Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties i...We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties in each construction phase.Specifically,the algorithm is developed for the Government Assisted Owner Driven(GAOD)reconstruction system to simulate long-term recovery trajectory.SDES,as a flexible modeling approach,can simulate any housing recovery scenario that follows phased reconstruction.The 2015 M 7.8 Gorkha earthquake sequence in Nepal is considered the extreme event,with 796,245 buildings requiring reconstruction.We present some recovery trajectories from severely hit,crisis hit,and earthquake hit parishes,comparing them with the actual reconstruction progress.We also assess quality and improvement of reconstructed buildings using seismic fragility functions,compared to pre-earthquake constructions.Housing recovery uncertainties are dissected in relation to reconstruction pace.We conclude that the vast majority of the reconstructed buildings followed the Build Back Better(BBB)approach and missed the opportunity to pursue the Build Back Resilient(BBR)approach due to multifaceted challenges ranging from unclear policies to economic constraints.We critically assess the GAOD vs Owner Driven(OD)recovery framework and conclude that insurance-supported and technically assisted OD approach could be the most suitable model for post extreme event housing recovery.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
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
The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-ti...The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.展开更多
This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionar...This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionary processes.By representing agents and their defined environments with probabilistic interactions,ABM allows the assessment of the effects of individual behavior at the micro level on the greater social phenomena at the macro level.The review looks into the applications of ABM in portraying some of the key components of emotions and cognition-empathy,cooperation,decision making,and emotional transmission-and analyzes the problems including scalability,empirical validation,and description of sensitive emotional states.The most important conclusion is that merging ABM with information neurobiological data and artificial intelligence(AI)techniques would allow for deepening the interactions within the system and enhancing its responsiveness to stimuli.This review highlights approaches that aim to exploit the ABM methodology more fully and integrates methods from biology,neuroscience,and engineering.This integration could contribute to our understanding of the human behavior evolution and adaptation within systems relevant to policymaking,healthcare,and education.展开更多
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
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
Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and find...Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and finding shelter are vital for search and rescue managers.At the same time,many unpredicted challenges,such as the sudden increase in travel demand,shifts in public behavior,and the change in the regular transport supply,may arise due to evacuation conditions,which lead to different situations.This paper aims to introduce an approach for quick decision-making and timely evacuation response required by establishing a situation-aware system to minimize these risks and ensure the success of the evacuation plans,to support and predict current and future actions within the dynamic space of the crisis.The main contribution is innovating a Situation-Aware Emergency Evacuation(SAEE)model to enable crisis managers and evacuees to make the right decisions by providing timely and reliable information about the situation.This method is utilized in two situations:designing the emergency evacuation plan and finding the shortest/safest routes to reduce travel time for evacuees.Therefore,a hybrid approach is introduced,which involves a Fuzzy Inference System(FIS)and Deep Long Short-Term Memory(DLSTM)algorithm to identify,infer,and extract the existing situation at different levels(e.g.people,vehicles,and surroundings)after a foreshock using multi-agent-based simulation.The method proposed was simulated in the traffic network of District 6 of Tehran,the capital of Iran.The model results show that the evacuees'spatial knowledge and perception,as well as awareness of the situation of other agents and their surroundings,led to a significant(40%)reduction in the complete evacuation time.This time is considered the most pivotal factor in saving human lives and their arrival in safer areas.The role of situation awareness systems and increasing human cognition and perception can significantly help in this matter.展开更多
This 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
The previous study on modeling of the tilt rotor aircraft used to put a premium on the complicated aerodynamic computation, and the research on the motion equations is often constrained to frequently use the oversimpl...The previous study on modeling of the tilt rotor aircraft used to put a premium on the complicated aerodynamic computation, and the research on the motion equations is often constrained to frequently use the oversimplified 6-degree of freedom （DOF） rigid body equations. However, the transfiguration of aircraft during transition stage, is complicated due to the aerodynamic interference and the change of center of gravity （CG）. Moreover, the gyroscopic moment caused by tilting the high-speed revolving rotors seriously interferes with the aircraft attitude. The above-cited 6-DOF single rigid body equations do not take the inertia coupling effects into account during transition. For this sake, the article, reckoning the body, the nacelles and the rotors to be independent entities, establishes a realistic model in the form of multi-body motion equations. First, by applying Newton＇s laws and angular momentum theorem to a mass of elements of the aircraft, the multi-body motion equations in inertial flame as well as in body frame are obtained by integrating over all elements. As the equations are of implicit nonlinear differential type, the consistent initial value problem should be solved. Then, a numerical simulation of the differential equations is conducted by means of the Runge-Kutta-Felhberg integral algorithm. The modeling and the simulation algorithm are verified against the data of XV-15 as an example. The model can be used in the area of flight dynamics, flight control and flight safety of tilt rotor air- craft.展开更多
The constitutive modeling and springback simulation for AA2524 sheet in creep age forming（CAF） process were presented.A series of creep aging tests were performed on AA2524 at the temperature of 180-200 °C and ...The constitutive modeling and springback simulation for AA2524 sheet in creep age forming（CAF） process were presented.A series of creep aging tests were performed on AA2524 at the temperature of 180-200 °C and under the stress of 140-210 MPa for 16 h.Based on these experimental data,material constitutive equations which can well characterize creep aging behaviors of the tested alloy were developed.The effect of interior stress distributed along the sheet thickness on springback was simulated using FE software MSC.MARC by compiling the established constitutive models into the user subroutine.The simulation results showed that the amount of sheet springback was 61.12% when merely considering tensile stress existing along the sheet thickness;while sheet springback was up to 65.93% when taking both tensile and compressive stresses into account.In addition,an AA2524 rectangular sheet was subjected to CAF experiment in resistance furnace.The springback value of the formed rectangular sheet was 68.2%,which was much closer to 65.93%.This confirms that both tensile and compressive stresses across the sheet thickness should be considered in accurately predicting springback of the sheet after forming,which can be more consistent with experimental results.展开更多
The stochastic extended finite-fault simulation method(EXSIM)is a widely used tool in seismological research,with applications in ground motion prediction and simulation,seismic hazard analysis,and engineering studies...The stochastic extended finite-fault simulation method(EXSIM)is a widely used tool in seismological research,with applications in ground motion prediction and simulation,seismic hazard analysis,and engineering studies.However,recent studies have revealed a significant limitation:EXSIM tends to overpredict ground motions in the low-to-intermediate frequency range,particularly for large thrust earthquakes that are often characterized by a double-corner-frequency source model.To address this issue and enhance simulation accuracy,this study introduces two key improvements:(1)a novel asperity-distributed stress-drop composite fault model and(2)a hybrid application of EXSIM with the composite fault model.The proposed method is validated through its application to the 2013 M_(w)6.7 Lushan earthquake that occurred in China and six thrust earthquakes with an M_(w)≥6.5 in Japan.By comparing the simulated ground motions with recorded data,the results demonstrate that the improved method achieves consistent accuracy across the high-and low-frequency spectrum(combined goodness-of-fit:CGOF<0.35).This study significantly broadens the applicability of stochastic finite-fault simulations,enabling more reliable predictions for a wider range of seismic scenarios,including complex thrust faulting events.展开更多
A more general narrowband regular-shaped geometry-based statistical model(RS-GBSM) combined with the line of sight(LoS) and single bounce(SB) rays for unmanned aerial vehicle(UAV) multiple-input multiple-output(MIMO) ...A more general narrowband regular-shaped geometry-based statistical model(RS-GBSM) combined with the line of sight(LoS) and single bounce(SB) rays for unmanned aerial vehicle(UAV) multiple-input multiple-output(MIMO) channel is proposed in this paper. The channel characteristics, including space-time correlation function(STCF), Doppler power spectral density(DPSD), level crossing rate(LCR) and average fade duration(AFD), are derived based on the single sphere reference model for a non-isotropic environment. The corresponding sum-of-sinusoids(SoS) simulation models including both the deterministic model and statistical model with finite scatterers are also proposed for practicable implementation. The simulation results illustrate that the simulation models well reproduce the channel characteristics of the single sphere reference model with sufficient simulation scatterers. And the statistical model has a better approximation of the reference model in comparison with the deterministic one when the simulation trials of the stochastic model are sufficient. The effects of the parameters such as flight height, moving direction and Rice factor on the characteristics are also studied.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
Because the normal operation of the engine is located near the equilibrium manifold, the method of equilibrium mani fold nonlinear dynamic modeling is adopted for turbofan engine more than the local train modeling. Th...Because the normal operation of the engine is located near the equilibrium manifold, the method of equilibrium mani fold nonlinear dynamic modeling is adopted for turbofan engine more than the local train modeling. The method studies the sys tem characteristics near the equilibrium manifold. The modeling method can be realized through dynamic and static twostep, and for the specific parameter modeling steps and algorithm are given. The output of the test data is compared with the model output through numerical simulation, to check the model with an additional set of test data. The simulation results show that the model has reached the requirements of engineering accuracy.展开更多
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
文摘We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties in each construction phase.Specifically,the algorithm is developed for the Government Assisted Owner Driven(GAOD)reconstruction system to simulate long-term recovery trajectory.SDES,as a flexible modeling approach,can simulate any housing recovery scenario that follows phased reconstruction.The 2015 M 7.8 Gorkha earthquake sequence in Nepal is considered the extreme event,with 796,245 buildings requiring reconstruction.We present some recovery trajectories from severely hit,crisis hit,and earthquake hit parishes,comparing them with the actual reconstruction progress.We also assess quality and improvement of reconstructed buildings using seismic fragility functions,compared to pre-earthquake constructions.Housing recovery uncertainties are dissected in relation to reconstruction pace.We conclude that the vast majority of the reconstructed buildings followed the Build Back Better(BBB)approach and missed the opportunity to pursue the Build Back Resilient(BBR)approach due to multifaceted challenges ranging from unclear policies to economic constraints.We critically assess the GAOD vs Owner Driven(OD)recovery framework and conclude that insurance-supported and technically assisted OD approach could be the most suitable model for post extreme event housing recovery.
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 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supported by the Advanced Materials-National Science and Technology Major Project(Grant No.2025ZD0618401)the National Natural Science Foundation of China(Grant No.12504285)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20250472)NFSG grant from BITS-Pilani,Dubai campus。
文摘The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.
文摘This review explores the use of agent-based modeling(ABM)within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions,adaptive changes,and evolutionary processes.By representing agents and their defined environments with probabilistic interactions,ABM allows the assessment of the effects of individual behavior at the micro level on the greater social phenomena at the macro level.The review looks into the applications of ABM in portraying some of the key components of emotions and cognition-empathy,cooperation,decision making,and emotional transmission-and analyzes the problems including scalability,empirical validation,and description of sensitive emotional states.The most important conclusion is that merging ABM with information neurobiological data and artificial intelligence(AI)techniques would allow for deepening the interactions within the system and enhancing its responsiveness to stimuli.This review highlights approaches that aim to exploit the ABM methodology more fully and integrates methods from biology,neuroscience,and engineering.This integration could contribute to our understanding of the human behavior evolution and adaptation within systems relevant to policymaking,healthcare,and education.
基金Financial support for this work was provided by the US Department of Commerce,the National Institute of Standards and Technology(NIST)under the Financial Assistance Award Number#70NANB20H008the US National Science Foundation(NSF)under Award Number 2052930.
文摘There has been a large increase in the number of days per year with numerous EF1-EF5 tornadoes.Given the significant damage incurred by tornadoes upon communities,community resilience analyses for tornado-stricken communities have been gaining momentum.As the community resilience analysis aims to guide how to lay out effective hazard mitigation strategies to decrease damage and improve recovery,a comprehensive and accurate approach is necessary.Agent-based modeling,an analysis approach in which different types of agents are created with their properties and behavior clearly defined to simulate the processes of those agents in an external environ-ment,is the most comprehensive and accurate approach so far to conducting community resilience simulations and investigating the decision-making for mitigation and recovery under natural hazards.In this paper,agent-based models(ABMs)are created to simulate the recovery process of a virtual testbed based on the real-world community in Joplin City,MO.The tornado path associated with the real-world tornado event that occurred in May 2011 is adopted in the tornado hazard modeling for the Joplin testbed.In addition,agent-based models are created for another virtual community in the Midwest United States named Centerville using an assumed tornado scenario of the same EF-scale as that in Joplin.The effects of hazard mitigation strategies on the two communities are also explored.A comparison between the analysis results of these two testbeds can indicate the influence of the characteristics of a tornado-prone community on the resilience of the community as well as on the effects of hazard mitigation strategies.It is observed that a community’s level of development significantly impacts the tornado resilience.In addition,the effects of a specific type of hazard mitigation strategy on the recovery process are contingent upon testbed characteristics.
文摘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Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and finding shelter are vital for search and rescue managers.At the same time,many unpredicted challenges,such as the sudden increase in travel demand,shifts in public behavior,and the change in the regular transport supply,may arise due to evacuation conditions,which lead to different situations.This paper aims to introduce an approach for quick decision-making and timely evacuation response required by establishing a situation-aware system to minimize these risks and ensure the success of the evacuation plans,to support and predict current and future actions within the dynamic space of the crisis.The main contribution is innovating a Situation-Aware Emergency Evacuation(SAEE)model to enable crisis managers and evacuees to make the right decisions by providing timely and reliable information about the situation.This method is utilized in two situations:designing the emergency evacuation plan and finding the shortest/safest routes to reduce travel time for evacuees.Therefore,a hybrid approach is introduced,which involves a Fuzzy Inference System(FIS)and Deep Long Short-Term Memory(DLSTM)algorithm to identify,infer,and extract the existing situation at different levels(e.g.people,vehicles,and surroundings)after a foreshock using multi-agent-based simulation.The method proposed was simulated in the traffic network of District 6 of Tehran,the capital of Iran.The model results show that the evacuees'spatial knowledge and perception,as well as awareness of the situation of other agents and their surroundings,led to a significant(40%)reduction in the complete evacuation time.This time is considered the most pivotal factor in saving human lives and their arrival in safer areas.The role of situation awareness systems and increasing human cognition and perception can significantly help in this matter.
文摘This 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Graduate Innovation and Practice Foundation of Beijing University of Aeronautics amd Astronautics
文摘The previous study on modeling of the tilt rotor aircraft used to put a premium on the complicated aerodynamic computation, and the research on the motion equations is often constrained to frequently use the oversimplified 6-degree of freedom （DOF） rigid body equations. However, the transfiguration of aircraft during transition stage, is complicated due to the aerodynamic interference and the change of center of gravity （CG）. Moreover, the gyroscopic moment caused by tilting the high-speed revolving rotors seriously interferes with the aircraft attitude. The above-cited 6-DOF single rigid body equations do not take the inertia coupling effects into account during transition. For this sake, the article, reckoning the body, the nacelles and the rotors to be independent entities, establishes a realistic model in the form of multi-body motion equations. First, by applying Newton＇s laws and angular momentum theorem to a mass of elements of the aircraft, the multi-body motion equations in inertial flame as well as in body frame are obtained by integrating over all elements. As the equations are of implicit nonlinear differential type, the consistent initial value problem should be solved. Then, a numerical simulation of the differential equations is conducted by means of the Runge-Kutta-Felhberg integral algorithm. The modeling and the simulation algorithm are verified against the data of XV-15 as an example. The model can be used in the area of flight dynamics, flight control and flight safety of tilt rotor air- craft.
基金Project(2014CB046602)supported by the National Basic Research Program of ChinaProject(20120162110003)supported by Ph D Programs Foundation of Ministry of Education of China
文摘The constitutive modeling and springback simulation for AA2524 sheet in creep age forming（CAF） process were presented.A series of creep aging tests were performed on AA2524 at the temperature of 180-200 °C and under the stress of 140-210 MPa for 16 h.Based on these experimental data,material constitutive equations which can well characterize creep aging behaviors of the tested alloy were developed.The effect of interior stress distributed along the sheet thickness on springback was simulated using FE software MSC.MARC by compiling the established constitutive models into the user subroutine.The simulation results showed that the amount of sheet springback was 61.12% when merely considering tensile stress existing along the sheet thickness;while sheet springback was up to 65.93% when taking both tensile and compressive stresses into account.In addition,an AA2524 rectangular sheet was subjected to CAF experiment in resistance furnace.The springback value of the formed rectangular sheet was 68.2%,which was much closer to 65.93%.This confirms that both tensile and compressive stresses across the sheet thickness should be considered in accurately predicting springback of the sheet after forming,which can be more consistent with experimental results.
基金National Key Research and Development Program of China under Grant No.2022YFC3003601National Natural Science Foundation of China under Grant No.52478570+1 种基金Heilongjiang Provincial Natural Science Foundation Outstanding Youth Program under Grant No.J020245002the Key Research and Development Program of Xinjiang Production and Construction Corps under Grant No.2024AB077。
文摘The stochastic extended finite-fault simulation method(EXSIM)is a widely used tool in seismological research,with applications in ground motion prediction and simulation,seismic hazard analysis,and engineering studies.However,recent studies have revealed a significant limitation:EXSIM tends to overpredict ground motions in the low-to-intermediate frequency range,particularly for large thrust earthquakes that are often characterized by a double-corner-frequency source model.To address this issue and enhance simulation accuracy,this study introduces two key improvements:(1)a novel asperity-distributed stress-drop composite fault model and(2)a hybrid application of EXSIM with the composite fault model.The proposed method is validated through its application to the 2013 M_(w)6.7 Lushan earthquake that occurred in China and six thrust earthquakes with an M_(w)≥6.5 in Japan.By comparing the simulated ground motions with recorded data,the results demonstrate that the improved method achieves consistent accuracy across the high-and low-frequency spectrum(combined goodness-of-fit:CGOF<0.35).This study significantly broadens the applicability of stochastic finite-fault simulations,enabling more reliable predictions for a wider range of seismic scenarios,including complex thrust faulting events.
基金supported in part by the National Natural Science Foundation of China under Grant 61622101 and Grant 61571020National Science and Technology Major Project under Grant 2018ZX03001031
文摘A more general narrowband regular-shaped geometry-based statistical model(RS-GBSM) combined with the line of sight(LoS) and single bounce(SB) rays for unmanned aerial vehicle(UAV) multiple-input multiple-output(MIMO) channel is proposed in this paper. The channel characteristics, including space-time correlation function(STCF), Doppler power spectral density(DPSD), level crossing rate(LCR) and average fade duration(AFD), are derived based on the single sphere reference model for a non-isotropic environment. The corresponding sum-of-sinusoids(SoS) simulation models including both the deterministic model and statistical model with finite scatterers are also proposed for practicable implementation. The simulation results illustrate that the simulation models well reproduce the channel characteristics of the single sphere reference model with sufficient simulation scatterers. And the statistical model has a better approximation of the reference model in comparison with the deterministic one when the simulation trials of the stochastic model are sufficient. The effects of the parameters such as flight height, moving direction and Rice factor on the characteristics are also studied.
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Because the normal operation of the engine is located near the equilibrium manifold, the method of equilibrium mani fold nonlinear dynamic modeling is adopted for turbofan engine more than the local train modeling. The method studies the sys tem characteristics near the equilibrium manifold. The modeling method can be realized through dynamic and static twostep, and for the specific parameter modeling steps and algorithm are given. The output of the test data is compared with the model output through numerical simulation, to check the model with an additional set of test data. The simulation results show that the model has reached the requirements of engineering accuracy.
