To reveal the influence of coupled effects of dry-wet cycling and precompression stress(CEDWCPS)on the damage evolution of limestone with horizontal fissure(LHF),a series of degradation and uniaxial compression tests ...To reveal the influence of coupled effects of dry-wet cycling and precompression stress(CEDWCPS)on the damage evolution of limestone with horizontal fissure(LHF),a series of degradation and uniaxial compression tests were conducted,and a corresponding piecewise damage constitutive model(PDCM)was established.We found that both dry-wet cycling and precompression stress deteriorate the physical properties,alter the microscopic characteristics,and reduce the mechanical properties of the LHF.These degradations are particularly pronounced under the CEDWCPS,although the magnitude of these changes gradually diminishes with the progression of dry-wet cycling.Meanwhile,they also reduce the deformation degree,prolong the micropore compaction stage,shorten the unstable crack propagation stage,lower the frequency and intensity of AE events,decrease the high-amplitude and high-frequency AE signals,enlarge crack scales,and shorten the crack initiation time.Among the changes of these indicators,the dry-wet cycling plays a dominant role.The crack types of LHF under the CEDWCPS(LHFCEDWCPS)are predominantly tensile cracks,supplemented by shear cracks.The failure mode can be defined as tensileshear composite failure.Finally,the established PDCM effectively captures the nonlinear deformation of micropore and the linear deformation of the matrix in LHFCEDWCPS,with all corresponding R^(2) consistently exceeding 0.97.展开更多
Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Couple...Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.展开更多
Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades ...Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling.This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions.By comparing various models,one can better assess the uncertainties in predictions,particularly those related to the conceptual models.The review explores how these methodologies have significantlyenhanced the fundamental understanding of how fractures respond to fluid injection and production,and improved predictive capabilities pertaining to coupled processes within fractured systems.It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience.The selection and calibration of model parameters should be based on typical ranges and applied to the specificconditions of applications.The challenges arising from inherent heterogeneity and uncertainties,nonlinear THM coupled processes,scale dependence,and computational limitations in representing fieldscale fractures are discussed.Realizing potential advances on computational capacity calls for methodical conceptualization,mathematical modeling,selection of numerical solution strategies,implementation,and calibration to foster simulation outcomes that intricately reflectthe nuanced complexities of geological phenomena.Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical fieldof study.展开更多
Laser powder bed fusion(LPBF)has revolutionized modern manufacturing by enabling high design freedom,rapid prototyping,and tailored mechanical properties.However,optimizing process parameters remains challenging due t...Laser powder bed fusion(LPBF)has revolutionized modern manufacturing by enabling high design freedom,rapid prototyping,and tailored mechanical properties.However,optimizing process parameters remains challenging due to the trial-and-error approaches required to capture subtle parameter-microstructure relationships.This study employed a multi-physics computational framework to investigate the melting and solidification dynamics of magnesium alloy.By integrating the discrete element method for powder bed generation,finite volume method with volume of fluid for melt pool behavior,and phase-field method for microstructural evolution,the critical physical phenomena,including powder melting,molten pool flow,and directional solidification were simulated.The effects of laser power and scanning speed on temperature distribution,melt pool geometry,and dendritic morphology were systematically analyzed.It was revealed that increasing laser power expanded melt pool dimensions and promoted columnar dendritic growth,while high scanning speeds reduced melt pool stability and refined dendritic structures.Furthermore,Marangoni convection and thermal gradients governed solute redistribution,with excessive energy input risking defects such as porosity and elemental evaporation.These insights establish quantitative correlations between process parameters,thermal history,and microstructural characteristics,providing a validated roadmap for LPBF-processed magnesium alloy with tailored performance.展开更多
Conventional concentrator photovoltaics(CPV)face a persistent trade-off between high efficiency and high cost,driven by expensive multi-junction solar cells and complex active cooling systems.This study presents a com...Conventional concentrator photovoltaics(CPV)face a persistent trade-off between high efficiency and high cost,driven by expensive multi-junction solar cells and complex active cooling systems.This study presents a computational investigation of a novel Multi-Focal Pyramidal Array(MFPA)-based CPV system designed to overcome this limitation.The MFPA architecture employs a geometrically optimized pyramidal concentrator to distribute concen-trated sunlight onto strategically placed,low-cost monocrystalline silicon cells,enabling high efficiency energy capture while passively managing thermal loads.Coupled optical thermal electrical simulations in COMSOL Multiphysics demonstrate a geometric concentration ratio of 120×,with system temperatures maintained below 110℃ under standard 1000 W/m2 Direct Normal Irradiance(DNI).Ray tracing confirms 95%optical efficiency and a concentrated light spot radius of 2.48 mm.Compared with conventional CPV designs,the MFPA improves power-per-cost by 25%and reduces tracking requirements by 50%owing to its wide±15°acceptance angle.These results highlight the MFPA’s potential as a scalable,low-cost,and energy-efficient pathway for expanding solar power generation.展开更多
Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion i...Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion in swimming,and provides additional support during terrestrial crawling.However,when the tail lifts off the ground during land crawling,its flexible underactuated structure tends to oscillate randomly due to minimal damping.These oscillations impart disruptive reaction torques to the body,critically impairing locomotion stability.To tackle this issue,we employed the standard Denavit-Hartenberg(DH)method and Newton-Euler equations to formulate a rigid-flexible coupled dynamic model for the tail,in which distributed elastic forces are embedded as internal forces in the force balance equations.Based on this model,we propose an oscillation suppression strategy based on an energy-optimized Nonlinear Model Predictive Controller(NMPC)with a single joint torque as the control input.This controller solves a constrained multi-objective optimization problem to effectively suppress the underactuated oscillations of the tail.Finally,experimental comparisons validate the accuracy of the dynamic model,and simulations based on this model substantiate the effectiveness of the oscillation suppression strategy.展开更多
A mechanistic understanding and modeling of the coupled human and natural systems(CHANS)are frontier of geographical sciences and essential for promoting regional sustainability.Modeling regional CHANS in the Yellow R...A mechanistic understanding and modeling of the coupled human and natural systems(CHANS)are frontier of geographical sciences and essential for promoting regional sustainability.Modeling regional CHANS in the Yellow River Basin(YRB)featuring high water stress,intense human interference,and a fragile ecosystem has always been a complex challenge.Here,we propose a conceptual modeling framework to capture key human-natural components and their interactions,focusing on human-water dynamics.The modeling framework encompasses five human(Population,Economy,Energy,Food,and Water Demand)and five natural sectors(Water Supply,Sediment,Land,Carbon,and Climate)that can be either fully interactive or standalone.The modeling framework,implemented using the system dynamics(SD)approach,can well reproduce the basin's historical evolution in human-natural processes and predict future dynamics under various scenarios.The flexibility,adaptability,and potential for integration with diverse methods position the framework as an instructive tool for guiding regional CHANS modeling.Our insights highlight pathways to advance regional CHANS modeling and its application to address regional sustainability challenges.展开更多
This study presents a coupled thermo-hydro-mechanical-fatigue(THM-F)model,developed based on variational phase-field fatigue theory,to simulate the freeze-thaw(F-T)damage process in concrete.The fracture phasefield mo...This study presents a coupled thermo-hydro-mechanical-fatigue(THM-F)model,developed based on variational phase-field fatigue theory,to simulate the freeze-thaw(F-T)damage process in concrete.The fracture phasefield model incorporates the F-T fatigue mechanism driven by energy dissipation during the free energy growth stage.Using microscopic inclusion theory,we derive an evolution model of pore size distribution(PSD)for concrete under F-T cycles by treating pore water as columnar inclusions.Drawing upon pore ice crystal theory,calculation models that account for concrete PSD characteristics are established to determine ice saturation,permeability coefficient,and pore pressure.To enhance computational accuracy,a segmented Gaussian integration strategy based on aperture levels is employed.The pore pressure estimation model is applied to assess the frost resistance of concrete with varying air-entraining agent contents,confirming that optimal air-entrainment significantly improves pore structure and lowers the overall freezing point of pore ice.The derived permeability coefficient and pore pressure estimation models are integrated into the THM-F coupled framework,which employs a staggered iterative solution scheme for efficient simulation.Mesoscale numerical examples of concrete demonstrate that the proposed THM-F model effectively captures structural degradation and accurately tracks the procession of F-T-induced fatigue cracks.Validations against experimental measurements,including temperature variations,stress-strain curves,and strain history,shows excellent agreement,underscoring the model’s accuracy and applicability.This study provides a robust theoretical and computational framework for quantitative analysis of coupled F-T-fatigue damage in concrete.展开更多
The axle box bearings of high-speed trains often operate in extremely harsh environments,bearing loads from different directions.Long-term operation and frequent changes in working conditions can easily lead to axle b...The axle box bearings of high-speed trains often operate in extremely harsh environments,bearing loads from different directions.Long-term operation and frequent changes in working conditions can easily lead to axle box bearing failures.Therefore,it is extremely important to study the mechanism of axle box bearings.Firstly,the medium of thermal deformation establishes a coupling relationship between the system dynamics model and the thermal grid model,and then obtains the thermal force coupling model of the high-speed train axle box bearing.The coupling model is validated from the perspectives of system dynamics response and temperature response,proving its effectiveness in system dynamics response and temperature characteristic response.Comparing the coupling model with the dynamics model,it is found that thermal deformation complicates the dynamic re-sponse.Finally,using the Lundberg-Palmgren(L-P)bearing fatigue calculation method and damage accumu-lation theory,the bearing fatigue life is calculated,and it is found that thermal deformation deteriorates the bearing operating environment,reducing the bearing fatigue life.Finally,by comparing the bearing fatigue life under different working conditions,it is concluded that the faster the vehicle speed,the greater the load,and the smaller the initial radial clearance of the bearing,the fatigue life of the bearing is reduced.The shorter the lifespan.展开更多
Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit signifi...Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.展开更多
Improving plasma uniformity is a critical issue in the development of large-area radio-frequency(RF)inductively coupled plasma(ICP)sources.In this work,the effects of coil structure and electromagnetic shielding on th...Improving plasma uniformity is a critical issue in the development of large-area radio-frequency(RF)inductively coupled plasma(ICP)sources.In this work,the effects of coil structure and electromagnetic shielding on the spatial distribution and uniformity of the plasma are systematically investigated using a three-dimensional fluid model.The model integrates plasma and electromagnetic field modules to simulate the discharge characteristics of a large-area RF ICP source with dimensions of 100 cm×50 cm.The results reveal that the electron density distribution varies significantly with the coil structure.For the rotating and translating coil structures,the electron density is high at off-axis positions and low at the center.In contrast,the mirror coil structure exhibits a significantly higher electron density at the chamber center,resulting in a high-center and low-edge density distribution.Among the three configurations,the rotating coil structure provides the best plasma uniformity.The incorporation of electromagnetic shielding further improves plasma uniformity,particularly for the mirror coil structure.For the rotating and translating coil structures,the electron density exhibits a saddle-shaped distribution regardless of electromagnetic shielding.However,introducing electromagnetic shielding into the mirror coil structure reduces the electron density at the chamber center and decreases the non-uniformity degree by 18.4%.Overall,the mirror coil structure with electromagnetic shielding achieves the highest uniformity,with an exceptional plasma uniformity of 94%.This work offers valuable insights for the design of large-area ICP sources in advanced plasma processing systems.展开更多
A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution t...A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution terms between the cold fluid and the hot rock are derived.Heat transfer obeys Fourier's law,and porosity is used to relate the thermodynamic parameters of the fracture and matrix domains.The net pressure difference between the fracture and the matrix is neglected,and thus the fluid flow is modeled by the unified fluid-governing equations.The evolution equations of porosity and Biot's coefficient during hydraulic fracturing are derived from their definitions.The effect of coal cleats is considered and modeled by Voronoi polygons,and this approach is shown to have high accuracy.The accuracy of the proposed model is verified by two sets of fracturing experiments in multilayer coal seams.Subsequently,the differences in fracture morphology,fluid pressure response,and fluid pressure distribution between direct fracturing of coal seams and indirect fracturing of shale interlayers are explored,and the effects of the cluster number and cluster spacing on fracture morphology for multi-cluster fracturing are also examined.The numerical results show that the proposed model is expected to be a powerful tool for the fracturing design and optimization of deep coalbed methane.展开更多
Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper...Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper presents a data-driven approach to expansion estimation using electromechanical coupled models with machine learning.The proposed method integrates reduced-order impedance models with data-driven mechanical models,coupling the electrochemical and mechanical states through the state of charge(SOC)and mechanical pressure within a state estimation framework.The coupling relationship was established through experimental insights into pressure-related impedance parameters and the nonlinear mechanical behavior with SOC and pressure.The data-driven model was interpreted by introducing a novel swelling coefficient defined by component stiffnesses to capture the nonlinear mechanical behavior across various mechanical constraints.Sensitivity analysis of the impedance model shows that updating model parameters with pressure can reduce the mean absolute error of simulated voltage by 20 mV and SOC estimation error by 2%.The results demonstrate the model's estimation capabilities,achieving a root mean square error of less than 1 kPa when the maximum expansion force is from 30 kPa to 120 kPa,outperforming calibrated stiffness models and other machine learning techniques.The model's robustness and generalizability are further supported by its effective handling of SOC estimation and pressure measurement errors.This work highlights the importance of the proposed framework in enhancing state estimation and fault diagnosis for lithium-ion batteries.展开更多
Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems,shaped by the complex interactions of thermal,hydraulic,mechanical and chemical(THMC)fiel...Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems,shaped by the complex interactions of thermal,hydraulic,mechanical and chemical(THMC)fields.This paper presents a systematic review of this subject with special emphasis on the multi-physics governing it.First,we elucidate the interdependent mechanisms and governing equations,highlighting the nonlinear,path-dependent,and evolving nature of the relationship between stress and permeability.Next,mainstream modeling approaches,including equivalent continuum,discrete fracture network(DFN),and dual-porosity/dual-permeability methods,are critically evaluated,and a strategy for model selection based on project scale and geological context is proposed accordingly.Moreover,experimental insights from single-fracture and triaxial flow studies are synthesized,revealing how effective stress,shear displacement,and fracture roughness control permeability evolution.In particular,the practical significance of THMC coupling is demonstrated through case studies on nuclear waste disposal,Enhanced Geothermal Systems,and tunneling projects.The reviewfurther explores AI-and machine learning-driven innovations,particularly physics-informed neural networks and hybrid modeling,which address limitations in computational efficiency,data scarcity,and physical consistency.Finally,persistent challenges,including multi-scale coupling,parameter uncertainty,and complex fracture network representation are identified and critically discussed while paying attention to future developments.展开更多
The Electro–Hydrostatic Actuator(EHA)is applied to drive the control surface in flightcontrol system of more electric aircraft.In EHA,the Oil-Immersed Motor Pump(OMP)serves asthe core as a power assembly.However,the ...The Electro–Hydrostatic Actuator(EHA)is applied to drive the control surface in flightcontrol system of more electric aircraft.In EHA,the Oil-Immersed Motor Pump(OMP)serves asthe core as a power assembly.However,the compact integration of the OMP presents challenges inefficiently dissipating internal heat,leading to a performance degradation of the EHA due to ele-vated temperatures.Therefore,accurately modeling and predicting the internal thermal dynamicsof the OMP hold considerable significance for monitoring the operational condition of the EHA.In view of this,a modeling method considering cumulative thermal coupling was hereby proposed.Based on the proposed method,the thermal models of the motor and the pump were established,taking into account heat accumulation and transfer.Taking the leakage oil as the heat couplingpoint between the motor and the pump,the dynamic thermal coupling model of the OMP wasdeveloped,with the thermal characteristics of the oil considered.Additionally,the comparativeexperiments were conducted to illustrate the efficiency of the proposed model.The experimentalresults demonstrate that the proposed dynamic thermal coupling model accurately captured thethermal behavior of OMP,outperforming the static thermal parameter model.Overall,thisadvancement is crucial for effectively monitoring the health of EHA and ensuring flight safety.展开更多
Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many ...Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.展开更多
Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie conditio...Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.展开更多
Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite ...Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.展开更多
The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes...The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes in ENSO forecasts,resulting in significant progress.Most deep learning-based ENSO prediction models which primarily rely solely on reanalysis data may lead to challenges in intensity underestimation in long-term forecasts,reducing the forecasting skills.To this end,we propose a deep residual-coupled model prediction(Res-CMP)model,which integrates historical reanalysis data and coupled model forecast data for multiyear ENSO prediction.The Res-CMP model is designed as a lightweight model that leverages only short-term reanalysis data and nudging assimilation prediction results of the Community Earth System Model(CESM)for effective prediction of the Niño 3.4 index.We also developed a transfer learning strategy for this model to overcome the limitations of inadequate forecast data.After determining the optimal configuration,which included selecting a suitable transfer learning rate during training,along with input variables and CESM forecast lengths,Res-CMP demonstrated a high correlation ability for 19-month lead time predictions(correlation coefficients exceeding 0.5).The Res-CMP model also alleviated the spring predictability barrier(SPB).When validated against actual ENSO events,Res-CMP successfully captured the temporal evolution of the Niño 3.4 index during La Niña events(1998/99 and 2020/21)and El Niño events(2009/10 and 2015/16).Our proposed model has the potential to further enhance ENSO prediction performance by using coupled models to assist deep learning methods.展开更多
To perform an integral simulation of a pool-type reactor using CFD code,a multi-physics coupled code MPC-LBE for an LBE-cooled reactor was proposed by integrating a point kinetics model and a fuel pin heat transfer mo...To perform an integral simulation of a pool-type reactor using CFD code,a multi-physics coupled code MPC-LBE for an LBE-cooled reactor was proposed by integrating a point kinetics model and a fuel pin heat transfer model into self-developed CFD code.For code verification,a code-to-code comparison was employed to validate the CFD code.Furthermore,a typical BT transient benchmark on the LBE-cooled XADS reactor was selected for verification in terms of the integral or system performance.Based on the verification results,it was demonstrated that the MPC-LBE coupled code can perform thermal-hydraulics or safety analyses for analysis for processes involved in LBE-cooled pool-type reactors.展开更多
基金supported by the Yunnan Province Science and Technology Plan Project(No.202403AA080001-4)the Key Research and Development Project of Guangxi,China(No.guikeAB24010144)the National Key Research and Development Project of China(Nos.2021YFB3901402 and 2018YFC1504802)。
文摘To reveal the influence of coupled effects of dry-wet cycling and precompression stress(CEDWCPS)on the damage evolution of limestone with horizontal fissure(LHF),a series of degradation and uniaxial compression tests were conducted,and a corresponding piecewise damage constitutive model(PDCM)was established.We found that both dry-wet cycling and precompression stress deteriorate the physical properties,alter the microscopic characteristics,and reduce the mechanical properties of the LHF.These degradations are particularly pronounced under the CEDWCPS,although the magnitude of these changes gradually diminishes with the progression of dry-wet cycling.Meanwhile,they also reduce the deformation degree,prolong the micropore compaction stage,shorten the unstable crack propagation stage,lower the frequency and intensity of AE events,decrease the high-amplitude and high-frequency AE signals,enlarge crack scales,and shorten the crack initiation time.Among the changes of these indicators,the dry-wet cycling plays a dominant role.The crack types of LHF under the CEDWCPS(LHFCEDWCPS)are predominantly tensile cracks,supplemented by shear cracks.The failure mode can be defined as tensileshear composite failure.Finally,the established PDCM effectively captures the nonlinear deformation of micropore and the linear deformation of the matrix in LHFCEDWCPS,with all corresponding R^(2) consistently exceeding 0.97.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272411 and 42007259).
文摘Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.
基金funding from the European Research Council(ERC)under the European Union’s Horizon 2020 Research and Innovation Program through the Starting Grant GEoREST(grant agreement No.801809)support by MICIU/AEI/10.13039/501100011033 and by"European Union Next Generation EU/PRTR"through the‘Ramón y Cajal’fellowship(reference RYC2021-032780-I)+9 种基金funding by MICIU/AEI/10.13039/501100011033 and by“ERDF,EU”through the‘HydroPoreII’project(reference PID2022-137652NBC44)support by the Institute for Korea Spent Nuclear Fuel(iKSNF)National Research Foundation of Korea(NRF)grant funded by the Korea government(Ministry of Science and ICT,MSIT)(2021M2E1A1085196)support by the Swedish Radiation Safety(SSM),Swedish Transport Administration(Trafikverket),Swedish Rock Engineering Foundation(BeFo),and Nordic Energy Research(Grant 187658)supported by the US Department of Energy(DOE),the Officeof Nuclear Energy,Spent Fuel and Waste Science and Technology Campaign,and by the US Department of Energy(DOE),the Office of Basic Energy Sciences,Chemical Sciences,Geosciences,and Biosciences Division both under Contract Number DE-AC02-05CH11231 with Lawrence Berkeley National Laboratorysupport from the US National Science Foundation(grant CMMI-2239630)funding from the European Research Council(ERC)under the European Union’s Horizon 2020 research and innovation programme(grant agreement No.101002507)the UK Natural Environment Research Council(NERC)for funding SeisGreen Project(Grant No.NE/W009293/1)which supported this workthe Royal Society UK for supporting this research through fellowship UF160443IMEDEA is an accredited"Maria de Maeztu Excellence Unit"(Grant CEX2021-001198,funded by MICIU/AEI/10.13039/501100011033).
文摘Coupled thermo-hydro-mechanical(THM)processes in fractured rock are playing a crucial role in geoscience and geoengineering applications.Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling.This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions.By comparing various models,one can better assess the uncertainties in predictions,particularly those related to the conceptual models.The review explores how these methodologies have significantlyenhanced the fundamental understanding of how fractures respond to fluid injection and production,and improved predictive capabilities pertaining to coupled processes within fractured systems.It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience.The selection and calibration of model parameters should be based on typical ranges and applied to the specificconditions of applications.The challenges arising from inherent heterogeneity and uncertainties,nonlinear THM coupled processes,scale dependence,and computational limitations in representing fieldscale fractures are discussed.Realizing potential advances on computational capacity calls for methodical conceptualization,mathematical modeling,selection of numerical solution strategies,implementation,and calibration to foster simulation outcomes that intricately reflectthe nuanced complexities of geological phenomena.Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical fieldof study.
基金supported by the Ministry of Science and Technology of the People’s Republic of China(2025YFE0110100)Xjenza Malta through SINOMALTA-2024-11(Science and Technology Cooperation)+8 种基金National Natural Science Foundation of China(52165043)Jiang Xi Provincial Natural Science Foundation of China(20224ACB214008,20232BAB214007)Jiangxi Provincial Cultivation Program for Academic and Technical Leaders of Major Subjects(20225BCJ23008)Excellent Research and Innovation Team in Anhui Province(2024AH010031)The University Synergy Innovation Program of Anhui Province(GXXT-2023-025,GXXT-2023-026)Anhui Province Science and Technology Innovation Tackle Plan Project of Anhui Province(202423i08050011)Anhui Provincial Natural Science Foundation of China(2308085ME171)The Project for Cultivating Academic(or Disciplinary)Leaders of Anhui University(DTR2024044)Talent research start-up fund project(2024tlxyrc056).
文摘Laser powder bed fusion(LPBF)has revolutionized modern manufacturing by enabling high design freedom,rapid prototyping,and tailored mechanical properties.However,optimizing process parameters remains challenging due to the trial-and-error approaches required to capture subtle parameter-microstructure relationships.This study employed a multi-physics computational framework to investigate the melting and solidification dynamics of magnesium alloy.By integrating the discrete element method for powder bed generation,finite volume method with volume of fluid for melt pool behavior,and phase-field method for microstructural evolution,the critical physical phenomena,including powder melting,molten pool flow,and directional solidification were simulated.The effects of laser power and scanning speed on temperature distribution,melt pool geometry,and dendritic morphology were systematically analyzed.It was revealed that increasing laser power expanded melt pool dimensions and promoted columnar dendritic growth,while high scanning speeds reduced melt pool stability and refined dendritic structures.Furthermore,Marangoni convection and thermal gradients governed solute redistribution,with excessive energy input risking defects such as porosity and elemental evaporation.These insights establish quantitative correlations between process parameters,thermal history,and microstructural characteristics,providing a validated roadmap for LPBF-processed magnesium alloy with tailored performance.
文摘Conventional concentrator photovoltaics(CPV)face a persistent trade-off between high efficiency and high cost,driven by expensive multi-junction solar cells and complex active cooling systems.This study presents a computational investigation of a novel Multi-Focal Pyramidal Array(MFPA)-based CPV system designed to overcome this limitation.The MFPA architecture employs a geometrically optimized pyramidal concentrator to distribute concen-trated sunlight onto strategically placed,low-cost monocrystalline silicon cells,enabling high efficiency energy capture while passively managing thermal loads.Coupled optical thermal electrical simulations in COMSOL Multiphysics demonstrate a geometric concentration ratio of 120×,with system temperatures maintained below 110℃ under standard 1000 W/m2 Direct Normal Irradiance(DNI).Ray tracing confirms 95%optical efficiency and a concentrated light spot radius of 2.48 mm.Compared with conventional CPV designs,the MFPA improves power-per-cost by 25%and reduces tracking requirements by 50%owing to its wide±15°acceptance angle.These results highlight the MFPA’s potential as a scalable,low-cost,and energy-efficient pathway for expanding solar power generation.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFB3213600).
文摘Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion in swimming,and provides additional support during terrestrial crawling.However,when the tail lifts off the ground during land crawling,its flexible underactuated structure tends to oscillate randomly due to minimal damping.These oscillations impart disruptive reaction torques to the body,critically impairing locomotion stability.To tackle this issue,we employed the standard Denavit-Hartenberg(DH)method and Newton-Euler equations to formulate a rigid-flexible coupled dynamic model for the tail,in which distributed elastic forces are embedded as internal forces in the force balance equations.Based on this model,we propose an oscillation suppression strategy based on an energy-optimized Nonlinear Model Predictive Controller(NMPC)with a single joint torque as the control input.This controller solves a constrained multi-objective optimization problem to effectively suppress the underactuated oscillations of the tail.Finally,experimental comparisons validate the accuracy of the dynamic model,and simulations based on this model substantiate the effectiveness of the oscillation suppression strategy.
基金supported by the National Natural Science Foundation of China(Grant No.42041007)the Fundamental Research Funds for the Central Universities。
文摘A mechanistic understanding and modeling of the coupled human and natural systems(CHANS)are frontier of geographical sciences and essential for promoting regional sustainability.Modeling regional CHANS in the Yellow River Basin(YRB)featuring high water stress,intense human interference,and a fragile ecosystem has always been a complex challenge.Here,we propose a conceptual modeling framework to capture key human-natural components and their interactions,focusing on human-water dynamics.The modeling framework encompasses five human(Population,Economy,Energy,Food,and Water Demand)and five natural sectors(Water Supply,Sediment,Land,Carbon,and Climate)that can be either fully interactive or standalone.The modeling framework,implemented using the system dynamics(SD)approach,can well reproduce the basin's historical evolution in human-natural processes and predict future dynamics under various scenarios.The flexibility,adaptability,and potential for integration with diverse methods position the framework as an instructive tool for guiding regional CHANS modeling.Our insights highlight pathways to advance regional CHANS modeling and its application to address regional sustainability challenges.
基金supported by the National Natural Science Foundation of China(Grant Nos.11932006 and 12172121).
文摘This study presents a coupled thermo-hydro-mechanical-fatigue(THM-F)model,developed based on variational phase-field fatigue theory,to simulate the freeze-thaw(F-T)damage process in concrete.The fracture phasefield model incorporates the F-T fatigue mechanism driven by energy dissipation during the free energy growth stage.Using microscopic inclusion theory,we derive an evolution model of pore size distribution(PSD)for concrete under F-T cycles by treating pore water as columnar inclusions.Drawing upon pore ice crystal theory,calculation models that account for concrete PSD characteristics are established to determine ice saturation,permeability coefficient,and pore pressure.To enhance computational accuracy,a segmented Gaussian integration strategy based on aperture levels is employed.The pore pressure estimation model is applied to assess the frost resistance of concrete with varying air-entraining agent contents,confirming that optimal air-entrainment significantly improves pore structure and lowers the overall freezing point of pore ice.The derived permeability coefficient and pore pressure estimation models are integrated into the THM-F coupled framework,which employs a staggered iterative solution scheme for efficient simulation.Mesoscale numerical examples of concrete demonstrate that the proposed THM-F model effectively captures structural degradation and accurately tracks the procession of F-T-induced fatigue cracks.Validations against experimental measurements,including temperature variations,stress-strain curves,and strain history,shows excellent agreement,underscoring the model’s accuracy and applicability.This study provides a robust theoretical and computational framework for quantitative analysis of coupled F-T-fatigue damage in concrete.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12393780,12032017,12302067)College Education Scientific Research Project of Hebei Province(Grant No.JZX2024006)Hebei Provincial S&T Program(Grant No.21567622 H).
文摘The axle box bearings of high-speed trains often operate in extremely harsh environments,bearing loads from different directions.Long-term operation and frequent changes in working conditions can easily lead to axle box bearing failures.Therefore,it is extremely important to study the mechanism of axle box bearings.Firstly,the medium of thermal deformation establishes a coupling relationship between the system dynamics model and the thermal grid model,and then obtains the thermal force coupling model of the high-speed train axle box bearing.The coupling model is validated from the perspectives of system dynamics response and temperature response,proving its effectiveness in system dynamics response and temperature characteristic response.Comparing the coupling model with the dynamics model,it is found that thermal deformation complicates the dynamic re-sponse.Finally,using the Lundberg-Palmgren(L-P)bearing fatigue calculation method and damage accumu-lation theory,the bearing fatigue life is calculated,and it is found that thermal deformation deteriorates the bearing operating environment,reducing the bearing fatigue life.Finally,by comparing the bearing fatigue life under different working conditions,it is concluded that the faster the vehicle speed,the greater the load,and the smaller the initial radial clearance of the bearing,the fatigue life of the bearing is reduced.The shorter the lifespan.
基金Supported by the Laoshan Laboratory(No.LSKJ 202202404)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 42000000)+1 种基金the National Natural Science Foundation of China(NSFC)(No.42030410)the Startup Foundation for Introducing Talent of NUIST,and the Jiangsu Innovation Research Group(No.JSSCTD 202346)。
文摘Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.
基金supported by the National Natural Science Foundation of China(Grant Nos.12075049 and 11935005)。
文摘Improving plasma uniformity is a critical issue in the development of large-area radio-frequency(RF)inductively coupled plasma(ICP)sources.In this work,the effects of coil structure and electromagnetic shielding on the spatial distribution and uniformity of the plasma are systematically investigated using a three-dimensional fluid model.The model integrates plasma and electromagnetic field modules to simulate the discharge characteristics of a large-area RF ICP source with dimensions of 100 cm×50 cm.The results reveal that the electron density distribution varies significantly with the coil structure.For the rotating and translating coil structures,the electron density is high at off-axis positions and low at the center.In contrast,the mirror coil structure exhibits a significantly higher electron density at the chamber center,resulting in a high-center and low-edge density distribution.Among the three configurations,the rotating coil structure provides the best plasma uniformity.The incorporation of electromagnetic shielding further improves plasma uniformity,particularly for the mirror coil structure.For the rotating and translating coil structures,the electron density exhibits a saddle-shaped distribution regardless of electromagnetic shielding.However,introducing electromagnetic shielding into the mirror coil structure reduces the electron density at the chamber center and decreases the non-uniformity degree by 18.4%.Overall,the mirror coil structure with electromagnetic shielding achieves the highest uniformity,with an exceptional plasma uniformity of 94%.This work offers valuable insights for the design of large-area ICP sources in advanced plasma processing systems.
基金Project supported by the National Natural Science Foundation of China(No.42202314)。
文摘A coupled thermal-hydro-mechanical cohesive phase-field model for hydraulic fracturing in deep coal seams is presented.Heat exchange between the cold fluid and the hot rock is considered,and the thermal contribution terms between the cold fluid and the hot rock are derived.Heat transfer obeys Fourier's law,and porosity is used to relate the thermodynamic parameters of the fracture and matrix domains.The net pressure difference between the fracture and the matrix is neglected,and thus the fluid flow is modeled by the unified fluid-governing equations.The evolution equations of porosity and Biot's coefficient during hydraulic fracturing are derived from their definitions.The effect of coal cleats is considered and modeled by Voronoi polygons,and this approach is shown to have high accuracy.The accuracy of the proposed model is verified by two sets of fracturing experiments in multilayer coal seams.Subsequently,the differences in fracture morphology,fluid pressure response,and fluid pressure distribution between direct fracturing of coal seams and indirect fracturing of shale interlayers are explored,and the effects of the cluster number and cluster spacing on fracture morphology for multi-cluster fracturing are also examined.The numerical results show that the proposed model is expected to be a powerful tool for the fracturing design and optimization of deep coalbed methane.
基金Fund supported this work for Excellent Youth Scholars of China(Grant No.52222708)the National Natural Science Foundation of China(Grant No.51977007)+1 种基金Part of this work is supported by the research project“SPEED”(03XP0585)at RWTH Aachen Universityfunded by the German Federal Ministry of Education and Research(BMBF)。
文摘Developing sensorless techniques for estimating battery expansion is essential for effective mechanical state monitoring,improving the accuracy of digital twin simulation and abnormality detection.Therefore,this paper presents a data-driven approach to expansion estimation using electromechanical coupled models with machine learning.The proposed method integrates reduced-order impedance models with data-driven mechanical models,coupling the electrochemical and mechanical states through the state of charge(SOC)and mechanical pressure within a state estimation framework.The coupling relationship was established through experimental insights into pressure-related impedance parameters and the nonlinear mechanical behavior with SOC and pressure.The data-driven model was interpreted by introducing a novel swelling coefficient defined by component stiffnesses to capture the nonlinear mechanical behavior across various mechanical constraints.Sensitivity analysis of the impedance model shows that updating model parameters with pressure can reduce the mean absolute error of simulated voltage by 20 mV and SOC estimation error by 2%.The results demonstrate the model's estimation capabilities,achieving a root mean square error of less than 1 kPa when the maximum expansion force is from 30 kPa to 120 kPa,outperforming calibrated stiffness models and other machine learning techniques.The model's robustness and generalizability are further supported by its effective handling of SOC estimation and pressure measurement errors.This work highlights the importance of the proposed framework in enhancing state estimation and fault diagnosis for lithium-ion batteries.
文摘Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems,shaped by the complex interactions of thermal,hydraulic,mechanical and chemical(THMC)fields.This paper presents a systematic review of this subject with special emphasis on the multi-physics governing it.First,we elucidate the interdependent mechanisms and governing equations,highlighting the nonlinear,path-dependent,and evolving nature of the relationship between stress and permeability.Next,mainstream modeling approaches,including equivalent continuum,discrete fracture network(DFN),and dual-porosity/dual-permeability methods,are critically evaluated,and a strategy for model selection based on project scale and geological context is proposed accordingly.Moreover,experimental insights from single-fracture and triaxial flow studies are synthesized,revealing how effective stress,shear displacement,and fracture roughness control permeability evolution.In particular,the practical significance of THMC coupling is demonstrated through case studies on nuclear waste disposal,Enhanced Geothermal Systems,and tunneling projects.The reviewfurther explores AI-and machine learning-driven innovations,particularly physics-informed neural networks and hybrid modeling,which address limitations in computational efficiency,data scarcity,and physical consistency.Finally,persistent challenges,including multi-scale coupling,parameter uncertainty,and complex fracture network representation are identified and critically discussed while paying attention to future developments.
基金supported by the National Key R&D Program of China(No.2021YFB2011300)the National Natural Science Foundation of China(Nos.52275044,U2233212)。
文摘The Electro–Hydrostatic Actuator(EHA)is applied to drive the control surface in flightcontrol system of more electric aircraft.In EHA,the Oil-Immersed Motor Pump(OMP)serves asthe core as a power assembly.However,the compact integration of the OMP presents challenges inefficiently dissipating internal heat,leading to a performance degradation of the EHA due to ele-vated temperatures.Therefore,accurately modeling and predicting the internal thermal dynamicsof the OMP hold considerable significance for monitoring the operational condition of the EHA.In view of this,a modeling method considering cumulative thermal coupling was hereby proposed.Based on the proposed method,the thermal models of the motor and the pump were established,taking into account heat accumulation and transfer.Taking the leakage oil as the heat couplingpoint between the motor and the pump,the dynamic thermal coupling model of the OMP wasdeveloped,with the thermal characteristics of the oil considered.Additionally,the comparativeexperiments were conducted to illustrate the efficiency of the proposed model.The experimentalresults demonstrate that the proposed dynamic thermal coupling model accurately captured thethermal behavior of OMP,outperforming the static thermal parameter model.Overall,thisadvancement is crucial for effectively monitoring the health of EHA and ensuring flight safety.
基金supported by the National Natural Science Foundation of China(Grant No.42076214)Natural Science Foundation of Shandong Province(Grant No.ZR2024QD057).
文摘Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.
基金a U.S. Federal Railroad Administration (FRA)BAA project,titled “Mitigation of Differential Movement at Railway Transitions for High-Speed Passenger Rail and Joint Passenger/Freight Corridors”the financial support provided by the China Scholarship Council (CSC),which funded Zhongyi Liu’s and Wenjing Li’s time and research efforts for this study
文摘Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.
基金supported by the Major Research Instrument Development Project of the National Natural Science Foundation of China(82327810)the Foundation of the President of Hebei University(XZJJ202202)the Hebei Province“333 talent project”(A202101058).
文摘Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
基金The National Key Research and Development Program of China under contract Nos 2024YFF0808900,2023YFF0805300,and 2020YFA0608804the Civilian Space Programme of China under contract No.D040305.
文摘The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes in ENSO forecasts,resulting in significant progress.Most deep learning-based ENSO prediction models which primarily rely solely on reanalysis data may lead to challenges in intensity underestimation in long-term forecasts,reducing the forecasting skills.To this end,we propose a deep residual-coupled model prediction(Res-CMP)model,which integrates historical reanalysis data and coupled model forecast data for multiyear ENSO prediction.The Res-CMP model is designed as a lightweight model that leverages only short-term reanalysis data and nudging assimilation prediction results of the Community Earth System Model(CESM)for effective prediction of the Niño 3.4 index.We also developed a transfer learning strategy for this model to overcome the limitations of inadequate forecast data.After determining the optimal configuration,which included selecting a suitable transfer learning rate during training,along with input variables and CESM forecast lengths,Res-CMP demonstrated a high correlation ability for 19-month lead time predictions(correlation coefficients exceeding 0.5).The Res-CMP model also alleviated the spring predictability barrier(SPB).When validated against actual ENSO events,Res-CMP successfully captured the temporal evolution of the Niño 3.4 index during La Niña events(1998/99 and 2020/21)and El Niño events(2009/10 and 2015/16).Our proposed model has the potential to further enhance ENSO prediction performance by using coupled models to assist deep learning methods.
基金supported by the National Natural Science Foundation of China(Nos.12005025,41774190).
文摘To perform an integral simulation of a pool-type reactor using CFD code,a multi-physics coupled code MPC-LBE for an LBE-cooled reactor was proposed by integrating a point kinetics model and a fuel pin heat transfer model into self-developed CFD code.For code verification,a code-to-code comparison was employed to validate the CFD code.Furthermore,a typical BT transient benchmark on the LBE-cooled XADS reactor was selected for verification in terms of the integral or system performance.Based on the verification results,it was demonstrated that the MPC-LBE coupled code can perform thermal-hydraulics or safety analyses for analysis for processes involved in LBE-cooled pool-type reactors.
