Integration and Optimization of Railway Engineering Laboratory Resources under the Background of"Double First Class"

With the continuous development of China's social economy,it has correspondingly promoted the development of the railway engineering experimental career,and has made tremendous progress in the cultivation of railway engineering experimental talents.At the same time,there are still many problems in the development of rail transit in the construction of"double first-class".Only by solving the existing problems can we further promote the smooth development of the training of railway engineering experimental talents.Therefore,the article mainly analyzes the problems and countermeasures of railway engineering experimental training,combined with the status and role of laboratories in the training of talents under the background of"double first-class",according to the society's demand for first-class engineering talents,we reformed and explored laboratory resource integration and optimization.

Railway Engineering Experimental Teaching Research Based on the Combination of Field Experiment and Virtual Reality(VR)Technology——Taking Central South University as an Example

At present,rail transit is developing rapidly in the world,and this means new and changing requirements for the training of talents in railway engineering experiments.Given the current problems of limited laboratory/field instruments for railway engineering experimentsand the safety/administrative difficulties of going to the frontline of railway lines to teach railway engineering experiemnts in the field,the Department of Railway Engineering of Central South University tried to introduce virtual reality(VR)technology to teach students experiments in the field of railway engineering.Through the virtualized experimental methods,students can carry out railway engineering experiments such as;vehicle wheel pair off-axis experiments,track geometry and position detection,etc.by immersive means.It was observed that after performing virtual simulation experiments,students appeared conversant in subsequent field experiments.Thus,VR greatly improves the teaching efficiency of railway engineering experiments.

A Unified Dimensionless Parameter for Finite Element Mesh for Beams Resting on Elastic Foundation

Discretising a structure into elements is a key step in finite element(FE)analysis.The discretised geometry used to formulate an FE model can greatly affect accuracy and validity.This paper presents a unified dimensionless parameter to generate a mesh of cubic FEs for the analysis of very long beams resting on an elastic foundation.A uniform beam resting on elastic foundation with various values of flexural stiffness and elastic supporting coefficients subject to static load and moving load is used to illustrate the application of the proposed parameter.The numerical results show that(a)Even if the values of the flexural stiffness of the beam and elastic supporting coefficient of the elastic foundation are different,the same proposed parameter“s”can ensure the same accuracy of the FE solution,but the accuracy may differ for use of the same element length;(b)The proposed dimensionless parameter“s”can indeed be used as a unified index to generate the mesh for a beam resting on elastic foundation,whereas the use of the same element length as a criterion may be misleading;(c)The errors between the FE and analytical solutions for the maximum vertical displacement,shear force and bending moment of the beam increase with the dimensionless parameter“s”;and(d)For the given allowable errors for the vertical displacement,shear force and bending moment of the beam under static load and moving load,the corresponding values of the proposed parameter are provided to guide the mesh generation.

Manufacturing enterprise collaboration network:An empirical research and evolutionary model

With the increasingly fierce market competition,manufacturing enterprises have to continuously improve their competitiveness through their collaboration and labor division with each other,i.e.forming manufacturing enterprise collaborative network(MECN)through their collaboration and labor division is an effective guarantee for obtaining competitive advantages.To explore the topology and evolutionary process of MECN,in this paper we investigate an empirical MECN from the viewpoint of complex network theory,and construct an evolutionary model to reproduce the topological properties found in the empirical network.Firstly,large-size empirical data related to the automotive industry are collected to construct an MECN.Topological analysis indicates that the MECN is not a scale-free network,but a small-world network with disassortativity.Small-world property indicates that the enterprises can respond quickly to the market,but disassortativity shows the risk spreading is fast and the coordinated operation is difficult.Then,an evolutionary model based on fitness preferential attachment and entropy-TOPSIS is proposed to capture the features of MECN.Besides,the evolutionary model is compared with a degree-based model in which only node degree is taken into consideration.The simulation results show the proposed evolutionary model can reproduce a number of critical topological properties of empirical MECN,while the degree-based model does not,which validates the effectiveness of the proposed evolutionary model.

Research on Experimental Teaching Reform of Railway Engineering under the Training of International Students

The railway engineering major shows extremely strong applicability,with the internationalization of railway engineering teaching and communication,how to solve the problem of cultivating the international students of the railway engineering major experimental teaching is a core problem that the railway engineering majors in universities need to solve at this stage.Through reform,a new type of experimental teaching system for railway engineering specialty was constructed,that is,the experimental course system and content system determined by the international students training program were taken as the core,the construction of teachers,experimental facilities,practice bases and other conditions as the basis,and the system construction and operation organization to build an organic whole composed of four elements for guarantee.It is closely integrated with the theoretical teaching system and relatively independent.It guarantees the realization of the goal of international students training.And it can integrate and optimize the experimental teaching links,content,methods and evaluation system,and build a“gradual experimentprofessional experiment-comprehensive experiment”progressive gradient experiment teaching system.Form a benign pattern of collaborative training of laboratories,practice bases and scientific research bases,mutual promotion of teaching and scientific research,and effectively promote the improvement of students’experimental innovation ability.

Quantitative Variation in Water-Use Efficiency across Water Regimes and Its Relationship with Circadian, Vegetative, Reproductive, and Leaf Gas-Exchange Traits

Drought limits light harvesting, resulting in lower plant growth and reproduction. One trait important for plant drought response is water-use efficiency （WUE）. We investigated （1） how the joint genetic architecture of WUE, reproductive characters, and vegetative traits changed across drought and well-watered conditions, （2） whether traits with distinct developmental bases （e.g. leaf gas exchange versus reproduction） differed in the environmental sensitivity of their genetic architecture, and （3） whether quantitative variation in circadian period was related to drought response in Brassica rapa. Overall, WUE increased in drought, primarily because stomatal conductance, and thus water loss, declined more than carbon fixation. Genotypes with the highest WUE in drought expressed the lowest WUE in well-watered conditions, and had the largest vegetative and floral organs in both treatments. Thus, large changes in WUE enabled some genotypes to approach vegetative and reproductive trait optima across environments. The genetic architecture differed for gas-exchange and vegetative traits across drought and well-watered conditions, but not for floral traits. Correlations between circadian and leaf gas-exchange traits were significant but did not vary across treatments, indicating that circadian period affects physiological function regardless of water availability. These results suggest that WUE is important for drought tolerance in Brassica rapa and that artificial selection for increased WUE in drought will not result in maladaptive expression of other traits that are correlated with WUE.

Key point selection in large-scale FBG temperature sensors for thermal error modeling of heavy-duty CNC machine tools

Thermal error is one of the main factors that influence the machining accuracy of computer numerical control(CNC)machine tools.It is usually reduced by thermal error compensation.Temperature field monitoring and key temperature measurement point(TMP)selection are the bases of thermal error modeling and compensation for CNC machine tools.Compared with small-and medium-sized CNC machine tools,heavy-duty CNC machine tools require the use of more temperature sensors to measure their temperature comprehensively because of their larger size and more complex heat sources.However,the presence of many TMPs counteracts the movement of CNC machine tools due to sensor cables,and too many temperature variables may adversely influence thermal error modeling.Novel temperature sensors based on fiber Bragg grating(FBG)are developed in this study.A total of 128 FBG temperature sensors that are connected in series through a thin optical fiber are mounted on a heavy-duty CNC machine tool to monitor its temperature field.Key TMPs are selected using these large-scale FBG temperature sensors by using the density-based spatial clustering of applications with noise algorithm to reduce the calculation workload and avoid problems in the coupling of TMPs for thermal error modeling.Back propagation neural network thermal error prediction models are established to verify the performance of the proposed TMP selection method.Results show that the number of TMPs is reduced from 128 to 5,and the developed model demonstrates good prediction effects and strong robustness under different working conditions of the heavy-duty CNC machine tool.

Vertical temperature gradients of concrete box girder caused by solar radiation in Sichuan-Tibet railway

Spatial and temporal temperature variations are critical for concrete box girders,and non-uniform temperature distributions induced by solar radiation depend on the structural shapes and shadows cast on them.There have been many studies of temperature distributions and temperature gradients of concrete box girders,but few have considered a high altitude plateau climatic environment.In this study,the nonlinear temperature distributions of concrete box girders in the Sichuan-Tibet railway caused by solar radiation were investigated based on experimental analysis,real-time shadow-selection algorithm,and finite element method.Furthermore,a vertical temperature gradient model of the concrete box girders was obtained.The vertical temperature gradient values first rise,then decrease,and finally rise again from Chengdu to Lhasa,with samples forming a normal distribution.The recommended vertical temperature gradient value was 25℃with a confidence interval of 95%.This provides a reference for the design and maintenance of concrete box girders on the Sichuan-Tibet railway.

Degradation mechanism analysis of LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2) single crystal cathode materials through machine learning

LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2)(NCM523)has become one of the most popular cathode materials for current lithium-ion batteries due to its high-energy density and cost performance.However,the rapid capacity fading of NCM severely hinders its development and applications.Here,the single crystal NCM523 materials under different degradation states are characterized using scanning transmission electron microscopy(STEM).Then we developed a neural network model with a two-sequential attention block to recognize the crystal structure and locate defects in STEM images.The number of point defects in NCM523 is observed to experience a trend of increasing first and then decreasing in the degradation process.The space between the transition metal columns shrinks obviously,inducing dramatic capacity decay.This analysis sheds light on the defect evolution and chemical transformation correlated with layered material degradation.It also provides interesting hints for researchers to regenerate the electrochemical capacity and design better battery materials with longer life.