbody sway of an urban rail transit train is introduced with full-scale field tests,through which the rail alternate side wear is characterized and the formatted track irregularity are presented.Then,multibody vehicle dynamic models are developed to reproduce the carbody sway behaviour induced by the track irregularity from the rail alternate side wear.The creep forces acting on the wheel and rail are preliminarily discussed to study the influence of the carbody sway on the wear of the wheel flange and the rail corner.Finally,some potential solutions,e.g.improving the damping ratio of carbody rigid mode and rail grinding,are proposed to relieve this issue.It is concluded that an increased damping ratio of the carbody mode can alleviate the carbody sway and wheel–rail interactions,while properly maintaining track conditions can improve the vehicle performance.
基金supported by the National Nature Science Foundation of China National Outstanding Youth Science Fund Project(Grant No.52122109)the National Natural Science Foundation of China(Grants No.51861165102 and 52039005).
文摘Offshore wind power plays a crucial role in energy strategies.The results of traditional small-scale physical models may be unreliable when extrapolated to large field scales.This study addressed this limitation by conducting large-scale(1:13)experiments to investigate the scour hole pattern and equilibrium scour depth around both slender and large monopiles under irregular waves.The experiments adopted KeuleganeCarpenter number(NKC)values from 1.01 to 8.89 and diffraction parameter(D/L,where D is the diameter of the monopile,and L is the wave length)values from 0.016 to 0.056.The results showed that changes in the maximum scour location and scour hole shape around a slender monopile were associated with NKC,with differences observed between irregular and regular waves.Improving the calculation of NKC enhanced the accuracy of existing scour formulae under irregular waves.The maximum scour locations around a large monopile were consistently found on both sides,regardless of NKC and D/L,but the scour hole topography was influenced by both parameters.Notably,the scour range around a large monopile was at least as large as the monopile diameter.
基金supported by the Sichuan Science and Technology Program(Nos.2024JDRC0100 and 2023YFQ0091)the National Natural Science Foundation of China(Nos.U21A20167 and 52475138)the Scientific Research Foundation of the State Key Laboratory of Rail Transit Vehicle System(No.2024RVL-T08).
文摘Accurate monitoring of track irregularities is very helpful to improving the vehicle operation quality and to formulating appropriate track maintenance strategies.Existing methods have the problem that they rely on complex signal processing algorithms and lack multi-source data analysis.Driven by multi-source measurement data,including the axle box,the bogie frame and the carbody accelerations,this paper proposes a track irregularities monitoring network(TIMNet)based on deep learning methods.TIMNet uses the feature extraction capability of convolutional neural networks and the sequence map-ping capability of the long short-term memory model to explore the mapping relationship between vehicle accelerations and track irregularities.The particle swarm optimization algorithm is used to optimize the network parameters,so that both the vertical and lateral track irregularities can be accurately identified in the time and spatial domains.The effectiveness and superiority of the proposed TIMNet is analyzed under different simulation conditions using a vehicle dynamics model.Field tests are conducted to prove the availability of the proposed TIMNet in quantitatively monitoring vertical and lateral track irregularities.Furthermore,comparative tests show that the TIMNet has a better fitting degree and timeliness in monitoring track irregularities(vertical R2 of 0.91,lateral R2 of 0.84 and time cost of 10 ms),compared to other classical regression.The test also proves that the TIMNet has a better anti-interference ability than other regression models.
基金innovation consortium project of China Petroleum and Southwest Petroleum University(No.2020CX010201)Sichuan Science and Technology Program(No.2024NSFSC0081)。
文摘With the continued expansion of oil and gas exploration,both in the eastern and western regions,the quality of seismic acquisition has become a key factor in oil and gas exploration in complex areas.However,conventional seismic acquisition methods cannot efficiently avoid challenging acquisition locations and produce high-quality seismic data.In this regard,based on the curvelet transform,this paper proposes an irregular seismic acquisition method,which utilizes the high-precision characteristics of the curvelet transform and simulated annealing algorithm to establish a method for the evaluation of the coherence of irregular sampling matrices and design of observation systems.The method was verified using forward simulation and actual acquisition data.The results suggest the superior quality of seismic data gathered in complicated areas through this method over those acquired using traditional methods,which can provide technical guidance for the design of observation systems in complex areas.
文摘Objective:To explore the clinical correlation between the detection of irregular antibodies in red blood cell blood groups and hemolytic disease of the newborn.Methods:This study selected newborns who underwent examinations and were diagnosed with hemolytic disease at our hospital from October 2024 to October 2025 as the research subjects.Based on the severity of their hemolytic disease,the infants were divided into a severe group and a mild group.All the infants underwent detection for irregular antibodies in their red blood cell blood groups.General information,blood types,and irregular antibody test results of the two groups were recorded.Univariate analysis was conducted,and variables with statistical significance from the univariate analysis were included in a multivariate logistic regression analysis to explore the clinical correlation between the detection of irregular antibodies in red blood cell blood groups and hemolytic disease of the newborn.Results:Through univariate analysis,it was found that IgG1 and IgG3 subclass antibodies,as well as ABO blood group incompatibility,were statistically significant(p<0.05).When these factors were included in a multivariate logistic regression analysis,it was discovered that IgG1(OR=2.461,95%CI:1.859-2.709),IgG3(OR=2.509,95%CI:1.918-2.893),and ABO blood group incompatibility(OR=2.998,95%CI:2.149-3.493)all exhibited a positive correlation with hemolytic disease of the newborn.Conclusion:As levels of IgG1,IgG3,and ABO blood group incompatibility increase,the incidence of hemolytic disease of the newborn also rises,warranting clinical attention.
基金Supported by Fundamental Research Funds for the Central Universities(Grant No.2024QYBS031)Fundamental Research Funds for the Central Universities(Grant No.2022JBQY007)。
文摘Current research on rail vehicle system vibrations primarily relies on numerical methods,with vibration transfer functions commonly derived through data fitting.However,the physical mechanisms underlying these vibrations are not well understood.To clarify the vibration transfer function and its characteristics,four basic input vectors are defined,and an analytical method is proposed.The vibration transfer functions of the vehicle system are solved,and their spatial coherence is analyzed.The results show that there are two spatial scales and four coherent modes in the vehicle system.The track irregularity wavelengths are combined with two spatial scales to alter the proportions of basic input vectors and then show the characteristics of spatial coherence.Four coherent modes are involved in wheel-rail force and primary suspension force;two coherent modes are involved in bogie vertical motion;and their dominant modes vary with the input frequency.On the other hand,the coherent modes involved in the bogie pitching motion and vehicle body motion are single and fixed over the whole range of frequency.This study presents an analytical method for the rapid solution of dynamic responses in vehicle systems and systematically analyzes the coherence behavior of vibration transfer functions with respect to tracking irregularity wavelengths.
基金supported by the National Natural Science Foundation of China(Nos.42404134,U24B2031,42174160)the China Postdoctoral Science Foundation(No.2024M753204)the National Key R&D Program of China(Nos.2021YFA0716901,2022YFB3904601)。
文摘The finite-difference method(FDM)is an essential tool in exploration geophysics,particularly for simulating wave propagation in fluid-solid coupled media.Despite its widespread use,FDM faces significant challenges that affect its accuracy and efficiency.Firstly,the implicit handling of fluid-solid boundary conditions through parameter averaging strategy often results in low simulation accuracy.Secondly,surface topography can introduce staircase diffraction noise when grid spacing is large.To address these issues,this paper presents a novel approach.We derive an implicit expression for fluidsolid boundary conditions based on average medium theory,translating explicit boundary conditions into model parameter modification.This enables implicit handling of fluid-solid boundaries by modifying the parameters near the boundary.Furthermore,to mitigate staircase diffraction noise,we employ multiple interface discretization based on the superposition method.This effectively suppresses staircase diffraction noise without requiring grid refinement.The efficacy of our method in accurately modeling wave propagation phenomena in fluid-solid coupled media is demonstrated by numerical examples.Results align well with those obtained using the spectral element method(SEM),with significant reduction in staircase diffraction noise.
基金supported by the Beijing Natural Science Foundation(Certificate Number:L234025).
文摘Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.
