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
This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergen...This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.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
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
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 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
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
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
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
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
In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for la...In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for launch vehicles in China. It realizes a complex coupling model within a unified model for different domains, so that technologists can work on one model. It ensured the success of YL-1 first launch mission, supports rapid iteration, full validation, and tight design collaboration.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
The analysis of the characteristics of the cushion process of the pneumatic cushion cylinder is presented, and the nonlinear model of pneumatic cushion cylinders is built in the form of nonlinear differential equation...The analysis of the characteristics of the cushion process of the pneumatic cushion cylinder is presented, and the nonlinear model of pneumatic cushion cylinders is built in the form of nonlinear differential equations. Besides, through the simulation of the pressure in the cushion chamber, the characteristics of the pneumatic cushion cylinder are obtained, which helps to understand the performance of the pneumatic cushion cylinder and improve or design the better cushion structure.展开更多
This paper presents two approaches for system-level simulation of force-balance accelerometers. The derivation of the system-level model is elaborated and simulation results are obtained from the implementation of tho...This paper presents two approaches for system-level simulation of force-balance accelerometers. The derivation of the system-level model is elaborated and simulation results are obtained from the implementation of those strategies on the fabricated silicon force-balance MEMS accelerometer. The mathematical model presented is implemented in VHDL- AMS and SIMULINK TM,respectively. The simulation results from the two approaches are compared and show a slight difference. Using VHDL-AMS is flexible,reusable,and more accurate. But there is not a mature solver developed for the language and this approach takes more time, while the simulation model can be easily built and quickly evaluated using SIMULINK.展开更多
In order to explore the influence of welding parameters and to investigate the Al alloy (AA) nugget formation process, a comprehensive model involving electrical-thermal-mechanical and metallurgical analysis was estab...In order to explore the influence of welding parameters and to investigate the Al alloy (AA) nugget formation process, a comprehensive model involving electrical-thermal-mechanical and metallurgical analysis was established to numerically display the resistance spot welding (RSW) process within multiple fields and understand the AA-RSW physics. A multi-disciplinary finite element method (FEM) framework and a empirical sub-model were built to analyze the affecting factors on weld nugget and the underlying nature of welding physics with dynamic simulation procedure. Specifically, a counter-intuitive phenomenon of the resistance time-variation caused by the transient inverse virtual variation (TIVV) effect was highlighted and analyzed on the basis of welding current and temperature distribution simulation. The empirical model describing the TIVV phenomenon was used for modifying the dynamic resistance simulation during the AA spot welding process. The numerical and experimental results show that the proposed multi-field FEM model agrees with the measured AA welding feature, and the modified dynamic resistance model captures the physics of nugget growth and the electrical-thermal behavior under varying welding current and fluctuating heat input.展开更多
AIGaN/GaN HEMTs are investigated by numerical simulation from the self-consistent solution of Schr6dinger-Poisson-hydrodynamic （HD） systems. The influences of polarization charge and quantum effects are considered i...AIGaN/GaN HEMTs are investigated by numerical simulation from the self-consistent solution of Schr6dinger-Poisson-hydrodynamic （HD） systems. The influences of polarization charge and quantum effects are considered in this model. Then the two-dimensional conduction band and electron distribution, electron temperature characteristics, Id versus Vd and Id versus Vg, transfer characteristics and transconductance curves are obtained. Corresponding analysis and discussion based on the simulation results are subsequently given.展开更多
Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate b...Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.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.
文摘This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.
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.
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.
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 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 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.
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.
文摘In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for launch vehicles in China. It realizes a complex coupling model within a unified model for different domains, so that technologists can work on one model. It ensured the success of YL-1 first launch mission, supports rapid iteration, full validation, and tight design collaboration.
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.
文摘The analysis of the characteristics of the cushion process of the pneumatic cushion cylinder is presented, and the nonlinear model of pneumatic cushion cylinders is built in the form of nonlinear differential equations. Besides, through the simulation of the pressure in the cushion chamber, the characteristics of the pneumatic cushion cylinder are obtained, which helps to understand the performance of the pneumatic cushion cylinder and improve or design the better cushion structure.
文摘This paper presents two approaches for system-level simulation of force-balance accelerometers. The derivation of the system-level model is elaborated and simulation results are obtained from the implementation of those strategies on the fabricated silicon force-balance MEMS accelerometer. The mathematical model presented is implemented in VHDL- AMS and SIMULINK TM,respectively. The simulation results from the two approaches are compared and show a slight difference. Using VHDL-AMS is flexible,reusable,and more accurate. But there is not a mature solver developed for the language and this approach takes more time, while the simulation model can be easily built and quickly evaluated using SIMULINK.
基金Projects (11202125, 61175038) supported by the National Natural Science Foundation of China
文摘In order to explore the influence of welding parameters and to investigate the Al alloy (AA) nugget formation process, a comprehensive model involving electrical-thermal-mechanical and metallurgical analysis was established to numerically display the resistance spot welding (RSW) process within multiple fields and understand the AA-RSW physics. A multi-disciplinary finite element method (FEM) framework and a empirical sub-model were built to analyze the affecting factors on weld nugget and the underlying nature of welding physics with dynamic simulation procedure. Specifically, a counter-intuitive phenomenon of the resistance time-variation caused by the transient inverse virtual variation (TIVV) effect was highlighted and analyzed on the basis of welding current and temperature distribution simulation. The empirical model describing the TIVV phenomenon was used for modifying the dynamic resistance simulation during the AA spot welding process. The numerical and experimental results show that the proposed multi-field FEM model agrees with the measured AA welding feature, and the modified dynamic resistance model captures the physics of nugget growth and the electrical-thermal behavior under varying welding current and fluctuating heat input.
文摘AIGaN/GaN HEMTs are investigated by numerical simulation from the self-consistent solution of Schr6dinger-Poisson-hydrodynamic （HD） systems. The influences of polarization charge and quantum effects are considered in this model. Then the two-dimensional conduction band and electron distribution, electron temperature characteristics, Id versus Vd and Id versus Vg, transfer characteristics and transconductance curves are obtained. Corresponding analysis and discussion based on the simulation results are subsequently given.
基金supported by the National Natural Science Foundation of China(Grant No.52109010)the Postdoctoral Science Foundation of China(Grant No.2021M701047)the China National Postdoctoral Program for Innovative Talents(Grant No.BX20200113).
文摘Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.
