Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

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.

Two Monte Carlo-based simulators for imaging-system modeling and projection simulation of flat-panel X-ray source

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.

Novel Sum-of-Sinusoids Simulation Channel Modeling for 6G Multiple-Input Multiple-Output Vehicle-to-Everything Communications

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.

Application of Modelica Based Multi- Domain Modeling and Simulation for Gravity-1

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.

Agent-based Modeling and Simulation for the Electricity Market with Residential Demand Response

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.

An agent-based model of agricultural land expansion in the mountain forest of Timor Island,Indonesia

The Mutis-Timau Forest Complex,located on Timor Island,Indonesia,is a mountainous tropical forest area that gradually decreases due to deforestation and forest degradation.Previous modelling studies based on patterns indicate that deforestation primarily occurs at lower elevations and near the boundaries of forests and settlements,often associated with shifting cultivation by local farmers.This study adopts a process-based modelling approach,specifically the agent-based model,to simulate land changes,particularly farmers'expansion of agricultural land around the Mutis mountain forest.The underlying concept of this agent-based approach is the interaction between the human and environmental systems.Farmers,representing the human system,interact with the land,which represents the environmental system,through land use decision-making mechanisms.The research was conducted in the Community Forest of the Timor Tengah Utara District,one of the sites within the Mutis-Timau Forest Complex with the highest deforestation rate.Land use change simulations were performed using agent-based modelling from 1999 to 2030,considering the socio-economic conditions of farmers,spatial preferences,land use decisions,and natural transitions.The results revealed that the agricultural area increased by 14%under the Business as Usual scenario and 5%under the Reducing Emission from Deforestation and Forest Degradation scenario,compared to the initial agricultural area of 245 hectares.The probability of farmers deciding to extend agricultural activities was positively associated with the number of livestock maintained by farmers and the size of the village area.Conversely,the likelihood of farmers opting for agricultural extensification decreased with an increase in the area of private land and the farmer's age.These findings are crucial for the managers of the Mutis-Timau Forest Complex and other relevant stakeholders,as they aid in arranging actions to combat deforestation,designing proper forest-related policies,and providing support for initiatives such as reducing emissions from deforestation and forest degradation programs or further incentive schemes.

Investigating impacts of different building contents on the post-earthquake evacuation time using an agent-based model with considering turning behavior

Accurate assessment of crowd evacuation inside the post-earthquake environment is critical from many perspectives,but this issue receives much less attention compared to the seismic losses of structural and non-structural components.This could be attributed to the fact that post-earthquake evacuation analysis is complex due to the interaction between human behavior and the actual built environment induced by different building contents.This study attempts to tackle this problem by investigating the impacts of different building contents on post-earthquake evacuation time by using an agent-based model that considers turning behavior.To this end,the agent-based model is first described,including:properties of the agent-based model with turning behavior,key aspects in its formulation considering different evacuation stages,and influence of different building contents(namely,debris from partition walls and ceiling systems,and various types of equipment)on the agent’s behavior.Subsequently,a school building is used as a benchmark problem to validate the model without earthquake,and the findings indicate that the agent-based model can match the real safety drill results reasonably well.After the validation,the school building is subsequently designed in accordance with modern seismic design codes,and the influence of debris and equipment on post-earthquake evacuation time is quantitatively studied using a suite of pulse-type ground motions as input.Based on this case study,recommendations are made for structural and architectural designers in an effort to reduce the potential evacuation time.Specifically,debris induced by partition walls or ceiling systems should be controlled as it has the greatest impact on the total evacuation time.

Facilitated Prediction of Micropollutant Degradation via UV-AOPs in Various Waters by Combining Model Simulation and Portable Measurement

The degradation of micropollutants in water via ultraviolet(UV)-based advanced oxidation processes(AOPs)is strongly dependent on the water matrix.Various reactive radicals(RRs)formed in UV-AOPs have different reaction selectivities toward water matrices and degradation efficiencies for target micropollutants.Hence,process selection and optimization are crucial.This study developed a facilitated prediction method for the photon fluence-based rate constant for micropollutant degradation(K′_(p,MP))in various UV-AOPs by combining model simulation with portable measurement.Portable methods for measuring the scavenging capacities of the principal RRs(RRSCs)involved in UV-AOPs(i.e.,HO^(·),SO_(4)^(·-),and Cl^(·))using a mini-fluidic photoreaction system were proposed.The simulation models consisted of photochemical,quantitative structure–activity relationship,and radical concentration steady-state approximation models.The RRSCs were determined in eight test waters,and a higher RRSC was found to be associated with a more complex water matrix.Then,by taking sulfamethazine,caffeine,and carbamazepine as model micropollutants,the k′_(p,MP) values in various UV-AOPs were predicted and further verified experimentally.A lower k′_(p,MP) was found to be associated with a higher RRSC for a stronger RR competition;for example,k′_(p,MP) values of 130.9 and 332.5 m^(2) einstein^(–1),respectively,were obtained for carbamazepine degradation by UV/H_(2)O_(2) in the raw water(RRSC=9.47×10^(4) s^(-1))and sand-filtered effluent(RRSC=2.87×10^(4) s^(-1))of a drinking water treatment plant.The developed method facilitates process selection and optimization for UV-AOPs,which is essential for increasing the efficiency and cost-effectiveness of water treatment.

Multi-scenario Simulation and Spatial-temporal Analysis of LUCC in China's Coastal Zone Based on Coupled SD-FLUS Model

Increased human activities in China's coastal zone have resulted in the depletion of ecological land resources.Thus,conducting current and future multi-scenario simulation research on land use and land cover change(LUCC)is crucial for guiding the healthy and sustainable development of coastal zones.System dynamic(SD)-future land use simulation(FLUS)model,a coupled simulation model,was developed to analyze land use dynamics in China's coastal zone.This model encompasses five scenarios,namely,SSP1-RCP2.6(A),SSP2-RCP4.5(B),SSP3-RCP4.5(C),SSP4-RCP4.5(D),and SSP5-RCP8.5(E).The SD model simulates land use demand on an annual basis up to the year 2100.Subsequently,the FLUS model determines the spatial distribution of land use for the near term(2035),medium term(2050),and long term(2100).Results reveal a slowing trend in land use changes in China's coastal zone from 2000–2020.Among these changes,the expansion rate of construction land was the highest and exhibited an annual decrease.By 2100,land use predictions exhibit high accuracy,and notable differences are observed in trends across scenarios.In summary,the expansion of production,living,and ecological spaces toward the sea remains prominent.Scenario A emphasizes reduced land resource dependence,benefiting ecological land protection.Scenario B witnesses an intensified expansion of artificial wetlands.Scenario C sees substantial land needs for living and production,while Scenario D shows coastal forest and grassland shrinkage.Lastly,in Scenario E,the conflict between humans and land intensifies.This study presents pertinent recommendations for the future development,utilization,and management of coastal areas in China.The research contributes valuable scientific support for informed,long-term strategic decision making within coastal regions.

Explosion resistance performance of reinforced concrete box girder coated with polyurea:Model test and numerical simulation

To study the anti-explosion protection effect of polyurea coating on reinforced concrete box girder,two segmental girder specimens were made at a scale of 1:3,numbered as G(without polyurea coating)and PCG(with polyurea coating).The failure characteristics and dynamic responses of the specimens were compared through conducting explosion tests.The reliability of the numerical simulation using LS-DYNA software was verified by the test results.The effects of different scaled distances,reinforcement ratios,concrete strengths,coating thicknesses and ranges of polyurea were studied.The results show that the polyurea coating can effectively enhance the anti-explosion performance of the girder.The top plate of middle chamber in specimen G forms an elliptical penetrating hole,while that in specimen PCG only shows a very slight local dent.The peak vertical displacement and residual displacement of PCG decrease by 74.8% and 73.7%,respectively,compared with those of specimen G.For the TNT explosion with small equivalent,the polyurea coating has a more significant protective effect on reducing the size of fracture.With the increase of TNT equivalent,the protective effect of polyurea on reducing girder displacement becomes more significant.The optimal reinforcement ratio,concrete strength,thickness and range of polyurea coating were also drawn.

Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation

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.

Application of Patient Simulators Combined with Internet plus Scenario Simulation Teaching Models on Intravenous Infusion Nursing Education in China

Objective: To explore the effectiveness of applying patient simulators combined with Internet Plus scenario simulation teaching models on intravenous (IV) infusion nursing education, and to provide scientific evidence for the implementation of advanced teaching models in future nursing education. Methods: Enrolled 60 nurses who took the IV infusion therapy training program in our hospital from January 2022 to December 2023 for research. 30 nurses who were trained in traditional teaching models from January to December 2022 were selected as the control group, and 30 nurses who were trained with simulation-based teaching models with methods including simulated patients, internet, online meetings which can be replayed and scenario simulation, etc. from January to December 2023 were selected as the experimental group. Evaluated the learning outcomes based on the Competency Inventory for Nursing Students (CINS), Problem-Solving Inventory (PSI), comprehensive learning ability, scientific research ability, and proficiency in the theoretical knowledge and practical skills of IV infusion therapy. Nursing quality, the incidence of IV infusion therapy complications and nurse satisfaction with different teaching models were also measured. Results: The scientific research ability, PSI scores, CINS scores, and comprehensive learning ability of the experimental group were better than those of the control group (P 0.05), and their assessment results of practical skills, nursing quality of IV infusion therapy during training, and satisfaction with teaching models were all better than those of the control group with statistical significance (P < 0.05). The incidence of IV infusion therapy complications in the experimental group was lower than that in the control group, indicating statistical significance (P < 0.05). Conclusions: Teaching models based on patient simulators combined with Internet Plus scenario simulation enable nursing students to learn more directly and practice at any time and in any place, and can improve their proficiency in IV infusion theoretical knowledge and skills (e.g. PICC catheterization), core competencies, problem-solving ability, comprehensive learning ability, scientific research ability and the ability to deal with complicated cases. Also, it helps provide high-quality nursing education, improve the nursing quality of IV therapy, reduce the incidence of related complications, and ensure the safety of patients with IV therapy.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Full Dynamic Model for Liquid Sloshing Simulation in Cylindrical Tank Shape

This study presents a comprehensive full dynamic model designed for simulating liquid sloshing behavior within cylindrical tank structures. The model employs a discretization approach, representing the liquid as a network of interconnected spring-damper-mass systems. Key aspects include the adaptation of liquid discretization techniques to cylindrical lateral cross-sections and the calculation of stiffness and damping coefficients. External forces, simulating various vehicle maneuvers, are also integrated into the model. The resulting system of equations is solved using Maple Software with the Runge-Kutta-Fehlberg method. This model enables accurate prediction of liquid displacement and pressure forces, offering valuable insights for tank design and fluid dynamics applications. Ongoing refinement aims to broaden its applicability across different liquid types and tank geometries.

Bubble size modeling approach for the simulation of bubble columns

The constant bubble size modeling approach(CBSM)and variable bubble size modeling approach(VBSM)are frequently employed in Eulerian–Eulerian simulation of bubble columns.However,the accuracy of CBSM is limited while the computational efficiency of VBSM needs to be improved.This work aims to develop method for bubble size modeling which has high computational efficiency and accuracy in the simulation of bubble columns.The distribution of bubble sizes is represented by a series of discrete points,and the percentage of bubbles with various sizes at gas inlet is determined by the results of computational fluid dynamics(CFD)–population balance model(PBM)simulations,whereas the influence of bubble coalescence and breakup is neglected.The simulated results of a 0.15 m diameter bubble column suggest that the developed method has high computational speed and can achieve similar accuracy as CFD–PBM modeling.Furthermore,the convergence issues caused by solving population balance equations are addressed.

A goal-based approach for modeling and simulation of different types of system-of-systems

A system of systems(SoS)composes a set of independent constituent systems(CSs),where the degree of authority to control the independence of CSs varies,depending on different SoS types.Key researchers describe four SoS types with descending levels of central authority:directed,acknowledged,collaborative and virtual.Although the definitions have been recognized in SoS engineering,what is challenging is the difficulty of translating these definitions into models and simulation environments.Thus,we provide a goal-based method including a mathematical baseline to translate these definitions into more effective agent-based modeling and simulations.First,we construct the theoretical models of CS and SoS.Based on the theoretical models,we analyze the degree of authority influenced by SoS characteristics.Next,we propose a definition of SoS types by quantitatively explaining the degree of authority.Finally,we recognize the differences between acknowledged SoS and collaborative SoS using a migrating waterfowl flock by an agentbased model(ABM)simulation.This paper contributes to the SoS body of knowledge by increasing our understanding of the degree of authority in an SoS,so we may identify suitable SoS types to achieve SoS goals by modeling and simulation.

Cosserat Dynamic Modeling and Simulation of Mobile Cable on Satellite

Mainly for the problems that the configuration of the mobile cable on the satellite is very easy to change,the motion trajectory and dynamic characteristics of the cable can not be accu-rately predicted,which affects the laying quality seriously,the dynamic modeling and simulation of mobile cable on the satellite are carried out.On the basis of referring to the previous papers,the existing mathematical model is improved.The equations of the base vector of the cable section principal axis coordinate system with respect to the arc coordinate s,the distribution force of cable balance equation,the matrix expression of the base vector after the rotation motion transformation in the section principal axis coordinate system,the angular velocity of cable,the section elastic strain and velocity calculation equations are given,and the Cosserat dynamic modeling of the mobile cable is established.Finally,the dynamic simulation model of the mobile cable assembly of the kinematic mechanism is established,and the changes of the force and torque on the cable con-straint end are obtained,which provides a reference for the dynamic modeling and simulation of the mobile cable on satellite.

Simulation-based Graphic Method for Dynamic System Modeling

The first step for engineering students to understand the practical system is to describe the system,which means to establish the mathematic model for the considered system.However,traditional mathematical modeling techniques are not readily assimilated by students,because the traditional modeling needs to obey the complicated physical laws for different engineering areas and requires a highly iterative process.In this paper,the simulation-based graphic modeling method is introduced to help students model the system and improve their performance in engineering education.The results from the questionnaire indicate that the simulation-based graphic method can help students to do the modeling of the system and improve their performance compared to the traditional ways.

Simulation and Modeling of Common Mode EMI Noise in Planar Transformers

The transformer is the key circuit component of the common-mode noise current when an isolated converter is working.The highfrequency characteristics of the transformer have an important influence on the common-mode noise of the converter.Traditionally,the measurement method is used for transformer modeling,and a single lumped device is used to establish the transformer model,which cannot be predicted in the transformer design stage.Based on the transformer common-mode noise transmission mechanism,this paper derives the transformer common-mode equivalent capacitance under ideal conditions.According to the principle of experimental measurement of the network analyzer,the electromagnetic field finite element simulation software three-dimensional(3D)modeling and simulation method is used to obtain the two-port parameters of the transformer,extract the high-frequency parameters of the transformer,and establish its electromagnetic compatibility equivalent circuit model.Finally,an experimental prototype is used to verify the correctness of the model by comparing the experimental measurement results with the simulation prediction results.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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.