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
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
Currently,critical peak load caused by residential customers has attracted utility companies and policymakers to pay more attention to residential demand response(RDR)programs.In typical RDR programs,residential custo...Currently,critical peak load caused by residential customers has attracted utility companies and policymakers to pay more attention to residential demand response(RDR)programs.In typical RDR programs,residential customers react to the price or incentive-based signals,but the actions can fall behind flexible market situations.For those residential customers equipped with smart meters,they may contribute more DR loads if they can participate in DR events in a proactive way.In this paper,we propose a comprehensive market framework in which residential customers can provide proactive RDR actions in a day-ahead market(DAM).We model and evaluate the interactions between generation companies(GenCos),retailers,residential customers,and the independent system operator(ISO)via an agent-based modeling and simulation(ABMS)approach.The simulation framework contains two main procedures—the bottom-up modeling procedure and the reinforcement learning(RL)procedure.The bottom-up modeling procedure models the residential load profiles separately by household types to capture the RDR potential differences in advance so that residential customers may rationally provide automatic DR actions.Retailers and GenCos optimize their bidding strategies via the RL procedure.The modified optimization approach in this procedure can prevent the training results from falling into local optimum solutions.The ISO clears the DAM to maximize social welfare via Karush-Kuhn-Tucker(KKT)conditions.Based on realistic residential data in China,the proposed models and methods are verified and compared in a large multi-scenario test case with 30,000 residential households.Results show that proactive RDR programs and interactions between market entities may yield significant benefits for both the supply and demand sides.The models and methods in this paper may be used by utility companies,electricity retailers,market operators,and policy makers to evaluate the consequences of a proactive RDR and the interactions among multi-entities.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
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
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 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
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
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
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
Oilfields worldwide are increasingly grappling with challenges such as early water breakthrough and high water production,yet direct,targeted solutions remain elusive.In recent years,chemical flooding techniques desig...Oilfields worldwide are increasingly grappling with challenges such as early water breakthrough and high water production,yet direct,targeted solutions remain elusive.In recent years,chemical flooding techniques designed for tertiary oil recovery have garnered significant attention,with microgel flooding emerging as a particularly prominent area of research.Despite its promise,the complex mechanisms underlying microgel flooding have been rarely investigated numerically.This study aims to address these gaps by characterizing the distribution of microgel concentration and viscosity within different pore structures.To enhance the accuracy of these characterizations,the viscosity of microgels is adjusted to account for the shear effects induced by flow rate and the swelling effects driven by salinity variations.The absolute permeability of the rock and the relative permeability of both oil and microgel are also analyzed to elucidate the mechanisms of microgel flooding.Additionally,a connectivity model is employed to achieve a quantitative representation of fluid flow capacity.The proposed model is validated through conceptual examples and applied to real oilfield blocks,demonstrating its accuracy and practical applicability.展开更多
Model-based system-of-systems(SOS)engineering(MBSoSE)is becoming a promising solution for the design of SoS with increasing complexity.However,bridging the models from the design phase to the simulation phase poses si...Model-based system-of-systems(SOS)engineering(MBSoSE)is becoming a promising solution for the design of SoS with increasing complexity.However,bridging the models from the design phase to the simulation phase poses significant challenges and requires an integrated approach.In this study,a unified requirement modeling approach is proposed based on unified architecture framework(UAF).Theoretical models are proposed which compose formalized descriptions from both topdown and bottom-up perspectives.Based on the description,the UAF profile is proposed to represent the SoS mission and constituent systems(CS)goal.Moreover,the agent-based simulation information is also described based on the overview,design concepts,and details(ODD)protocol as the complement part of the SoS profile,which can be transformed into different simulation platforms based on the eXtensible markup language(XML)technology and model-to-text method.In this way,the design of the SoS is simulated automatically in the early design stage.Finally,the method is implemented and an example is given to illustrate the whole process.展开更多
We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresp...We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresponding extended ab initio data set,we construct interpolation formulas covering the range from low-density,high-temperature to high-density,low-temperature plasmas.Our conductivity model repro-duces the well-known limits of the Spitzer and Ziman theory.We compare with available experimental data andfind very good agreement.The new conductivity model can be applied,for example,in dynamo simulations for magneticfield generation in gas giant planets,brown dwarfs,and stellar envelopes.展开更多
A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions.The effect of the hazard geomet...A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions.The effect of the hazard geometry(center and angle of tornado path as well as the tornado width)is studied herein on how it influences the recovery of physical and social systems within the community.Given that pre-disaster preparedness including mitigation strategies(e.g.,retrofits)and policies(e.g.,insurance)is crucial for increasing the resilience of the community and facilitating a faster recovery process,in this study,the impact of various mitigation strategies and policies on the recovery trajectory and resilience of a typical US community subjected to a tornado is investigated considering different sources of uncertainties.The virtual testbed of Centerville is selected in this paper and is modeled by adopting the Agent-based modeling(ABM)approach which is a powerful tool for conducting community resilience analysis that simulates the behavior of different types of agents and their interactions to capture their interdependencies.The results are presented in the form of recovery time series as well as calculated resilience indices for various community systems(lifeline networks,schools,healthcare,businesses,and households).The results of this study can help deepen our understanding of how to efficiently expedite the recovery process of a community.展开更多
Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises.This study developed a universal dynamic agent-based supply cha...Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises.This study developed a universal dynamic agent-based supply chain model to achieve tradeoffs between environmental risk reduction and economic sus-tainability.The model was used to conduct high-resolution daily simulations of the dynamic shifts in enterprise operations and their cascading effects on supply chain networks.It includes production,con-sumption,and transportation agents,attributing economic features to supply chain components and cap-turing their interactions.It also accounts for adaptive responses to daily external shocks and replicates realistic firm behaviors.By coupling high spatial-temporal resolution firm-level data from 18916 chemical enterprises,this study investigates the economic and environmental impacts of an environmen-tal policy resulting in the closure of 1800 chemical enterprises over three years.The results revealed a significant economic loss of 25.8 billion USD,ranging from 23.8 billion to 31.8 billion USD.Notably,over 80%of this loss was attributed to supply chain propagation.Counterfactual analyses indicated that imple-menting a staggered shutdown strategy prevented 18.8%of supply chain losses,highlighting the impor-tance of a gradual policy implementation to prevent abrupt supply chain disruptions.Furthermore,the study highlights the effectiveness of a multi-objective policy design in reducing economic losses(about 29%)and environmental risks(about 40%),substantially enhancing the efficiency of the environmental policy.The high-resolution simulations provide valuable insights for policy designers to formulate strategies with staggered implementation and multiple objectives to mitigate supply chain losses and environmental risks and ensure a sustainable future.展开更多
The advantages of a flat-panel X-ray source(FPXS)make it a promising candidate for imaging applications.Accurate imaging-system modeling and projection simulation are critical for analyzing imaging performance and res...The advantages of a flat-panel X-ray source(FPXS)make it a promising candidate for imaging applications.Accurate imaging-system modeling and projection simulation are critical for analyzing imaging performance and resolving overlapping projection issues in FPXS.The conventional analytical ray-tracing approach is limited by the number of patterns and is not applicable to FPXS-projection calculations.However,the computation time of Monte Carlo(MC)simulation is independent of the size of the patterned arrays in FPXS.This study proposes two high-efficiency MC projection simulators for FPXS:a graphics processing unit(GPU)-based phase-space sampling MC(gPSMC)simulator and GPU-based fluence sampling MC(gFSMC)simulator.The two simulators comprise three components:imaging-system modeling,photon initialization,and physical-interaction simulations in the phantom.Imaging-system modeling was performed by modeling the FPXS,imaging geometry,and detector.The gPSMC simulator samples the initial photons from the phase space,whereas the gFSMC simulator performs photon initialization from the calculated energy spectrum and fluence map.The entire process of photon interaction with the geometry and arrival at the detector was simulated in parallel using multiple GPU kernels,and projections based on the two simulators were calculated.The accuracies of the two simulators were evaluated by comparing them with the conventional analytical ray-tracing approach and acquired projections,and the efficiencies were evaluated by comparing the computation time.The results of simulated and realistic experiments illustrate the accuracy and efficiency of the proposed gPSMC and gFSMC simulators in the projection calculation of various phantoms.展开更多
In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environ...In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.展开更多
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.
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.
基金supported in part by the National Key Research and Development Program of China(2016YFB0901100)the National Natural Science Foundation of China(U1766203)+1 种基金the Science and Technology Project of State Grid Corporation of China(Friendly interaction system of supply-demand between urban electric power customers and power grid)the China Scholarship Council(CSC).
文摘Currently,critical peak load caused by residential customers has attracted utility companies and policymakers to pay more attention to residential demand response(RDR)programs.In typical RDR programs,residential customers react to the price or incentive-based signals,but the actions can fall behind flexible market situations.For those residential customers equipped with smart meters,they may contribute more DR loads if they can participate in DR events in a proactive way.In this paper,we propose a comprehensive market framework in which residential customers can provide proactive RDR actions in a day-ahead market(DAM).We model and evaluate the interactions between generation companies(GenCos),retailers,residential customers,and the independent system operator(ISO)via an agent-based modeling and simulation(ABMS)approach.The simulation framework contains two main procedures—the bottom-up modeling procedure and the reinforcement learning(RL)procedure.The bottom-up modeling procedure models the residential load profiles separately by household types to capture the RDR potential differences in advance so that residential customers may rationally provide automatic DR actions.Retailers and GenCos optimize their bidding strategies via the RL procedure.The modified optimization approach in this procedure can prevent the training results from falling into local optimum solutions.The ISO clears the DAM to maximize social welfare via Karush-Kuhn-Tucker(KKT)conditions.Based on realistic residential data in China,the proposed models and methods are verified and compared in a large multi-scenario test case with 30,000 residential households.Results show that proactive RDR programs and interactions between market entities may yield significant benefits for both the supply and demand sides.The models and methods in this paper may be used by utility companies,electricity retailers,market operators,and policy makers to evaluate the consequences of a proactive RDR and the interactions among multi-entities.
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.
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.
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 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 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 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supported by the National Natural Science Foundation project“Micro-Scale Effect of Oil-Gas Flow and the Mechanism of Enhancing Shale Oil Recovery by Natural Gas Injection”(No.52074317)。
文摘Oilfields worldwide are increasingly grappling with challenges such as early water breakthrough and high water production,yet direct,targeted solutions remain elusive.In recent years,chemical flooding techniques designed for tertiary oil recovery have garnered significant attention,with microgel flooding emerging as a particularly prominent area of research.Despite its promise,the complex mechanisms underlying microgel flooding have been rarely investigated numerically.This study aims to address these gaps by characterizing the distribution of microgel concentration and viscosity within different pore structures.To enhance the accuracy of these characterizations,the viscosity of microgels is adjusted to account for the shear effects induced by flow rate and the swelling effects driven by salinity variations.The absolute permeability of the rock and the relative permeability of both oil and microgel are also analyzed to elucidate the mechanisms of microgel flooding.Additionally,a connectivity model is employed to achieve a quantitative representation of fluid flow capacity.The proposed model is validated through conceptual examples and applied to real oilfield blocks,demonstrating its accuracy and practical applicability.
基金Fifth Electronic Research Institute of the Ministry of Industry and Information Technology(HK07202200877)Pre-research Project on Civil Aerospace Technologies of CNSA(D020101)+2 种基金Zhejiang Provincial Science and Technology Plan Project(2022C01052)Frontier Scientific Research Program of Deep Space Exploration Laboratory(2022-QYKYJHHXYF-018,2022-QYKYJH-GCXD-001)Zhiyuan Laboratory(ZYL2024001)。
文摘Model-based system-of-systems(SOS)engineering(MBSoSE)is becoming a promising solution for the design of SoS with increasing complexity.However,bridging the models from the design phase to the simulation phase poses significant challenges and requires an integrated approach.In this study,a unified requirement modeling approach is proposed based on unified architecture framework(UAF).Theoretical models are proposed which compose formalized descriptions from both topdown and bottom-up perspectives.Based on the description,the UAF profile is proposed to represent the SoS mission and constituent systems(CS)goal.Moreover,the agent-based simulation information is also described based on the overview,design concepts,and details(ODD)protocol as the complement part of the SoS profile,which can be transformed into different simulation platforms based on the eXtensible markup language(XML)technology and model-to-text method.In this way,the design of the SoS is simulated automatically in the early design stage.Finally,the method is implemented and an example is given to illustrate the whole process.
基金supported by the Priority Program SPP 1992 of the German Science Foundation(DFG)The Diversity of Exoplanets under project number 362460292.
文摘We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresponding extended ab initio data set,we construct interpolation formulas covering the range from low-density,high-temperature to high-density,low-temperature plasmas.Our conductivity model repro-duces the well-known limits of the Spitzer and Ziman theory.We compare with available experimental data andfind very good agreement.The new conductivity model can be applied,for example,in dynamo simulations for magneticfield generation in gas giant planets,brown dwarfs,and stellar envelopes.
基金Financial support for this work was provided by the US Department of Commerce,National Institute of Standards and Technology(NIST)under the Financial Assistance Award Number(FAIN)#70NANB20H008.
文摘A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions.The effect of the hazard geometry(center and angle of tornado path as well as the tornado width)is studied herein on how it influences the recovery of physical and social systems within the community.Given that pre-disaster preparedness including mitigation strategies(e.g.,retrofits)and policies(e.g.,insurance)is crucial for increasing the resilience of the community and facilitating a faster recovery process,in this study,the impact of various mitigation strategies and policies on the recovery trajectory and resilience of a typical US community subjected to a tornado is investigated considering different sources of uncertainties.The virtual testbed of Centerville is selected in this paper and is modeled by adopting the Agent-based modeling(ABM)approach which is a powerful tool for conducting community resilience analysis that simulates the behavior of different types of agents and their interactions to capture their interdependencies.The results are presented in the form of recovery time series as well as calculated resilience indices for various community systems(lifeline networks,schools,healthcare,businesses,and households).The results of this study can help deepen our understanding of how to efficiently expedite the recovery process of a community.
基金supported by the National Natural Science Foundation of China(52200228 and 72022004)the China Postdoctoral Science Foundation(2022M721817)the National Key Scientific Research Project(2021YFC3200200).
文摘Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises.This study developed a universal dynamic agent-based supply chain model to achieve tradeoffs between environmental risk reduction and economic sus-tainability.The model was used to conduct high-resolution daily simulations of the dynamic shifts in enterprise operations and their cascading effects on supply chain networks.It includes production,con-sumption,and transportation agents,attributing economic features to supply chain components and cap-turing their interactions.It also accounts for adaptive responses to daily external shocks and replicates realistic firm behaviors.By coupling high spatial-temporal resolution firm-level data from 18916 chemical enterprises,this study investigates the economic and environmental impacts of an environmen-tal policy resulting in the closure of 1800 chemical enterprises over three years.The results revealed a significant economic loss of 25.8 billion USD,ranging from 23.8 billion to 31.8 billion USD.Notably,over 80%of this loss was attributed to supply chain propagation.Counterfactual analyses indicated that imple-menting a staggered shutdown strategy prevented 18.8%of supply chain losses,highlighting the impor-tance of a gradual policy implementation to prevent abrupt supply chain disruptions.Furthermore,the study highlights the effectiveness of a multi-objective policy design in reducing economic losses(about 29%)and environmental risks(about 40%),substantially enhancing the efficiency of the environmental policy.The high-resolution simulations provide valuable insights for policy designers to formulate strategies with staggered implementation and multiple objectives to mitigate supply chain losses and environmental risks and ensure a sustainable future.
文摘The advantages of a flat-panel X-ray source(FPXS)make it a promising candidate for imaging applications.Accurate imaging-system modeling and projection simulation are critical for analyzing imaging performance and resolving overlapping projection issues in FPXS.The conventional analytical ray-tracing approach is limited by the number of patterns and is not applicable to FPXS-projection calculations.However,the computation time of Monte Carlo(MC)simulation is independent of the size of the patterned arrays in FPXS.This study proposes two high-efficiency MC projection simulators for FPXS:a graphics processing unit(GPU)-based phase-space sampling MC(gPSMC)simulator and GPU-based fluence sampling MC(gFSMC)simulator.The two simulators comprise three components:imaging-system modeling,photon initialization,and physical-interaction simulations in the phantom.Imaging-system modeling was performed by modeling the FPXS,imaging geometry,and detector.The gPSMC simulator samples the initial photons from the phase space,whereas the gFSMC simulator performs photon initialization from the calculated energy spectrum and fluence map.The entire process of photon interaction with the geometry and arrival at the detector was simulated in parallel using multiple GPU kernels,and projections based on the two simulators were calculated.The accuracies of the two simulators were evaluated by comparing them with the conventional analytical ray-tracing approach and acquired projections,and the efficiencies were evaluated by comparing the computation time.The results of simulated and realistic experiments illustrate the accuracy and efficiency of the proposed gPSMC and gFSMC simulators in the projection calculation of various phantoms.
基金supported by National Natural Science Foundation of China(NSFC)(No.62101274 and 62101275)Natural Science Foundation of Jiangsu Province(BK20210640)Open Research Fund of National Mobile Communications Research Laboratory Southeast University under Grant 2021D03。
文摘In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.
