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
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
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
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
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
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
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
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
To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and ...To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and the pavement.According to the Timoshenko beam theory,a dynamic model of pavement structure with a finite length beam was formulated on a nonlinear Pasternak foundation.To more accurately describe the coupling relationship between the tire and the pavement,and to take into account the vibration state under vehicle-pavement interaction,the load distribution between the tire and the pavement is modeled as a dynamic non-uniform contact.Combined with the classic LuGre tire model,the adhesion between the tire and the pavement is calculated.The Galerkin truncation method is employed to transform the pavement vibration partial differential equation into a finite ordinary differential equation,and the integral expression of the nonlinear foundation beam term is derived using the product to sum formula.By using the Runge-Kutta method,the tire-road coupled system can be numerically calculated,thus determining tire adhesion.This research demonstrates that compared with tire force under the traditional static load distribution,load distribution has a significant influence on adhesion.This study offers valuable insights for pavement structure design and vehicle performance control.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
This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and o...This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and ocean components of the coupled system are represented by the China Meteorological Administration’s Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS)and the LASG/IAP Climate system Ocean Model(LICOM),respectively.The Ocean Atmosphere Sea Ice Soil VersionH 3(OASIS3)software has been utilized for the exchange of momentum,heat,and freshwater fluxes between these two components.An assessment of the coupled model’s three-day predictions for five TCs’gales was conducted.Preliminary findings indicate that the predicted TC tracks show less sensitivity to oceanic influences than the predicted TC intensities.Significant improvement in predicting the surface TC gales has been achieved through coupling the ocean model.This improvement is attributed to the impact of the warmer ocean’s effect on TC intensification,counteracting the cooling effect of the cold wake.In summary,coupling has enhanced the model’s predictive capabilities for TC gales.A detailed assessment of the coupled model’s performance in predicting other tropical weather phenomena is forthcoming.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
Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this st...Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.展开更多
This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3...This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3SMv2-MPAS)at 60 km to 10 km resolution.Multi-source observational data are utilized to validate sea surface temperature/salinity,sea ice,three-dimensional thermal-saline structures,mixed layer depth,ocean heat content,and sea surface height.Key results show the following:(1)E3SMv2-MPAS captures seasonal-to-decadal variability in surface fields and sea ice,but shows systematic biases in sea surface temperature of western boundary currents(inadequate eddy parameterization)and Arctic sea surface salinity(misrepresented freshwater fluxes and mixing processes).(2)The model robustly represents three-dimensional climate variability,yet underestimates mixed layer depth in key regions(Antarctic Circumpolar Current and North Atlantic),revealing deficiencies in extreme mixing.(3)Ocean heat content distributions are well-simulated.(4)Sea surface height spatial patterns and interannual variability are accurately reproduced.This work identifies critical refinements for unstructured-mesh models:mesoscale eddy parameterization,polar ocean-sea ice coupling,and multi-scale energy processes,advancing high-resolution climate model development and laying the groundwork for improved ocean forecasting systems.展开更多
This study presents a fully coupled thermo-hydro-mechanical (THM) constitutive model for clay rocks. The model is formulated within the elastic-viscoplasticity framework, which considers nonlinearity and softening aft...This study presents a fully coupled thermo-hydro-mechanical (THM) constitutive model for clay rocks. The model is formulated within the elastic-viscoplasticity framework, which considers nonlinearity and softening after peak strength, anisotropy of stiffness and strength, as well as permeability variation due to damage. In addition, the mechanical properties are coupled with thermal phenomena and accumulated plastic strains. The adopted nonlocal and viscoplastic approaches enhance numerical efficiency and provide the possibility to simulate localization phenomena. The model is validated against experimental data from laboratory tests conducted on Callovo-Oxfordian (COx) claystone samples that are initially unsaturated and under suction. The tests include a thermal phase where the COx specimens are subjected to different temperature increases. A good agreement with experimental data is obtained. In addition, parametric analyses are carried out to investigate the influence of the hydraulic boundary conditions (B.C.) and post-failure behavior models on the THM behavior evolution. It is shown that different drainage conditions affect the thermally induced pore pressures that, in turn, influence the onset of softening. The constitutive model presented constitutes a promising approach for simulating the most important features of the THM behavior of clay rocks. It is a tool with a high potential for application to several relevant case studies, such as thermal fracturing analysis of nuclear waste disposal systems.展开更多
Cold regions often feature complex geological environments where various physical phenomena interact,with a particularly notable thermo-hydro-mechanical(THM)coupling.In this study,fully coupled THM cyclic tests were c...Cold regions often feature complex geological environments where various physical phenomena interact,with a particularly notable thermo-hydro-mechanical(THM)coupling.In this study,fully coupled THM cyclic tests were conducted,followed by fatigue tests,to explore how THM treatment influences the fatigue properties of damaged sandstone.Experimental results indicate that rock fatigue deformation,damage evolution,and failure characteristics are highly sensitive to initial damage caused by coupled THM treatment.Rocks subjected to multiple THM cycles exhibit lower initial irreversible strain,shorter fatigue life,lower critical total dissipated energy,and higher irreversible strain increments,indicating accelerated deterioration.After THM coupling,rock fatigue failure shows complex crack networks,with macroscopic failure modes shifting from shear to tensile failure.Polarized microscopy and acoustic emission analyses reveal that this transition stems from micro-scale transgranular to intergranular fractures.We introduced a fractional order-based damage fatigue model to quantitatively describe the rock viscoelastic parameters after different initial damage treatments.Rock viscoelastic-plastic parameters decrease with increasing coupled THM cycles.Finally,we discussed the feasibility of applying these results to the long-term stability analysis of rock slopes.This study provides unique insights and modeling tools from fully coupled THM experiments to understand the rock fatigue characteristics,offering potential applications for slope stability assessment.展开更多
Considering the influence of hydrogen gas generated during electrochemical machining on the conductivity of electrolyte, a two-phase turbulent flow model is presented to describe the gas bubbles distribution.The k-e t...Considering the influence of hydrogen gas generated during electrochemical machining on the conductivity of electrolyte, a two-phase turbulent flow model is presented to describe the gas bubbles distribution.The k-e turbulent model is used to describe the electrolyte flow field.The Euler–Euler model based on viscous drag and pressure force is used to calculate the twodimensional distribution of gas volume fraction.A multi-physics coupling model of electric field,two-phase flow field and temperature field is established and solved by weak coupling iteration method.The numerical simulation results of gas volume fraction, temperature and conductivity in equilibrium state are discussed.The distributions of machining gap at different time are analyzed.The predicted results of the machining gap are consistent with the experimental results, and the maximum deviation between them is less than 50 lm.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
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.
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.
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.
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 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.
基金financially supported by the National Natural Science Foundation of China(Grant No.12072204).
文摘To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and the pavement.According to the Timoshenko beam theory,a dynamic model of pavement structure with a finite length beam was formulated on a nonlinear Pasternak foundation.To more accurately describe the coupling relationship between the tire and the pavement,and to take into account the vibration state under vehicle-pavement interaction,the load distribution between the tire and the pavement is modeled as a dynamic non-uniform contact.Combined with the classic LuGre tire model,the adhesion between the tire and the pavement is calculated.The Galerkin truncation method is employed to transform the pavement vibration partial differential equation into a finite ordinary differential equation,and the integral expression of the nonlinear foundation beam term is derived using the product to sum formula.By using the Runge-Kutta method,the tire-road coupled system can be numerically calculated,thus determining tire adhesion.This research demonstrates that compared with tire force under the traditional static load distribution,load distribution has a significant influence on adhesion.This study offers valuable insights for pavement structure design and vehicle performance control.
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 Key R&D Program of China [grant number 2023YFC3008005]the Guangdong Basic and Applied Basic Research Foundation [grant numbers 2022A1515011288 and 2024A1515030210]+1 种基金the Key Innovation Team of the China Meteorological Administration [grant number CMA2023ZD08]the Guangdong Provincial Marine Meteorology Science Data Center [grant number 2024B1212070014]。
文摘This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and ocean components of the coupled system are represented by the China Meteorological Administration’s Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS)and the LASG/IAP Climate system Ocean Model(LICOM),respectively.The Ocean Atmosphere Sea Ice Soil VersionH 3(OASIS3)software has been utilized for the exchange of momentum,heat,and freshwater fluxes between these two components.An assessment of the coupled model’s three-day predictions for five TCs’gales was conducted.Preliminary findings indicate that the predicted TC tracks show less sensitivity to oceanic influences than the predicted TC intensities.Significant improvement in predicting the surface TC gales has been achieved through coupling the ocean model.This improvement is attributed to the impact of the warmer ocean’s effect on TC intensification,counteracting the cooling effect of the cold wake.In summary,coupling has enhanced the model’s predictive capabilities for TC gales.A detailed assessment of the coupled model’s performance in predicting other tropical weather phenomena is forthcoming.
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jointly funded by the National Natural Science Foundation of China(NSFC)[grant number 42130608]the China Postdoctoral Science Foundation[grant number 2024M753169]。
文摘Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.
基金The National Key R&D Program of China under contract No.2021YFC3101503the Science and Technology Innovation Program of Hunan Province under contract No.2022RC3070+1 种基金the National Natural Science Foundation of China under contract Nos 42305176 and 42276205the Hunan Provincial Natural Science Foundation of China under contract No.2023JJ10053.
文摘This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3SMv2-MPAS)at 60 km to 10 km resolution.Multi-source observational data are utilized to validate sea surface temperature/salinity,sea ice,three-dimensional thermal-saline structures,mixed layer depth,ocean heat content,and sea surface height.Key results show the following:(1)E3SMv2-MPAS captures seasonal-to-decadal variability in surface fields and sea ice,but shows systematic biases in sea surface temperature of western boundary currents(inadequate eddy parameterization)and Arctic sea surface salinity(misrepresented freshwater fluxes and mixing processes).(2)The model robustly represents three-dimensional climate variability,yet underestimates mixed layer depth in key regions(Antarctic Circumpolar Current and North Atlantic),revealing deficiencies in extreme mixing.(3)Ocean heat content distributions are well-simulated.(4)Sea surface height spatial patterns and interannual variability are accurately reproduced.This work identifies critical refinements for unstructured-mesh models:mesoscale eddy parameterization,polar ocean-sea ice coupling,and multi-scale energy processes,advancing high-resolution climate model development and laying the groundwork for improved ocean forecasting systems.
基金funded by the European Union's Horizon 2020 research and innovation programme under a grant agreement (Grant No.847593)partially supported by the Fundamental Research Funds for the Central Universities (Grant No.22120240029).
文摘This study presents a fully coupled thermo-hydro-mechanical (THM) constitutive model for clay rocks. The model is formulated within the elastic-viscoplasticity framework, which considers nonlinearity and softening after peak strength, anisotropy of stiffness and strength, as well as permeability variation due to damage. In addition, the mechanical properties are coupled with thermal phenomena and accumulated plastic strains. The adopted nonlocal and viscoplastic approaches enhance numerical efficiency and provide the possibility to simulate localization phenomena. The model is validated against experimental data from laboratory tests conducted on Callovo-Oxfordian (COx) claystone samples that are initially unsaturated and under suction. The tests include a thermal phase where the COx specimens are subjected to different temperature increases. A good agreement with experimental data is obtained. In addition, parametric analyses are carried out to investigate the influence of the hydraulic boundary conditions (B.C.) and post-failure behavior models on the THM behavior evolution. It is shown that different drainage conditions affect the thermally induced pore pressures that, in turn, influence the onset of softening. The constitutive model presented constitutes a promising approach for simulating the most important features of the THM behavior of clay rocks. It is a tool with a high potential for application to several relevant case studies, such as thermal fracturing analysis of nuclear waste disposal systems.
基金supported by the National Natural Science Foundation of China(Grant No.42372326)supported by the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project(Grant No.SKLGP2023Z015)supported by the Sichuan Science and Technology Program(Grant No.2024YFFK0416).
文摘Cold regions often feature complex geological environments where various physical phenomena interact,with a particularly notable thermo-hydro-mechanical(THM)coupling.In this study,fully coupled THM cyclic tests were conducted,followed by fatigue tests,to explore how THM treatment influences the fatigue properties of damaged sandstone.Experimental results indicate that rock fatigue deformation,damage evolution,and failure characteristics are highly sensitive to initial damage caused by coupled THM treatment.Rocks subjected to multiple THM cycles exhibit lower initial irreversible strain,shorter fatigue life,lower critical total dissipated energy,and higher irreversible strain increments,indicating accelerated deterioration.After THM coupling,rock fatigue failure shows complex crack networks,with macroscopic failure modes shifting from shear to tensile failure.Polarized microscopy and acoustic emission analyses reveal that this transition stems from micro-scale transgranular to intergranular fractures.We introduced a fractional order-based damage fatigue model to quantitatively describe the rock viscoelastic parameters after different initial damage treatments.Rock viscoelastic-plastic parameters decrease with increasing coupled THM cycles.Finally,we discussed the feasibility of applying these results to the long-term stability analysis of rock slopes.This study provides unique insights and modeling tools from fully coupled THM experiments to understand the rock fatigue characteristics,offering potential applications for slope stability assessment.
基金funded by the National Natural Science Foundation of China(Nos.51775161 and 51775158)。
文摘Considering the influence of hydrogen gas generated during electrochemical machining on the conductivity of electrolyte, a two-phase turbulent flow model is presented to describe the gas bubbles distribution.The k-e turbulent model is used to describe the electrolyte flow field.The Euler–Euler model based on viscous drag and pressure force is used to calculate the twodimensional distribution of gas volume fraction.A multi-physics coupling model of electric field,two-phase flow field and temperature field is established and solved by weak coupling iteration method.The numerical simulation results of gas volume fraction, temperature and conductivity in equilibrium state are discussed.The distributions of machining gap at different time are analyzed.The predicted results of the machining gap are consistent with the experimental results, and the maximum deviation between them is less than 50 lm.
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.
