In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical propert...In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.展开更多
Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and requir...Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and require a high level of expertise.This article proposes an innovative alternative solution that overcomes these limitations by automatically generating comprehensive Business Process Modelling and Notation(BPMN)diagrams solely from verbal descriptions of the processes to be modeled,utilizing Large Language Models(LLMs)and multimodal Artificial Intelligence(AI).Experimental results,based on video recordings of process explanations provided by an expert from an organization(in this case,the Commercial Courts of a public justice administration),demonstrate that the proposed methodology successfully enables the automatic generation of complete and accurate BPMN diagrams,leading to significant improvements in the speed,accuracy,and accessibility of process modeling.This research makes a substantial contribution to the field of business process modeling,as its methodology is groundbreaking in its use of LLMs and multimodal AI capabilities to handle different types of source material(text and video),combining several tools to minimize the number of queries and reduce the complexity of the prompts required for the automatic generation of successful BPMN diagrams.展开更多
In view of the frequent deterioration of molten steel quality during the tundish filling process,the slag-steel-air interface behavior in a tundish,including liquid level fluctuation,slag eyes,slag entrapment and air ...In view of the frequent deterioration of molten steel quality during the tundish filling process,the slag-steel-air interface behavior in a tundish,including liquid level fluctuation,slag eyes,slag entrapment and air suction during the steady-state casting and filling process,was comparatively studied through physical modeling and mathematical simulation methods.During the filling process,the liquid surface forms a large-size slag eye under the impact of molten steel from a ladle shroud,which simultaneously results in a violent fluctuation of liquid level.Concurrently,the liquid flow entrains the air phase and the cover slag into the tundish impact zone,resulting in slag entrapment and air suction.At filling flow rates of 1.5Q,2.0Q,and 2.5Q(Q is the flow rate under steady-state casting),the amount of slag entrapped is 8.39×10^(-5),9.65×10^(-5),and 12.7×10^(-5)m^(3),respectively,while the volume of air aspirated is 0.84×10^(-4),1.47×10^(-4),and 2.01×10^(-4)m^(3),indicating that slag entrapment and air suction intensify with an increase in tundish filling flow rate.Flow field characterization identifies eddy currents in the impact zone as the primary driver of the above phenomena.Proper filling process parameters were proposed to improve the steel quality during the tundish filling.展开更多
This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity p...This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity prediction model is proposed to compensate for the unknown dynamic model,as the kinematic model cannot accurately characterize the motion characteristics of the robot.Then,by introducing the Lorentz function,the improved iterative linear quadratic regulator(iLQR) method is used to solve the nonlinear MPC(NMPC) controller with constraints.In addition,in order to reduce computational burden,a closed gradient calculation method is introduced to improve algorithm efficiency.Finally,the feasibility and effectiveness of this method are verified through simulation and experiment.展开更多
Accurately assessing the carbon sequestration capacity of forests is crucial for mitigating climate change.Traditional methods for estimating Gross Primary Productivity(GPP)of vegetation involve significant uncertaint...Accurately assessing the carbon sequestration capacity of forests is crucial for mitigating climate change.Traditional methods for estimating Gross Primary Productivity(GPP)of vegetation involve significant uncertainties.As a novel remote sensing approach,Solar-Induced chlorophyll Fluorescence(SIF)is directly related to photosynthesis and has demonstrated strong correlations with GPP across various ecosystems,climate zones,and spatial scales.Current GPP estimation methods based on SIF include Light Use Efficiency(LUE)models,the SCOPE process models,and the latest mechanistic light response(MLR)models.Future research should focus on improving the mechanistic understanding of SIF-related processes and promoting the integration of multi-source remote sensing data with SIF-based modeling to enhance the accuracy and universality of GPP estimation.展开更多
Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening pa...Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.展开更多
Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective...Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective Coriolis condition,the velocity component parallel to the rotational axis exerts no influence on the magnitude of Coriolis acceleration.This circumstance implies a potential mitigation of the Coriolis force's deflective impact.Regrettably,extant investigations predominantly emphasize the dilative and compressive Coriolis effects,largely neglecting the pragmatic import of the deflective Coriolis condition.In pursuit of this gap,a series of discrete element method(DEM)simulations have been conducted to scrutinize the feasibility of centrifugal modelling for dry granular run-out processes under deflective Coriolis conditions.The findings concerning the deflective Coriolis effect reveal a consistent rise in the run-out distance by 2%–16%,a modest increase in bulk flow velocity of under 4%,and a slight elevation in average flow depth by no more than 25%.These alterations display smaller dependence on the specific testing conditions due to the granular flow undergoing dual deflections in opposing directions.This underscores the significance and utility of the deflective Coriolis condition.Notably,the anticipated reduction in error in predicting the final run-out distance is substantial,potentially reaching a 150%improvement compared to predictions made under the dilative and compressive Coriolis conditions.Therefore,the deflective Coriolis condition is advised when the final run-out distance of the granular flow is the main concern.To mitigate the impact of Coriolis acceleration,a greater initial height of the granular column is recommended,with a height/width ratio exceeding 1,as the basal friction of the granular material plays a crucial role in mitigating the deflective Coriolis effect.For more transverse-uniform flow properties,the width of the granular column should be as large as possible.展开更多
Integrated continuous stirred-tank reactors and distillation columns with recycle(CSTR-DC-recycle)are essential components in chemical processes.This paper proposes a method to establish a normal operating zone(NOZ)mo...Integrated continuous stirred-tank reactors and distillation columns with recycle(CSTR-DC-recycle)are essential components in chemical processes.This paper proposes a method to establish a normal operating zone(NOZ)model to represent allowable variations of the CSTR-DC-recycle chemical processes.The NOZ is a geometric space containing all safe operating points of the CSTR-DC-recycle chemical processes,so that it is an effective model for process monitoring.The novelty of the proposed method is to establish the NOZ model based on boundary points.The boundary points make it possible to capture the actual geometric space irrespective of the space shape.In contrast,existing methods represent the NOZ of processes by fixed mathematical models such as ellipsoidal and convex-hull models;they are not suitable for the CSTR-DC-recycle chemical processes whose NOZs cannot be exactly defined by fixed mathematical structures.Simulated case studies based on Aspen Hysys software are given to illustrate the proposed method.展开更多
The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of ...The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.展开更多
The Tibetan Plateau(TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospect...The Tibetan Plateau(TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospecting the latest research progress in the simulation of land-surface processes(LSPs) over the past 20 years, this study discusses both the simulation ability of land-surface models(LSMs) and the modification of parameterization schemes from two perspectives, the models' applicability and improved parameterization schemes. Our review suggests that different LSMs can well capture the spatiotemporal variations of the physical quantities of LSPs; but none of them can be fully applied to the plateau, meaning that all need to be revised according to the characteristics specific to the TP. Avoiding the unstable iterative computation and determining the freeze-thaw critical temperature according to the thermodynamic equilibrium equation, the unreasonable freeze-thaw parameterization scheme can be improved. Due to the complex underlying surface of the TP, no parameterization scheme of roughness length can well simulate the various characteristics of the turbulent flux over the TP at different temporal scales. The uniform soil thermodynamic and hydraulic parameterization scheme is unreasonable when it is applied to the plateau, as a result of the strong soil heterogeneity. There is little research on the snow-cover process so far,and the improved scheme has no advantage over the original one due to the lack of some related physical processes. The constant interaction among subprocesses of LSPs makes the improvement of a multiparameterization scheme yield better simulation results. According to the review of existing research, adding high-quality observation stations, developing a parameterization scheme suitable for the special LSPs of the TP, and adjusting the model structures can be helpful to the simulation of LSPs on the TP.展开更多
On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang st...On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km<SUP>2</SUP> of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.展开更多
With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process...With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.展开更多
Convective processes affect large-scale environments through cloud-radiation interaction, cloud micro- physical processes, and surface rainfall processes. Over the last three decades, cloud-resolving models （CRMs） h...Convective processes affect large-scale environments through cloud-radiation interaction, cloud micro- physical processes, and surface rainfall processes. Over the last three decades, cloud-resolving models （CRMs） have demonstrated to be capable of simulating convective-radiative responses to an imposed large-scale forcing. The CRM-produced cloud and radiative properties have been utilized to study the convective- related processes and their ensemble effects on large-scale circulations. This review the recent progress on the understanding of convective processes with the use of CRM simulations, including precipitation processes; cloud microphysical and radiative processes; dynamical processes; precipitation efficiency; diurnal variations of tropical oceanic convection; local-scale atmosphere-ocean coupling processes; and tropical convective-radiative equilibrium states. Two different ongoing applications of CRMs to general circulation models （GCMs） are discussed： replacing convection and cloud schemes for studying the interaction between cloud systems and large-scale circulation, and improving the schemes for climate simulations.展开更多
A batch-to-batch optimal iterative learning control （ILC） strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation （LTVP） model is built for produc...A batch-to-batch optimal iterative learning control （ILC） strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation （LTVP） model is built for product quality around the nominal trajectories. To address problems of model-plant mismatches, model prediction errors in the previous batch run are added to the model predictions for the current batch run. Then tracking error transition models can be built, and the ILC law with direct error feedback is explicitly obtained, A rigorous theorem is proposed, to prove the convergence of tracking error under ILC, The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC.展开更多
An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong ...An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.展开更多
Many high-quality forging productions require the large-sized hydraulic press machine（HPM） to have a desirable dynamic response. Since the forging process is complex under the low velocity, its response is difficult...Many high-quality forging productions require the large-sized hydraulic press machine（HPM） to have a desirable dynamic response. Since the forging process is complex under the low velocity, its response is difficult to estimate. And this often causes the desirable low-velocity forging condition difficult to obtain. So far little work has been found to estimate the dynamic response of the forging process under low velocity. In this paper, an approximate-model based estimation method is proposed to estimate the dynamic response of the forging process under low velocity. First, an approximate model is developed to represent the forging process of this complex HPM around the low-velocity working point. Under guaranteeing the modeling performance, the model may greatly ease the complexity of the subsequent estimation of the dynamic response because it has a good linear structure. On this basis, the dynamic response is estimated and the conditions for stability, vibration, and creep are derived according to the solution of the velocity. All these analytical results are further verified by both simulations and experiment. In the simulation verification for modeling, the original movement model and the derived approximate model always have the same dynamic responses with very small approximate error. The simulations and experiment finally demonstrate and test the effectiveness of the derived conditions for stability, vibration, and creep, and these conditions will benefit both the prediction of the dynamic response of the forging process and the design of the controller for the high-quality forging. The proposed method is an effective solution to achieve the desirable low-velocity forging condition.展开更多
The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 da...The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction （NCEP） / Global Data Assimilation System （GDAS） data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared （RMS） difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate （0.753 mm h^-1） and the observed rain rate （0.833 mm h^-1）. The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean Ps mainly comes from large-scale convergence （QWVF） and local vapor loss （positive QWVT）. Large underestimation （about 15%） of Ps will occur if QWVT and QCM （cloud source/sink） are not considered as contributors to Ps ,QWVF accounts for the variation of P during most of the integration time, while it is not always a contributor to Ps,Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to Ps - Surface rainfall is a result ofmulti-timescale interactions. QWVE possesses the longest time scale and the lowest frequeney the second and QCM of variation with time and may exert impact on P on longer time scales. QWVF possesses longest time scale and lowest frequency and can explain most of the variation of Ps. QWVT possess shorter time scales and higher frequencies, which can explain more detailed variations in Ps. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of QWVT in rainfall-free regions contribute less to that of the domain-mean QWVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of QWVF in rainfall regions are the main contributors to that of the domain-mean QWVF, then the main contributors to the surface rain rate before the afternoon of 28 July.展开更多
Beijing faces the challenge of high levels of ozone(O_(3))pollution.In this study,the Weather Research and Forecasting model and Community Multiscale Air Qualitymodel(CMAQ)were used to simulate atmospheric O_(3) conce...Beijing faces the challenge of high levels of ozone(O_(3))pollution.In this study,the Weather Research and Forecasting model and Community Multiscale Air Qualitymodel(CMAQ)were used to simulate atmospheric O_(3) concentrations in Beijing.To investigate the formation mechanisms and source contributions of O_(3) pollution in different regions of Beijing,process analysis and the integrated source apportionmentmethodwithin the CMAQwere applied to O_(3) concentrations in the summer of 2018.The process analysis results showed that vertical diffusion was the major contributor to O_(3) concentrations at all receptor sites in Beijing,at>65.94μg/(m^(3)·hr).Gas-phase chemical reactions consumed a significant amount of O_(3) in urban and inner suburban areas(>−5.57μg/(m^(3)·hr)),while near-surface chemical reactions made positive contributions in outer suburban areas(>4.72μg/(m^(3)·hr)).The O_(3) formation chemical reactions indicated that NO titration,which removes O_(3) at night-time,mainly occurred in urban areas.The weaker chemical reactions occurring near the surface in outer suburbs suggested that suburban-area O_(3) was produced in the upper atmospheric layers and was transported vertically to the lower layers.The O_(3) source apportionment results showed that boundary contributions were the dominant contributor to O_(3) pollution in Beijing(>40%).The contribution of non-local emissions to O_(3) levels was significantly greater in the outer suburbs than in urban and inner suburban areas due to topography.This study increases the understanding of the complex processes of O_(3) formation in different areas of Beijing and informs the implementation of O_(3) control plans.展开更多
To investigate groundwater flow and solute transport characteristics of the karst trough zone in China,tracer experiments were conducted at two adjacent typical karst groundwater flow systems(Yuquandong(YQD)and Migong...To investigate groundwater flow and solute transport characteristics of the karst trough zone in China,tracer experiments were conducted at two adjacent typical karst groundwater flow systems(Yuquandong(YQD)and Migongquan(MGQ))in Sixi valley,western Hubei,China.Highresolution continuous monitoring was utilized to obtain breakthrough curves(BTCs),which were then analyzed using the multi-dispersion model(MDM)and the two-region nonequilibrium model(2RNE)with basic parameters calculated by CXTFIT and QTRACER2.Results showed that:(1)YQD flow system had a complex infiltration matrix with overland flow,conduit flow and fracture flow,while the MGQ flow system was dominated by conduit flow with fast flow transport velocity,but also small amount of fracture flow there;(2)They were well fitted based on the MDM(R^2=0.928)and 2RNE(R^2=0.947)models,indicating that they had strong adaptability in the karst trough zone;(3)conceptual models for YQD and MGQ groundwater systems were generalized.In YQD system,the solute was transported via overland flow during intense rainfall,while some infiltrated down into fissures and conduits.In MGQ system,most were directly transported to spring outlet in the fissureconduit network.展开更多
Hydrogeochemistry and factor analysis were conducted together to assess the distribution and the major geochemical processes in fluoride-contaminated shallow groundwater in the Yuncheng Basin.Spatially,fluoride concen...Hydrogeochemistry and factor analysis were conducted together to assess the distribution and the major geochemical processes in fluoride-contaminated shallow groundwater in the Yuncheng Basin.Spatially,fluoride concentration was low(<1.5 mg/L)in the southern piedmont plain,medium(<4 mg/L)in the central basin,and high(up to 14.1 mg/L)in Kaolao lowland areas in shallow aquifers.A three-factor principal component analysis model explained over 75.1%of the total variance.Sediment weathering leaching and evapotranspiration were recognized as the first primary hydrochemical processes response for the groundwater chemistry and explained the largest portion(42.1%)of the total variance.Factor two reflects the negative influence of human activities,with a positive loading of NO3^-and HCO3^-,and negative loading of well depth.Fluoride-bearing mineral dissolution and alkaline condition was ranked as the third factors responding for groundwater chemistry and explained 11.2%of the total variance.展开更多
基金support from the National Natural Science Foundation of China(Grant Nos.42277161 and 42230709).
文摘In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.
基金funded by Fundación CajaCanarias and Fundación Bancaria“la Caixa”,grant number 2023DIG11.
文摘Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and require a high level of expertise.This article proposes an innovative alternative solution that overcomes these limitations by automatically generating comprehensive Business Process Modelling and Notation(BPMN)diagrams solely from verbal descriptions of the processes to be modeled,utilizing Large Language Models(LLMs)and multimodal Artificial Intelligence(AI).Experimental results,based on video recordings of process explanations provided by an expert from an organization(in this case,the Commercial Courts of a public justice administration),demonstrate that the proposed methodology successfully enables the automatic generation of complete and accurate BPMN diagrams,leading to significant improvements in the speed,accuracy,and accessibility of process modeling.This research makes a substantial contribution to the field of business process modeling,as its methodology is groundbreaking in its use of LLMs and multimodal AI capabilities to handle different types of source material(text and video),combining several tools to minimize the number of queries and reduce the complexity of the prompts required for the automatic generation of successful BPMN diagrams.
基金support from National Natural Science Foundation of China(Grant No.51874033)to Prof.Hai-Yan Tang.
文摘In view of the frequent deterioration of molten steel quality during the tundish filling process,the slag-steel-air interface behavior in a tundish,including liquid level fluctuation,slag eyes,slag entrapment and air suction during the steady-state casting and filling process,was comparatively studied through physical modeling and mathematical simulation methods.During the filling process,the liquid surface forms a large-size slag eye under the impact of molten steel from a ladle shroud,which simultaneously results in a violent fluctuation of liquid level.Concurrently,the liquid flow entrains the air phase and the cover slag into the tundish impact zone,resulting in slag entrapment and air suction.At filling flow rates of 1.5Q,2.0Q,and 2.5Q(Q is the flow rate under steady-state casting),the amount of slag entrapped is 8.39×10^(-5),9.65×10^(-5),and 12.7×10^(-5)m^(3),respectively,while the volume of air aspirated is 0.84×10^(-4),1.47×10^(-4),and 2.01×10^(-4)m^(3),indicating that slag entrapment and air suction intensify with an increase in tundish filling flow rate.Flow field characterization identifies eddy currents in the impact zone as the primary driver of the above phenomena.Proper filling process parameters were proposed to improve the steel quality during the tundish filling.
基金Supported by the Zhejiang Provincial Natural Science Foundation of China (No.LR23F030002)。
文摘This article proposes a Gaussian process(GP) based model predictive control(MPC) method to solve the tracking control of wheeled mobile robot( WMR) with uncertain model parameters.Firstly,a Gaussian process velocity prediction model is proposed to compensate for the unknown dynamic model,as the kinematic model cannot accurately characterize the motion characteristics of the robot.Then,by introducing the Lorentz function,the improved iterative linear quadratic regulator(iLQR) method is used to solve the nonlinear MPC(NMPC) controller with constraints.In addition,in order to reduce computational burden,a closed gradient calculation method is introduced to improve algorithm efficiency.Finally,the feasibility and effectiveness of this method are verified through simulation and experiment.
基金sponsored by the National Natural Science Foundation of China(Grant number 42250205,42471510)the Open Found of Technology Innovation Center for Intelligent Monitoring and Spatial Regulation of Land Carbon Sinks,MNR(CUG-SRCS-0002)the Open Fund of Hubei Key Laboratory of Regional Ecological Process and Environmental Evolution(REEC-OF-202405).
文摘Accurately assessing the carbon sequestration capacity of forests is crucial for mitigating climate change.Traditional methods for estimating Gross Primary Productivity(GPP)of vegetation involve significant uncertainties.As a novel remote sensing approach,Solar-Induced chlorophyll Fluorescence(SIF)is directly related to photosynthesis and has demonstrated strong correlations with GPP across various ecosystems,climate zones,and spatial scales.Current GPP estimation methods based on SIF include Light Use Efficiency(LUE)models,the SCOPE process models,and the latest mechanistic light response(MLR)models.Future research should focus on improving the mechanistic understanding of SIF-related processes and promoting the integration of multi-source remote sensing data with SIF-based modeling to enhance the accuracy and universality of GPP estimation.
基金financial support of the National Natural Science Foundation of China(No.52371103)the Fundamental Research Funds for the Central Universities,China(No.2242023K40028)+1 种基金the Open Research Fund of Jiangsu Key Laboratory for Advanced Metallic Materials,China(No.AMM2023B01).financial support of the Research Fund of Shihezi Key Laboratory of AluminumBased Advanced Materials,China(No.2023PT02)financial support of Guangdong Province Science and Technology Major Project,China(No.2021B0301030005)。
文摘Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.
基金supported by the National Natural Science Foundation of China(Grant Nos.42120104008 and 42307214)the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20230620).
文摘Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective Coriolis condition,the velocity component parallel to the rotational axis exerts no influence on the magnitude of Coriolis acceleration.This circumstance implies a potential mitigation of the Coriolis force's deflective impact.Regrettably,extant investigations predominantly emphasize the dilative and compressive Coriolis effects,largely neglecting the pragmatic import of the deflective Coriolis condition.In pursuit of this gap,a series of discrete element method(DEM)simulations have been conducted to scrutinize the feasibility of centrifugal modelling for dry granular run-out processes under deflective Coriolis conditions.The findings concerning the deflective Coriolis effect reveal a consistent rise in the run-out distance by 2%–16%,a modest increase in bulk flow velocity of under 4%,and a slight elevation in average flow depth by no more than 25%.These alterations display smaller dependence on the specific testing conditions due to the granular flow undergoing dual deflections in opposing directions.This underscores the significance and utility of the deflective Coriolis condition.Notably,the anticipated reduction in error in predicting the final run-out distance is substantial,potentially reaching a 150%improvement compared to predictions made under the dilative and compressive Coriolis conditions.Therefore,the deflective Coriolis condition is advised when the final run-out distance of the granular flow is the main concern.To mitigate the impact of Coriolis acceleration,a greater initial height of the granular column is recommended,with a height/width ratio exceeding 1,as the basal friction of the granular material plays a crucial role in mitigating the deflective Coriolis effect.For more transverse-uniform flow properties,the width of the granular column should be as large as possible.
基金partially funded by the National Natural Science Foundation of China(62273215)。
文摘Integrated continuous stirred-tank reactors and distillation columns with recycle(CSTR-DC-recycle)are essential components in chemical processes.This paper proposes a method to establish a normal operating zone(NOZ)model to represent allowable variations of the CSTR-DC-recycle chemical processes.The NOZ is a geometric space containing all safe operating points of the CSTR-DC-recycle chemical processes,so that it is an effective model for process monitoring.The novelty of the proposed method is to establish the NOZ model based on boundary points.The boundary points make it possible to capture the actual geometric space irrespective of the space shape.In contrast,existing methods represent the NOZ of processes by fixed mathematical models such as ellipsoidal and convex-hull models;they are not suitable for the CSTR-DC-recycle chemical processes whose NOZs cannot be exactly defined by fixed mathematical structures.Simulated case studies based on Aspen Hysys software are given to illustrate the proposed method.
基金supported by the National Key Program for Developing Basic Science(Nos.2022YFF0801702 and 2022YFE0106600)the National Natural Science Foundation of China(Nos.42175060 and 42175021)the Jiangsu Province Science Foundation(No.BK20250200302).
文摘The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.
基金funded by the National Natural Science Foundation of China (41571066, 41601077, and 41771068)the Strategic Priority Research Pro gram of the Chinese Academy of Sciences (CAS) (XDA20100102, XDA19070204)+2 种基金the CAS "Light of West China" Programthe Youth Innovation Promo tion Association CAS (2018460)the Program of China Scholarship Council (201804910129)
文摘The Tibetan Plateau(TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospecting the latest research progress in the simulation of land-surface processes(LSPs) over the past 20 years, this study discusses both the simulation ability of land-surface models(LSMs) and the modification of parameterization schemes from two perspectives, the models' applicability and improved parameterization schemes. Our review suggests that different LSMs can well capture the spatiotemporal variations of the physical quantities of LSPs; but none of them can be fully applied to the plateau, meaning that all need to be revised according to the characteristics specific to the TP. Avoiding the unstable iterative computation and determining the freeze-thaw critical temperature according to the thermodynamic equilibrium equation, the unreasonable freeze-thaw parameterization scheme can be improved. Due to the complex underlying surface of the TP, no parameterization scheme of roughness length can well simulate the various characteristics of the turbulent flux over the TP at different temporal scales. The uniform soil thermodynamic and hydraulic parameterization scheme is unreasonable when it is applied to the plateau, as a result of the strong soil heterogeneity. There is little research on the snow-cover process so far,and the improved scheme has no advantage over the original one due to the lack of some related physical processes. The constant interaction among subprocesses of LSPs makes the improvement of a multiparameterization scheme yield better simulation results. According to the review of existing research, adding high-quality observation stations, developing a parameterization scheme suitable for the special LSPs of the TP, and adjusting the model structures can be helpful to the simulation of LSPs on the TP.
基金The research is jointly supported financially by the National Natural Science Foundation of China under Grant No. 40171016 and 49794030.
文摘On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km<SUP>2</SUP> of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.
基金supported by the National Natural Science Foundation of China(62225302,623B2014,and 62173023).
文摘With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.
文摘Convective processes affect large-scale environments through cloud-radiation interaction, cloud micro- physical processes, and surface rainfall processes. Over the last three decades, cloud-resolving models （CRMs） have demonstrated to be capable of simulating convective-radiative responses to an imposed large-scale forcing. The CRM-produced cloud and radiative properties have been utilized to study the convective- related processes and their ensemble effects on large-scale circulations. This review the recent progress on the understanding of convective processes with the use of CRM simulations, including precipitation processes; cloud microphysical and radiative processes; dynamical processes; precipitation efficiency; diurnal variations of tropical oceanic convection; local-scale atmosphere-ocean coupling processes; and tropical convective-radiative equilibrium states. Two different ongoing applications of CRMs to general circulation models （GCMs） are discussed： replacing convection and cloud schemes for studying the interaction between cloud systems and large-scale circulation, and improving the schemes for climate simulations.
基金Supported by the National Natural Science Foundation of China （60404012, 60674064）, UK EPSRC （GR/N13319 and GR/R10875）, the National High Technology Research and Development Program of China （2007AA04Z193）, New Star of Science and Technology of Beijing City （2006A62）, and IBM China Research Lab 2007 UR-Program.
文摘A batch-to-batch optimal iterative learning control （ILC） strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation （LTVP） model is built for product quality around the nominal trajectories. To address problems of model-plant mismatches, model prediction errors in the previous batch run are added to the model predictions for the current batch run. Then tracking error transition models can be built, and the ILC law with direct error feedback is explicitly obtained, A rigorous theorem is proposed, to prove the convergence of tracking error under ILC, The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC.
基金Supported by the National Creative Research Groups Science Foundation of China （60721062） and the National High Technology Research and Development Program of China （2007AA04Z162）.
文摘An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.
基金Supported by National Basic Research Program of China(973 Program,Grant No.2011CB706802)National Natural Science Foundation of China(Grant No.51205420)+1 种基金Program for New Century Excellent Talents in University of China(Grant No.NCET-13-0593)Hunan Provincial Natural Science Foundation of China(Grant No.14JJ3011)
文摘Many high-quality forging productions require the large-sized hydraulic press machine（HPM） to have a desirable dynamic response. Since the forging process is complex under the low velocity, its response is difficult to estimate. And this often causes the desirable low-velocity forging condition difficult to obtain. So far little work has been found to estimate the dynamic response of the forging process under low velocity. In this paper, an approximate-model based estimation method is proposed to estimate the dynamic response of the forging process under low velocity. First, an approximate model is developed to represent the forging process of this complex HPM around the low-velocity working point. Under guaranteeing the modeling performance, the model may greatly ease the complexity of the subsequent estimation of the dynamic response because it has a good linear structure. On this basis, the dynamic response is estimated and the conditions for stability, vibration, and creep are derived according to the solution of the velocity. All these analytical results are further verified by both simulations and experiment. In the simulation verification for modeling, the original movement model and the derived approximate model always have the same dynamic responses with very small approximate error. The simulations and experiment finally demonstrate and test the effectiveness of the derived conditions for stability, vibration, and creep, and these conditions will benefit both the prediction of the dynamic response of the forging process and the design of the controller for the high-quality forging. The proposed method is an effective solution to achieve the desirable low-velocity forging condition.
基金National Basic Research Program of China (973 Program) (2009CB421505)National Natural Science Foundation of China (40775036)Knowledge Innovation Program of Chinese Academy of Sciences (IAP07214)
文摘The detailed surface rainfall processes associated with landfalling typhoon Kaemi（2006） are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction （NCEP） / Global Data Assimilation System （GDAS） data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared （RMS） difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate （0.753 mm h^-1） and the observed rain rate （0.833 mm h^-1）. The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean Ps mainly comes from large-scale convergence （QWVF） and local vapor loss （positive QWVT）. Large underestimation （about 15%） of Ps will occur if QWVT and QCM （cloud source/sink） are not considered as contributors to Ps ,QWVF accounts for the variation of P during most of the integration time, while it is not always a contributor to Ps,Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to Ps - Surface rainfall is a result ofmulti-timescale interactions. QWVE possesses the longest time scale and the lowest frequeney the second and QCM of variation with time and may exert impact on P on longer time scales. QWVF possesses longest time scale and lowest frequency and can explain most of the variation of Ps. QWVT possess shorter time scales and higher frequencies, which can explain more detailed variations in Ps. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of QWVT in rainfall-free regions contribute less to that of the domain-mean QWVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of QWVF in rainfall regions are the main contributors to that of the domain-mean QWVF, then the main contributors to the surface rain rate before the afternoon of 28 July.
基金supported by the National Key Research and Development Program of China(No.2018YFC0213500)the National Key Research and Development Program of China(No.2017YFC0213003).
文摘Beijing faces the challenge of high levels of ozone(O_(3))pollution.In this study,the Weather Research and Forecasting model and Community Multiscale Air Qualitymodel(CMAQ)were used to simulate atmospheric O_(3) concentrations in Beijing.To investigate the formation mechanisms and source contributions of O_(3) pollution in different regions of Beijing,process analysis and the integrated source apportionmentmethodwithin the CMAQwere applied to O_(3) concentrations in the summer of 2018.The process analysis results showed that vertical diffusion was the major contributor to O_(3) concentrations at all receptor sites in Beijing,at>65.94μg/(m^(3)·hr).Gas-phase chemical reactions consumed a significant amount of O_(3) in urban and inner suburban areas(>−5.57μg/(m^(3)·hr)),while near-surface chemical reactions made positive contributions in outer suburban areas(>4.72μg/(m^(3)·hr)).The O_(3) formation chemical reactions indicated that NO titration,which removes O_(3) at night-time,mainly occurred in urban areas.The weaker chemical reactions occurring near the surface in outer suburbs suggested that suburban-area O_(3) was produced in the upper atmospheric layers and was transported vertically to the lower layers.The O_(3) source apportionment results showed that boundary contributions were the dominant contributor to O_(3) pollution in Beijing(>40%).The contribution of non-local emissions to O_(3) levels was significantly greater in the outer suburbs than in urban and inner suburban areas due to topography.This study increases the understanding of the complex processes of O_(3) formation in different areas of Beijing and informs the implementation of O_(3) control plans.
基金supported by the National Natural Science Foundation of China(Nos.42007178 and 41907327)the Natural Science Foundation of Hubei(Nos.2020CFB463 and 2019CFB372)+4 种基金China Geological Survey(Nos.DD20160304 and DD20190824)Fundamental Research Funds for the Central Universities(Nos.CUG 190644 and CUGL180817)National Key Research and Development Program(No.2019YFC1805502)Key Laboratory of Karst Dynamics,MNR and GZAR(Institute of Karst Geology,CAGS)Guilin(No.KDL201703)Key Laboratory of Karst Ecosystem and Treatment of Rocky Desertification,MNR and IRCK by UNESCO(No.KDL201903)。
文摘To investigate groundwater flow and solute transport characteristics of the karst trough zone in China,tracer experiments were conducted at two adjacent typical karst groundwater flow systems(Yuquandong(YQD)and Migongquan(MGQ))in Sixi valley,western Hubei,China.Highresolution continuous monitoring was utilized to obtain breakthrough curves(BTCs),which were then analyzed using the multi-dispersion model(MDM)and the two-region nonequilibrium model(2RNE)with basic parameters calculated by CXTFIT and QTRACER2.Results showed that:(1)YQD flow system had a complex infiltration matrix with overland flow,conduit flow and fracture flow,while the MGQ flow system was dominated by conduit flow with fast flow transport velocity,but also small amount of fracture flow there;(2)They were well fitted based on the MDM(R^2=0.928)and 2RNE(R^2=0.947)models,indicating that they had strong adaptability in the karst trough zone;(3)conceptual models for YQD and MGQ groundwater systems were generalized.In YQD system,the solute was transported via overland flow during intense rainfall,while some infiltrated down into fissures and conduits.In MGQ system,most were directly transported to spring outlet in the fissureconduit network.
基金financially supported by the National Natural Science Foundation of China(41877204)Foundation for Innovative Research Groups of the National Natural Science Foundation of China(41521001)the China Postdoctoral Science Foundation(2018M642944)。
文摘Hydrogeochemistry and factor analysis were conducted together to assess the distribution and the major geochemical processes in fluoride-contaminated shallow groundwater in the Yuncheng Basin.Spatially,fluoride concentration was low(<1.5 mg/L)in the southern piedmont plain,medium(<4 mg/L)in the central basin,and high(up to 14.1 mg/L)in Kaolao lowland areas in shallow aquifers.A three-factor principal component analysis model explained over 75.1%of the total variance.Sediment weathering leaching and evapotranspiration were recognized as the first primary hydrochemical processes response for the groundwater chemistry and explained the largest portion(42.1%)of the total variance.Factor two reflects the negative influence of human activities,with a positive loading of NO3^-and HCO3^-,and negative loading of well depth.Fluoride-bearing mineral dissolution and alkaline condition was ranked as the third factors responding for groundwater chemistry and explained 11.2%of the total variance.
