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
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
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
To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new lig...To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.展开更多
A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary ...A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary micro-variables evolution at different temperatures and their interaction.The dislocation density was incorporated into the model to capture the effect of creep deformation on precipitation.Quantitative transmission electron microscopy and experimental data obtained from a previous study were used to calibrate the model.Subsequently,the developed constitutive model was implemented in the finite element(FE)software ABAQUS via the user subroutines for TSCA process simulation and the springback prediction of an integral panel.A TSCA test was performed.The result shows that the maximum radius deviation between the formed plate and the simulation results is less than 0.4 mm,thus validating the effectiveness of the developed constitutive model and FE model.展开更多
Mo has been widely reported as a conducive element for the corrosion resistance of massive alloy sys-tems.However,the mechanism of Mo optimizing the corrosion resistance is complicated,and in-depth studies are still r...Mo has been widely reported as a conducive element for the corrosion resistance of massive alloy sys-tems.However,the mechanism of Mo optimizing the corrosion resistance is complicated,and in-depth studies are still required.The present work comprehensively and quantitatively studied the critical influ-ences of Mo on the passivation and repassivation behavior of CoCrFeNi HEA based on the dissolution-diffusion-deposition model proposed in our previous work.The experimental results indicated that Mo remarkably eliminated the metastable pitting corrosion,significantly improved the breakdown potential and perfectly protected the CoCrFeNiMo_(0.2)HEA from pitting corrosion.The modelling and X-ray photo-electron spectroscopy(XPS)results both show that in the passivation process,MoO_(2)was the last product to deposit,thereby existing in the outer layer of the passive film.Mo addition increased the Cr content by weakening the deposition of Fe_(2)O_(3)and Fe_(3)O_(4)and also improved the Cr_(2)O_(3)/Cr(OH)3 ratio by promot-ing deprotonation of Cr(OH)_(3),thus enhancing the quality of passive film.Besides,when pitting corrosion occurred,MoO_(2),MoO_(3),and FeMoO_(4)were the first products to deposit and accelerated the repassivation process of HEA by timely covering the matrix in the pit cavity,thereby preventing further corrosion of the matrix.展开更多
With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.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
This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving ...This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.展开更多
This study systematically investigates the hot deformation behavior and microstructural evolution of CoNiV medium-entropy alloy(MEA)in the temperature range of 950-1100℃ and strain rates of 0.001-1 s^(-1).The Arrheni...This study systematically investigates the hot deformation behavior and microstructural evolution of CoNiV medium-entropy alloy(MEA)in the temperature range of 950-1100℃ and strain rates of 0.001-1 s^(-1).The Arrhenius model and machine learning model were developed to forecast flow stresses at various conditions.The predictive capability of both models was assessed using the coefficients of determination(R^(2)),average absolute relative error(AARE),and root mean square error(RMSE).The findings show that the osprey optimization algorithm convolutional neural network(OOA-CNN)model outperforms the Arrhenius model,achieving a high R^(2) value of 0.99959 and lower AARE and RMSE values.The flow stress that the OOA-CNN model predicted was used to generate power dissipation maps and instability maps under different strains.Finally,combining the processing map and microstructure characterization,the ideal processing domain was identified as 1100℃ at strain rates of 0.01-0.1 s^(-1).This study provided key insights into optimizing the hot working process of CoNiV MEA.展开更多
Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured a...Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured and unstructured sources—including process parameters, experimental results, simulation data, and textual specifications—these systems address longstanding challenges such as manual parameter tuning, subjective expert reliance, and the gap between theoretical models and industrial application. This paper reviews the key barriers to broader adoption of large language model-based agent systems, including unstable software interfaces, limited dynamic modeling accuracy, and difficulties in multimodal data integration, which hinder scalable deployment. We then survey recent progress in domain-specific foundation models, model interpretability techniques, and industrial-grade validation platforms. Building on these insights, we propose a technical framework centered on three pillars: multimodal task perception, autonomous planning, and knowledge-driven iterative optimization. This framework supports adaptive reasoning and robust execution in complex simulation environments. Finally, we outline a next-generation intelligent paradigm where natural language-driven agent workflows unify high-level strategic intent with automated task execution. The paper concludes by identifying future research directions to enhance robustness, adaptability, and safety, paving the way for practical integration of large language model based agent systems into industrial-scale chemical process simulation.展开更多
Renewable energies including solar and wind are intermittent,causing difficulty in connection to conventional power grids due to instability of output duty.Compressed air energy storage(CAES)in underground caverns has...Renewable energies including solar and wind are intermittent,causing difficulty in connection to conventional power grids due to instability of output duty.Compressed air energy storage(CAES)in underground caverns has been considered a potential large-scale energy storage technology.In order to explore the gas injection char-acteristic of underground cavern,a detailed thermodynamic model of the system is established in the process modelling software gPROMS.The four subsystem models,i.e.the compressor,heat exchanger,underground cavern storage and expander,are connected with inlet-outlet equilibrium of flow rate/pressure/temperature to form an integrated CAES system model in gPROMS.The maximum air pressure and temperature in the cavern are focused to interrogate the critical condition of the cavern during the injection process.When analyzing the mass flow rate-pressure ratio relationship,it’s found that under specified operating conditions,an increase in mass flow rate can lead to a higher pressure ratio.Compression power demand also escalates significantly with increasing mass flow rates,underscoring the system’s energy-intensive nature.Additionally,the cooler outlet energy rate progressively decreases,becoming increasingly negative as the mass flow rate increases.These in-sights offer critical theoretical foundations for optimizing practical efficiency of CAES.展开更多
During the excavation of deep engineering,high in situ stress is one prominent feature that often causes instability in the vicinity of underground openings.The propagation and coalescence of cracks in the surrounding...During the excavation of deep engineering,high in situ stress is one prominent feature that often causes instability in the vicinity of underground openings.The propagation and coalescence of cracks in the surrounding rock are characterized by anisotropy under a true triaxial stress state and play a crucial role in the development of stress-induced engineering disasters.Thus,a three-dimensional anisotropic fracturing model of hard rock is proposed to interpret fracturing activities and evaluate the mechanical property deterioration under complex stress conditions.This anisotropic fracturing model is derived from the evolution of microcracks and attributes the inelastic deformation of hard rock to crack propagation and coalescence.Through analyzing the competitive process of crack propagation in different orientations,the stress-induced anisotropic fracturing characteristics and the post-peak brittle-ductile transition could be revealed.Finally,the accuracy and effectiveness of this model are validated.Results show that this proposed anisotropic fracturing model can elucidate the primary characteristics observed in triaxial compression tests,which offers a fresh perspective on comprehending the failure process of hard rock.展开更多
Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However...Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.展开更多
Gelugpa is the most influential extant religious sect of Tibetan Buddhism,which is the spiritual prop for Tibetans,with thousands of monasteries and followers in Tibetan areas of China.Studies on the spatial diffusion...Gelugpa is the most influential extant religious sect of Tibetan Buddhism,which is the spiritual prop for Tibetans,with thousands of monasteries and followers in Tibetan areas of China.Studies on the spatial diffusion processes of Gelugpa can not only reveal its historical geographical development but also lay the foundation for anticipating its future development trend.However,existing studies on Gelugpa lack geographical perspective,making it difficult to explore the spatial characteristics.Furthermore,the prevailing macro-perspective overlooks spatiotemporal heterogeneity in diffusion processes.Therefore,taking monastery as the carrier,this study establishes a multi-level diffusion model to reconstruct the diffusion networks of Gelugpa monasteries,as well as a framework to explore the detailed features in the spatial diffusion processes of Gelugpa in Tibetan areas of China based on a geodatabase of Gelugpa monastery.The results show that the multi-level diffusion model has a considerable applicability in the reconstruction of the diffusion networks of Gelugpa monasteries.Gelugpa monasteries in the Three Tibetan Inhabited Areas present disparate spatial diffusion processes with diverse diffusion bases,speeds,stages,as well as diffusion regions and centers.A powerful single-center diffusion-centered Gandan Monastery was rapidly formed in U-Tsang.Kham experienced a slower and more varied spatial diffusion process with multiple diffusion systems far apart from each other.The spatial diffusion process of Amdo was the most complex,with the highest diffusion intensity.Amdo possessed the most influential diffusion centers,with different diffusion shapes and diffusion ranges crossing and overlapping with each other.Multiple natural and human factors may contribute to the formation of Gelugpa monasteries.This study contributes to the understanding of the geography of Gelugpa and provides reference to studies on religion diffusion.展开更多
The human body displays various symptoms of altitude sickness due to hypoxia in environments with low pressure and oxygen levels.While existing studies are primarily focused on the adverse effects of hypoxia and oxyge...The human body displays various symptoms of altitude sickness due to hypoxia in environments with low pressure and oxygen levels.While existing studies are primarily focused on the adverse effects of hypoxia and oxygen supplementation strategies at high altitudes,there is a notable gap in understanding the fundamental mechanisms driving altitude hypoxia.In this context,we propose a sophisticated two-way fluid–structure interaction model that simulates respiratory processes with precisely structured and deformable upper airways.This model reveals that,under identical pressure differentials at the airway’s inlet and outlet,the inspiratory air volume remains largely consistent and is minimally affected by specific pressure changes.However,an increase in the pressure differential enhances gas inhalation efficiency.Furthermore,airway morphology emerges as a pivotal factor influencing oxygen intake.Distorted airway shapes create areas of high flow velocity,where low wall pressure hampers effective airway opening,thus diminishing gas inhalation.These results may shed light on the effects of low-pressure conditions and upper airway structure on respiratory dynamics at high altitudes and inform the development of effective oxygen supply strategies.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
The metal cutting process is accompanied by complex stress field,strain field,temperature field.The comprehensive effects of process parameters on chip morphology,cutting force,tool wear and residual stress are comple...The metal cutting process is accompanied by complex stress field,strain field,temperature field.The comprehensive effects of process parameters on chip morphology,cutting force,tool wear and residual stress are complex and inter-connected.Finite element method(FEM)is considered as an effective method to predict process variables and reveal microscopic physical phenomena in the cutting process.Therefore,the finite element(FE)simulation is used to research the conventional and micro scale cutting process,and the differences in the establishment of process variable FE simulation models are distinguished,thereby improving the accuracy of FE simulation.The reliability and effectiveness of FE simulation model largely depend on the accuracy of the simulation method,constitutive model,friction model,damage model in describing mesh element,the dynamic mechanical behavior of materials,the tool-chip-workpiece contact process and the chip formation mechanism.In this paper,the FE models of conventional and micro process variables are comprehensively and up-to-date reviewed for different materials and machining methods.The purpose is to establish a FE model that is more in line with the real cutting conditions,and to provide the possibility for optimizing the cutting process variables.The development direction of FE simulation of metal cutting process is discussed,which provides guidance for future cutting process modeling.展开更多
Geomaterials with inferior hydraulic and strength characteristics often need improvement to enhance their engineering behaviors.Traditional ground improvement techniques require enormous mechanical effort or synthetic...Geomaterials with inferior hydraulic and strength characteristics often need improvement to enhance their engineering behaviors.Traditional ground improvement techniques require enormous mechanical effort or synthetic chemicals.Sustainable stabilization technique such as microbially induced calcite precipitation(MICP)utilizes bacterial metabolic processes to precipitate cementitious calcium carbonate.The reactive transport of biochemical species in the soil mass initiates the precipitation of biocement during the MICP process.The precipitated biocement alters the hydro-mechanical performance of the soil mass.Usually,the flow,deformation,and transport phenomena regulate the biocementation technique via coupled bio-chemo-hydro-mechanical(BCHM)processes.Among all,one crucial phenomenon controlling the precipitation mechanism is the encapsulation of biomass by calcium carbonate.Biomass encapsulation can potentially reduce the biochemical reaction rate and decelerate biocementation.Laboratory examination of the encapsulation process demands a thorough analysis of associated coupled effects.Despite this,a numerical model can assist in capturing the coupled processes influencing encapsulation during the MICP treatment.However,most numerical models did not consider biochemical reaction rate kinetics accounting for the influence of bacterial encapsulation.Given this,the current study developed a coupled BCHM model to evaluate the effect of encapsulation on the precipitated calcite content using a micro-scale semiempirical relationship.Firstly,the developed BCHM model was verified and validated using numerical and experimental observations of soil column tests.Later,the encapsulation phenomenon was investigated in the soil columns of variable maximum calcite crystal sizes.The results depict altered reaction rates due to the encapsulation phenomenon and an observable change in the precipitated calcite content for each maximum crystal size.Furthermore,the permeability and deformation of the soil mass were affected by the simultaneous precipitation of calcium carbonate.Overall,the present study comprehended the influence of the encapsulation of bacteria on cement morphology-induced permeability,biocement-induced stresses and displacements.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
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.
基金support provided by the National Natural Science Foundation of China(22122802,22278044,and 21878028)the Chongqing Science Fund for Distinguished Young Scholars(CSTB2022NSCQ-JQX0021)the Fundamental Research Funds for the Central Universities(2022CDJXY-003).
文摘To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.
基金supported by the National Key R&D Program of China(No.2021YFB3400900)the National Natural Science Foundation of China(Nos.52175373,52205435)+1 种基金Natural Science Foundation of Hunan Province,China(No.2022JJ40621)the Innovation Fund of National Commercial Aircraft Manufacturing Engineering Technology Center,China(No.COMACSFGS-2022-1875)。
文摘A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary micro-variables evolution at different temperatures and their interaction.The dislocation density was incorporated into the model to capture the effect of creep deformation on precipitation.Quantitative transmission electron microscopy and experimental data obtained from a previous study were used to calibrate the model.Subsequently,the developed constitutive model was implemented in the finite element(FE)software ABAQUS via the user subroutines for TSCA process simulation and the springback prediction of an integral panel.A TSCA test was performed.The result shows that the maximum radius deviation between the formed plate and the simulation results is less than 0.4 mm,thus validating the effectiveness of the developed constitutive model and FE model.
基金funded by the National Natural Science Foun-dation of China(Grant Nos.U1960203,52004060,52325406,and 52174308)Science Fund for Distinguished Young Scholars of Liaon-ing Province(Grant No.2023JH6/100500008)Fundamental Re-search Funds for the Central Universities(Grant Nos.N2125017 and N2225031).Special thanks are due to the instrumental analysis from the Analytical and Testing Centre,Northeastern University.
文摘Mo has been widely reported as a conducive element for the corrosion resistance of massive alloy sys-tems.However,the mechanism of Mo optimizing the corrosion resistance is complicated,and in-depth studies are still required.The present work comprehensively and quantitatively studied the critical influ-ences of Mo on the passivation and repassivation behavior of CoCrFeNi HEA based on the dissolution-diffusion-deposition model proposed in our previous work.The experimental results indicated that Mo remarkably eliminated the metastable pitting corrosion,significantly improved the breakdown potential and perfectly protected the CoCrFeNiMo_(0.2)HEA from pitting corrosion.The modelling and X-ray photo-electron spectroscopy(XPS)results both show that in the passivation process,MoO_(2)was the last product to deposit,thereby existing in the outer layer of the passive film.Mo addition increased the Cr content by weakening the deposition of Fe_(2)O_(3)and Fe_(3)O_(4)and also improved the Cr_(2)O_(3)/Cr(OH)3 ratio by promot-ing deprotonation of Cr(OH)_(3),thus enhancing the quality of passive film.Besides,when pitting corrosion occurred,MoO_(2),MoO_(3),and FeMoO_(4)were the first products to deposit and accelerated the repassivation process of HEA by timely covering the matrix in the pit cavity,thereby preventing further corrosion of the matrix.
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
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 by the National Research Council of Thailand(NRCT)under Contract No.N42A670894.
文摘This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.
基金supported by the National Natural Science Foundation of China(NSFC)(Grant No.51901078)the Central Guidance for Local Scientific and Technological Development Funding Project(Grant No.236Z1003G)+3 种基金the Science and Technology Plan Project of Tangshan City(Grant No.24130207C)the Natural Science Foundation of Hebei Province(Grant No.E2022209070)the High-level Talent Project of Hebei(Grant No.E2019100007)the Open Project Program of Key Laboratory of Ministry of Education for Modern Metallurgy Technology(Grant No.2024YJKF02).
文摘This study systematically investigates the hot deformation behavior and microstructural evolution of CoNiV medium-entropy alloy(MEA)in the temperature range of 950-1100℃ and strain rates of 0.001-1 s^(-1).The Arrhenius model and machine learning model were developed to forecast flow stresses at various conditions.The predictive capability of both models was assessed using the coefficients of determination(R^(2)),average absolute relative error(AARE),and root mean square error(RMSE).The findings show that the osprey optimization algorithm convolutional neural network(OOA-CNN)model outperforms the Arrhenius model,achieving a high R^(2) value of 0.99959 and lower AARE and RMSE values.The flow stress that the OOA-CNN model predicted was used to generate power dissipation maps and instability maps under different strains.Finally,combining the processing map and microstructure characterization,the ideal processing domain was identified as 1100℃ at strain rates of 0.01-0.1 s^(-1).This study provided key insights into optimizing the hot working process of CoNiV MEA.
文摘Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured and unstructured sources—including process parameters, experimental results, simulation data, and textual specifications—these systems address longstanding challenges such as manual parameter tuning, subjective expert reliance, and the gap between theoretical models and industrial application. This paper reviews the key barriers to broader adoption of large language model-based agent systems, including unstable software interfaces, limited dynamic modeling accuracy, and difficulties in multimodal data integration, which hinder scalable deployment. We then survey recent progress in domain-specific foundation models, model interpretability techniques, and industrial-grade validation platforms. Building on these insights, we propose a technical framework centered on three pillars: multimodal task perception, autonomous planning, and knowledge-driven iterative optimization. This framework supports adaptive reasoning and robust execution in complex simulation environments. Finally, we outline a next-generation intelligent paradigm where natural language-driven agent workflows unify high-level strategic intent with automated task execution. The paper concludes by identifying future research directions to enhance robustness, adaptability, and safety, paving the way for practical integration of large language model based agent systems into industrial-scale chemical process simulation.
基金supported by National Natural Science Foundation of China Excellent Young Scientists Fund Program,Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(grant No.2024ZD1004105)Shandong Excellent Young Scientists Fund Program(Overseas)(grant No.2022HWYQ-020)Shenzhen Science and Technology Program(grant No.JCYJ20220530141016036,GJHZ20240218113359001).
文摘Renewable energies including solar and wind are intermittent,causing difficulty in connection to conventional power grids due to instability of output duty.Compressed air energy storage(CAES)in underground caverns has been considered a potential large-scale energy storage technology.In order to explore the gas injection char-acteristic of underground cavern,a detailed thermodynamic model of the system is established in the process modelling software gPROMS.The four subsystem models,i.e.the compressor,heat exchanger,underground cavern storage and expander,are connected with inlet-outlet equilibrium of flow rate/pressure/temperature to form an integrated CAES system model in gPROMS.The maximum air pressure and temperature in the cavern are focused to interrogate the critical condition of the cavern during the injection process.When analyzing the mass flow rate-pressure ratio relationship,it’s found that under specified operating conditions,an increase in mass flow rate can lead to a higher pressure ratio.Compression power demand also escalates significantly with increasing mass flow rates,underscoring the system’s energy-intensive nature.Additionally,the cooler outlet energy rate progressively decreases,becoming increasingly negative as the mass flow rate increases.These in-sights offer critical theoretical foundations for optimizing practical efficiency of CAES.
基金support from the National Natural Science Foundation of China(Grant No.52209125).
文摘During the excavation of deep engineering,high in situ stress is one prominent feature that often causes instability in the vicinity of underground openings.The propagation and coalescence of cracks in the surrounding rock are characterized by anisotropy under a true triaxial stress state and play a crucial role in the development of stress-induced engineering disasters.Thus,a three-dimensional anisotropic fracturing model of hard rock is proposed to interpret fracturing activities and evaluate the mechanical property deterioration under complex stress conditions.This anisotropic fracturing model is derived from the evolution of microcracks and attributes the inelastic deformation of hard rock to crack propagation and coalescence.Through analyzing the competitive process of crack propagation in different orientations,the stress-induced anisotropic fracturing characteristics and the post-peak brittle-ductile transition could be revealed.Finally,the accuracy and effectiveness of this model are validated.Results show that this proposed anisotropic fracturing model can elucidate the primary characteristics observed in triaxial compression tests,which offers a fresh perspective on comprehending the failure process of hard rock.
基金the financial support from the Strategic Priority Research Program of Chinese Academy of Sciences(XDA21010100)。
文摘Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.
基金supported by the Humanities and Social Sciences Foundation of the Ministry of Education of China(Grant No.18YJAZH140).
文摘Gelugpa is the most influential extant religious sect of Tibetan Buddhism,which is the spiritual prop for Tibetans,with thousands of monasteries and followers in Tibetan areas of China.Studies on the spatial diffusion processes of Gelugpa can not only reveal its historical geographical development but also lay the foundation for anticipating its future development trend.However,existing studies on Gelugpa lack geographical perspective,making it difficult to explore the spatial characteristics.Furthermore,the prevailing macro-perspective overlooks spatiotemporal heterogeneity in diffusion processes.Therefore,taking monastery as the carrier,this study establishes a multi-level diffusion model to reconstruct the diffusion networks of Gelugpa monasteries,as well as a framework to explore the detailed features in the spatial diffusion processes of Gelugpa in Tibetan areas of China based on a geodatabase of Gelugpa monastery.The results show that the multi-level diffusion model has a considerable applicability in the reconstruction of the diffusion networks of Gelugpa monasteries.Gelugpa monasteries in the Three Tibetan Inhabited Areas present disparate spatial diffusion processes with diverse diffusion bases,speeds,stages,as well as diffusion regions and centers.A powerful single-center diffusion-centered Gandan Monastery was rapidly formed in U-Tsang.Kham experienced a slower and more varied spatial diffusion process with multiple diffusion systems far apart from each other.The spatial diffusion process of Amdo was the most complex,with the highest diffusion intensity.Amdo possessed the most influential diffusion centers,with different diffusion shapes and diffusion ranges crossing and overlapping with each other.Multiple natural and human factors may contribute to the formation of Gelugpa monasteries.This study contributes to the understanding of the geography of Gelugpa and provides reference to studies on religion diffusion.
基金National Natural Science Foundation of China(Grant Nos.12072252)the Natural Science Basic Research Plan in Shaanxi Province of China(No.2019JC-02)Guang-kui Xu+1 种基金National Natural Science Foundation of China(Grant No.12302221)Jiu-Tao HangFundamental Research Funds for the Central Universities of China Guang-kui Xu and Jiu-Tao Hang National Natural Science Foundation of China(Grant No.11972361)Dong Wei.
文摘The human body displays various symptoms of altitude sickness due to hypoxia in environments with low pressure and oxygen levels.While existing studies are primarily focused on the adverse effects of hypoxia and oxygen supplementation strategies at high altitudes,there is a notable gap in understanding the fundamental mechanisms driving altitude hypoxia.In this context,we propose a sophisticated two-way fluid–structure interaction model that simulates respiratory processes with precisely structured and deformable upper airways.This model reveals that,under identical pressure differentials at the airway’s inlet and outlet,the inspiratory air volume remains largely consistent and is minimally affected by specific pressure changes.However,an increase in the pressure differential enhances gas inhalation efficiency.Furthermore,airway morphology emerges as a pivotal factor influencing oxygen intake.Distorted airway shapes create areas of high flow velocity,where low wall pressure hampers effective airway opening,thus diminishing gas inhalation.These results may shed light on the effects of low-pressure conditions and upper airway structure on respiratory dynamics at high altitudes and inform the development of effective oxygen supply strategies.
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supported by the National Natural Science Foundation of China(No.52175393)。
文摘The metal cutting process is accompanied by complex stress field,strain field,temperature field.The comprehensive effects of process parameters on chip morphology,cutting force,tool wear and residual stress are complex and inter-connected.Finite element method(FEM)is considered as an effective method to predict process variables and reveal microscopic physical phenomena in the cutting process.Therefore,the finite element(FE)simulation is used to research the conventional and micro scale cutting process,and the differences in the establishment of process variable FE simulation models are distinguished,thereby improving the accuracy of FE simulation.The reliability and effectiveness of FE simulation model largely depend on the accuracy of the simulation method,constitutive model,friction model,damage model in describing mesh element,the dynamic mechanical behavior of materials,the tool-chip-workpiece contact process and the chip formation mechanism.In this paper,the FE models of conventional and micro process variables are comprehensively and up-to-date reviewed for different materials and machining methods.The purpose is to establish a FE model that is more in line with the real cutting conditions,and to provide the possibility for optimizing the cutting process variables.The development direction of FE simulation of metal cutting process is discussed,which provides guidance for future cutting process modeling.
基金the funding support from the Ministry of Education,Government of India,under the Prime Minister Research Fellowship programme(Grant Nos.SB21221901CEPMRF008347 and SB22230217CEPMRF008347).
文摘Geomaterials with inferior hydraulic and strength characteristics often need improvement to enhance their engineering behaviors.Traditional ground improvement techniques require enormous mechanical effort or synthetic chemicals.Sustainable stabilization technique such as microbially induced calcite precipitation(MICP)utilizes bacterial metabolic processes to precipitate cementitious calcium carbonate.The reactive transport of biochemical species in the soil mass initiates the precipitation of biocement during the MICP process.The precipitated biocement alters the hydro-mechanical performance of the soil mass.Usually,the flow,deformation,and transport phenomena regulate the biocementation technique via coupled bio-chemo-hydro-mechanical(BCHM)processes.Among all,one crucial phenomenon controlling the precipitation mechanism is the encapsulation of biomass by calcium carbonate.Biomass encapsulation can potentially reduce the biochemical reaction rate and decelerate biocementation.Laboratory examination of the encapsulation process demands a thorough analysis of associated coupled effects.Despite this,a numerical model can assist in capturing the coupled processes influencing encapsulation during the MICP treatment.However,most numerical models did not consider biochemical reaction rate kinetics accounting for the influence of bacterial encapsulation.Given this,the current study developed a coupled BCHM model to evaluate the effect of encapsulation on the precipitated calcite content using a micro-scale semiempirical relationship.Firstly,the developed BCHM model was verified and validated using numerical and experimental observations of soil column tests.Later,the encapsulation phenomenon was investigated in the soil columns of variable maximum calcite crystal sizes.The results depict altered reaction rates due to the encapsulation phenomenon and an observable change in the precipitated calcite content for each maximum crystal size.Furthermore,the permeability and deformation of the soil mass were affected by the simultaneous precipitation of calcium carbonate.Overall,the present study comprehended the influence of the encapsulation of bacteria on cement morphology-induced permeability,biocement-induced stresses and displacements.
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.
