Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in p...The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in passenger boarding,alighting,and onboard movements.Although there are initial findings on the effectiveness of some of the mitigation policies(such as face-covering and ventilation),evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways,boarding and alighting patterns,and seating capacity control.This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA,in which it brings crucial insights on combating current and future epidemics.We use an agent-based simulation model(ABSM)based on standard design characteristics for urban buses in USA and two different service frequency settings(10-min and 20-min headways).We find that wearing face-coverings(surgical masks)significantly reduces onboard transmission rates,from no mitigation rates of 85%in higher-frequency buses and 75%in lower-frequency buses to 12.5%.The most effective prevention outcome is the combination of KN-95 masks,open window policies,and half-capacity seating control during higher-frequency bus services,with an outcome of nearly 0%onboard infection rate.Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design,which is crucial to ensuring passenger safety.The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies.展开更多
Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to i...Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.展开更多
An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. This model was built to approximately rep...An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. This model was built to approximately reproduce some essential findings that were previously reported for a rather complex model of diabetes progression. Our models are translations of basicelements of this previously reported system dynamics model of diabetes. The system dynamics model, which mimics diabetes progression over an aggregated US population, was disaggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. The four estimated models attempted to replicate stock counts representing disease states in the system dynamics model while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent’s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. All three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model, although behavioral factors appeared to contribute more than the elderliness factor. The results illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.展开更多
Grain security is one of the most important issues worldwide.Many developing countries,including China,have adopted the Agriculture Support Price(ASP)program to stimulate farmers’enthusiasm for growing grain,to ensur...Grain security is one of the most important issues worldwide.Many developing countries,including China,have adopted the Agriculture Support Price(ASP)program to stimulate farmers’enthusiasm for growing grain,to ensure self-sufficiency in grain and the stable development of the grain market.To propose decision support for the government in designing a more reasonable support price in the ASP program,we formulate an agent-based model to simulate the operation of the wheat market in the harvest period.To formulate the formation process of the market price influenced by farmers’expected sale price,processors’expected purchase price,and the ASP,the time series and regression methods are adopted.Based on the proposed market price model,to quantitatively analyze the grain transaction process and the ASP program’s impacts on market agents,we develop an agent-based simulation model to describe the adaptive evolution and interaction among market agents.Furthermore,we validate and implement the simulation model with public wheat market data.Finally,insights and suggestions about the decision of the ASP program are provided.展开更多
Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and find...Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and finding shelter are vital for search and rescue managers.At the same time,many unpredicted challenges,such as the sudden increase in travel demand,shifts in public behavior,and the change in the regular transport supply,may arise due to evacuation conditions,which lead to different situations.This paper aims to introduce an approach for quick decision-making and timely evacuation response required by establishing a situation-aware system to minimize these risks and ensure the success of the evacuation plans,to support and predict current and future actions within the dynamic space of the crisis.The main contribution is innovating a Situation-Aware Emergency Evacuation(SAEE)model to enable crisis managers and evacuees to make the right decisions by providing timely and reliable information about the situation.This method is utilized in two situations:designing the emergency evacuation plan and finding the shortest/safest routes to reduce travel time for evacuees.Therefore,a hybrid approach is introduced,which involves a Fuzzy Inference System(FIS)and Deep Long Short-Term Memory(DLSTM)algorithm to identify,infer,and extract the existing situation at different levels(e.g.people,vehicles,and surroundings)after a foreshock using multi-agent-based simulation.The method proposed was simulated in the traffic network of District 6 of Tehran,the capital of Iran.The model results show that the evacuees'spatial knowledge and perception,as well as awareness of the situation of other agents and their surroundings,led to a significant(40%)reduction in the complete evacuation time.This time is considered the most pivotal factor in saving human lives and their arrival in safer areas.The role of situation awareness systems and increasing human cognition and perception can significantly help in this matter.展开更多
This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionar...This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionary processes.By representing agents and their defined environments with probabilistic interactions,ABM allows the assessment of the effects of individual behavior at the micro level on the greater social phenomena at the macro level.The review looks into the applications of ABM in portraying some of the key components of emotions and cognition-empathy,cooperation,decision making,and emotional transmission-and analyzes the problems including scalability,empirical validation,and description of sensitive emotional states.The most important conclusion is that merging ABM with information neurobiological data and artificial intelligence(AI)techniques would allow for deepening the interactions within the system and enhancing its responsiveness to stimuli.This review highlights approaches that aim to exploit the ABM methodology more fully and integrates methods from biology,neuroscience,and engineering.This integration could contribute to our understanding of the human behavior evolution and adaptation within systems relevant to policymaking,healthcare,and education.展开更多
Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subs...Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.展开更多
There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes.Given the significant damage incurred by tornadoes upon communities,community resilience analyses for tornado-stricken com...There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes.Given the significant damage incurred by tornadoes upon communities,community resilience analyses for tornado-stricken communities have been gaining momentum.As the community resilience analysis aims to guide how to lay out effective hazard mitigation strategies to decrease damage and improve recovery,a comprehensive and accurate approach is necessary.Agent-based modeling,an analysis approach in which different types of agents are created with their properties and behavior clearly defined to simulate the processes of those agents in an external environ-ment,is the most comprehensive and accurate approach so far to conducting community resilience simulations and investigating the decision-making for mitigation and recovery under natural hazards.In this paper,agent-based models(ABMs)are created to simulate the recovery process of a virtual testbed based on the real-world community in Joplin City,MO.The tornado path associated with the real-world tornado event that occurred in May 2011 is adopted in the tornado hazard modeling for the Joplin testbed.In addition,agent-based models are created for another virtual community in the Midwest United States named Centerville using an assumed tornado scenario of the same EF-scale as that in Joplin.The effects of hazard mitigation strategies on the two communities are also explored.A comparison between the analysis results of these two testbeds can indicate the influence of the characteristics of a tornado-prone community on the resilience of the community as well as on the effects of hazard mitigation strategies.It is observed that a community’s level of development significantly impacts the tornado resilience.In addition,the effects of a specific type of hazard mitigation strategy on the recovery process are contingent upon testbed characteristics.展开更多
The global rise in energy demand, particularly in remote and sparsely populated regions, necessitates innovative and cost-effective electrical distribution solutions. Traditional Rural Electrification (RE) methods, li...The global rise in energy demand, particularly in remote and sparsely populated regions, necessitates innovative and cost-effective electrical distribution solutions. Traditional Rural Electrification (RE) methods, like Conventional Rural Electrification (CRE), have proven economically unfeasible in such areas due to high infrastructure costs and low electricity demand. Consequently, Unconventional Rural Electrification (URE) technologies, such as Capacitor Coupled Substations (CCS), are gaining attention as viable alternatives. This study presents the design and simulation of an 80 kW CCS system, which taps power directly from a 132 kV transmission line to supply low-voltage consumers. The critical components of the CCS, the capacitors are calculated, then a MATLAB/Simulink model with the attained results is executed. Mathematical representation and state-space representation for maintaining the desired tapped voltage area also developed. The research further explores the feasibility and operational performance of this CCS configuration, aiming to address the challenges of rural electrification by offering a sustainable and scalable solution. The results show that the desired value of the tapped voltage can be achieved at any level of High Voltage (HV) with the selection of capacitors that are correctly rated. With an adequately designed control strategy, the research also shows that tapped voltage can be attained under both steady-state and dynamic loads. By leveraging CCS technology, the study demonstrates the potential for delivering reliable electricity to underserved areas, highlighting the system’s practicality and effectiveness in overcoming the limitations of conventional distribution methods.展开更多
Various velocity models have been built for Southeast Qinghai-Xizang Plateau with the purpose of revealing the internal dynamics and estimating local seismic hazards.In this study,we use a 3-D full-waveform modeling p...Various velocity models have been built for Southeast Qinghai-Xizang Plateau with the purpose of revealing the internal dynamics and estimating local seismic hazards.In this study,we use a 3-D full-waveform modeling package to systematically validate three published continental-scale velocity models,that is,Shen2016,FWEA18,and USTClitho1.0,leveraging the ample datasets in Southeast Qinghai-Xizang Plateau region.Travel time residuals and waveform similarities are measured between observed empirical Green’s functions and synthetic waveforms.The results show that the Shen2016 model,derived from traditional surface wave tomography,performs best in fitting Rayleigh waves in the Southeast Qinghai-Xizang Plateau,followed by FWEA18,built from full-waveform inversion of long-period body and surface waves.The USTClitho1.0 model,although inverted from body wave datasets,is comparable with FWEA18 in fitting Rayleigh waves.The results also show that all the models are faster than the ground-truth model and show relatively large travel-time residuals and poor waveform similarities at shorter period bands,possibly caused by small-scale structural heterogeneities in the shallower crust.We further invert the time residuals for spatial velocity residuals and reveal that all three models underestimate the amplitudes of high-and low-velocity anomalies.The underestimated amplitude is up to 4%,which is non-negligible considering that the overall amplitude of anomalies is only 5%−10%in the crust.These results suggest that datasets and the inversion method are both essential to building accurate models and further refinements of these models are necessary.展开更多
The nozzle is a critical component responsible for generating most of the net thrust in a scramjet engine.The quality of its design directly affects the performance of the entire propulsion system.However,most turbule...The nozzle is a critical component responsible for generating most of the net thrust in a scramjet engine.The quality of its design directly affects the performance of the entire propulsion system.However,most turbulence models struggle to make accurate predictions for subsonic and supersonic flows in nozzles.In this study,we explored a novel model,the algebraic stress model k-kL-ARSM+J,to enhance the accuracy of turbulence numerical simulations.This new model was used to conduct numerical simulations of the design and off-design performance of a 3D supersonic asymmetric truncated nozzle designed in our laboratory,with the aim of providing a realistic pattern of changes.The research indicates that,compared to linear eddy viscosity turbulence models such as k-kL and shear stress transport(SST),the k-kL-ARSM+J algebraic stress model shows better accuracy in predicting the performance of supersonic nozzles.Its predictions were identical to the experimental values,enabling precise calculations of the nozzle.The performance trends of the nozzle are as follows:as the inlet Mach number increases,both thrust and pitching moment increase,but the rate of increase slows down.Lift peaks near the design Mach number and then rapidly decreases.With increasing inlet pressure,the nozzle thrust,lift,and pitching moment all show linear growth.As the flight altitude rises,the internal flow field within the nozzle remains relatively consistent due to the same supersonic nozzle inlet flow conditions.However,external to the nozzle,the change in external flow pressure results in the nozzle exit transitioning from over-expanded to under-expanded,leading to a shear layer behind the nozzle that initially converges towards the nozzle center and then diverges.展开更多
This paper investigates the impact of the model top and damping layer on the numerical simulation of tropical cyclones(TCs)and reveals the significant role of stratospheric gravity waves(SGWs).TCs can generate SGWs,wh...This paper investigates the impact of the model top and damping layer on the numerical simulation of tropical cyclones(TCs)and reveals the significant role of stratospheric gravity waves(SGWs).TCs can generate SGWs,which propagate upward and outward into the stratosphere.These SGWs can reach the damping layer,which is a consequence of the numerical scheme employed,where they can affect the tangential circulation through the dragging and forcing processes.In models with a higher top boundary,this tangential circulation develops far from the TC and has minimal direct impact on TC intensity.By comparison,in models with a lower top(e.g.,20 km),the damping layer is located just above the top of the TC.The SGW dragging in the damping layer and the consequent tangential force can thus induce ascent outside the eyewall,promote latent heat release,tilt the eyewall,and enlarge the inner-core radius.This process will reduce inner-core vorticity advection within the boundary layer,and eventually inhibits the intensification of the TC.This suggests that when the thickness of the damping layer is 5 km,the TC numerical model top height should be at least higher than 20 km to generate more accurate simulations.展开更多
The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope ...The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.展开更多
Coal underground gasification(UCG)transforms the physical extraction of coal into the chemical extraction of gas,which is effective for exploiting deep coal deposits.Numerical simulation technology for UCG is a crucia...Coal underground gasification(UCG)transforms the physical extraction of coal into the chemical extraction of gas,which is effective for exploiting deep coal deposits.Numerical simulation technology for UCG is a crucial tool for studying the complex processes involved in coal gasification.This study was conducted to determine the direction in which UCG numerical simulation is developing,specifically by reviewing the research progress and achievements made in this area and identifying the existing problems and future research directions.The findings indicate the following:(1)Research has focused on the reaction issues of coal underground gasification,considering mass and heat transfer effects and gasification cavity expansion.Chemical equilibrium,gasification block,packed bed,and gasification channel models have been developed,which have certain advantages in solving gasification reaction problems influenced by cavity structure and reasonable simplifications capable of describing local issues.(2)The dynamic description of gasification cavity structures is a challenging problem that UCG numerical simulation needs to address.The cavity expansion mechanism includes thermochemical consumption,coal spalling,roof collapse,and debris accumulation.Thermochemical consumption causes the mechanical properties of coal and rock to change,leading to spalling under stress.(3)Process models emphasize dynamic simulations of the gasification process,including cavity evolution and gasification products.The reactor combination model,continuous medium equivalent model,and multimodule integration model are primarily used.(4)Future UCG numerical simulation technology development will prioritize modularity,systematization,and intelligence.There is an urgent need to facilitate the chemical reaction kinetics of large coal blocks,the coupling of discontinuous media,and the integration of multifunctional systems,including that of numerical simulation technology with artificial intelligence.With continuous improvements,numerical simulation technology will play a greater technical supporting role in UCG industrialization.展开更多
Purpose:The major limitation of tumor microwave ablation(MWA)operation is the lack of predictability of the ablation zone before surgery.Operators rely on their individual experience to select a treatment plan,which i...Purpose:The major limitation of tumor microwave ablation(MWA)operation is the lack of predictability of the ablation zone before surgery.Operators rely on their individual experience to select a treatment plan,which is prone to either inadequate or excessive ablation.This paper aims to establish an ablation prediction model that guides MWA tumor surgical planning.Methods:An MWA process was first simulated by incorporating electromagnetic radiation equations,thermal equations,and optimized biological tissue parameters(dynamic dielectric and thermophysical parameters).The temperature distributions(the short/long diameters,and the total volume of the ablation zone)were then generated and verified by 60 cases ex vivo porcine liver experiments.Subsequently,a series of data were obtained from the simulated temperature distributions and to further fit the novel ablation coagulated area prediction model(ACAPM),thus rendering the ablation-dose table for the guiding surgical plan.The MWA clinical patient data and clinical devices suggested data were used to validate the accuracy and practicability of the established predicted model.Results:The 60 cases ex vivo porcine liver experiments demonstrated the accuracy of the simulated temperature distributions.Compared to traditional simulation methods,our approach reduces the long-diameter error of the ablation zone from 1.1 cm to 0.29 cm,achieving a 74%reduction in error.Further,the clinical data including the patients'operation results and devices provided values were consistent well with our predicated data,indicating the great potential of ACAPM to assist preoperative planning.展开更多
Shale gas serves as a significant strategic successor resource for future oil and gas reserves and production in China.Thus,a profound understanding of the adsorption mechanism of shale gas in shale reservoirs is cruc...Shale gas serves as a significant strategic successor resource for future oil and gas reserves and production in China.Thus,a profound understanding of the adsorption mechanism of shale gas in shale reservoirs is crucial to accurately predict and evaluate shale gas reserves.In this study,we utilized two simulation methods,molecular dynamics simulation and Giant Canonical Monte Carlo simulation to examine the adsorption characteristics of kerogen under varying temperature and pressure conditions.We compared the results under identical temperature and pressure conditions for different mineral-kerogen composite models.Moreover,we examined the effects of temperature,pressure,and mineral species on the kerogen adsorption mechanism.The results indicate that shale formations with high organic matter content and a substantial proportion of non-clay inorganic minerals,as well as those subjected to higher temperature and pressure conditions than the shallow layer,possess a greater capacity to accommodate shale gas.This study examined the adsorption mechanism of methane in shale gas using different mineral-kerogen composite models.The findings of this study provide more accurate guidance and support for efficient development of shale gas.展开更多
Understanding the structure of coal is helpful to understand the diverse reactivity of coal at a molecular scale and offer support for clean and effective utilization of coal.The physical properties of a typical coal ...Understanding the structure of coal is helpful to understand the diverse reactivity of coal at a molecular scale and offer support for clean and effective utilization of coal.The physical properties of a typical coal from east of Ningxia were characterized by some analysis methods such as elemental analysis,FT-IR,XPS,and ^(13)C NMR.And the key parameters of the microstructure of the coal sample were obtained such as the type,valence and chemical bond and so on.The molecular composition of coal has been established as C_(202)H_(153)O_(38)N_(3)S_(2),and a three-dimensional representation of its molecular structure was created.The molecular dynamics approach utilizing reactive force fields was employed to model the process of coal gasification.The influence of reaction force fields and temperature on coal gasification process were investigated,and the main small molecule products in different atmospheres were tracked.It was indicated that the consumption and consumption rate of raw coal and the production of primary products increased with increasing of the temperature.All carbon elements in coal were converted into fragments with less than three carbon atoms at the H_(2)O atmosphere and 3500-4000 K,and the C_(1) content can reach 97.73% at 4000 K.It was proved indirectly that the gasification reaction process had been completed.In mixed atmospheres,the gasification condition closest to industrial scenarios was 500H_(2)O + 1500CO_(2),yielding a CO/H_(2) ratio of 3.52,matching actual outcomes.Molecular dynamics simulation of gasification process based on coal macromolecules is conducive to reveal gasification reaction mechanism.展开更多
The Erenhot-Huailai zone, as an important dust emission source area in northern China, affects the air quality of Beijing City, Tianjin City, and Hebei Province and human activities in this zone have a profound impact...The Erenhot-Huailai zone, as an important dust emission source area in northern China, affects the air quality of Beijing City, Tianjin City, and Hebei Province and human activities in this zone have a profound impact on surface dust emission. In order to explore the main source areas of surface dust emission and quantify the impacts of human activities on surface dust emission, we investigated the surface dust emission of different land types on the Erenhot-Huailai zone by model simulation, field observation, and comparative analysis. The results showed that the average annual inhalable atmospheric particles(PM_(10)) dust emission fluxes in arid grassland, Hunshandake Sandy Land, semi-arid grassland,semi-arid agro-pastoral area, dry sub-humid agro-pastoral area, and semi-humid agro-pastoral area were 4.41, 0.71, 3.64, 1.94, 0.24, and 0.14 t/hm^(2), respectively, and dust emission in these lands occurred mainly from April to May. Due to the influence of human activities on surface dust emission, dust emission fluxes from different land types were 1.66–4.41 times greater than those of their background areas, and dust emission fluxes from the main dust source areas were 1.66–3.89 times greater than those of their background areas. According to calculation, the amount of PM_(10) dust emission influenced by human disturbance accounted for up to 58.00% of the total dust emission in the study area. In addition, the comparative analysis of model simulation and field observation results showed that the simulated and observed dust emission fluxes were relatively close to each other, with differences ranging from 0.01 to 0.21 t/hm^(2) in different months, which indicated that the community land model version 4.5(CLM4.5) had a high accuracy. In conclusion, model simulation results have important reference significance for identifying dust source areas and quantifying the contribution of human activities to surface dust emission.展开更多
In the context of global climate change,the increasing frequency of extreme weather events presents significant challenges to urban water systems.This study focuses on the Beijing section of the Beijing-Hangzhou Grand...In the context of global climate change,the increasing frequency of extreme weather events presents significant challenges to urban water systems.This study focuses on the Beijing section of the Beijing-Hangzhou Grand Canal,introduces the SEE model,and develops an integrated“comprehensive water environment simulation model”to systematically examine the path for enhancing its climate resilience.Through the coupling of multiple models(MIKE 11,MIKE URBAN,MIKE 21)and scenario simulations,this study analyzes the response mechanisms of various governance strategies under extreme climate conditions.The research proposes four specific measures to enhance resilience:dual-scenario simulation of climate and governance,identification and reinforcement of weak points in resilience,parametric modeling of ecological restoration interventions,and the development of a“digital twin canal system”.The research findings indicate that the system integration of the SEE model substantially improves the adaptability,endurance,and recovery capacity of canals in response to climate shocks,including heavy rainfall and drought.This provides a scientific foundation and a practical path for achieving long-term resilience and sustainable development of urban water systems.展开更多
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
文摘The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in passenger boarding,alighting,and onboard movements.Although there are initial findings on the effectiveness of some of the mitigation policies(such as face-covering and ventilation),evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways,boarding and alighting patterns,and seating capacity control.This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA,in which it brings crucial insights on combating current and future epidemics.We use an agent-based simulation model(ABSM)based on standard design characteristics for urban buses in USA and two different service frequency settings(10-min and 20-min headways).We find that wearing face-coverings(surgical masks)significantly reduces onboard transmission rates,from no mitigation rates of 85%in higher-frequency buses and 75%in lower-frequency buses to 12.5%.The most effective prevention outcome is the combination of KN-95 masks,open window policies,and half-capacity seating control during higher-frequency bus services,with an outcome of nearly 0%onboard infection rate.Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design,which is crucial to ensuring passenger safety.The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies.
基金supported by the Shanghai Philosophy and Social Science Foundation(2022ECK004)Shanghai Soft Science Research Project(23692123400)。
文摘Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.
文摘An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. This model was built to approximately reproduce some essential findings that were previously reported for a rather complex model of diabetes progression. Our models are translations of basicelements of this previously reported system dynamics model of diabetes. The system dynamics model, which mimics diabetes progression over an aggregated US population, was disaggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. The four estimated models attempted to replicate stock counts representing disease states in the system dynamics model while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent’s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. All three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model, although behavioral factors appeared to contribute more than the elderliness factor. The results illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.
基金the National Natural Science Foundation of China(NSFC),under grant No.72131001Construction Project of Baoding Low Carbon Economy Industry Research Institute(1106/9100615009).
文摘Grain security is one of the most important issues worldwide.Many developing countries,including China,have adopted the Agriculture Support Price(ASP)program to stimulate farmers’enthusiasm for growing grain,to ensure self-sufficiency in grain and the stable development of the grain market.To propose decision support for the government in designing a more reasonable support price in the ASP program,we formulate an agent-based model to simulate the operation of the wheat market in the harvest period.To formulate the formation process of the market price influenced by farmers’expected sale price,processors’expected purchase price,and the ASP,the time series and regression methods are adopted.Based on the proposed market price model,to quantitatively analyze the grain transaction process and the ASP program’s impacts on market agents,we develop an agent-based simulation model to describe the adaptive evolution and interaction among market agents.Furthermore,we validate and implement the simulation model with public wheat market data.Finally,insights and suggestions about the decision of the ASP program are provided.
文摘Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and finding shelter are vital for search and rescue managers.At the same time,many unpredicted challenges,such as the sudden increase in travel demand,shifts in public behavior,and the change in the regular transport supply,may arise due to evacuation conditions,which lead to different situations.This paper aims to introduce an approach for quick decision-making and timely evacuation response required by establishing a situation-aware system to minimize these risks and ensure the success of the evacuation plans,to support and predict current and future actions within the dynamic space of the crisis.The main contribution is innovating a Situation-Aware Emergency Evacuation(SAEE)model to enable crisis managers and evacuees to make the right decisions by providing timely and reliable information about the situation.This method is utilized in two situations:designing the emergency evacuation plan and finding the shortest/safest routes to reduce travel time for evacuees.Therefore,a hybrid approach is introduced,which involves a Fuzzy Inference System(FIS)and Deep Long Short-Term Memory(DLSTM)algorithm to identify,infer,and extract the existing situation at different levels(e.g.people,vehicles,and surroundings)after a foreshock using multi-agent-based simulation.The method proposed was simulated in the traffic network of District 6 of Tehran,the capital of Iran.The model results show that the evacuees'spatial knowledge and perception,as well as awareness of the situation of other agents and their surroundings,led to a significant(40%)reduction in the complete evacuation time.This time is considered the most pivotal factor in saving human lives and their arrival in safer areas.The role of situation awareness systems and increasing human cognition and perception can significantly help in this matter.
文摘This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionary processes.By representing agents and their defined environments with probabilistic interactions,ABM allows the assessment of the effects of individual behavior at the micro level on the greater social phenomena at the macro level.The review looks into the applications of ABM in portraying some of the key components of emotions and cognition-empathy,cooperation,decision making,and emotional transmission-and analyzes the problems including scalability,empirical validation,and description of sensitive emotional states.The most important conclusion is that merging ABM with information neurobiological data and artificial intelligence(AI)techniques would allow for deepening the interactions within the system and enhancing its responsiveness to stimuli.This review highlights approaches that aim to exploit the ABM methodology more fully and integrates methods from biology,neuroscience,and engineering.This integration could contribute to our understanding of the human behavior evolution and adaptation within systems relevant to policymaking,healthcare,and education.
基金supported by National Natural Science Foundation of China(72288101,72361137002,and 72101018)the Dutch Research Council(NWO Grant 482.22.01).
文摘Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.
基金Financial support for this work was provided by the US Department of Commerce,the National Institute of Standards and Technology(NIST)under the Financial Assistance Award Number#70NANB20H008the US National Science Foundation(NSF)under Award Number 2052930.
文摘There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes.Given the significant damage incurred by tornadoes upon communities,community resilience analyses for tornado-stricken communities have been gaining momentum.As the community resilience analysis aims to guide how to lay out effective hazard mitigation strategies to decrease damage and improve recovery,a comprehensive and accurate approach is necessary.Agent-based modeling,an analysis approach in which different types of agents are created with their properties and behavior clearly defined to simulate the processes of those agents in an external environ-ment,is the most comprehensive and accurate approach so far to conducting community resilience simulations and investigating the decision-making for mitigation and recovery under natural hazards.In this paper,agent-based models(ABMs)are created to simulate the recovery process of a virtual testbed based on the real-world community in Joplin City,MO.The tornado path associated with the real-world tornado event that occurred in May 2011 is adopted in the tornado hazard modeling for the Joplin testbed.In addition,agent-based models are created for another virtual community in the Midwest United States named Centerville using an assumed tornado scenario of the same EF-scale as that in Joplin.The effects of hazard mitigation strategies on the two communities are also explored.A comparison between the analysis results of these two testbeds can indicate the influence of the characteristics of a tornado-prone community on the resilience of the community as well as on the effects of hazard mitigation strategies.It is observed that a community’s level of development significantly impacts the tornado resilience.In addition,the effects of a specific type of hazard mitigation strategy on the recovery process are contingent upon testbed characteristics.
文摘The global rise in energy demand, particularly in remote and sparsely populated regions, necessitates innovative and cost-effective electrical distribution solutions. Traditional Rural Electrification (RE) methods, like Conventional Rural Electrification (CRE), have proven economically unfeasible in such areas due to high infrastructure costs and low electricity demand. Consequently, Unconventional Rural Electrification (URE) technologies, such as Capacitor Coupled Substations (CCS), are gaining attention as viable alternatives. This study presents the design and simulation of an 80 kW CCS system, which taps power directly from a 132 kV transmission line to supply low-voltage consumers. The critical components of the CCS, the capacitors are calculated, then a MATLAB/Simulink model with the attained results is executed. Mathematical representation and state-space representation for maintaining the desired tapped voltage area also developed. The research further explores the feasibility and operational performance of this CCS configuration, aiming to address the challenges of rural electrification by offering a sustainable and scalable solution. The results show that the desired value of the tapped voltage can be achieved at any level of High Voltage (HV) with the selection of capacitors that are correctly rated. With an adequately designed control strategy, the research also shows that tapped voltage can be attained under both steady-state and dynamic loads. By leveraging CCS technology, the study demonstrates the potential for delivering reliable electricity to underserved areas, highlighting the system’s practicality and effectiveness in overcoming the limitations of conventional distribution methods.
基金supported by the Special Fund of the Institute of Geophysics,China Earthquake Administration(Nos.DQJB23R28 and DQJB22K40)the National Natural Science Foundation of China(Nos.42304078,U1839210 and 42104043).
文摘Various velocity models have been built for Southeast Qinghai-Xizang Plateau with the purpose of revealing the internal dynamics and estimating local seismic hazards.In this study,we use a 3-D full-waveform modeling package to systematically validate three published continental-scale velocity models,that is,Shen2016,FWEA18,and USTClitho1.0,leveraging the ample datasets in Southeast Qinghai-Xizang Plateau region.Travel time residuals and waveform similarities are measured between observed empirical Green’s functions and synthetic waveforms.The results show that the Shen2016 model,derived from traditional surface wave tomography,performs best in fitting Rayleigh waves in the Southeast Qinghai-Xizang Plateau,followed by FWEA18,built from full-waveform inversion of long-period body and surface waves.The USTClitho1.0 model,although inverted from body wave datasets,is comparable with FWEA18 in fitting Rayleigh waves.The results also show that all the models are faster than the ground-truth model and show relatively large travel-time residuals and poor waveform similarities at shorter period bands,possibly caused by small-scale structural heterogeneities in the shallower crust.We further invert the time residuals for spatial velocity residuals and reveal that all three models underestimate the amplitudes of high-and low-velocity anomalies.The underestimated amplitude is up to 4%,which is non-negligible considering that the overall amplitude of anomalies is only 5%−10%in the crust.These results suggest that datasets and the inversion method are both essential to building accurate models and further refinements of these models are necessary.
基金supported by the Zhejiang Provincial Key Research and Development Program of China(No.2020C01020).
文摘The nozzle is a critical component responsible for generating most of the net thrust in a scramjet engine.The quality of its design directly affects the performance of the entire propulsion system.However,most turbulence models struggle to make accurate predictions for subsonic and supersonic flows in nozzles.In this study,we explored a novel model,the algebraic stress model k-kL-ARSM+J,to enhance the accuracy of turbulence numerical simulations.This new model was used to conduct numerical simulations of the design and off-design performance of a 3D supersonic asymmetric truncated nozzle designed in our laboratory,with the aim of providing a realistic pattern of changes.The research indicates that,compared to linear eddy viscosity turbulence models such as k-kL and shear stress transport(SST),the k-kL-ARSM+J algebraic stress model shows better accuracy in predicting the performance of supersonic nozzles.Its predictions were identical to the experimental values,enabling precise calculations of the nozzle.The performance trends of the nozzle are as follows:as the inlet Mach number increases,both thrust and pitching moment increase,but the rate of increase slows down.Lift peaks near the design Mach number and then rapidly decreases.With increasing inlet pressure,the nozzle thrust,lift,and pitching moment all show linear growth.As the flight altitude rises,the internal flow field within the nozzle remains relatively consistent due to the same supersonic nozzle inlet flow conditions.However,external to the nozzle,the change in external flow pressure results in the nozzle exit transitioning from over-expanded to under-expanded,leading to a shear layer behind the nozzle that initially converges towards the nozzle center and then diverges.
基金supported by the National Natural Science Foundation of China(Grant Nos.42475016,42192555 and 42305085)the China Postdoctoral Science Foundation(Grant No.2023M741615)the 2023 Graduate Research Innovation Project of Hunan Province(Grant No.CX20230011)。
文摘This paper investigates the impact of the model top and damping layer on the numerical simulation of tropical cyclones(TCs)and reveals the significant role of stratospheric gravity waves(SGWs).TCs can generate SGWs,which propagate upward and outward into the stratosphere.These SGWs can reach the damping layer,which is a consequence of the numerical scheme employed,where they can affect the tangential circulation through the dragging and forcing processes.In models with a higher top boundary,this tangential circulation develops far from the TC and has minimal direct impact on TC intensity.By comparison,in models with a lower top(e.g.,20 km),the damping layer is located just above the top of the TC.The SGW dragging in the damping layer and the consequent tangential force can thus induce ascent outside the eyewall,promote latent heat release,tilt the eyewall,and enlarge the inner-core radius.This process will reduce inner-core vorticity advection within the boundary layer,and eventually inhibits the intensification of the TC.This suggests that when the thickness of the damping layer is 5 km,the TC numerical model top height should be at least higher than 20 km to generate more accurate simulations.
基金Funded by the National Natural Science Foundation of China Academy of Engineering Physics and Jointly Setup"NSAF"Joint Fund(No.U1430119)。
文摘The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.
基金supported by Natural Science Research Project of Yangzhou University Guangling College,China(Grant No.ZKZD25002)Youth Science and Technology Special Project of PetroChina(Grant No.2024DQ03221)Basic Research Project of Institute Research Institute of Exploration and Development,PetroChina(Grant No.101001cq0b52394).
文摘Coal underground gasification(UCG)transforms the physical extraction of coal into the chemical extraction of gas,which is effective for exploiting deep coal deposits.Numerical simulation technology for UCG is a crucial tool for studying the complex processes involved in coal gasification.This study was conducted to determine the direction in which UCG numerical simulation is developing,specifically by reviewing the research progress and achievements made in this area and identifying the existing problems and future research directions.The findings indicate the following:(1)Research has focused on the reaction issues of coal underground gasification,considering mass and heat transfer effects and gasification cavity expansion.Chemical equilibrium,gasification block,packed bed,and gasification channel models have been developed,which have certain advantages in solving gasification reaction problems influenced by cavity structure and reasonable simplifications capable of describing local issues.(2)The dynamic description of gasification cavity structures is a challenging problem that UCG numerical simulation needs to address.The cavity expansion mechanism includes thermochemical consumption,coal spalling,roof collapse,and debris accumulation.Thermochemical consumption causes the mechanical properties of coal and rock to change,leading to spalling under stress.(3)Process models emphasize dynamic simulations of the gasification process,including cavity evolution and gasification products.The reactor combination model,continuous medium equivalent model,and multimodule integration model are primarily used.(4)Future UCG numerical simulation technology development will prioritize modularity,systematization,and intelligence.There is an urgent need to facilitate the chemical reaction kinetics of large coal blocks,the coupling of discontinuous media,and the integration of multifunctional systems,including that of numerical simulation technology with artificial intelligence.With continuous improvements,numerical simulation technology will play a greater technical supporting role in UCG industrialization.
基金supported by the National Major Scientific Instruments and Equipment Development Project Funded by the National Natural Science Foundation of China(81827803)the Jiangsu Province Key Research and Development Program(Social Development)Project(BE2020705).
文摘Purpose:The major limitation of tumor microwave ablation(MWA)operation is the lack of predictability of the ablation zone before surgery.Operators rely on their individual experience to select a treatment plan,which is prone to either inadequate or excessive ablation.This paper aims to establish an ablation prediction model that guides MWA tumor surgical planning.Methods:An MWA process was first simulated by incorporating electromagnetic radiation equations,thermal equations,and optimized biological tissue parameters(dynamic dielectric and thermophysical parameters).The temperature distributions(the short/long diameters,and the total volume of the ablation zone)were then generated and verified by 60 cases ex vivo porcine liver experiments.Subsequently,a series of data were obtained from the simulated temperature distributions and to further fit the novel ablation coagulated area prediction model(ACAPM),thus rendering the ablation-dose table for the guiding surgical plan.The MWA clinical patient data and clinical devices suggested data were used to validate the accuracy and practicability of the established predicted model.Results:The 60 cases ex vivo porcine liver experiments demonstrated the accuracy of the simulated temperature distributions.Compared to traditional simulation methods,our approach reduces the long-diameter error of the ablation zone from 1.1 cm to 0.29 cm,achieving a 74%reduction in error.Further,the clinical data including the patients'operation results and devices provided values were consistent well with our predicated data,indicating the great potential of ACAPM to assist preoperative planning.
基金supported by the National Natural Science Foundation of China(Grant No.42102145)the Science Foundation of China University of Petroleum,Beijing(Grant No.2462022YXZZ007)。
文摘Shale gas serves as a significant strategic successor resource for future oil and gas reserves and production in China.Thus,a profound understanding of the adsorption mechanism of shale gas in shale reservoirs is crucial to accurately predict and evaluate shale gas reserves.In this study,we utilized two simulation methods,molecular dynamics simulation and Giant Canonical Monte Carlo simulation to examine the adsorption characteristics of kerogen under varying temperature and pressure conditions.We compared the results under identical temperature and pressure conditions for different mineral-kerogen composite models.Moreover,we examined the effects of temperature,pressure,and mineral species on the kerogen adsorption mechanism.The results indicate that shale formations with high organic matter content and a substantial proportion of non-clay inorganic minerals,as well as those subjected to higher temperature and pressure conditions than the shallow layer,possess a greater capacity to accommodate shale gas.This study examined the adsorption mechanism of methane in shale gas using different mineral-kerogen composite models.The findings of this study provide more accurate guidance and support for efficient development of shale gas.
基金supported by the National Natural Science Foundation of China (U21A20319)the National Discipline Construction Project of Ningxia (NXYLXK2017A04)。
文摘Understanding the structure of coal is helpful to understand the diverse reactivity of coal at a molecular scale and offer support for clean and effective utilization of coal.The physical properties of a typical coal from east of Ningxia were characterized by some analysis methods such as elemental analysis,FT-IR,XPS,and ^(13)C NMR.And the key parameters of the microstructure of the coal sample were obtained such as the type,valence and chemical bond and so on.The molecular composition of coal has been established as C_(202)H_(153)O_(38)N_(3)S_(2),and a three-dimensional representation of its molecular structure was created.The molecular dynamics approach utilizing reactive force fields was employed to model the process of coal gasification.The influence of reaction force fields and temperature on coal gasification process were investigated,and the main small molecule products in different atmospheres were tracked.It was indicated that the consumption and consumption rate of raw coal and the production of primary products increased with increasing of the temperature.All carbon elements in coal were converted into fragments with less than three carbon atoms at the H_(2)O atmosphere and 3500-4000 K,and the C_(1) content can reach 97.73% at 4000 K.It was proved indirectly that the gasification reaction process had been completed.In mixed atmospheres,the gasification condition closest to industrial scenarios was 500H_(2)O + 1500CO_(2),yielding a CO/H_(2) ratio of 3.52,matching actual outcomes.Molecular dynamics simulation of gasification process based on coal macromolecules is conducive to reveal gasification reaction mechanism.
基金supported by the National Basic Research Program of China (2016YFA0601901)Basic Scientific Research of Henan Academy of Sciences (240601083)Joint Fund of Henan Province Science and Technology Research and Development Program (225200810047)。
文摘The Erenhot-Huailai zone, as an important dust emission source area in northern China, affects the air quality of Beijing City, Tianjin City, and Hebei Province and human activities in this zone have a profound impact on surface dust emission. In order to explore the main source areas of surface dust emission and quantify the impacts of human activities on surface dust emission, we investigated the surface dust emission of different land types on the Erenhot-Huailai zone by model simulation, field observation, and comparative analysis. The results showed that the average annual inhalable atmospheric particles(PM_(10)) dust emission fluxes in arid grassland, Hunshandake Sandy Land, semi-arid grassland,semi-arid agro-pastoral area, dry sub-humid agro-pastoral area, and semi-humid agro-pastoral area were 4.41, 0.71, 3.64, 1.94, 0.24, and 0.14 t/hm^(2), respectively, and dust emission in these lands occurred mainly from April to May. Due to the influence of human activities on surface dust emission, dust emission fluxes from different land types were 1.66–4.41 times greater than those of their background areas, and dust emission fluxes from the main dust source areas were 1.66–3.89 times greater than those of their background areas. According to calculation, the amount of PM_(10) dust emission influenced by human disturbance accounted for up to 58.00% of the total dust emission in the study area. In addition, the comparative analysis of model simulation and field observation results showed that the simulated and observed dust emission fluxes were relatively close to each other, with differences ranging from 0.01 to 0.21 t/hm^(2) in different months, which indicated that the community land model version 4.5(CLM4.5) had a high accuracy. In conclusion, model simulation results have important reference significance for identifying dust source areas and quantifying the contribution of human activities to surface dust emission.
基金Sponsored by 2025 Postgraduate Teaching Reform Project of North China University of Technology。
文摘In the context of global climate change,the increasing frequency of extreme weather events presents significant challenges to urban water systems.This study focuses on the Beijing section of the Beijing-Hangzhou Grand Canal,introduces the SEE model,and develops an integrated“comprehensive water environment simulation model”to systematically examine the path for enhancing its climate resilience.Through the coupling of multiple models(MIKE 11,MIKE URBAN,MIKE 21)and scenario simulations,this study analyzes the response mechanisms of various governance strategies under extreme climate conditions.The research proposes four specific measures to enhance resilience:dual-scenario simulation of climate and governance,identification and reinforcement of weak points in resilience,parametric modeling of ecological restoration interventions,and the development of a“digital twin canal system”.The research findings indicate that the system integration of the SEE model substantially improves the adaptability,endurance,and recovery capacity of canals in response to climate shocks,including heavy rainfall and drought.This provides a scientific foundation and a practical path for achieving long-term resilience and sustainable development of urban water systems.
