This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theo...This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theorem,fixed point index theory and the analytic technique,we give the bifurcation point of the parameter which divides the range of parameter for the existence of at least two,one and no positive solutions for the problem.And,by using a fixed point theorem of generalized concave operator and cone theory,we establish the maximum parameter interval for the existence of the unique positive solution for the problem and show that such a positive solution continuously depends on the parameter.In the end,some examples are given to illustrate our main results.展开更多
The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogo...The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogonality error of grating grooves not only improves the positioning accuracy of grating interferometers but also provides essential feedback for optimizing two-dimensional grating fabrication.This study proposes a method for simultaneous calibration of these parameters using orthogonal heterodyne laser interferometry.A two-dimensional grating interferometer is built with the grating to be measured,and a biaxial laser interferometer provides a displacement reference for it.The phase mapping relationship between grating interference and laser interference is established.The interference phase information obtained by any two displacements can simultaneously solve the above three parameters and obtain the grating installation error.The feasibility of the proposed method is verified by using a 1200 gr/mm two-dimensional grating.The standard deviation of the grating groove density in the X and Y directions is 0.012 gr/mm and 0.014 gr/mm,respectively.The standard deviation of the orthogonality error of grating grooves is 0.004°,and the standard deviation of the installation error is 0.002°.Compared with the atomic force microscope method,the consistency of the grating groove density in the X and Y directions is better than 0.03 gr/mm and 0.06 gr/mm,and the orthogonality error of grating grooves is better than 0.008°.The experimental results show that the proposed method can be simply and efficiently applied to the calibration of the grating line parameters of the two-dimensional grating.展开更多
We investigate the null tests of cosmic accelerated expansion by using the baryon acoustic oscillation(BAO)data measured by the dark energy spectroscopic instrument(DESI)and reconstruct the dimensionless Hubble parame...We investigate the null tests of cosmic accelerated expansion by using the baryon acoustic oscillation(BAO)data measured by the dark energy spectroscopic instrument(DESI)and reconstruct the dimensionless Hubble parameter E(z)from the DESI BAO Alcock-Paczynski(AP)data using Gaussian process to perform the null test.We find strong evidence of accelerated expansion from the DESI BAO AP data.By reconstructing the deceleration parameter q(z) from the DESI BAO AP data,we find that accelerated expansion persisted until z■0.7 with a 99.7%confidence level.Additionally,to provide insights into the Hubble tension problem,we propose combining the reconstructed E(z) with D_(H)/r_(d) data to derive a model-independent result r_(d)h=99.8±3.1 Mpc.This result is consistent with measurements from cosmic microwave background(CMB)anisotropies using the ΛCDM model.We also propose a model-independent method for reconstructing the comoving angular diameter distance D_(M)(z) from the distance modulus μ,using SNe Ia data and combining this result with DESI BAO data of D_(M)/r_(d) to constrain the value of r_(d).We find that the value of r_(d),derived from this model-independent method,is smaller than that obtained from CMB measurements,with a significant discrepancy of at least 4.17σ.All the conclusions drawn in this paper are independent of cosmological models and gravitational theories.展开更多
Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft ...Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft flight at conventional rotational speeds in the Martian atmosphere.In this paper,we employ the Particle Swarm Optimization(PSO)algorithm to search for the control points of the Bezier curve,completing the parameterization of the airfoil upper and lower curves based on these control points.In order to directly enhance the lift-to-drag ratio of the airfoil at high angles of attack,the NSGA-II algorithm is utilized to optimize the lift-to-drag ratio of NACA 6904 at a=17.5°,Ma=0.43,Re=7600,and CLF 5605 at a=15°,Ma=0.7,Re=7481,respectively.The two-dimensional RANS(Reynolds Average NavierStokes)and k-ωSST turbulence models are employed in the optimization process by CFD to predict the lift and drag characteristics of the airfoil in a Martian environment.Under simulated Mars atmospheric conditions(pressure of 1380 Pa,test temperature of 24°C,equivalent Mars atmospheric density at the surface of 0.0162 g/cm~3),the airfoil after optimized is subjected to rotor lift-drag characteristic tests where a single-rotor lift-drag characteristic test bench is employed for verification.The experimental results demonstrate that the RB-TB-II blade,which is obtained by optimizing the airfoil based on the RB-SWQ-I blade,exhibits a 19.6%increase in Power Loading(PL)and a 20.4%increase in Figure of Merit(FM)compared with the RB-SWQ-I blade.Based on the results of airfoil optimization,increasing the camber at the leading edge of the airfoil under high angles of attack contributes to an improved lift-to-drag ratio.展开更多
In this study,the dynamic characteristics and microstructures of lacustrine soft clays were studied.Dynamic character tests were conducted on undisturbed,remolded,and saturated lacustrine soft clays,using a dynamic tr...In this study,the dynamic characteristics and microstructures of lacustrine soft clays were studied.Dynamic character tests were conducted on undisturbed,remolded,and saturated lacustrine soft clays,using a dynamic triaxial tester.A scanning electron microscope(SEM)was employed to assess the soil samples after dynamic testing.The results indicate that the dynamic characteristics of lacustrine soft clay were significantly affected by confining pressure and water content.A quantitative relationship was established among confining pressures,water content,and the dynamic shear modulus ratio.The dynamic characteristic parameters of undisturbed,remolded and saturated soil are obviously different,and the original structure can enhance the shear strength of soil.By comparing the results with those from other studies,we found that the dynamic characters of soft clays were considerably varied in different regions,and lacustrine soft clays had a larger dynamic shear modulus ratio and a smaller damping ratio when the dynamic shear strain was large.Using IPP software to process the microstructural images,we found that the soil was dominated by small pores and medium particles,and the roundness of pores and particles had an apparently positive correlation with the maximum diameter.Moreover,the pores and particles of the soil showed fractal characteristics and directionality,and the fractal dimensions and probability entropy were strongly correlated with the macrostructural parameters.Finally,we developed a prediction model for macrostructural and microstructural parameters.展开更多
This paper examines whether the parametric regression model is correctly specified for both source and target data and whether the regression pattern in the source domain aligns with that of the target domain.This eva...This paper examines whether the parametric regression model is correctly specified for both source and target data and whether the regression pattern in the source domain aligns with that of the target domain.This evaluation is a critical prerequisite for applying model-based transfer learning methods under covariate shift assumptions.Traditional regression model checks and twosample regression tests are insufficient to address this issue.To overcome these limitations,the authors propose a novel adaptive-to-regression test statistic that is asymptotically distribution-free.Under the null hypothesis,the test follows a chi-square weak limit,preserving the significance level and enabling critical value determination without resampling techniques.Additionally,the authors systematically analyze the test's power performance,highlighting its sensitivity to different sub-local alternatives that deviate from the null hypothesis.Numerical studies,including simulations,assess finite-sample performance,and a real-world data example is provided for illustration.展开更多
Thermal spalling in heterogeneous rocks under rapid heating poses critical risks to deep mining and geothermal operations.In this study,we develop a coupled thermal-mechanical-damage(TM D)model that explicitly incorpo...Thermal spalling in heterogeneous rocks under rapid heating poses critical risks to deep mining and geothermal operations.In this study,we develop a coupled thermal-mechanical-damage(TM D)model that explicitly incorporates Weibull distributed heterogeneity to a single fracture in rock,and validate it against ceramic quenching and granite acoustic emission experiments.Distance based generalized sensitivity analysis(DGSA)is applied to quantify the influence and interactions of key parameters,revealing the dominant controls on spalling onset,severity,and damage morphology.The results demonstrate that thermal stress dominates crack initiation and propagation,that lateral constraints can significantly delay and suppress spalling,and that material heterogeneity markedly influences peak stress and damage modes within a certain range of thermal expansion coefficient and has multiple effects on thermal spalling.This study provides a theoretical basis for quantitative assessment and parameter optimization of thermal spalling processes in rock masses.展开更多
With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stabil...With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stability,and failure resilience.Electrochemical models(EMs),serving as pivotal mechanismdriven analytical frameworks in battery research and applications,demonstrate unprecedented quantitative fidelity in characterizing intricate multi-physics dynamics for the next-generation battery management systems(BMS).The breakthrough innovations in artificial intelligence(AI)driven methods have revolutionized the dynamic modeling of LIBs.However,the deployment of AI-augmented EMs in BMS faces significant identifiability challenges due to strong parameter coupling.In addition,research on model simplification,parameter determination,and dynamic parameter identification remains largely fragmented.There is a lack of a comprehensive review to pave the way for the cross-domain innovations in BMS.To fill this gap,this paper presents a systematic review of the EMs for LIBs and examines the advancements in parameter determination techniques from both experimental measurement and numerical simulation perspectives.Besides,a comprehensive assessment of the progress in parameter identification from the standpoint of dynamic recognition is presented,encompassing both modelbased approaches and intelligent methods.Additionally,from the BMS standpoint,the strengths and limitations of existing approaches are evaluated.Finally,a coordinated framework for multi-stage identification needs to be established in the future.The potential of digital twins(DT),deep reinforcement learning(DRL),and large language models(LLMs)in enhancing EMs also warrants further exploration.The purpose of this work is to provide insights and guidance for the future development of EMs in LIB applications.展开更多
In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typica...In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.展开更多
Accurately predicting fatigue life under multiaxial fatigue damage conditions is essential for ensuring the safety of critical components in service.However,due to the complexity of fatigue failure mechanisms,achievin...Accurately predicting fatigue life under multiaxial fatigue damage conditions is essential for ensuring the safety of critical components in service.However,due to the complexity of fatigue failure mechanisms,achieving accurate multiaxial fatigue life predictions remains challenging.Traditional multiaxial fatigue prediction models are often limited by specific material properties and loading conditions,making it difficult to maintain reliable life prediction results beyond these constraints.This paper presents a study on the impact of seven key feature quantities on multiaxial fatigue life,using Convolutional Neural Networks(CNN),Long Short-Term Memory Networks(LSTM),and Fully Connected Neural Networks(FCNN)within a deep learning framework.Fatigue test results from eight metal specimens were analyzed to identify these feature quantities,which were then extracted as critical time-series features.Using a CNN-LSTM network,these features were combined to form a feature matrix,which was subsequently input into an FCNN to predict metal fatigue life.A comparison of the fatigue life prediction results from the STFAN model with those from traditional prediction models—namely,the equivalent strain method,the maximum shear strain method,and the critical plane method—shows that the majority of predictions for the five metal materials and various loading conditions based on the STFAN model fall within an error band of 1.5 times.Additionally,all data points are within an error band of 2 times.These findings indicate that the STFAN model provides superior prediction accuracy compared to the traditional models,highlighting its broad applicability and high precision.展开更多
This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the pred...This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.展开更多
The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution l...The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution laws and fracture network characteristics of shale gas infill wells.A mechanism model of CN platform logging data and geomechanical parameters is established to simulate the influence of parent well’s production on the geostress in the infill well area.It is suggested that with the increase of production time,normal fault stress state and horizontal stress deflection will occur.The smaller the parent well spacing and the longer the production time,the earlier the normal fault stress state appears and the larger the range.Based on the model,the fracture network morphology and construction parameters of infill wells are optimized.parentparentparentparent The results indicate that:1:A well spacing of 500 m achieves a Pareto optimum between“full reserve coverage”and“stress barrier”;2:A parent well recovery degree of 30%corresponds to the critical point of stress reversal,where the lateral deflection rate of the infill fracture is less than 8%and the SRV loss is minimized;3:6-cluster intensive completion with twice the liquid intensity increases the fracture complexity index by 1.7 times,enhances well group EUR by 15.4%,and reduces single-well cost by 22%.This research fills the theoretical gap in the collaborative optimization of“multi-parameter,multi-objective and multi-constraint”and provide parameter optimization basis for shale gas infill well development in China and help to improve the development efficiency and economic benefits.展开更多
We theoretically investigate the phase sensitivity of a truncated SU(1,1)interferometer fed with a two-mode coherent state and employing double-port homodyne detection.On the one hand,we analytically demonstrate that ...We theoretically investigate the phase sensitivity of a truncated SU(1,1)interferometer fed with a two-mode coherent state and employing double-port homodyne detection.On the one hand,we analytically demonstrate that the two-mode coherent state provides better phase sensitivity than the single-mode coherent state.In addition,we show that the doubleport homodyne detection is a quasi-optimal measurement.For a bright coherent-state input,the sensitivity of this scheme saturates the phase-sensitivity bound determined by the quantum Fisher information.On the other hand,we quantitatively illustrate the advantage of double-port homodyne detection over the single-port scheme under ideal conditions and in the presence of photon loss,respectively.Furthermore,our analysis indicates that the scheme we propose is robust against photon loss.展开更多
Since the view that the localized rail third-order bending mode can cause high-order polygonization(mainly 18-23)of high-speed train wheels was put forward in 2017,many scholars have attempted to link a connection bet...Since the view that the localized rail third-order bending mode can cause high-order polygonization(mainly 18-23)of high-speed train wheels was put forward in 2017,many scholars have attempted to link a connection between the localized rail bending modes and wheel polygonization phenomenon and polygonal wheel passing frequency.This paper first establishes a flexible track model considering the structural and parametric characteristics of fasteners,verifies the model by using vehicle tracking test data,then investigates the influence of fastener parameter matching on the localized rail bending modes,and obtains the following conclusions:(1)There is nearly a 1:1 mapping relationship between the localized rail bending modal frequency and polygonal wheel passing(PWP)frequency,which supports that the localized rail bending mode is one of the causes of wheel polygonization.(2)The iron plate of the fastener system plays a role of dynamic vibration absorber in the vehicle-rail coupled system,and the fastener parameters significantly influence the localized rail bending modal vibration.Finally,this paper proposes a design principle of a high-frequency vibration-absorbing fastener,which provides a feasible solution to mitigate the localized rail bending modal vibration and high-order wheel polygonization.Meanwhile,it points out that this measure may induce other high-frequency vibration problems,e.g.,aggravating modal vibration above 800 Hz.Further,this paper proposes a concept of differentiated arrangement of fasteners,suggesting that different high-frequency vibration-absorbing fasteners be installed in different sections of the whole line to make the localized rail bending modal frequency of the whole line disordered,thus disrupting and further mitigating the development of the wheel polygonization.展开更多
Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drill...Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drilling extension limits,underground target distribution and trajectory collision risks,a model of platform location-wellbore trajectory collaborative optimization for a complex-structure well factory is developed.A hybrid heuristic algorithm is proposed by combining an improved sparrow search algorithm(ISSA)for optimizing platform parameters in the outer layer and a directed artificial bee colony algorithm(DABC)for optimizing trajectory parameters in the inner layer.The alternating iteration of ISSA-DABC facilitates the resolution of the collaborative optimization problem.The ISSA-DABC provides an effective solution to the platform-trajectory collaborative optimization problem for complex-structure well factories and overcomes the tendency of the traditional platform-trajectory stepwise optimization workflow to become trapped in local optima and yield inconsistent designs.The ISSA-DABC has a strong global search capability,fast convergence and good robustness,and can simultaneously satisfy multiple engineering constraints on drilling footage,trajectory complexity and collision risk,and enables automated,workflow-wide generation of constraint-compliant,near-globally optimal platform-trajectory configurations.Field applications further demonstrate that ISSA-DABC significantly reduces the objective function value and collision risk,yielding more rational platform layouts and well factory design parameters.展开更多
In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory mode...In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.展开更多
In this paper,we investigate data-driven bright soliton solutions of the nonlocal reverse-time nonlinear Schrodinger(NLS)equation and the parameter identification using the physically informed neural networks(PINNs)al...In this paper,we investigate data-driven bright soliton solutions of the nonlocal reverse-time nonlinear Schrodinger(NLS)equation and the parameter identification using the physically informed neural networks(PINNs)algorithm.Accurate simulations and comparative analyses of relative and absolute errors are performed for two-soliton and four-soliton solutions including linear solitary waves and periodic waves.In the training process,the standard PINNs scheme is employed for linear solitary wave solutions,while the prior information is added at local sharp regions for periodic wave solutions due to the complicated collision behaviors.For the parameter identification,we accurately recognize the nonlinear coefficients of the nonlocal NLS equation from known solutions with different noises.These results reinforce the application of deep learning with the PINNs framework to successfully study nonlocal integrable systems.展开更多
The Tibetan Plateau(TP),characterized by its elevated topography,plays a crucial role in regional environmental and climate dynamics,where the understanding of radiation energy budgets is essential.However,accurately ...The Tibetan Plateau(TP),characterized by its elevated topography,plays a crucial role in regional environmental and climate dynamics,where the understanding of radiation energy budgets is essential.However,accurately estimating the spatiotemporal variations of radiation budget components and surface albedo across the diverse landscapes of the TP remains a significant challenge for the scientific community.To address this issue,numerous atmospheric experiments and research initiatives have been conducted since the 1960s,focusing on quantitatively assessing the spatial distribution and temporal variations of radiation fluxes through both observational data and remote sensing techniques.This paper systematically reviews the key advancements in radiation energy studies over the past 35 years,with a particular focus on measurements derived from tens of radiation flux stations and satellite observations across the TP.Additionally,the development of parameterization schemes in topographical effects on radiation fluxes is also summarized.Finally,the paper discusses potential future research directions in this field.展开更多
The detection of gravitational waves by the LIGO-Virgo-KAGRA collaboration has ushered in a new era of observational astronomy,emphasizing the need for rapid and detailed parameter estimation and population-level anal...The detection of gravitational waves by the LIGO-Virgo-KAGRA collaboration has ushered in a new era of observational astronomy,emphasizing the need for rapid and detailed parameter estimation and population-level analyses.Traditional Bayesian inference methods,particularly Markov chain Monte Carlo,face significant computational challenges when dealing with the high-dimensional parameter spaces and complex noise characteristics inherent in gravitational wave data.This review examines the emerging role of simulation-based inference methods in gravitational wave astronomy,with a focus on approaches that leverage machine-learning techniques such as normalizing flows and neural posterior estimation.We provide a comprehensive overview of the theoretical foundations underlying various simulation-based inference methods,including neural posterior estimation,neural ratio estimation,neural likelihood estimation,flow matching,and consistency models.We explore the applications of these methods across diverse gravitational wave data processing scenarios,from single-source parameter estimation and overlapping signal analysis to testing general relativity and conducting population studies.Although these techniques demonstrate speed improvements over traditional methods in controlled studies,their model-dependent nature and sensitivity to prior assumptions are barriers to their widespread adoption.Their accuracy,which is similar to that of conventional methods,requires further validation across broader parameter spaces and noise conditions.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
基金Supported by the National Natural Science Foundation of China(11361047)Fundamental Research Program of Shanxi Province(20210302124529)。
文摘This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theorem,fixed point index theory and the analytic technique,we give the bifurcation point of the parameter which divides the range of parameter for the existence of at least two,one and no positive solutions for the problem.And,by using a fixed point theorem of generalized concave operator and cone theory,we establish the maximum parameter interval for the existence of the unique positive solution for the problem and show that such a positive solution continuously depends on the parameter.In the end,some examples are given to illustrate our main results.
文摘The two-dimensional grating serves as a critical component in plane grating interferometers for achieving high-precision multidimensional displacement measurements.The calibration of grating groove density and orthogonality error of grating grooves not only improves the positioning accuracy of grating interferometers but also provides essential feedback for optimizing two-dimensional grating fabrication.This study proposes a method for simultaneous calibration of these parameters using orthogonal heterodyne laser interferometry.A two-dimensional grating interferometer is built with the grating to be measured,and a biaxial laser interferometer provides a displacement reference for it.The phase mapping relationship between grating interference and laser interference is established.The interference phase information obtained by any two displacements can simultaneously solve the above three parameters and obtain the grating installation error.The feasibility of the proposed method is verified by using a 1200 gr/mm two-dimensional grating.The standard deviation of the grating groove density in the X and Y directions is 0.012 gr/mm and 0.014 gr/mm,respectively.The standard deviation of the orthogonality error of grating grooves is 0.004°,and the standard deviation of the installation error is 0.002°.Compared with the atomic force microscope method,the consistency of the grating groove density in the X and Y directions is better than 0.03 gr/mm and 0.06 gr/mm,and the orthogonality error of grating grooves is better than 0.008°.The experimental results show that the proposed method can be simply and efficiently applied to the calibration of the grating line parameters of the two-dimensional grating.
基金supported in part by the National Key Research and Development Program of China (Grant No.2020YFC2201504)the National Natural Science Foundation of China (Grant Nos.12588101 and 12535002)。
文摘We investigate the null tests of cosmic accelerated expansion by using the baryon acoustic oscillation(BAO)data measured by the dark energy spectroscopic instrument(DESI)and reconstruct the dimensionless Hubble parameter E(z)from the DESI BAO Alcock-Paczynski(AP)data using Gaussian process to perform the null test.We find strong evidence of accelerated expansion from the DESI BAO AP data.By reconstructing the deceleration parameter q(z) from the DESI BAO AP data,we find that accelerated expansion persisted until z■0.7 with a 99.7%confidence level.Additionally,to provide insights into the Hubble tension problem,we propose combining the reconstructed E(z) with D_(H)/r_(d) data to derive a model-independent result r_(d)h=99.8±3.1 Mpc.This result is consistent with measurements from cosmic microwave background(CMB)anisotropies using the ΛCDM model.We also propose a model-independent method for reconstructing the comoving angular diameter distance D_(M)(z) from the distance modulus μ,using SNe Ia data and combining this result with DESI BAO data of D_(M)/r_(d) to constrain the value of r_(d).We find that the value of r_(d),derived from this model-independent method,is smaller than that obtained from CMB measurements,with a significant discrepancy of at least 4.17σ.All the conclusions drawn in this paper are independent of cosmological models and gravitational theories.
基金supported by the National Key R&D Program of China(No.2024YFC3015804)the Basic Science Center Program for“Space Robot Intelligent Manipulation”,China(No.T2388101)。
文摘Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft flight at conventional rotational speeds in the Martian atmosphere.In this paper,we employ the Particle Swarm Optimization(PSO)algorithm to search for the control points of the Bezier curve,completing the parameterization of the airfoil upper and lower curves based on these control points.In order to directly enhance the lift-to-drag ratio of the airfoil at high angles of attack,the NSGA-II algorithm is utilized to optimize the lift-to-drag ratio of NACA 6904 at a=17.5°,Ma=0.43,Re=7600,and CLF 5605 at a=15°,Ma=0.7,Re=7481,respectively.The two-dimensional RANS(Reynolds Average NavierStokes)and k-ωSST turbulence models are employed in the optimization process by CFD to predict the lift and drag characteristics of the airfoil in a Martian environment.Under simulated Mars atmospheric conditions(pressure of 1380 Pa,test temperature of 24°C,equivalent Mars atmospheric density at the surface of 0.0162 g/cm~3),the airfoil after optimized is subjected to rotor lift-drag characteristic tests where a single-rotor lift-drag characteristic test bench is employed for verification.The experimental results demonstrate that the RB-TB-II blade,which is obtained by optimizing the airfoil based on the RB-SWQ-I blade,exhibits a 19.6%increase in Power Loading(PL)and a 20.4%increase in Figure of Merit(FM)compared with the RB-SWQ-I blade.Based on the results of airfoil optimization,increasing the camber at the leading edge of the airfoil under high angles of attack contributes to an improved lift-to-drag ratio.
基金National Natural Science Foundation of China under Grant No.52278340Natural Science Foundation of Hebei Province under Grant No.E2023202028。
文摘In this study,the dynamic characteristics and microstructures of lacustrine soft clays were studied.Dynamic character tests were conducted on undisturbed,remolded,and saturated lacustrine soft clays,using a dynamic triaxial tester.A scanning electron microscope(SEM)was employed to assess the soil samples after dynamic testing.The results indicate that the dynamic characteristics of lacustrine soft clay were significantly affected by confining pressure and water content.A quantitative relationship was established among confining pressures,water content,and the dynamic shear modulus ratio.The dynamic characteristic parameters of undisturbed,remolded and saturated soil are obviously different,and the original structure can enhance the shear strength of soil.By comparing the results with those from other studies,we found that the dynamic characters of soft clays were considerably varied in different regions,and lacustrine soft clays had a larger dynamic shear modulus ratio and a smaller damping ratio when the dynamic shear strain was large.Using IPP software to process the microstructural images,we found that the soil was dominated by small pores and medium particles,and the roundness of pores and particles had an apparently positive correlation with the maximum diameter.Moreover,the pores and particles of the soil showed fractal characteristics and directionality,and the fractal dimensions and probability entropy were strongly correlated with the macrostructural parameters.Finally,we developed a prediction model for macrostructural and microstructural parameters.
基金supported by the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science(East China Normal University),Ministry of Educationsupported by the National Natural Scientific Foundation of China under Grant No.NSFC12131006the Scientific and Technological Innovation Project of China Academy of Chinese Medical Science under Grant No.CI2023C063YLL。
文摘This paper examines whether the parametric regression model is correctly specified for both source and target data and whether the regression pattern in the source domain aligns with that of the target domain.This evaluation is a critical prerequisite for applying model-based transfer learning methods under covariate shift assumptions.Traditional regression model checks and twosample regression tests are insufficient to address this issue.To overcome these limitations,the authors propose a novel adaptive-to-regression test statistic that is asymptotically distribution-free.Under the null hypothesis,the test follows a chi-square weak limit,preserving the significance level and enabling critical value determination without resampling techniques.Additionally,the authors systematically analyze the test's power performance,highlighting its sensitivity to different sub-local alternatives that deviate from the null hypothesis.Numerical studies,including simulations,assess finite-sample performance,and a real-world data example is provided for illustration.
基金funded by the National Natural Science Foundation of China(Nos.52574100,52574001,and 52311530070)the Major National Science and Technology Project for Deep Earth of China(No.2024ZD1003805)+1 种基金the Fundamental Research Funds for the Central Universities of China(No.FRF-IDRY-20-003,Interdisciplinary Research Project for Young Teachers of USTB)DE gratefully acknowledges support from the G.Albert Shoemaker endowment.
文摘Thermal spalling in heterogeneous rocks under rapid heating poses critical risks to deep mining and geothermal operations.In this study,we develop a coupled thermal-mechanical-damage(TM D)model that explicitly incorporates Weibull distributed heterogeneity to a single fracture in rock,and validate it against ceramic quenching and granite acoustic emission experiments.Distance based generalized sensitivity analysis(DGSA)is applied to quantify the influence and interactions of key parameters,revealing the dominant controls on spalling onset,severity,and damage morphology.The results demonstrate that thermal stress dominates crack initiation and propagation,that lateral constraints can significantly delay and suppress spalling,and that material heterogeneity markedly influences peak stress and damage modes within a certain range of thermal expansion coefficient and has multiple effects on thermal spalling.This study provides a theoretical basis for quantitative assessment and parameter optimization of thermal spalling processes in rock masses.
基金supported by the National Natural Science Foundation of China(52477222)the Key Research and Development Program of Shaanxi Province(2024GX-YBXM-442)the Xinjiang Uygur Autonomous Region Key R&D Program under Grant(2022B01019-2)。
文摘With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stability,and failure resilience.Electrochemical models(EMs),serving as pivotal mechanismdriven analytical frameworks in battery research and applications,demonstrate unprecedented quantitative fidelity in characterizing intricate multi-physics dynamics for the next-generation battery management systems(BMS).The breakthrough innovations in artificial intelligence(AI)driven methods have revolutionized the dynamic modeling of LIBs.However,the deployment of AI-augmented EMs in BMS faces significant identifiability challenges due to strong parameter coupling.In addition,research on model simplification,parameter determination,and dynamic parameter identification remains largely fragmented.There is a lack of a comprehensive review to pave the way for the cross-domain innovations in BMS.To fill this gap,this paper presents a systematic review of the EMs for LIBs and examines the advancements in parameter determination techniques from both experimental measurement and numerical simulation perspectives.Besides,a comprehensive assessment of the progress in parameter identification from the standpoint of dynamic recognition is presented,encompassing both modelbased approaches and intelligent methods.Additionally,from the BMS standpoint,the strengths and limitations of existing approaches are evaluated.Finally,a coordinated framework for multi-stage identification needs to be established in the future.The potential of digital twins(DT),deep reinforcement learning(DRL),and large language models(LLMs)in enhancing EMs also warrants further exploration.The purpose of this work is to provide insights and guidance for the future development of EMs in LIB applications.
基金supported in part by the National Natural Science Foundation of China(62373070 and 52272388)in part by the Chongqing Natural Science Foundation(CSTB2024NSCQ-QCXMX0054,CSTB2022NSCQ-MSX1225 and CSTC2024YCJH-BGZXM0042)in part by the Key Research and Development Project of Anhui Province(202304a05020060).
文摘In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.
基金supported by Key Program of National Natural Science Foundation of China(U2368215)the Science and Technology Research and Development Program Project of China Railway Group Co.,Ltd.(N2023J056).
文摘Accurately predicting fatigue life under multiaxial fatigue damage conditions is essential for ensuring the safety of critical components in service.However,due to the complexity of fatigue failure mechanisms,achieving accurate multiaxial fatigue life predictions remains challenging.Traditional multiaxial fatigue prediction models are often limited by specific material properties and loading conditions,making it difficult to maintain reliable life prediction results beyond these constraints.This paper presents a study on the impact of seven key feature quantities on multiaxial fatigue life,using Convolutional Neural Networks(CNN),Long Short-Term Memory Networks(LSTM),and Fully Connected Neural Networks(FCNN)within a deep learning framework.Fatigue test results from eight metal specimens were analyzed to identify these feature quantities,which were then extracted as critical time-series features.Using a CNN-LSTM network,these features were combined to form a feature matrix,which was subsequently input into an FCNN to predict metal fatigue life.A comparison of the fatigue life prediction results from the STFAN model with those from traditional prediction models—namely,the equivalent strain method,the maximum shear strain method,and the critical plane method—shows that the majority of predictions for the five metal materials and various loading conditions based on the STFAN model fall within an error band of 1.5 times.Additionally,all data points are within an error band of 2 times.These findings indicate that the STFAN model provides superior prediction accuracy compared to the traditional models,highlighting its broad applicability and high precision.
基金supported by the National Key R&D Program of China[grant number 2023YFC3008004]。
文摘This study introduces a new ocean surface friction velocity scheme and a modified Thompson cloud microphysics parameterization scheme into the CMA-TYM model.The impact of these two parameterization schemes on the prediction of the movement track and intensity of Typhoon Kompasu in 2021 is examined.Additionally,the possible reasons for their effects on tropical cyclone(TC)intensity prediction are analyzed.Statistical results show that both parameterization schemes improve the predictions of Typhoon Kompasu’s track and intensity.The influence on track prediction becomes evident after 60 h of model integration,while the significant positive impact on intensity prediction is observed after 66 h.Further analysis reveals that these two schemes affect the timing and magnitude of extreme TC intensity values by influencing the evolution of the TC’s warm-core structure.
文摘The shale gas development in China faces challenges such as complex reservoir conditions and high development costs.Based on the pore pressure and geostress coupling theory,this paper studies the geostress evolution laws and fracture network characteristics of shale gas infill wells.A mechanism model of CN platform logging data and geomechanical parameters is established to simulate the influence of parent well’s production on the geostress in the infill well area.It is suggested that with the increase of production time,normal fault stress state and horizontal stress deflection will occur.The smaller the parent well spacing and the longer the production time,the earlier the normal fault stress state appears and the larger the range.Based on the model,the fracture network morphology and construction parameters of infill wells are optimized.parentparentparentparent The results indicate that:1:A well spacing of 500 m achieves a Pareto optimum between“full reserve coverage”and“stress barrier”;2:A parent well recovery degree of 30%corresponds to the critical point of stress reversal,where the lateral deflection rate of the infill fracture is less than 8%and the SRV loss is minimized;3:6-cluster intensive completion with twice the liquid intensity increases the fracture complexity index by 1.7 times,enhances well group EUR by 15.4%,and reduces single-well cost by 22%.This research fills the theoretical gap in the collaborative optimization of“multi-parameter,multi-objective and multi-constraint”and provide parameter optimization basis for shale gas infill well development in China and help to improve the development efficiency and economic benefits.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12104193 and U24A2017)National Undergraduate Training Program for Innovation and Entrepreneurship(Grant No.202411463037Z)the project of Changzhou Physics Society Fund(Grant No.CW20250102)。
文摘We theoretically investigate the phase sensitivity of a truncated SU(1,1)interferometer fed with a two-mode coherent state and employing double-port homodyne detection.On the one hand,we analytically demonstrate that the two-mode coherent state provides better phase sensitivity than the single-mode coherent state.In addition,we show that the doubleport homodyne detection is a quasi-optimal measurement.For a bright coherent-state input,the sensitivity of this scheme saturates the phase-sensitivity bound determined by the quantum Fisher information.On the other hand,we quantitatively illustrate the advantage of double-port homodyne detection over the single-port scheme under ideal conditions and in the presence of photon loss,respectively.Furthermore,our analysis indicates that the scheme we propose is robust against photon loss.
基金supported by the National Natural Science Foundation of China(Grant Nos.:52202423,U2268211,and 52475136)the China Postdoctoral Science Foundation(Grant Nos.:2022M712636 and 2023T160546)+1 种基金the Natural Science Foundation of Sichuan Province(Grant No.:2025ZNSFSC0398)the Independent R&D Project of the State Key Laboratory of Traction Power(Grant No.:2023TPL-T14).
文摘Since the view that the localized rail third-order bending mode can cause high-order polygonization(mainly 18-23)of high-speed train wheels was put forward in 2017,many scholars have attempted to link a connection between the localized rail bending modes and wheel polygonization phenomenon and polygonal wheel passing frequency.This paper first establishes a flexible track model considering the structural and parametric characteristics of fasteners,verifies the model by using vehicle tracking test data,then investigates the influence of fastener parameter matching on the localized rail bending modes,and obtains the following conclusions:(1)There is nearly a 1:1 mapping relationship between the localized rail bending modal frequency and polygonal wheel passing(PWP)frequency,which supports that the localized rail bending mode is one of the causes of wheel polygonization.(2)The iron plate of the fastener system plays a role of dynamic vibration absorber in the vehicle-rail coupled system,and the fastener parameters significantly influence the localized rail bending modal vibration.Finally,this paper proposes a design principle of a high-frequency vibration-absorbing fastener,which provides a feasible solution to mitigate the localized rail bending modal vibration and high-order wheel polygonization.Meanwhile,it points out that this measure may induce other high-frequency vibration problems,e.g.,aggravating modal vibration above 800 Hz.Further,this paper proposes a concept of differentiated arrangement of fasteners,suggesting that different high-frequency vibration-absorbing fasteners be installed in different sections of the whole line to make the localized rail bending modal frequency of the whole line disordered,thus disrupting and further mitigating the development of the wheel polygonization.
基金Supported by Key Program of Natural Science Foundation of China(52234002)Major Program Project of the National Natural Science Foundation of China(52394255)。
文摘Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drilling extension limits,underground target distribution and trajectory collision risks,a model of platform location-wellbore trajectory collaborative optimization for a complex-structure well factory is developed.A hybrid heuristic algorithm is proposed by combining an improved sparrow search algorithm(ISSA)for optimizing platform parameters in the outer layer and a directed artificial bee colony algorithm(DABC)for optimizing trajectory parameters in the inner layer.The alternating iteration of ISSA-DABC facilitates the resolution of the collaborative optimization problem.The ISSA-DABC provides an effective solution to the platform-trajectory collaborative optimization problem for complex-structure well factories and overcomes the tendency of the traditional platform-trajectory stepwise optimization workflow to become trapped in local optima and yield inconsistent designs.The ISSA-DABC has a strong global search capability,fast convergence and good robustness,and can simultaneously satisfy multiple engineering constraints on drilling footage,trajectory complexity and collision risk,and enables automated,workflow-wide generation of constraint-compliant,near-globally optimal platform-trajectory configurations.Field applications further demonstrate that ISSA-DABC significantly reduces the objective function value and collision risk,yielding more rational platform layouts and well factory design parameters.
基金funded by the National Key R&D Program of China,China(No.2024YFF0507903)the National Key Research and Development Program of China(Grant No.2024YFF0507904)the National Natural Science Foundation of China,China(Grant No.52379114).
文摘In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.
基金supported by the National Natural Science Foundation of China(Grant Nos.12171217 and 12375003)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LMS 25A010013)。
文摘In this paper,we investigate data-driven bright soliton solutions of the nonlocal reverse-time nonlinear Schrodinger(NLS)equation and the parameter identification using the physically informed neural networks(PINNs)algorithm.Accurate simulations and comparative analyses of relative and absolute errors are performed for two-soliton and four-soliton solutions including linear solitary waves and periodic waves.In the training process,the standard PINNs scheme is employed for linear solitary wave solutions,while the prior information is added at local sharp regions for periodic wave solutions due to the complicated collision behaviors.For the parameter identification,we accurately recognize the nonlinear coefficients of the nonlocal NLS equation from known solutions with different noises.These results reinforce the application of deep learning with the PINNs framework to successfully study nonlocal integrable systems.
基金supported by the National Natural Science Foundation of China(Grant Nos.42230610 and U2442213)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.2022069)。
文摘The Tibetan Plateau(TP),characterized by its elevated topography,plays a crucial role in regional environmental and climate dynamics,where the understanding of radiation energy budgets is essential.However,accurately estimating the spatiotemporal variations of radiation budget components and surface albedo across the diverse landscapes of the TP remains a significant challenge for the scientific community.To address this issue,numerous atmospheric experiments and research initiatives have been conducted since the 1960s,focusing on quantitatively assessing the spatial distribution and temporal variations of radiation fluxes through both observational data and remote sensing techniques.This paper systematically reviews the key advancements in radiation energy studies over the past 35 years,with a particular focus on measurements derived from tens of radiation flux stations and satellite observations across the TP.Additionally,the development of parameterization schemes in topographical effects on radiation fluxes is also summarized.Finally,the paper discusses potential future research directions in this field.
基金supported by the National Key Research and Development Program of China(2021YFC2203004)the National Natural Science Foundation of China(NSFC)(12405076,12247187,and 12147103)+1 种基金the National Astronomical Data Center(NADC2023YDS-01)the Fundamental Research Funds for the Central Universities.
文摘The detection of gravitational waves by the LIGO-Virgo-KAGRA collaboration has ushered in a new era of observational astronomy,emphasizing the need for rapid and detailed parameter estimation and population-level analyses.Traditional Bayesian inference methods,particularly Markov chain Monte Carlo,face significant computational challenges when dealing with the high-dimensional parameter spaces and complex noise characteristics inherent in gravitational wave data.This review examines the emerging role of simulation-based inference methods in gravitational wave astronomy,with a focus on approaches that leverage machine-learning techniques such as normalizing flows and neural posterior estimation.We provide a comprehensive overview of the theoretical foundations underlying various simulation-based inference methods,including neural posterior estimation,neural ratio estimation,neural likelihood estimation,flow matching,and consistency models.We explore the applications of these methods across diverse gravitational wave data processing scenarios,from single-source parameter estimation and overlapping signal analysis to testing general relativity and conducting population studies.Although these techniques demonstrate speed improvements over traditional methods in controlled studies,their model-dependent nature and sensitivity to prior assumptions are barriers to their widespread adoption.Their accuracy,which is similar to that of conventional methods,requires further validation across broader parameter spaces and noise conditions.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
