Accurately predicting battery degradation is crucial for battery system management.However,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation ...Accurately predicting battery degradation is crucial for battery system management.However,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation solely through maximum capacity loss assessment is challenging.While machine learning offers promising solutions,it often overlooks domain knowledge,resulting in reduced accu racy,increased computational burden and decreased interpretability.Here,this study proposes a method to predict the voltage-capacity(V-Q) curve during battery degradation with limited historical data.This process is achieved through two physically interpretable components:a lightweight interpretable physical model and a physics-informed neural network.These components incorporate domain knowledge into machine learning to improve V-Q curve prediction performance and enhance interpretability.Extensive validation was conducted on 52 batteries of different types under different testing conditions.The proposed method can accurately predict future V-Q.curves for hundreds of cycles using only one-present-cycle V-Q curve,with root mean square error and mean absolute error basically less than 0.035 Ah and R^(2) basically less than 98.5%.This means that incremental capacity curves can be extracted from the predicted results for a more comprehensive and accurate battery degradation analysis.Furthermore,the method can flexibly adjust prediction length and density to cater to the practical needs of long-cycle prediction and data generation.This study provides a viable method for rapid degradation prediction and is expected to be generalized to in-vehicle implementations.展开更多
The high-pressure mercury intrusion (HPMI) experiment is widely used to assess the pore architecture oftight sandstone reservoirs. However, the conventional analysis of the high- pressure mercury intrusionhas always f...The high-pressure mercury intrusion (HPMI) experiment is widely used to assess the pore architecture oftight sandstone reservoirs. However, the conventional analysis of the high- pressure mercury intrusionhas always focused on the mercury injection curves themselves, neglecting the important geologicalinformation conveyed by the mercury ejection curves. This paper quantitatively describes the fractalcharacteristics of ejection curves by using four fractal models, i.e.,. Menger model, Thermodynamicmodel, Sierpinski model, and multi- fractal model. In comparison with mercury injection curves, weexplore the fractal significance of mercury ejection curves and define the applicability of different fractalmodels in characterizing pore architectures. Investigated tight sandstone samples can be divided intofour types (Types A, B, C and D) based on porosity, permeability, and mercury removal efficiency. Type Dsamples are unique in that they have higher permeability (>0.6 mD) but lower mercury removal effi-ciency (<35%). Fractal studies of the mercury injection curve show that it mainly reflects the pore throatcharacteristics, while the mercury ejection curve serves to reveal the pore features, and porosity andpermeability correlate well with the fractal dimension of the injection curve, while mercury removalefficiency correlates only with the Ds' value of the ejection curve. The studies on the mercury ejectioncurves also reveal that the small pores and micropores of the Type C and Type D samples are moredeveloped, with varying pore architecture. The fractal dimension Ds' value of Type D samples is greaterthan that of Type C samples, and the dissolution of Type D samples is more intense than that of Type Csamples, which further indicates that the Type D samples are smaller in pore size, rougher in surface, andwith greater difficulty for the hydrocarbon to enter, resulting in their reservoir capacity probably lessthan that of Type C samples. In this regard, the important information characterized by the mercuryejection curve should be considered in evaluating the tight sandstone reservoirs. Finally, the Menger andThermodynamic models prove to be more suitable for describing the total pore architecture, while theSierpinski model is better for characterizing the variability of the interconnected pores.展开更多
Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated opt...Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.Design/methodology/approach–Taking a small-radius curve of a high-speed railway as the research object,field measurements were conducted to obtain track parameters and wheel–rail profiles.A coupled vehicle-track dynamics model was established.Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.Findings–Key service parameters affecting wheel–rail creepage were identified,including the matching relationship between curve geometry and vehicle speed and rail profile parameters.The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis,leading to the establishment of parameter optimization criteria.Originality/value–This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves.A response surface-based parameter-creepage relationship model was established,and a multi-parameter coordinated optimization strategy was proposed.The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves.展开更多
In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curv...In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.展开更多
With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair compar...With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.展开更多
The present study aims to obtain p-y curves(Winkler spring properties for lateral pile-soil interaction)for liquefied soil from 12 comprehensive centrifuge test cases where pile groups were embedded in liquefiable soi...The present study aims to obtain p-y curves(Winkler spring properties for lateral pile-soil interaction)for liquefied soil from 12 comprehensive centrifuge test cases where pile groups were embedded in liquefiable soil.The p-y curve for fully liquefied soil is back-calculated from the dynamic centrifuge test data using a numerical procedure from the recorded soil response and strain records from the instrumented pile.The p-y curves were obtained for two ground conditions:(a)lateral spreading of liquefied soil,and(b)liquefied soil in level ground.These ground conditions are simulated in the model by having collapsing and non-collapsing intermittent boundaries,which are modelled as quay walls.The p-y curves back-calculated from the centrifuge tests are compared with representative reduced API p-y curves for liquefied soils(known as p-multiplier).The response of p-y curves at full liquefaction is presented and critical observations of lateral pile-soil interaction are discussed.Based on the results of these model tests,guidance for the construction of p-y curves for use in engineering practice is also provided.展开更多
Global inland surface water bodies such as lakes and reservoirs,important components of the hydrosphere and ecosphere,are increasingly affected by climate change.Generating bathymetric volume-areaheight (BVAH) curves ...Global inland surface water bodies such as lakes and reservoirs,important components of the hydrosphere and ecosphere,are increasingly affected by climate change.Generating bathymetric volume-areaheight (BVAH) curves for global inland surface water bodies can enhance our understanding of their topography and climate impacts.However,accurately quantifying the topographic patterns of these water bodies remains challenging due to the difficulties in collecting comprehensive bathymetric data.Therefore,we collected and processed over 2000 bathymetric maps of global water bodies from over 50 different data sources and then developed the BVAH model.Finally,the BVAH hydrological curves of 16671 global inland surface water bodies (larger than 10 km~2) were generated.The results include but are not limited to (1) For most targeted water bodies,area (A) and volume (V) exhibit significant power function relationships with surface heights (H),with optimal power values quantified as 1.42 for A and 2.42 for V.(2) The BVAH model outperforms GLOBathy in estimating area and volume changes,achieving higher correlation coefficients (CC) of approximately 0.962 for the area and 0.991 for volume,and demonstrating lower percentages of root mean squared errors (PRMSE) around 10.9% for the area and 4.8% for volume.(3) In the case study of the Xizang Plateau and various large global reservoirs,the BVAH curve database can capture dynamic volume changes.As a unified simulation of the bathymetric topographical patterns,our bathymetric dataset and corresponding BVAH curve database have great potential to contribute to effective water resource management and ecological conservation efforts worldwide.展开更多
AASHTO’s guideline for geometric design of highways and similar guidelines require that roadside areas on the inside of horizontal curves be cleared of high objects to provide stopping sight distance. The guidelines ...AASHTO’s guideline for geometric design of highways and similar guidelines require that roadside areas on the inside of horizontal curves be cleared of high objects to provide stopping sight distance. The guidelines have analytical models for determining the extent of clearance, known as the horizontal sightline offset or clearance offset, for simple curves. Researchers in the past have developed analytical models for clearance offsets for spiraled and reverse curves. Very few researchers developed analytical models for available sight distances for compound curves. Still missing are models for horizontal sightline offsets and locations of the offsets for compound curves. The objective of this paper is to present development of analytical models and charts for determining horizontal sightline offsets and their locations for compound curves. The paper considers curves whose component arcs are individually shorter than stopping sight distance. The resulting models and the charts have been verified with accurate values determined using graphical methods. The models and the charts will find application in geometric design of highway compound curves.展开更多
In this study,centrifuge model tests of vertical and batter pile groups in liquefied sand were conducted on a centrifuge shaking table.The dynamic p-y curves for these pile groups before and during sand liquefaction w...In this study,centrifuge model tests of vertical and batter pile groups in liquefied sand were conducted on a centrifuge shaking table.The dynamic p-y curves for these pile groups before and during sand liquefaction were obtained from calculations based on test data.The results confirm that liquefaction contributes to a reduction in the energy consumption of pile foundations,with the degradation effect being more pronounced for batter pile groups.At shallow depths,the difference in the backbone gradients of the p-y curves after liquefaction for vertical and batter pile groups indicates that the lateral stiffness of a batter pile group is greater than that of a vertical pile group.As shaking intensity increases,the lateral stiffness of a vertical pile group increases with depth during the late stage of sand liquefaction.However,the lateral stiffness of a batter pile group during liquefaction does not vary with depth.The results of this study provide a reference for the seismic design of vertical and batter pile groups in liquefied soil.展开更多
Background: The signal-to-noise ratio (SNR) is recognized as an index of measurements reproducibility. We derive the maximum likelihood estimators of SNR and discuss confidence interval construction on the difference ...Background: The signal-to-noise ratio (SNR) is recognized as an index of measurements reproducibility. We derive the maximum likelihood estimators of SNR and discuss confidence interval construction on the difference between two correlated SNRs when the readings are from bivariate normal and bivariate lognormal distribution. We use the Pearsons system of curves to approximate the difference between the two estimates and use the bootstrap methods to validate the approximate distributions of the statistic of interest. Methods: The paper uses the delta method to find the first four central moments, and hence the skewness and kurtosis which are important in the determination of the parameters of the Pearsons distribution. Results: The approach is illustrated in two examples;one from veterinary microbiology and food safety data and the other on data from clinical medicine. We derived the four central moments of the target statistics, together with the bootstrap method to evaluate the parameters of Pearsons distribution. The fitted Pearsons curves of Types I and II were recommended based on the available data. The R-codes are also provided to be readily used by the readers.展开更多
Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation sector.However,the exchange of beacons and messages ov...Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation sector.However,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy violations.To address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed recently.However,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many attacks.As such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)operations.The formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably secure.The proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and unlinkability.Moreover,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and impersonations.From the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security features.Therefore,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.展开更多
The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of ...The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of security while optimizing the efficiency of computer resources. This study focuses on how elliptic curves cryptography helps to protect sensitive data. Text is encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. The elliptic curves cryptography of this study is better than using a 256-bit RSA key. To achieve equivalent protection by using the elliptic curves cryptography, several Python libraries such as cryptography, pycryptodome, pyQt5, secp256k1, etc. were used. These technologies are used to develop a software based on elliptic curves. If built, the software helps to encrypt and decrypt data such as a text messages and it offers the authentication for the communication.展开更多
In recent years,various internet architectures,such as Integrated Services(IntServ),Differentiated Services(DiffServ),Time Sensitive Networking(TSN)and Deterministic Networking(DetNet),have been proposed to meet the q...In recent years,various internet architectures,such as Integrated Services(IntServ),Differentiated Services(DiffServ),Time Sensitive Networking(TSN)and Deterministic Networking(DetNet),have been proposed to meet the quality-of-service(QoS)requirements of different network services.Concurrently,network calculus has found widespread application in network modeling and QoS analysis.Network calculus abstracts the details of how nodes or networks process data packets using the concept of service curves.This paper summarizes the service curves for typical scheduling algorithms,including Strict Priority(SP),Round Robin(RR),Cycling Queuing and Forwarding(CQF),Time Aware Shaper(TAS),Credit Based Shaper(CBS),and Asynchronous Traffic Shaper(ATS).It introduces the theory of network calculus and then provides an overview of various scheduling algorithms and their associated service curves.The delay bound analysis for different scheduling algorithms in specific scenarios is also conducted for more insights.展开更多
The dynamic viscoelastic properties of asphalt AC-20 and its composites with Organic-Montmorillonite clay (OMMt) and SBS were modeled using the empirical Havriliak-Negami (HN) model, based on linear viscoelastic theor...The dynamic viscoelastic properties of asphalt AC-20 and its composites with Organic-Montmorillonite clay (OMMt) and SBS were modeled using the empirical Havriliak-Negami (HN) model, based on linear viscoelastic theory (LVE). The HN parameters, α, β, G0, G∞and τHN were determined by solving the HN equation across various temperatures and frequencies. The HN model successfully predicted the rheological behavior of the asphalt and its blends within the temperature range of 25˚C - 40˚C. However, deviations occurred between 40˚C - 75˚C, where the glass transition temperature Tg of the asphalt components and the SBS polymer are located, rendering the HN model ineffective for predicting the dynamic viscoelastic properties of composites containing OMMt under these conditions. Yet, the prediction error of the HN model dropped to 2.28% - 2.81% for asphalt and its mixtures at 100˚C, a temperature exceeding the Tg values of both polymer and asphalt, where the mixtures exhibited a liquid-like behavior. The exponent α and the relaxation time increased with temperature across all systems. Incorporating OMMt clay into the asphalt blends significantly enhanced the relaxation dynamics of the resulting composites.展开更多
Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the geometric characteristics of a...Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the geometric characteristics of any point on the discrete curve, a distance-based Gaussian weighted algorithm is proposed to estimate the geometric characteristics of three-dimensional space discrete curves. According to the definition of discrete derivatives, the algorithm fully considers the relative position difference between a specific point and its neighboring points, introduces the distance weighting idea, and integrates the smoothing strategy. The experiment uses two spatial discrete curves for uniform and non-uniform sampling, and compares them with two commonly used estimation algorithms. The comparative analysis is carried out in terms of sampling density, neighborhood radius and noise resistance. The experimental results show that the Gaussian distance weighted algorithm is effective and provides an efficient algorithm for underground pipeline safety detection.展开更多
This article is based on a recent model specifically defining magnetic field values around electrical wires. With this model, calculations of field around parallel wires were obtained. Now, this model is extended with...This article is based on a recent model specifically defining magnetic field values around electrical wires. With this model, calculations of field around parallel wires were obtained. Now, this model is extended with the new concept of magnetic equipotential surface to magnetic field curves around crossing wires. Cases of single, double, and triple wires are described. Subsequent article will be conducted for more general scenarios where wires are neither infinite nor parallel.展开更多
Supermassive DEOs (SMDEOs) are cosmologically evolved objects made of irreducible incompressible supranuclear dense superfluids: The state we consider to govern the matter inside the cores of massive neutron stars. Th...Supermassive DEOs (SMDEOs) are cosmologically evolved objects made of irreducible incompressible supranuclear dense superfluids: The state we consider to govern the matter inside the cores of massive neutron stars. These cores are practically trapped in false vacua, rendering their detection by outside observers impossible. Based on massive parallel computations and theoretical investigations, we show that SMDEOs at the centres of spiral galaxies that are surrounded by massive rotating torii of normal matter may serve as powerful sources for gravitational waves carrying away roughly 1042 erg/s. Due to the extensive cooling by GWs, the SMDEO-Torus systems undergo glitching, through which both rotational and gravitational energies are abruptly ejected into the ambient media, during which the topologies of the embedding spacetimes change from curved into flatter ones, thereby triggering a burst gravitational energy of order 1059 erg. Also, the effects of glitches found to alter the force balance of objects in the Lagrangian-L1 region between the central SMDEO-Torus system and the bulge, enforcing the enclosed objects to develop violent motions, that may explain the origin of the rotational curve irregularities observed in the innermost part of spiral galaxies. Our study shows that the generated GWs at the centres of galaxies, which traverse billions of objects during their outward propagations throughout the entire galaxy, lose energy due to repeatedly squeezing and stretching the objects. Here, we find that these interactions may serve as damping processes that give rise to the formation of collective forces f∝m(r)/r, that point outward, endowing the objects with the observed flat rotation curves. Our approach predicts a correlation between the baryonic mass and the rotation velocities in galaxies, which is in line with the Tully-Fisher relation. The here-presented self-consistent approach explains nicely the observed rotation curves without invoking dark matter or modifying Newtonian gravitation in the low-field approximation.展开更多
基金jointly supported by the National Natural Science Foundation of China(Grant No.52277213,52177210,and 52207229)key project of science and technology research program of Chongqing Education Commission of China (Grant No. KJZD-K202201103,KJZD-K202301108)Chongqing Graduate Research Innovation Project (Grant No.CYS240657).
文摘Accurately predicting battery degradation is crucial for battery system management.However,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation solely through maximum capacity loss assessment is challenging.While machine learning offers promising solutions,it often overlooks domain knowledge,resulting in reduced accu racy,increased computational burden and decreased interpretability.Here,this study proposes a method to predict the voltage-capacity(V-Q) curve during battery degradation with limited historical data.This process is achieved through two physically interpretable components:a lightweight interpretable physical model and a physics-informed neural network.These components incorporate domain knowledge into machine learning to improve V-Q curve prediction performance and enhance interpretability.Extensive validation was conducted on 52 batteries of different types under different testing conditions.The proposed method can accurately predict future V-Q.curves for hundreds of cycles using only one-present-cycle V-Q curve,with root mean square error and mean absolute error basically less than 0.035 Ah and R^(2) basically less than 98.5%.This means that incremental capacity curves can be extracted from the predicted results for a more comprehensive and accurate battery degradation analysis.Furthermore,the method can flexibly adjust prediction length and density to cater to the practical needs of long-cycle prediction and data generation.This study provides a viable method for rapid degradation prediction and is expected to be generalized to in-vehicle implementations.
基金The research project was co-funded by the National Natural Science Foundation of China(No.42072172,No.41772120)Shandong Province Natural Science Fund for Distinguished Young Scholars(No.JQ201311)the Graduate Scientific and Technological Innovation Project Financially Supported by Shandong University of Science and Technology(No.SDKDYC190313).
文摘The high-pressure mercury intrusion (HPMI) experiment is widely used to assess the pore architecture oftight sandstone reservoirs. However, the conventional analysis of the high- pressure mercury intrusionhas always focused on the mercury injection curves themselves, neglecting the important geologicalinformation conveyed by the mercury ejection curves. This paper quantitatively describes the fractalcharacteristics of ejection curves by using four fractal models, i.e.,. Menger model, Thermodynamicmodel, Sierpinski model, and multi- fractal model. In comparison with mercury injection curves, weexplore the fractal significance of mercury ejection curves and define the applicability of different fractalmodels in characterizing pore architectures. Investigated tight sandstone samples can be divided intofour types (Types A, B, C and D) based on porosity, permeability, and mercury removal efficiency. Type Dsamples are unique in that they have higher permeability (>0.6 mD) but lower mercury removal effi-ciency (<35%). Fractal studies of the mercury injection curve show that it mainly reflects the pore throatcharacteristics, while the mercury ejection curve serves to reveal the pore features, and porosity andpermeability correlate well with the fractal dimension of the injection curve, while mercury removalefficiency correlates only with the Ds' value of the ejection curve. The studies on the mercury ejectioncurves also reveal that the small pores and micropores of the Type C and Type D samples are moredeveloped, with varying pore architecture. The fractal dimension Ds' value of Type D samples is greaterthan that of Type C samples, and the dissolution of Type D samples is more intense than that of Type Csamples, which further indicates that the Type D samples are smaller in pore size, rougher in surface, andwith greater difficulty for the hydrocarbon to enter, resulting in their reservoir capacity probably lessthan that of Type C samples. In this regard, the important information characterized by the mercuryejection curve should be considered in evaluating the tight sandstone reservoirs. Finally, the Menger andThermodynamic models prove to be more suitable for describing the total pore architecture, while theSierpinski model is better for characterizing the variability of the interconnected pores.
基金sponsored by the National Natural Science Foundation of China(Grant No.52405443)the Technology Research and Development Plan of China Railway(Grant No.N2023G063)the Fund of China Academy of Railway Sciences Corporation Limited(Grant No.2023YJ054).
文摘Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.Design/methodology/approach–Taking a small-radius curve of a high-speed railway as the research object,field measurements were conducted to obtain track parameters and wheel–rail profiles.A coupled vehicle-track dynamics model was established.Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.Findings–Key service parameters affecting wheel–rail creepage were identified,including the matching relationship between curve geometry and vehicle speed and rail profile parameters.The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis,leading to the establishment of parameter optimization criteria.Originality/value–This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves.A response surface-based parameter-creepage relationship model was established,and a multi-parameter coordinated optimization strategy was proposed.The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves.
基金supported by the Scientific and Technological Research and Development Programs of China Railway Group Limited(Grant No.2022 Major Special Project-07)Gansu Provincial Technology Innovation Guidance Program-Special Funding for Capacity Building of Enterprise R&D Institutions(Grant No.23CXJA0011)Key R&D and transformation plan of Qinghai Province,China(Special Project for Transformation of Scientific and Technological Achievements No.2022-SF-158).
文摘In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.
基金supported by the National Natural Science Foundation of China (52075420)the National Key Research and Development Program of China (2020YFB1708400)。
文摘With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.
文摘The present study aims to obtain p-y curves(Winkler spring properties for lateral pile-soil interaction)for liquefied soil from 12 comprehensive centrifuge test cases where pile groups were embedded in liquefiable soil.The p-y curve for fully liquefied soil is back-calculated from the dynamic centrifuge test data using a numerical procedure from the recorded soil response and strain records from the instrumented pile.The p-y curves were obtained for two ground conditions:(a)lateral spreading of liquefied soil,and(b)liquefied soil in level ground.These ground conditions are simulated in the model by having collapsing and non-collapsing intermittent boundaries,which are modelled as quay walls.The p-y curves back-calculated from the centrifuge tests are compared with representative reduced API p-y curves for liquefied soils(known as p-multiplier).The response of p-y curves at full liquefaction is presented and critical observations of lateral pile-soil interaction are discussed.Based on the results of these model tests,guidance for the construction of p-y curves for use in engineering practice is also provided.
基金supported by the National Natural Science Foundation of China (No. 41971377 & No. 41901346)the Fundamental Research Funds for the Central Universities, Peking University。
文摘Global inland surface water bodies such as lakes and reservoirs,important components of the hydrosphere and ecosphere,are increasingly affected by climate change.Generating bathymetric volume-areaheight (BVAH) curves for global inland surface water bodies can enhance our understanding of their topography and climate impacts.However,accurately quantifying the topographic patterns of these water bodies remains challenging due to the difficulties in collecting comprehensive bathymetric data.Therefore,we collected and processed over 2000 bathymetric maps of global water bodies from over 50 different data sources and then developed the BVAH model.Finally,the BVAH hydrological curves of 16671 global inland surface water bodies (larger than 10 km~2) were generated.The results include but are not limited to (1) For most targeted water bodies,area (A) and volume (V) exhibit significant power function relationships with surface heights (H),with optimal power values quantified as 1.42 for A and 2.42 for V.(2) The BVAH model outperforms GLOBathy in estimating area and volume changes,achieving higher correlation coefficients (CC) of approximately 0.962 for the area and 0.991 for volume,and demonstrating lower percentages of root mean squared errors (PRMSE) around 10.9% for the area and 4.8% for volume.(3) In the case study of the Xizang Plateau and various large global reservoirs,the BVAH curve database can capture dynamic volume changes.As a unified simulation of the bathymetric topographical patterns,our bathymetric dataset and corresponding BVAH curve database have great potential to contribute to effective water resource management and ecological conservation efforts worldwide.
文摘AASHTO’s guideline for geometric design of highways and similar guidelines require that roadside areas on the inside of horizontal curves be cleared of high objects to provide stopping sight distance. The guidelines have analytical models for determining the extent of clearance, known as the horizontal sightline offset or clearance offset, for simple curves. Researchers in the past have developed analytical models for clearance offsets for spiraled and reverse curves. Very few researchers developed analytical models for available sight distances for compound curves. Still missing are models for horizontal sightline offsets and locations of the offsets for compound curves. The objective of this paper is to present development of analytical models and charts for determining horizontal sightline offsets and their locations for compound curves. The paper considers curves whose component arcs are individually shorter than stopping sight distance. The resulting models and the charts have been verified with accurate values determined using graphical methods. The models and the charts will find application in geometric design of highway compound curves.
基金Supported by:National Natural Science Foundation of China under Grant No.51778207the Project of Graduate Students′Innovative Ability Training of Hebei Province under Grant No.CXZZBS2019041the Natural Science Foundation of Hebei Province under Grant No.E2018202107。
文摘In this study,centrifuge model tests of vertical and batter pile groups in liquefied sand were conducted on a centrifuge shaking table.The dynamic p-y curves for these pile groups before and during sand liquefaction were obtained from calculations based on test data.The results confirm that liquefaction contributes to a reduction in the energy consumption of pile foundations,with the degradation effect being more pronounced for batter pile groups.At shallow depths,the difference in the backbone gradients of the p-y curves after liquefaction for vertical and batter pile groups indicates that the lateral stiffness of a batter pile group is greater than that of a vertical pile group.As shaking intensity increases,the lateral stiffness of a vertical pile group increases with depth during the late stage of sand liquefaction.However,the lateral stiffness of a batter pile group during liquefaction does not vary with depth.The results of this study provide a reference for the seismic design of vertical and batter pile groups in liquefied soil.
文摘Background: The signal-to-noise ratio (SNR) is recognized as an index of measurements reproducibility. We derive the maximum likelihood estimators of SNR and discuss confidence interval construction on the difference between two correlated SNRs when the readings are from bivariate normal and bivariate lognormal distribution. We use the Pearsons system of curves to approximate the difference between the two estimates and use the bootstrap methods to validate the approximate distributions of the statistic of interest. Methods: The paper uses the delta method to find the first four central moments, and hence the skewness and kurtosis which are important in the determination of the parameters of the Pearsons distribution. Results: The approach is illustrated in two examples;one from veterinary microbiology and food safety data and the other on data from clinical medicine. We derived the four central moments of the target statistics, together with the bootstrap method to evaluate the parameters of Pearsons distribution. The fitted Pearsons curves of Types I and II were recommended based on the available data. The R-codes are also provided to be readily used by the readers.
基金supported by Teaching Reform Project of Shenzhen University of Technology under Grant No.20231016.
文摘Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation sector.However,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy violations.To address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed recently.However,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many attacks.As such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)operations.The formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably secure.The proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and unlinkability.Moreover,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and impersonations.From the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security features.Therefore,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.
文摘The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of security while optimizing the efficiency of computer resources. This study focuses on how elliptic curves cryptography helps to protect sensitive data. Text is encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. The elliptic curves cryptography of this study is better than using a 256-bit RSA key. To achieve equivalent protection by using the elliptic curves cryptography, several Python libraries such as cryptography, pycryptodome, pyQt5, secp256k1, etc. were used. These technologies are used to develop a software based on elliptic curves. If built, the software helps to encrypt and decrypt data such as a text messages and it offers the authentication for the communication.
基金supported by ZTE Industry-University-Institute Cooperation Funds。
文摘In recent years,various internet architectures,such as Integrated Services(IntServ),Differentiated Services(DiffServ),Time Sensitive Networking(TSN)and Deterministic Networking(DetNet),have been proposed to meet the quality-of-service(QoS)requirements of different network services.Concurrently,network calculus has found widespread application in network modeling and QoS analysis.Network calculus abstracts the details of how nodes or networks process data packets using the concept of service curves.This paper summarizes the service curves for typical scheduling algorithms,including Strict Priority(SP),Round Robin(RR),Cycling Queuing and Forwarding(CQF),Time Aware Shaper(TAS),Credit Based Shaper(CBS),and Asynchronous Traffic Shaper(ATS).It introduces the theory of network calculus and then provides an overview of various scheduling algorithms and their associated service curves.The delay bound analysis for different scheduling algorithms in specific scenarios is also conducted for more insights.
文摘The dynamic viscoelastic properties of asphalt AC-20 and its composites with Organic-Montmorillonite clay (OMMt) and SBS were modeled using the empirical Havriliak-Negami (HN) model, based on linear viscoelastic theory (LVE). The HN parameters, α, β, G0, G∞and τHN were determined by solving the HN equation across various temperatures and frequencies. The HN model successfully predicted the rheological behavior of the asphalt and its blends within the temperature range of 25˚C - 40˚C. However, deviations occurred between 40˚C - 75˚C, where the glass transition temperature Tg of the asphalt components and the SBS polymer are located, rendering the HN model ineffective for predicting the dynamic viscoelastic properties of composites containing OMMt under these conditions. Yet, the prediction error of the HN model dropped to 2.28% - 2.81% for asphalt and its mixtures at 100˚C, a temperature exceeding the Tg values of both polymer and asphalt, where the mixtures exhibited a liquid-like behavior. The exponent α and the relaxation time increased with temperature across all systems. Incorporating OMMt clay into the asphalt blends significantly enhanced the relaxation dynamics of the resulting composites.
文摘Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the geometric characteristics of any point on the discrete curve, a distance-based Gaussian weighted algorithm is proposed to estimate the geometric characteristics of three-dimensional space discrete curves. According to the definition of discrete derivatives, the algorithm fully considers the relative position difference between a specific point and its neighboring points, introduces the distance weighting idea, and integrates the smoothing strategy. The experiment uses two spatial discrete curves for uniform and non-uniform sampling, and compares them with two commonly used estimation algorithms. The comparative analysis is carried out in terms of sampling density, neighborhood radius and noise resistance. The experimental results show that the Gaussian distance weighted algorithm is effective and provides an efficient algorithm for underground pipeline safety detection.
文摘This article is based on a recent model specifically defining magnetic field values around electrical wires. With this model, calculations of field around parallel wires were obtained. Now, this model is extended with the new concept of magnetic equipotential surface to magnetic field curves around crossing wires. Cases of single, double, and triple wires are described. Subsequent article will be conducted for more general scenarios where wires are neither infinite nor parallel.
文摘Supermassive DEOs (SMDEOs) are cosmologically evolved objects made of irreducible incompressible supranuclear dense superfluids: The state we consider to govern the matter inside the cores of massive neutron stars. These cores are practically trapped in false vacua, rendering their detection by outside observers impossible. Based on massive parallel computations and theoretical investigations, we show that SMDEOs at the centres of spiral galaxies that are surrounded by massive rotating torii of normal matter may serve as powerful sources for gravitational waves carrying away roughly 1042 erg/s. Due to the extensive cooling by GWs, the SMDEO-Torus systems undergo glitching, through which both rotational and gravitational energies are abruptly ejected into the ambient media, during which the topologies of the embedding spacetimes change from curved into flatter ones, thereby triggering a burst gravitational energy of order 1059 erg. Also, the effects of glitches found to alter the force balance of objects in the Lagrangian-L1 region between the central SMDEO-Torus system and the bulge, enforcing the enclosed objects to develop violent motions, that may explain the origin of the rotational curve irregularities observed in the innermost part of spiral galaxies. Our study shows that the generated GWs at the centres of galaxies, which traverse billions of objects during their outward propagations throughout the entire galaxy, lose energy due to repeatedly squeezing and stretching the objects. Here, we find that these interactions may serve as damping processes that give rise to the formation of collective forces f∝m(r)/r, that point outward, endowing the objects with the observed flat rotation curves. Our approach predicts a correlation between the baryonic mass and the rotation velocities in galaxies, which is in line with the Tully-Fisher relation. The here-presented self-consistent approach explains nicely the observed rotation curves without invoking dark matter or modifying Newtonian gravitation in the low-field approximation.
