Hydraulic stimulation technology is widely employed to enhance the permeability of geothermal reservoirs.Nevertheless,accurately predicting hydraulic fracture propagation in complex geological conditions remains chall...Hydraulic stimulation technology is widely employed to enhance the permeability of geothermal reservoirs.Nevertheless,accurately predicting hydraulic fracture propagation in complex geological conditions remains challenging,thereby hindering the effective utilization of existing natural fractures.In this study,a phase field model was developed utilizing the finite element method to examine the influence of fluid presence,stress conditions,and natural fractures on the initiation and propagation of hydraulic fractures.The model employs Biot's poroelasticity theory to establish the coupling between the displacement field and the fluid field,while the phase field theory is applied to simulate fracture behavior.The results show that whenσ_(x0)/σ_(y0)<3 or qf<20 kg/(m^(3)·s),the presence of natural fractures can alter the original propagation direction of hydraulic fractures.Conversely,in the absence of these conditions,the propagation path of natural fractures is predominantly influenced by the initial stress field.Furthermore,based on the analysis of breakdown pressure and damage area,the optimal intersection angle between natural fractures and hydraulic fractures is determined to range from 45°to 60°.Finally,once a dominant channel forms,initiating and propagating hydraulic fractures in other directions becomes increasingly difficult,even in highly fractured areas.This method tackles the challenges of initiating and propagating hydraulic fractures in complex geological conditions,providing a theoretical basis for optimizing Enhanced Geothermal System(EGS)projects.展开更多
To accelerate the practicality of electromagnetic railguns,it is necessary to use a combination of threedimensional numerical simulation and experiments to study the mechanism of bore damage.In this paper,a three-dime...To accelerate the practicality of electromagnetic railguns,it is necessary to use a combination of threedimensional numerical simulation and experiments to study the mechanism of bore damage.In this paper,a three-dimensional numerical model of the augmented railgun with four parallel unconventional rails is introduced to simulate the internal ballistic process and realize the multi-physics field coupling calculation of the rail gun,and a test experiment of a medium-caliber electromagnetic launcher powered by pulse formation network(PFN)is carried out.Various test methods such as spectrometer,fiber grating and high-speed camera are used to test several parameters such as muzzle initial velocity,transient magnetic field strength and stress-strain of rail.Combining the simulation results and experimental data,the damage condition of the contact surface is analyzed.展开更多
A numerical model coupled with a multi-physical field based on dynamic formation of slag skin is established.After validation by comparing the experimental and simulation results of depth of metal pool,slag skin thick...A numerical model coupled with a multi-physical field based on dynamic formation of slag skin is established.After validation by comparing the experimental and simulation results of depth of metal pool,slag skin thickness and melt rate,it is utilized to investigate the effect of melt current on the coupled multi-physical field,slag skin thickness,metal pool depth and the heat flow distribution during electroslag remelting(ESR)Inconel 625 solidification process.The results showed that with the increase in the melt current,the velocities of ESR system and the temperature of metal pool increased,whereas the highest temperature of slag bath firstly decreased and then increased.With the increase in the melt current,the slag skin thickness,metal pool depth and melt rate increased.Furthermore,the characteristics of the heat flow distribution and the effect of melt current on the heat flow distribution were analysed.展开更多
Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these i...Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.展开更多
The movement of global ocean circulation in the Earth’s main magnetic field generates a measurable induced magnetic field(about 2 nT at geomagnetic satellite altitudes).However,this ocean circulation-induced magnetic...The movement of global ocean circulation in the Earth’s main magnetic field generates a measurable induced magnetic field(about 2 nT at geomagnetic satellite altitudes).However,this ocean circulation-induced magnetic field has not been previously estimated or incorporated into geomagnetic field models,potentially causing leakage into the core field model.Here,we present a method to account for the circulation-induced magnetic field during geomagnetic field modeling.First,a forward model of the circulation-induced magnetic field is constructed by numerically solving electromagnetic induction equations based on a realistic ocean circulation model.Then,this forward model is subtracted from the observed data.Finally,the core and lithospheric fields,magnetospheric and Earth’s mantle-induced fields,and the ocean tide-induced magnetic field are co-estimated.Applying our method to over 20 years of MSS-1,Swarm,CryoSat-2,and CHAMP satellite magnetic data,we derive a new multisource geomagnetic field model(MGFM).We find that incorporating a forward model of the circulation-induced magnetic field marginally improves the fit to the data.Furthermore,we demonstrate that neglecting the circulation-induced magnetic field in geomagnetic field modeling results in leakage into the core field model.The highlights of the MGFM model include:(i)a good agreement with the widely used CHAOS model series;(ii)the incorporation of magnetic fields induced by both ocean tides and circulation;and(iii)the suppression of leakage of the circulation-induced magnetic field into the core field model.展开更多
The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is great...The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.展开更多
It is well known that coarse-grained super-elastic NiTi shape memory alloys(SMAs)exhibit localized rather than homogeneous martensite transformation(MT),which,however,can be strongly influenced by either internal size...It is well known that coarse-grained super-elastic NiTi shape memory alloys(SMAs)exhibit localized rather than homogeneous martensite transformation(MT),which,however,can be strongly influenced by either internal size(grain size,GS)or the external size(geometric size).The coupled effect of GS and geometric size on the functional properties has not been clearly understood yet.In this work,the super-elasticity,one-way,and stress-assisted two-way shape memory effects of the polycrystalline NiTi SMAs with different aspect ratios(length/width for the gauge section)and different GSs are investigated based on the phase field method.The coupled effect of the aspect ratio and GS on the functional properties is adequately revealed.The simulated results indicate that when the aspect ratio is lower than about 4:1,the stress biaxiality and stress heterogeneity in the gauge section of the sample become more and more obvious with decreasing the aspect ratio,which can significantly influence the microstructure evolution in the process involving external stress.Therefore,the corresponding functional property is strongly dependent on the aspect ratio.With decreasing the GS and the aspect ratio(to be lower than 4:1),both the aspect ratio and GS can affect the MT or martensite reorientation in each grain and the interaction among grains.Thus,due to the strong internal constraint(i.e.,the constraint of grain boundary)and the external constraint(i.e.,the constraint of geometric boundary),the capabilities of the functional properties of NiTi SMAs are gradually weakened and highly dependent on these two factors.展开更多
The smelting reduction process of the ilmenite in an electric arc furnace(EAF)is a commonly used technology for producing titanium slag in the world.It has particular significance to analyze the velocity-temperature-e...The smelting reduction process of the ilmenite in an electric arc furnace(EAF)is a commonly used technology for producing titanium slag in the world.It has particular significance to analyze the velocity-temperature-electromagnetics multi-physical field in an EAF for improving its productivity and reducing energy consumption.A transient three-dimensional mathematical model was developed to characterize the flow,heat transfer,and electromagnetic behavior in a titanium slag EAF.For describing the electromagnetic field and its effects on velocity and temperature distribution in the furnace,magnetohydrodynamic equations and conservation equations for mass,momentum,and energy were solved simultaneously by compiling the user-defined function program.The numerical model was verified by comparing with the literature data.The results indicate that the Lorentz force is the main driving force of the velocity and temperature distribution.Moreover,the influence of input current and location of electrodes on the multi-physical field distribution was also investigated.It is found that the appropriate range of input current and diameter of pitch circle are about 30,000 A and 3000-3500 mm,respectively.The mathematical model established can characterize the multi-physical field more accu-rately than before,which can provide valuable guidance for the operation improvement and design optimization of the EAF for producing titanium slag.展开更多
By combining data from the Challenging Minisatellite Payload(CHAMP),Swarm-A,and newest Macao Science Satellite-1(MSS-1) missions,we constructed a lithospheric magnetic field model up to spherical harmonic degree N = 1...By combining data from the Challenging Minisatellite Payload(CHAMP),Swarm-A,and newest Macao Science Satellite-1(MSS-1) missions,we constructed a lithospheric magnetic field model up to spherical harmonic degree N = 100.To isolate the lithospheric magnetic field signals,we utilized the latest CHAOS-8(CHAMP,Φrsted,and SAC-C 8) model and MGFM(Multisource Geomagnetic Field Model) to remove nonlithospheric sources,including the core field,magnetospheric field,ocean tidal field,and ocean circulation field.Subsequently,orbit-by-orbit processing was applied to both scalar and vector data,such as spherical harmonic high-pass filtering,singular spectrum analysis,and line leveling,to suppress noise and residual signals along the satellite tracks.With an orbital inclination of only 41°,MSS-1 effectively captures fine-scale lithospheric magnetic field signals in mid-to low-latitude regions.Its data exhibit a root mean square error of only 0.77 nT relative to the final model,confirming the high quality and utility of lithospheric field modeling.The resulting model exhibits excellent consistency with the MF7(Magnetic Field Model 7),maintaining a high correlation up to N = 90 and still exceeding 0.65 at N = 100.These results demonstrate the reliability and value of MSS-1 data in global lithospheric magnetic field modeling.展开更多
The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.Howeve...The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.However,the inversion for the ES model suffers from nonuniqueness and instability,which remain unresolved.To mitigate these issues,we introduce both the minimum and flattest models into the model objective function as an alternative regularization approach in the spherical ES method.We first present the methods,then analyze the accuracy of forward calculation and test the proposed ES method in this study by using synthetic data.The experimental results from simulation data indicate that our proposed regularization effectively suppresses the Backus effect and mitigates inversion instability in the low-latitude region.Finally,we apply the proposed method to magnetic anomaly data from China Seismo-Electromagnetic Satellite-1(CSES-1)and Macao Science Satellite-1(MSS-1)magnetic measurements over Africa by constructing an ES model of the large-scale lithospheric magnetic field.Compared with existing global lithospheric magnetic field models,our ES model demonstrates good consistency at high altitudes and predicts more stable fields at low altitudes.Furthermore,we derive the reduction to the pole(RTP)magnetic anomaly fields and the apparent susceptibility contrast distribution based on the ES model.The latter correlates well with the regional tectonic framework in Africa and surroundings.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
As the demand for advanced material design and performance prediction continues to grow,traditional phase-field models are increasingly challenged by limitations in computational efficiency and predictive accuracy,par...As the demand for advanced material design and performance prediction continues to grow,traditional phase-field models are increasingly challenged by limitations in computational efficiency and predictive accuracy,particularly when addressing high-dimensional and complex data in multicomponent systems.To overcome these challenges,this study proposes an innovative model,LSGWO-BP,which integrates an improved Grey Wolf Optimizer(GWO)with a backpropagation neural network(BP)to enhance the accuracy and efficiency of quasi-phase equilibrium predictions within the KKS phase-field framework.Three mapping enhancement strategies were investigated–Circle-Root,Tent-Cosine,and Logistic-Sine mappings-with the Logistic mapping further improved via Sine perturbation to boost global search capability and convergence speed in large-scale,complex data scenarios.Evaluation results demonstrate that the LSGWO-BP model significantly outperforms conventional machine learning approaches in predicting quasi-phase equilibrium,achieving a 14%–28%reduction in mean absolute error(MAE).Substantial improvements were also observed in mean squared error,root mean squared error,and mean absolute percentage error,alongside a 7%–33%increase in the coefficient of determination(R2).Furthermore,the model exhibits strong potential for microstructural simulation applications.Overall,the study confirms the effectiveness of the LSGWO-BP model in materials science,especially in enhancing phase-field modeling efficiency and enabling accurate,intelligent prediction for multicomponent alloy systems,thereby offering robust support for microstructure prediction and control.展开更多
Machine learning(ML)techniques have emerged as powerful tools for improving the predictive capabilities of Reynolds-averaged Navier-Stokes(RANS)turbulence models in separated flows.This improvement is achieved by leve...Machine learning(ML)techniques have emerged as powerful tools for improving the predictive capabilities of Reynolds-averaged Navier-Stokes(RANS)turbulence models in separated flows.This improvement is achieved by leveraging complex ML models,such as those developed using field inversion and machine learning(FIML),to dynamically adjust the constants within the baseline RANS model.However,the ML models often overlook the fundamental calibrations of the RANS turbulence model.Consequently,the basic calibration of the baseline RANS model is disrupted,leading to a degradation in the accuracy,particularly in basic wall-attached flows outside of the training set.To address this issue,a modified version of the Spalart-Allmaras(SA)turbulence model,known as Rubber-band SA(RBSA),has been proposed recently.This modification involves identifying and embedding constraints related to basic wall-attached flows directly into the model.It is shown that no matter how the parameters of the RBSA model are adjusted as constants throughout the flow field,its accuracy in wall-attached flows remains unaffected.In this paper,we propose a new constraint for the RBSA model,which better safeguards the law of wall in extreme conditions where the model parameter is adjusted dramatically.The resultant model is called the RBSA-poly model.We then show that when combined with FIML augmentation,the RBSA-poly model effectively preserves the accuracy of simple wall-attached flows,even when the adjusted parameters become functions of local flow variables rather than constants.A comparative analysis with the FIML-augmented original SA model reveals that the augmented RBSA-poly model reduces error in basic wall-attached flows by 50%while maintaining comparable accuracy in trained separated flows.These findings confirm the effectiveness of utilizing FIML in conjunction with the RBSA model,offering superior accuracy retention in cardinal flows.展开更多
The nonlinear traveling wave vibration of rotating ferromagnetic functionally graded(FG)cylindrical shells under multi-physics fields is investigated.Grounded in the Kirchhoff-Love thin shell theory,the geometric nonl...The nonlinear traveling wave vibration of rotating ferromagnetic functionally graded(FG)cylindrical shells under multi-physics fields is investigated.Grounded in the Kirchhoff-Love thin shell theory,the geometric nonlinearity is incorporated into the model,and the constitutive equations are derived.The physical parameters of functionally graded materials(FGMs),which exhibit continuous variation across the thickness gradient,are of particular interest.The nonlinear magneto-thermoelastic governing equations are derived in accord with Hamilton's principle.The nonlinear partial differential equations are discretized with the Galerkin method,and the analytical expression of traveling wave frequencies is derived with an approximate method.The accuracy of the proposed method is validated through the comparison with the results from the literature and numerical solutions.Finally,the visualization analyses are conducted to examine the effects of key parameters on the traveling wave frequencies.The results show that the factors including the power-law index,temperature,magnetic field intensity,and rotating speed have the coupling effects with respect to the nonlinear vibration behavior.展开更多
Reducing coke use is an effective measure to reduce carbon emission and energy consumption in the blast furnace(BF)ironmaking.Essentially,BF is a high-temperature moving bed reactor,where complex physical transformati...Reducing coke use is an effective measure to reduce carbon emission and energy consumption in the blast furnace(BF)ironmaking.Essentially,BF is a high-temperature moving bed reactor,where complex physical transformations coupled with complicated reactions occur.This makes it challenging to investigate the factors determining BF performance with the conventional method.A multi-physical field coupling mathematical model of BF was thus developed to describe its mass and heat transfer as well as its intrinsic reactions.Then,the proposed model was validated with the production data.Under coupling conditions,influences of dominating reactions on BF performance(temperature distribution,gas distribution,iron formation reaction,and direct reduction degree)were revealed.The results indicated that coke combustion,indirect reduction,and direct reduction of iron ore mainly took place nearby the shaft tuyere,cohesive zone,and dripping zone,respectively.Besides,the rate of coke solution loss reaction was increased with the rising coke porosity in the cohesive zone.Considering the effect of coke porosity on the efficiency and stability of BF,the coke porosity of 0.42 was regarded as a reasonable value.展开更多
The Earth's magnetic field,which has been extensively observed from ground to satellite altitudes over several decades,originates from multiple sources,such as the core dynamo,the conductive mantle,the magnetized ...The Earth's magnetic field,which has been extensively observed from ground to satellite altitudes over several decades,originates from multiple sources,such as the core dynamo,the conductive mantle,the magnetized lithosphere,and the space current systems.Modeling of the lithospheric contribution plays an important role in the geophysical studies and industrial applications.In this paper,we propose a new method for global and regional modeling of the lithospheric magnetic field based on the cubed-sphere.An equivalent dipole source method on a quasi-uniform cubed-sphere grid is employed in the forward modeling.The dipole directions are fixed according to a priori magnetization and the relative intensities are estimated by an inversion procedure of least-squares fitting with minimum model regularization.Several numerical tests are performed to validate the accuracy and efficiency of both forward modeling and inversion procedure.The proposed method is applied to the global and regional modeling based on the latest magnetic data from Swarm Alpha satellite and MSS-1 mission.The model results indicate that the proposed method works quite well for realistic satellite data and MSS-1 data is consistent with the Swarm data in terms of lithospheric field modeling.展开更多
With the intelligent transformation of process manufacturing,accurate and comprehensive perception information is fundamental for application of artificial intelligence methods.In zinc smelting,the fluidized bed roast...With the intelligent transformation of process manufacturing,accurate and comprehensive perception information is fundamental for application of artificial intelligence methods.In zinc smelting,the fluidized bed roaster is a key piece of large-scale equipment and plays a critical role in the manufacturing industry;its internal temperature field directly determines the quality of zinc calcine and other related products.However,due to its vast spatial dimensions,the limited observation methods,and the complex multiphase,multifield coupled reaction atmosphere inside it,accurately and timely perceiving its temperature field remains a significant challenge.To address these challenges,a spatial-temporal reduced-order model(STROM)is proposed,which can realize fast and accurate temperature field perception based on sparse observation data.Specifically,to address the difficulty in matching the initial physical field with the sparse observation data,an initial field construction based on data assimilation(IFCDA)method is proposed to ensure that the initial conditions of the model can be matched with the actual operation state,which provides a basis for constructing a high-precision computational fluid dynamics(CFD)model.Then,to address the high simulation cost of high-precision CFD models under full working conditions,a high uniformity(HU)-orthogonal test design(OTD)method with the centered L2 deviation is innovatively proposed to ensure high information coverage of the temperature field dataset under typical working conditions in terms of multiple factors and levels of the component,feed,and blast parameters.Finally,to address the difficulty in real-time and accurate temperature field prediction,considering the spatial correlation between the observed temperature and the temperature field,as well as the dynamic correlation of the observed temperature in the time dimension,a spatial-temporal predictive model(STPM)is established,which realizes rapid prediction of the temperature field through sparse observa-tion data.To verify the accuracy and validity of the proposed method,CFD model validation and reduced-order model prediction experiments are designed,and the results show that the proposed method can realize high-precision and fast prediction of the roaster temperature field under different working conditions through sparse observation data.Compared with the CFD model,the prediction root-mean-square error(RMSE)of STROM is less than 0.038,and the computational efficiency is improved by 3.4184×10^(4)times.In particular,STROM also has a good prediction ability for unmodeled conditions,with a prediction RMSE of less than 0.1089.展开更多
The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive...The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive a global lithospheric magnetic field model. While preparing the datasets for this lithospheric magnetic field model, researchers found that they still contained prominent residual trends within the magnetic anomaly even once signals from other sources had been eliminated. However, no processing was undertaken to deal with the residual trends during modeling to avoid subjective processing and represent the realistic nature of the data. In this work, we analyze the influence of these residual trends on the lithospheric magnetic field modeling.Polynomials of orders 0–3 were used to fit the trend of each track and remove it for detrending. We then derived four models through detrending-based processing, and compared their power spectra and grid maps with those of the CSES original model and CHAOS-7model. The misfit between the model and the dataset decreased after detrending the data, and the convergence of the inverted spherical harmonic coefficients improved. However, detrending reduced the signal strength and the power spectrum, while detrending based on high-order polynomials introduced prominent distortions in details of the magnetic anomaly. Based on this analysis, we recommend along-track detrending by using a zero-order polynomial(removing a constant value) on the CSES magnetic anomaly data to drag its mean value to zero. This would lead to only a slight reduction in the signal strength while significantly improving the stability of the inverted coefficients and details of the anomaly.展开更多
Typhoon Chaba was the most intense typhoon to strike western Guangdong since Typhoon Mujigae in 2015.According to the National Disaster Reduction Center of China,in the morning of July 7,2022,over 1.5 million people i...Typhoon Chaba was the most intense typhoon to strike western Guangdong since Typhoon Mujigae in 2015.According to the National Disaster Reduction Center of China,in the morning of July 7,2022,over 1.5 million people in Guangdong,Guangxi,and Hainan were affected by Typhoon Chaba.The typhoon also caused the“Fukui 001”ship to be in distress in the waters near Yangjiang,Guangdong,on July 2,resulting in big casualties.Studies have indicated that wind field forecast for Typhoon Chaba was not accurate.To better simulate typhoon events and assess their impacts,we proposed the use of a model wind field(Fujita-Takahashi)integrated with the Copernicus Marine and Environmental Monitoring Service(CMEMS)data to reconstruct effectively the overall wind field of Typhoon Chaba.The simulation result aligns well with the observations,particularly at the Dashu Island Station,showing consistent trends in wind speed changes.However,certain limitations were noted.The model shows that the attenuation of wind speed is slower when typhoon neared land than that observed,indicating that the model has a high simulation accuracy for the ocean wind field,but may have deviations near coastal areas.The result is accurate for open sea but deviated for near land due to the land friction effect.Therefore,we recommend to adjust the model to improve the accuracy for near coasts.展开更多
With the growing demand for high-precision flow field simulations in computational science and engineering,the super-resolution reconstruction of physical fields has attracted considerable research interest.However,tr...With the growing demand for high-precision flow field simulations in computational science and engineering,the super-resolution reconstruction of physical fields has attracted considerable research interest.However,tradi-tional numerical methods often entail high computational costs,involve complex data processing,and struggle to capture fine-scale high-frequency details.To address these challenges,we propose an innovative super-resolution reconstruction framework that integrates a Fourier neural operator(FNO)with an enhanced diffusion model.The framework employs an adaptively weighted FNO to process low-resolution flow field inputs,effectively capturing global dependencies and high-frequency features.Furthermore,a residual-guided diffusion model is introduced to further improve reconstruction performance.This model uses a Markov chain for noise injection in phys-ical fields and integrates a reverse denoising procedure,efficiently solved by an adaptive time-step ordinary differential equation solver,thereby ensuring both stability and computational efficiency.Experimental results demonstrate that the proposed framework significantly outperforms existing methods in terms of accuracy and efficiency,offering a promising solution for fine-grained data reconstruction in scientific simulations.展开更多
基金supported by the National Key Research and Development Program(2021YFB150740401)National Natural Science Foundation of China(42202336)the CAS Pioneer Hundred Talents Program in China(Y826031C01)。
文摘Hydraulic stimulation technology is widely employed to enhance the permeability of geothermal reservoirs.Nevertheless,accurately predicting hydraulic fracture propagation in complex geological conditions remains challenging,thereby hindering the effective utilization of existing natural fractures.In this study,a phase field model was developed utilizing the finite element method to examine the influence of fluid presence,stress conditions,and natural fractures on the initiation and propagation of hydraulic fractures.The model employs Biot's poroelasticity theory to establish the coupling between the displacement field and the fluid field,while the phase field theory is applied to simulate fracture behavior.The results show that whenσ_(x0)/σ_(y0)<3 or qf<20 kg/(m^(3)·s),the presence of natural fractures can alter the original propagation direction of hydraulic fractures.Conversely,in the absence of these conditions,the propagation path of natural fractures is predominantly influenced by the initial stress field.Furthermore,based on the analysis of breakdown pressure and damage area,the optimal intersection angle between natural fractures and hydraulic fractures is determined to range from 45°to 60°.Finally,once a dominant channel forms,initiating and propagating hydraulic fractures in other directions becomes increasingly difficult,even in highly fractured areas.This method tackles the challenges of initiating and propagating hydraulic fractures in complex geological conditions,providing a theoretical basis for optimizing Enhanced Geothermal System(EGS)projects.
文摘To accelerate the practicality of electromagnetic railguns,it is necessary to use a combination of threedimensional numerical simulation and experiments to study the mechanism of bore damage.In this paper,a three-dimensional numerical model of the augmented railgun with four parallel unconventional rails is introduced to simulate the internal ballistic process and realize the multi-physics field coupling calculation of the rail gun,and a test experiment of a medium-caliber electromagnetic launcher powered by pulse formation network(PFN)is carried out.Various test methods such as spectrometer,fiber grating and high-speed camera are used to test several parameters such as muzzle initial velocity,transient magnetic field strength and stress-strain of rail.Combining the simulation results and experimental data,the damage condition of the contact surface is analyzed.
基金supported by Special funding project for research and development of key core technologies and common technologies in Shanxi Province(20201102017)supported by National Natural Science Foundations of China(Grant No.51874085 and 52274323)the Fundamental Research Funds for the Central Universities(Grant No.N2125030).
文摘A numerical model coupled with a multi-physical field based on dynamic formation of slag skin is established.After validation by comparing the experimental and simulation results of depth of metal pool,slag skin thickness and melt rate,it is utilized to investigate the effect of melt current on the coupled multi-physical field,slag skin thickness,metal pool depth and the heat flow distribution during electroslag remelting(ESR)Inconel 625 solidification process.The results showed that with the increase in the melt current,the velocities of ESR system and the temperature of metal pool increased,whereas the highest temperature of slag bath firstly decreased and then increased.With the increase in the melt current,the slag skin thickness,metal pool depth and melt rate increased.Furthermore,the characteristics of the heat flow distribution and the effect of melt current on the heat flow distribution were analysed.
基金supported by the National Natural Science Foundation of China(42250101)the Macao Foundation。
文摘Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.
基金supported by the National Natural Science Foundation of China(42250101,42250102)the Macao Foundation.
文摘The movement of global ocean circulation in the Earth’s main magnetic field generates a measurable induced magnetic field(about 2 nT at geomagnetic satellite altitudes).However,this ocean circulation-induced magnetic field has not been previously estimated or incorporated into geomagnetic field models,potentially causing leakage into the core field model.Here,we present a method to account for the circulation-induced magnetic field during geomagnetic field modeling.First,a forward model of the circulation-induced magnetic field is constructed by numerically solving electromagnetic induction equations based on a realistic ocean circulation model.Then,this forward model is subtracted from the observed data.Finally,the core and lithospheric fields,magnetospheric and Earth’s mantle-induced fields,and the ocean tide-induced magnetic field are co-estimated.Applying our method to over 20 years of MSS-1,Swarm,CryoSat-2,and CHAMP satellite magnetic data,we derive a new multisource geomagnetic field model(MGFM).We find that incorporating a forward model of the circulation-induced magnetic field marginally improves the fit to the data.Furthermore,we demonstrate that neglecting the circulation-induced magnetic field in geomagnetic field modeling results in leakage into the core field model.The highlights of the MGFM model include:(i)a good agreement with the widely used CHAOS model series;(ii)the incorporation of magnetic fields induced by both ocean tides and circulation;and(iii)the suppression of leakage of the circulation-induced magnetic field into the core field model.
基金supported and financed by Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology (No.2024yjrc96)Anhui Provincial University Excellent Research and Innovation Team Support Project (No.2022AH010053)+2 种基金National Key Research and Development Program of China (Nos.2023YFC2907602 and 2022YFF1303302)Anhui Provincial Major Science and Technology Project (No.202203a07020011)Open Foundation of Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining (No.EC2023020)。
文摘The generalized rheological tests on sandstone were conducted under both dynamic stress and seepage fields.The results demonstrate that the rheological strain of the specimen under increased stress conditions is greater than that under creep conditions,indicating that the dynamic stress field significantly influences the rheological behaviours of sandstone.Following the rheological tests,the number of small pores in the sandstone decreased,while the number of medium-sized pores increased,forming new seepage channels.The high initial rheological stress accelerated fracture compression and the closure of seepage channels,resulting in reduction in the permeability of sandstone.Based on the principles of generalized rheology and the experimental findings,a novel rock rheological constitutive model incorporating both the dynamic stress field and seepage properties has been developed.Numerical simulations of surrounding rock deformation in geotechnical engineering were carried out using a secondary development version of this model,which confirmed the applicability of the generalized rheological numerical simulation method.These results provide theoretical support for the long-term stability evaluation of engineering rock masses and for predicting the deformation of surrounding rock.
基金supported by the National Natural Science Foundation of China (Grant Nos.12202294 and 12022208)the Project funded by China Postdoctoral Science Foundation (Grant No.2022M712243)the Fundamental Research Funds for the Central Universities (Grant No.2023SCU12098).
文摘It is well known that coarse-grained super-elastic NiTi shape memory alloys(SMAs)exhibit localized rather than homogeneous martensite transformation(MT),which,however,can be strongly influenced by either internal size(grain size,GS)or the external size(geometric size).The coupled effect of GS and geometric size on the functional properties has not been clearly understood yet.In this work,the super-elasticity,one-way,and stress-assisted two-way shape memory effects of the polycrystalline NiTi SMAs with different aspect ratios(length/width for the gauge section)and different GSs are investigated based on the phase field method.The coupled effect of the aspect ratio and GS on the functional properties is adequately revealed.The simulated results indicate that when the aspect ratio is lower than about 4:1,the stress biaxiality and stress heterogeneity in the gauge section of the sample become more and more obvious with decreasing the aspect ratio,which can significantly influence the microstructure evolution in the process involving external stress.Therefore,the corresponding functional property is strongly dependent on the aspect ratio.With decreasing the GS and the aspect ratio(to be lower than 4:1),both the aspect ratio and GS can affect the MT or martensite reorientation in each grain and the interaction among grains.Thus,due to the strong internal constraint(i.e.,the constraint of grain boundary)and the external constraint(i.e.,the constraint of geometric boundary),the capabilities of the functional properties of NiTi SMAs are gradually weakened and highly dependent on these two factors.
基金supported by the National Natural Science Foundation of China(No.U2003215).
文摘The smelting reduction process of the ilmenite in an electric arc furnace(EAF)is a commonly used technology for producing titanium slag in the world.It has particular significance to analyze the velocity-temperature-electromagnetics multi-physical field in an EAF for improving its productivity and reducing energy consumption.A transient three-dimensional mathematical model was developed to characterize the flow,heat transfer,and electromagnetic behavior in a titanium slag EAF.For describing the electromagnetic field and its effects on velocity and temperature distribution in the furnace,magnetohydrodynamic equations and conservation equations for mass,momentum,and energy were solved simultaneously by compiling the user-defined function program.The numerical model was verified by comparing with the literature data.The results indicate that the Lorentz force is the main driving force of the velocity and temperature distribution.Moreover,the influence of input current and location of electrodes on the multi-physical field distribution was also investigated.It is found that the appropriate range of input current and diameter of pitch circle are about 30,000 A and 3000-3500 mm,respectively.The mathematical model established can characterize the multi-physical field more accu-rately than before,which can provide valuable guidance for the operation improvement and design optimization of the EAF for producing titanium slag.
基金the support of the National Natural Science Foundation of China (Nos. 42250103, 41974073, and 41404053)the Macao Foundation and the preresearch project of Civil Aerospace Technologies (Nos. D020308 and D020303)funded by China’s National Space Administration, and the Specialized Research Fund for State Key Laboratories。
文摘By combining data from the Challenging Minisatellite Payload(CHAMP),Swarm-A,and newest Macao Science Satellite-1(MSS-1) missions,we constructed a lithospheric magnetic field model up to spherical harmonic degree N = 100.To isolate the lithospheric magnetic field signals,we utilized the latest CHAOS-8(CHAMP,Φrsted,and SAC-C 8) model and MGFM(Multisource Geomagnetic Field Model) to remove nonlithospheric sources,including the core field,magnetospheric field,ocean tidal field,and ocean circulation field.Subsequently,orbit-by-orbit processing was applied to both scalar and vector data,such as spherical harmonic high-pass filtering,singular spectrum analysis,and line leveling,to suppress noise and residual signals along the satellite tracks.With an orbital inclination of only 41°,MSS-1 effectively captures fine-scale lithospheric magnetic field signals in mid-to low-latitude regions.Its data exhibit a root mean square error of only 0.77 nT relative to the final model,confirming the high quality and utility of lithospheric field modeling.The resulting model exhibits excellent consistency with the MF7(Magnetic Field Model 7),maintaining a high correlation up to N = 90 and still exceeding 0.65 at N = 100.These results demonstrate the reliability and value of MSS-1 data in global lithospheric magnetic field modeling.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the MOST Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4).
文摘The equivalent source(ES)method in the spherical coordinate system has been widely applied to processing,reduction,field modeling,and geophysical and geological interpretation of satellite magnetic anomaly data.However,the inversion for the ES model suffers from nonuniqueness and instability,which remain unresolved.To mitigate these issues,we introduce both the minimum and flattest models into the model objective function as an alternative regularization approach in the spherical ES method.We first present the methods,then analyze the accuracy of forward calculation and test the proposed ES method in this study by using synthetic data.The experimental results from simulation data indicate that our proposed regularization effectively suppresses the Backus effect and mitigates inversion instability in the low-latitude region.Finally,we apply the proposed method to magnetic anomaly data from China Seismo-Electromagnetic Satellite-1(CSES-1)and Macao Science Satellite-1(MSS-1)magnetic measurements over Africa by constructing an ES model of the large-scale lithospheric magnetic field.Compared with existing global lithospheric magnetic field models,our ES model demonstrates good consistency at high altitudes and predicts more stable fields at low altitudes.Furthermore,we derive the reduction to the pole(RTP)magnetic anomaly fields and the apparent susceptibility contrast distribution based on the ES model.The latter correlates well with the regional tectonic framework in Africa and surroundings.
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supported by the National Natural Science Foundation of China(Grant Nos.52161002,51661020 and 11364024)。
文摘As the demand for advanced material design and performance prediction continues to grow,traditional phase-field models are increasingly challenged by limitations in computational efficiency and predictive accuracy,particularly when addressing high-dimensional and complex data in multicomponent systems.To overcome these challenges,this study proposes an innovative model,LSGWO-BP,which integrates an improved Grey Wolf Optimizer(GWO)with a backpropagation neural network(BP)to enhance the accuracy and efficiency of quasi-phase equilibrium predictions within the KKS phase-field framework.Three mapping enhancement strategies were investigated–Circle-Root,Tent-Cosine,and Logistic-Sine mappings-with the Logistic mapping further improved via Sine perturbation to boost global search capability and convergence speed in large-scale,complex data scenarios.Evaluation results demonstrate that the LSGWO-BP model significantly outperforms conventional machine learning approaches in predicting quasi-phase equilibrium,achieving a 14%–28%reduction in mean absolute error(MAE).Substantial improvements were also observed in mean squared error,root mean squared error,and mean absolute percentage error,alongside a 7%–33%increase in the coefficient of determination(R2).Furthermore,the model exhibits strong potential for microstructural simulation applications.Overall,the study confirms the effectiveness of the LSGWO-BP model in materials science,especially in enhancing phase-field modeling efficiency and enabling accurate,intelligent prediction for multicomponent alloy systems,thereby offering robust support for microstructure prediction and control.
基金supported by the National Natural Science Foundation of China(Grant Nos.12388101,12372288,U23A2069,and 92152301).
文摘Machine learning(ML)techniques have emerged as powerful tools for improving the predictive capabilities of Reynolds-averaged Navier-Stokes(RANS)turbulence models in separated flows.This improvement is achieved by leveraging complex ML models,such as those developed using field inversion and machine learning(FIML),to dynamically adjust the constants within the baseline RANS model.However,the ML models often overlook the fundamental calibrations of the RANS turbulence model.Consequently,the basic calibration of the baseline RANS model is disrupted,leading to a degradation in the accuracy,particularly in basic wall-attached flows outside of the training set.To address this issue,a modified version of the Spalart-Allmaras(SA)turbulence model,known as Rubber-band SA(RBSA),has been proposed recently.This modification involves identifying and embedding constraints related to basic wall-attached flows directly into the model.It is shown that no matter how the parameters of the RBSA model are adjusted as constants throughout the flow field,its accuracy in wall-attached flows remains unaffected.In this paper,we propose a new constraint for the RBSA model,which better safeguards the law of wall in extreme conditions where the model parameter is adjusted dramatically.The resultant model is called the RBSA-poly model.We then show that when combined with FIML augmentation,the RBSA-poly model effectively preserves the accuracy of simple wall-attached flows,even when the adjusted parameters become functions of local flow variables rather than constants.A comparative analysis with the FIML-augmented original SA model reveals that the augmented RBSA-poly model reduces error in basic wall-attached flows by 50%while maintaining comparable accuracy in trained separated flows.These findings confirm the effectiveness of utilizing FIML in conjunction with the RBSA model,offering superior accuracy retention in cardinal flows.
基金supported by the National Natural Science Foundation of China(No.12172321)。
文摘The nonlinear traveling wave vibration of rotating ferromagnetic functionally graded(FG)cylindrical shells under multi-physics fields is investigated.Grounded in the Kirchhoff-Love thin shell theory,the geometric nonlinearity is incorporated into the model,and the constitutive equations are derived.The physical parameters of functionally graded materials(FGMs),which exhibit continuous variation across the thickness gradient,are of particular interest.The nonlinear magneto-thermoelastic governing equations are derived in accord with Hamilton's principle.The nonlinear partial differential equations are discretized with the Galerkin method,and the analytical expression of traveling wave frequencies is derived with an approximate method.The accuracy of the proposed method is validated through the comparison with the results from the literature and numerical solutions.Finally,the visualization analyses are conducted to examine the effects of key parameters on the traveling wave frequencies.The results show that the factors including the power-law index,temperature,magnetic field intensity,and rotating speed have the coupling effects with respect to the nonlinear vibration behavior.
基金supported by the National Natural Science Foundation of China(Grant Nos.22278001 and 21776002)the Natural Science Foundation of Anhui Provincial Education Department(No.KJ2021A0407)+1 种基金the Natural Science Foundation of Anhui Province(Grant No.2008085QB87)Anhui Provincial Postdoctoral Science Foundation(No.2021B538).
文摘Reducing coke use is an effective measure to reduce carbon emission and energy consumption in the blast furnace(BF)ironmaking.Essentially,BF is a high-temperature moving bed reactor,where complex physical transformations coupled with complicated reactions occur.This makes it challenging to investigate the factors determining BF performance with the conventional method.A multi-physical field coupling mathematical model of BF was thus developed to describe its mass and heat transfer as well as its intrinsic reactions.Then,the proposed model was validated with the production data.Under coupling conditions,influences of dominating reactions on BF performance(temperature distribution,gas distribution,iron formation reaction,and direct reduction degree)were revealed.The results indicated that coke combustion,indirect reduction,and direct reduction of iron ore mainly took place nearby the shaft tuyere,cohesive zone,and dripping zone,respectively.Besides,the rate of coke solution loss reaction was increased with the rising coke porosity in the cohesive zone.Considering the effect of coke porosity on the efficiency and stability of BF,the coke porosity of 0.42 was regarded as a reasonable value.
基金supported by the National Natural Science Foundation of China(42250101,42250102,42250103,12250013)the Macao Foundation。
文摘The Earth's magnetic field,which has been extensively observed from ground to satellite altitudes over several decades,originates from multiple sources,such as the core dynamo,the conductive mantle,the magnetized lithosphere,and the space current systems.Modeling of the lithospheric contribution plays an important role in the geophysical studies and industrial applications.In this paper,we propose a new method for global and regional modeling of the lithospheric magnetic field based on the cubed-sphere.An equivalent dipole source method on a quasi-uniform cubed-sphere grid is employed in the forward modeling.The dipole directions are fixed according to a priori magnetization and the relative intensities are estimated by an inversion procedure of least-squares fitting with minimum model regularization.Several numerical tests are performed to validate the accuracy and efficiency of both forward modeling and inversion procedure.The proposed method is applied to the global and regional modeling based on the latest magnetic data from Swarm Alpha satellite and MSS-1 mission.The model results indicate that the proposed method works quite well for realistic satellite data and MSS-1 data is consistent with the Swarm data in terms of lithospheric field modeling.
基金supported in part by the National Key Research and Development Program of China(2022YFB3304900)in part by the National Natural Science Foundation of China(62394340 and 62073340)in part by the Science and Technology Innovation Program of Hunan Province(2022JJ10083).
文摘With the intelligent transformation of process manufacturing,accurate and comprehensive perception information is fundamental for application of artificial intelligence methods.In zinc smelting,the fluidized bed roaster is a key piece of large-scale equipment and plays a critical role in the manufacturing industry;its internal temperature field directly determines the quality of zinc calcine and other related products.However,due to its vast spatial dimensions,the limited observation methods,and the complex multiphase,multifield coupled reaction atmosphere inside it,accurately and timely perceiving its temperature field remains a significant challenge.To address these challenges,a spatial-temporal reduced-order model(STROM)is proposed,which can realize fast and accurate temperature field perception based on sparse observation data.Specifically,to address the difficulty in matching the initial physical field with the sparse observation data,an initial field construction based on data assimilation(IFCDA)method is proposed to ensure that the initial conditions of the model can be matched with the actual operation state,which provides a basis for constructing a high-precision computational fluid dynamics(CFD)model.Then,to address the high simulation cost of high-precision CFD models under full working conditions,a high uniformity(HU)-orthogonal test design(OTD)method with the centered L2 deviation is innovatively proposed to ensure high information coverage of the temperature field dataset under typical working conditions in terms of multiple factors and levels of the component,feed,and blast parameters.Finally,to address the difficulty in real-time and accurate temperature field prediction,considering the spatial correlation between the observed temperature and the temperature field,as well as the dynamic correlation of the observed temperature in the time dimension,a spatial-temporal predictive model(STPM)is established,which realizes rapid prediction of the temperature field through sparse observa-tion data.To verify the accuracy and validity of the proposed method,CFD model validation and reduced-order model prediction experiments are designed,and the results show that the proposed method can realize high-precision and fast prediction of the roaster temperature field under different working conditions through sparse observation data.Compared with the CFD model,the prediction root-mean-square error(RMSE)of STROM is less than 0.038,and the computational efficiency is improved by 3.4184×10^(4)times.In particular,STROM also has a good prediction ability for unmodeled conditions,with a prediction RMSE of less than 0.1089.
基金a project funded by the China National Space Administration (CNSA) and the Ministry of Emergency Management of Chinasupported by the Civil Aerospace Technology Pilot Research Project (D040203)+1 种基金the National Natural Science Foundation of China (42004051, 42274214)the APSCO Earthquake Research Project Phase Ⅱ and Dragon 6 cooperation 2025-2029 (95437)。
文摘The China Seismo-Electromagnetic Satellite(CSES) was successfully launched in February 2018. The high precision magnetometer(HPM) on board the CSES has captured high-quality magnetic data that have been used to derive a global lithospheric magnetic field model. While preparing the datasets for this lithospheric magnetic field model, researchers found that they still contained prominent residual trends within the magnetic anomaly even once signals from other sources had been eliminated. However, no processing was undertaken to deal with the residual trends during modeling to avoid subjective processing and represent the realistic nature of the data. In this work, we analyze the influence of these residual trends on the lithospheric magnetic field modeling.Polynomials of orders 0–3 were used to fit the trend of each track and remove it for detrending. We then derived four models through detrending-based processing, and compared their power spectra and grid maps with those of the CSES original model and CHAOS-7model. The misfit between the model and the dataset decreased after detrending the data, and the convergence of the inverted spherical harmonic coefficients improved. However, detrending reduced the signal strength and the power spectrum, while detrending based on high-order polynomials introduced prominent distortions in details of the magnetic anomaly. Based on this analysis, we recommend along-track detrending by using a zero-order polynomial(removing a constant value) on the CSES magnetic anomaly data to drag its mean value to zero. This would lead to only a slight reduction in the signal strength while significantly improving the stability of the inverted coefficients and details of the anomaly.
基金Supported by the National Key Research and Development Program of China(Nos.2021YFC3101801,2023YFC3008200)the National Natural Science Foundation of China(Nos.42476219,41976200)+6 种基金the National Foreign Experts Program(No.S20240134)the Innovative Team Plan of the Department of Education of Guangdong Province(No.2023KCXTD015)the Tropical Ocean Environment in Western Coastal Waters Observation and Research Station of Guangdong Province(No.2024B1212040008)the Independent Research Project of the Southern Ocean Laboratory(No.SML2022SP301)the Shandong Innovation and Development Research Institute Think Tank Projectthe Guangdong Ocean University Scientific Research Program(No.060302032106)the Start-up Fund for Ph D Researchers(No.060302032104)。
文摘Typhoon Chaba was the most intense typhoon to strike western Guangdong since Typhoon Mujigae in 2015.According to the National Disaster Reduction Center of China,in the morning of July 7,2022,over 1.5 million people in Guangdong,Guangxi,and Hainan were affected by Typhoon Chaba.The typhoon also caused the“Fukui 001”ship to be in distress in the waters near Yangjiang,Guangdong,on July 2,resulting in big casualties.Studies have indicated that wind field forecast for Typhoon Chaba was not accurate.To better simulate typhoon events and assess their impacts,we proposed the use of a model wind field(Fujita-Takahashi)integrated with the Copernicus Marine and Environmental Monitoring Service(CMEMS)data to reconstruct effectively the overall wind field of Typhoon Chaba.The simulation result aligns well with the observations,particularly at the Dashu Island Station,showing consistent trends in wind speed changes.However,certain limitations were noted.The model shows that the attenuation of wind speed is slower when typhoon neared land than that observed,indicating that the model has a high simulation accuracy for the ocean wind field,but may have deviations near coastal areas.The result is accurate for open sea but deviated for near land due to the land friction effect.Therefore,we recommend to adjust the model to improve the accuracy for near coasts.
基金supported by the National Natural Science Foundation of China(Grant Nos.42005003 and 41475094)National Key R&D Program of China(Grant No.2018YFC1506704).
文摘With the growing demand for high-precision flow field simulations in computational science and engineering,the super-resolution reconstruction of physical fields has attracted considerable research interest.However,tradi-tional numerical methods often entail high computational costs,involve complex data processing,and struggle to capture fine-scale high-frequency details.To address these challenges,we propose an innovative super-resolution reconstruction framework that integrates a Fourier neural operator(FNO)with an enhanced diffusion model.The framework employs an adaptively weighted FNO to process low-resolution flow field inputs,effectively capturing global dependencies and high-frequency features.Furthermore,a residual-guided diffusion model is introduced to further improve reconstruction performance.This model uses a Markov chain for noise injection in phys-ical fields and integrates a reverse denoising procedure,efficiently solved by an adaptive time-step ordinary differential equation solver,thereby ensuring both stability and computational efficiency.Experimental results demonstrate that the proposed framework significantly outperforms existing methods in terms of accuracy and efficiency,offering a promising solution for fine-grained data reconstruction in scientific simulations.
