A multi-phase-field model has been developed to simulate the microstructure evolution and kinetics of the austenite static recrystallization（SRX） in a C–Mn steel. In this model, the bulk free energy that coupling t...A multi-phase-field model has been developed to simulate the microstructure evolution and kinetics of the austenite static recrystallization（SRX） in a C–Mn steel. In this model, the bulk free energy that coupling the deformation stored energy with a special interpolation function is incorporated. Both the deformed grain topology and the deformation stored energy have been included in order to investigate the influence of pre-deformation on the subsequent austenite SRX at different hot deformation levels. Diverse scenarios of microstructure evolution show different deformation-dependent recrystallized grain sizes. The transformation kinetics is then discussed by analyzing the overall SRX fraction and the average interface velocity on the recrystallization front.展开更多
Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This...Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.展开更多
A graphics-processing-unit(GPU)-parallel-based computational scheme is developed to realize the competitive growth process of converging bi-crystal in two-dimensional states in the presence of forced convection condit...A graphics-processing-unit(GPU)-parallel-based computational scheme is developed to realize the competitive growth process of converging bi-crystal in two-dimensional states in the presence of forced convection conditions by coupling a multi-phase field model and a lattice Boltzmann model.The elimination mechanism in the evolution process is analyzed for the three conformational schemes constituting converging bi-crystals under pure diffusion and forced convection conditions,respectively,expanding the research of the competitive growth of columnar dendrites under melt convection conditions.The results show that the elimination mechanism for the competitive growth of converging bi-crystals of all three configurations under pure diffusion conditions follows the conventional Walton-Chalmers model.When there is forced convection with lateral flow in the liquid phase,the anomalous elimination phenomenon of unfavorable dendrites eliminating favorable dendrites occurs in the grain boundaries.In particular,the anomalous elimination phenomenon is relatively strong in conformation 1 and conformation 2 when the orientation angle of unfavorable dendrites is small,and relatively weak in conformation 3.Moreover,the presence of convection increases the tip growth rate of both favorable and unfavorable dendrites in the grain boundary.In addition,the parallelization of the multi-phase-field-lattice Boltzmann model is achieved by designing the parallel computation of the model on the GPU platform concerning the computerunified-device-architecture parallel technique,and the results show that the parallel computation of this model based on the GPU has absolute advantages,and the parallel acceleration is more obvious as the computation area increases.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
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
Based on the theory of superimposed deformation and the regional tectonic background,the multi-phase non-coaxial superimposed structures in Junggar Basin were systematically analyzed using seismic interpretation,field...Based on the theory of superimposed deformation and the regional tectonic background,the multi-phase non-coaxial superimposed structures in Junggar Basin were systematically analyzed using seismic interpretation,field outcrop observation,and paleo-stress field recovery methods according to the characteristics of the current tectonic framework.Moreover,the tectonic evolution process of the basin was reconstructed using sandbox analogue modelling technology.The results showed that the study area has experienced five phases of non-coaxial deformation with superimposition:The first phase of deformation(D1)is characterized by NNE-SSW extension during late Carboniferous to early Permian,which formed large graben,half graben and other extensional structure style around the basin.The second phase of deformation(D2)is represented by NE-SW compression during the middle to late Permian,and it comprised numerous contraction structures that developed based on D1.The basic form of the entire basin is alternating uplift and depression.The third phase of deformation(D3)is the NW-SE transpressional strike-slip in the Triassic-Jurassic,which produced numerous strike-slip structural styles in the middle part of the basin.The fourth phase of deformation(D4)is the uniform sedimentation during Cretaceous,and the fifth phase(D5)is the compression along NNE-SSW due to the North Tianshan northward thrust,which produced three rows of fold thrust belts and tear faults in the front of the mountain in the southern margin of the basin.The newly established three-dimensional tectonic evolution model shows that,based on the large number of NW-trending grabens and half grabens in the Carboniferous basement of Junggar Basin,multiple level NE trending uplifts have formed with the joint superposition of the late structural inversion and multiple stress fields.This has resulted in the current tectonic units of alternating uplifts and depressions in different directions in the study area.展开更多
A thermodynamically complete multi-phase equation of state(EOS)applicable to both dense and porous metals at wide ranges of temperature and pressure is constructed.A standard three-term decomposition of the Helmholtz ...A thermodynamically complete multi-phase equation of state(EOS)applicable to both dense and porous metals at wide ranges of temperature and pressure is constructed.A standard three-term decomposition of the Helmholtz free energy as a function of specific volume and temperature is presented,where the cold component models both compression and expansion states,the thermal ion component introduces the Debye approximation and melting entropy,and the thermal electron component employs the Thomas-Fermi-Kirzhnits(TFK)model.The porosity of materials is considered by introducing the dynamic porosity coefficientαand the constitutive P-αrelation,connecting the thermodynamic properties between dense and porous systems,allowing for an accurate description of the volume decrease caused by void collapse while maintaining the quasi-static thermodynamic properties of porous systems identical to the dense ones.These models enable the EOS applicable and robust at wide ranges of temperature,pressure and porosity.A systematic evaluation of the new EOS is conducted with aluminum(Al)as an example.300 K isotherm,shock Hugoniot,as well as melting curves of both dense and porous Al are calculated,which shows great agreements with experimental data and validates the effectiveness of the models and the accuracy of parameterizations.Notably,it is for the first time Hugoniot P-σcurves up to 10~6 GPa and shock melting behaviors of porous Al are derived from analytical EOS models,which predict much lower compression limit and shock melting temperatures than those of dense Al.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 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
This study integrates seismic and petrophysical data to evaluate the subsurface geology of the Keva Field,located onshore in the Niger Delta,with the objective of constructing a 3D geological model and estimating the ...This study integrates seismic and petrophysical data to evaluate the subsurface geology of the Keva Field,located onshore in the Niger Delta,with the objective of constructing a 3D geological model and estimating the recoverable hydrocarbon volumes.Seismic lines and well log data from six wells—KV-2,KV-3,KV-4,KV-5,KV-6,and KV-7—were utilized for the interpretation.The seismic profiles revealed that the KV-4 well is the only well drilled on the up-thrown side of a significant horst fault block,bounded by four major normal faults,while all the other wells penetrated the downthrown side.Petrophysical analysis identified three key reservoirs,C500,D200,and E900,which exhibit excellent reservoir quality with high net-to-gross ratios,good porosity,and high hydrocarbon saturation.The identified depositional environments are tidal-and fluvial-dominated shoreface settings,with sheet sands deposited in distributary splay systems.The C500,D200,and E900 reservoirs have Gas Initially in Place(GIIP)values of 156.37,28.44,and 27.89 BSCF,respectively,with corresponding Estimated Ultimate Recovery(EUR)values of 104.77,19.06,and 18.69 BSCF,respectively.The Stock Tank Original Oil in Place(STOOIP)values are 24.43,91.29,and 86.41 MMSTB,with EURs of 7.32,27.4,and 25.92 MMSTB,respectively.The combined GIIP is 212.72 BSCF with EUR of 142.52 BSCF,while the total STOOIP is 202.13 MMSTB with a recoverable volume of 60.64 MMSTB.The reservoirs present an average porosity of 22.62%,with gas saturation of 84.66%and oil saturation of 73%.The evaluated reservoir qualities suggest high potential for optimized hydrocarbon production.展开更多
Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the s...Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the solar array.It is necessary to accurately predict the output power of the array for any flight state.Because of the uneven solar radiation received by the solar array,the traditional model based on components has a slow simulation speed.In this study,a data-driven surrogate modeling approach for prediction the output power of the solar array is proposed.The surrogate model is trained using the samples obtained from the high-accuracy simulation model.By using the input parameter preprocessor,the accuracy of the surrogate model in predicting the output power of the solar array is improved to 98.65%.In addition,the predictive speed of the surrogate model is ten million times faster than the traditional simulation model.Finally,the surrogate model is used to predict the energy balance of stratospheric airships flying throughout the year under actual global wind fields.展开更多
As the commercialization of the fifth gen-eration communication(5G)is sped up,its system testing scheme is vital for the successful deployment of 5G.Especially,5G relies on the scale-increased multiple-input-multiple ...As the commercialization of the fifth gen-eration communication(5G)is sped up,its system testing scheme is vital for the successful deployment of 5G.Especially,5G relies on the scale-increased multiple-input-multiple output(MIMO)technique to improve its capacity and coverage.Thus,testing new functions of the 5G MIMO system accurately and ef-ficiently,including beamforming(beam-tracking with movement)and multiple-user(MU)multiplexing,is a challenging task.This paper tries to construct a lab-oratorial hardware and conduct equipment-controlled field testing.Firstly,the testing scheme is presented,which is composed of the framework,the channel models and the validation methods.Then,the channel model principles are explained in detail due to its di-rect influence on the testing accuracy.Specifically,we utilize the spatial consistency and the multi-link cor-relation properties to emulate the high-speed dynamic time-varying(HDT)and the multiple-cell(MC)-MU-MIMO channels.Finally,the above testing scheme is verified in a Shanghai 5G field experiment with the practical commercial equipment and the channel em-ulator.The results show that the 5G new functions are tested accurately and efficiently by switching the channel emulation configurations.展开更多
The multi-phase field model of grain competitive growth during directional solidification of alloy is established.Solving multi-phase field models for thin interface layer thickness conditions,the grain boundary evolu...The multi-phase field model of grain competitive growth during directional solidification of alloy is established.Solving multi-phase field models for thin interface layer thickness conditions,the grain boundary evolution and grain elimination during the competitive growth of SCN-0.24-wt%camphor model alloy bi-crystals are investigated.The effects of different crystal orientations and pulling velocities on grain boundary microstructure evolution are quantitatively analyzed.The obtained results are shown below.In the competitive growth of convergent bi-crystals,when favorably oriented dendrites are in the same direction as the heat flow and the pulling speed is too large,the orientation angle of the bi-crystal from small to large size is the normal elimination phenomenon of the favorably oriented dendrite,blocking the unfavorably oriented dendrite,and the grain boundary is along the growth direction of the favorably oriented dendrite.When the pulling speed becomes small,the grain boundary shows the anomalous elimination phenomenon of the unfavorably oriented dendrite,eliminating the favorably oriented dendrite.In the process of competitive growth of divergent bi-crystal,when the growth direction of favorably oriented dendrites is the same as the heat flow direction and the orientation angle of unfavorably oriented grains is small,the frequency of new spindles of favorably oriented grains is significantly higher than that of unfavorably oriented grains,and as the orientation angle of unfavorably oriented dendrites becomes larger,the unfavorably oriented grains are more likely to have stable secondary dendritic arms,which in turn develop new primary dendritic arms to occupy the liquid phase grain boundary space,but the grain boundary direction is still parallel to favorably oriented dendrites.In addition,the tertiary dendritic arms on the developed secondary dendritic arms may also be blocked by the surrounding lateral branches from further developing into nascent main axes,this blocking of the tertiary dendritic arms has a random nature,which can have aninfluence on the generation of nascent primary main axes in the grain boundaries.展开更多
基金financially supported by the National Science Foundation of China (Grant No. 51371169) and (Grant No. 51401214)
文摘A multi-phase-field model has been developed to simulate the microstructure evolution and kinetics of the austenite static recrystallization（SRX） in a C–Mn steel. In this model, the bulk free energy that coupling the deformation stored energy with a special interpolation function is incorporated. Both the deformed grain topology and the deformation stored energy have been included in order to investigate the influence of pre-deformation on the subsequent austenite SRX at different hot deformation levels. Diverse scenarios of microstructure evolution show different deformation-dependent recrystallized grain sizes. The transformation kinetics is then discussed by analyzing the overall SRX fraction and the average interface velocity on the recrystallization front.
基金supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(Project No.15308024)a grant from Research Centre for Carbon-Strategic Catalysis,The Hong Kong Polytechnic University(CE2X).
文摘Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.52161002,51661020,and 11364024)the Postdoctoral Science Foundation of China(Grant No.2014M560371)the Funds for Distinguished Young Scientists of Lanzhou University of Technology,China(Grant No.J201304).
文摘A graphics-processing-unit(GPU)-parallel-based computational scheme is developed to realize the competitive growth process of converging bi-crystal in two-dimensional states in the presence of forced convection conditions by coupling a multi-phase field model and a lattice Boltzmann model.The elimination mechanism in the evolution process is analyzed for the three conformational schemes constituting converging bi-crystals under pure diffusion and forced convection conditions,respectively,expanding the research of the competitive growth of columnar dendrites under melt convection conditions.The results show that the elimination mechanism for the competitive growth of converging bi-crystals of all three configurations under pure diffusion conditions follows the conventional Walton-Chalmers model.When there is forced convection with lateral flow in the liquid phase,the anomalous elimination phenomenon of unfavorable dendrites eliminating favorable dendrites occurs in the grain boundaries.In particular,the anomalous elimination phenomenon is relatively strong in conformation 1 and conformation 2 when the orientation angle of unfavorable dendrites is small,and relatively weak in conformation 3.Moreover,the presence of convection increases the tip growth rate of both favorable and unfavorable dendrites in the grain boundary.In addition,the parallelization of the multi-phase-field-lattice Boltzmann model is achieved by designing the parallel computation of the model on the GPU platform concerning the computerunified-device-architecture parallel technique,and the results show that the parallel computation of this model based on the GPU has absolute advantages,and the parallel acceleration is more obvious as the computation area increases.
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 National Natural Science Foundation of China,(Grant No.42072144)Shengli Oilfield,SINOPEC,China(Nos.30200018-21-ZC0613-0030 and 30200018-20-ZC0613-0116)。
文摘Based on the theory of superimposed deformation and the regional tectonic background,the multi-phase non-coaxial superimposed structures in Junggar Basin were systematically analyzed using seismic interpretation,field outcrop observation,and paleo-stress field recovery methods according to the characteristics of the current tectonic framework.Moreover,the tectonic evolution process of the basin was reconstructed using sandbox analogue modelling technology.The results showed that the study area has experienced five phases of non-coaxial deformation with superimposition:The first phase of deformation(D1)is characterized by NNE-SSW extension during late Carboniferous to early Permian,which formed large graben,half graben and other extensional structure style around the basin.The second phase of deformation(D2)is represented by NE-SW compression during the middle to late Permian,and it comprised numerous contraction structures that developed based on D1.The basic form of the entire basin is alternating uplift and depression.The third phase of deformation(D3)is the NW-SE transpressional strike-slip in the Triassic-Jurassic,which produced numerous strike-slip structural styles in the middle part of the basin.The fourth phase of deformation(D4)is the uniform sedimentation during Cretaceous,and the fifth phase(D5)is the compression along NNE-SSW due to the North Tianshan northward thrust,which produced three rows of fold thrust belts and tear faults in the front of the mountain in the southern margin of the basin.The newly established three-dimensional tectonic evolution model shows that,based on the large number of NW-trending grabens and half grabens in the Carboniferous basement of Junggar Basin,multiple level NE trending uplifts have formed with the joint superposition of the late structural inversion and multiple stress fields.This has resulted in the current tectonic units of alternating uplifts and depressions in different directions in the study area.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12205023,U2230401,12374056,U23A20537,11904027)。
文摘A thermodynamically complete multi-phase equation of state(EOS)applicable to both dense and porous metals at wide ranges of temperature and pressure is constructed.A standard three-term decomposition of the Helmholtz free energy as a function of specific volume and temperature is presented,where the cold component models both compression and expansion states,the thermal ion component introduces the Debye approximation and melting entropy,and the thermal electron component employs the Thomas-Fermi-Kirzhnits(TFK)model.The porosity of materials is considered by introducing the dynamic porosity coefficientαand the constitutive P-αrelation,connecting the thermodynamic properties between dense and porous systems,allowing for an accurate description of the volume decrease caused by void collapse while maintaining the quasi-static thermodynamic properties of porous systems identical to the dense ones.These models enable the EOS applicable and robust at wide ranges of temperature,pressure and porosity.A systematic evaluation of the new EOS is conducted with aluminum(Al)as an example.300 K isotherm,shock Hugoniot,as well as melting curves of both dense and porous Al are calculated,which shows great agreements with experimental data and validates the effectiveness of the models and the accuracy of parameterizations.Notably,it is for the first time Hugoniot P-σcurves up to 10~6 GPa and shock melting behaviors of porous Al are derived from analytical EOS models,which predict much lower compression limit and shock melting temperatures than those of dense Al.
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(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the support of African Union Commission through the Pan African University Life and Earth Sciences Institute(including Health and Agriculture),Ibadan,Nigeria,for funding this study。
文摘This study integrates seismic and petrophysical data to evaluate the subsurface geology of the Keva Field,located onshore in the Niger Delta,with the objective of constructing a 3D geological model and estimating the recoverable hydrocarbon volumes.Seismic lines and well log data from six wells—KV-2,KV-3,KV-4,KV-5,KV-6,and KV-7—were utilized for the interpretation.The seismic profiles revealed that the KV-4 well is the only well drilled on the up-thrown side of a significant horst fault block,bounded by four major normal faults,while all the other wells penetrated the downthrown side.Petrophysical analysis identified three key reservoirs,C500,D200,and E900,which exhibit excellent reservoir quality with high net-to-gross ratios,good porosity,and high hydrocarbon saturation.The identified depositional environments are tidal-and fluvial-dominated shoreface settings,with sheet sands deposited in distributary splay systems.The C500,D200,and E900 reservoirs have Gas Initially in Place(GIIP)values of 156.37,28.44,and 27.89 BSCF,respectively,with corresponding Estimated Ultimate Recovery(EUR)values of 104.77,19.06,and 18.69 BSCF,respectively.The Stock Tank Original Oil in Place(STOOIP)values are 24.43,91.29,and 86.41 MMSTB,with EURs of 7.32,27.4,and 25.92 MMSTB,respectively.The combined GIIP is 212.72 BSCF with EUR of 142.52 BSCF,while the total STOOIP is 202.13 MMSTB with a recoverable volume of 60.64 MMSTB.The reservoirs present an average porosity of 22.62%,with gas saturation of 84.66%and oil saturation of 73%.The evaluated reservoir qualities suggest high potential for optimized hydrocarbon production.
基金supported by the National Natural Science Foundation of China(Nos.51775021,52302511)the Fundamental Research Funds for the Central Universities,China(Nos.YWF-23-JC-01,YWF-23-JC-04,YWF-23-JC-09)。
文摘Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the solar array.It is necessary to accurately predict the output power of the array for any flight state.Because of the uneven solar radiation received by the solar array,the traditional model based on components has a slow simulation speed.In this study,a data-driven surrogate modeling approach for prediction the output power of the solar array is proposed.The surrogate model is trained using the samples obtained from the high-accuracy simulation model.By using the input parameter preprocessor,the accuracy of the surrogate model in predicting the output power of the solar array is improved to 98.65%.In addition,the predictive speed of the surrogate model is ten million times faster than the traditional simulation model.Finally,the surrogate model is used to predict the energy balance of stratospheric airships flying throughout the year under actual global wind fields.
基金supported in part by National Natural Science Foundation of China under Grant 62201087,Grant 62525101,in part by the National Key R&D Program of China under Grant 2023YFB2904803in part by the Guangdong Major Project of Basic and Applied Basic Research under Grant 2023B0303000001+1 种基金in part by the Natural Science Foundation of Beijing-Xiaomi Innovation Joint Foundation under Grant L243002in part by the Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Institute.
文摘As the commercialization of the fifth gen-eration communication(5G)is sped up,its system testing scheme is vital for the successful deployment of 5G.Especially,5G relies on the scale-increased multiple-input-multiple output(MIMO)technique to improve its capacity and coverage.Thus,testing new functions of the 5G MIMO system accurately and ef-ficiently,including beamforming(beam-tracking with movement)and multiple-user(MU)multiplexing,is a challenging task.This paper tries to construct a lab-oratorial hardware and conduct equipment-controlled field testing.Firstly,the testing scheme is presented,which is composed of the framework,the channel models and the validation methods.Then,the channel model principles are explained in detail due to its di-rect influence on the testing accuracy.Specifically,we utilize the spatial consistency and the multi-link cor-relation properties to emulate the high-speed dynamic time-varying(HDT)and the multiple-cell(MC)-MU-MIMO channels.Finally,the above testing scheme is verified in a Shanghai 5G field experiment with the practical commercial equipment and the channel em-ulator.The results show that the 5G new functions are tested accurately and efficiently by switching the channel emulation configurations.
基金supported by the National Natural Science Foundation of China(Grant Nos.52161002,51661020,and 11504149)the Postdoctoral Science Foundation of China(Grant No.2014M560371)the Funds for Distinguished Young Scientists of Lanzhou University of Technology,China(Grant No.J201304)。
文摘The multi-phase field model of grain competitive growth during directional solidification of alloy is established.Solving multi-phase field models for thin interface layer thickness conditions,the grain boundary evolution and grain elimination during the competitive growth of SCN-0.24-wt%camphor model alloy bi-crystals are investigated.The effects of different crystal orientations and pulling velocities on grain boundary microstructure evolution are quantitatively analyzed.The obtained results are shown below.In the competitive growth of convergent bi-crystals,when favorably oriented dendrites are in the same direction as the heat flow and the pulling speed is too large,the orientation angle of the bi-crystal from small to large size is the normal elimination phenomenon of the favorably oriented dendrite,blocking the unfavorably oriented dendrite,and the grain boundary is along the growth direction of the favorably oriented dendrite.When the pulling speed becomes small,the grain boundary shows the anomalous elimination phenomenon of the unfavorably oriented dendrite,eliminating the favorably oriented dendrite.In the process of competitive growth of divergent bi-crystal,when the growth direction of favorably oriented dendrites is the same as the heat flow direction and the orientation angle of unfavorably oriented grains is small,the frequency of new spindles of favorably oriented grains is significantly higher than that of unfavorably oriented grains,and as the orientation angle of unfavorably oriented dendrites becomes larger,the unfavorably oriented grains are more likely to have stable secondary dendritic arms,which in turn develop new primary dendritic arms to occupy the liquid phase grain boundary space,but the grain boundary direction is still parallel to favorably oriented dendrites.In addition,the tertiary dendritic arms on the developed secondary dendritic arms may also be blocked by the surrounding lateral branches from further developing into nascent main axes,this blocking of the tertiary dendritic arms has a random nature,which can have aninfluence on the generation of nascent primary main axes in the grain boundaries.
