Quantum computers accelerate many algorithms based on the superposition principle of quantum mechanics.The Grover algorithm provides significant performance to malicious users attacking symmetric key systems.Since the...Quantum computers accelerate many algorithms based on the superposition principle of quantum mechanics.The Grover algorithm provides significant performance to malicious users attacking symmetric key systems.Since the performance of attacks using quantum computers depends on the efficiency of the quantum circuit of the encryption algorithms,research research on the implementation of quantum circuits is essential.This paper presents a new framework to construct quantum circuits of substitution boxes(S-boxes)using system modeling.We model the quantum circuits of S-boxes using two layers:Toffoli and linear layers.We generate vector spaces based on the values of qubits used in the linear layers and apply them to find quantum circuits.The framework finds the circuit bymatching elements of vector spaces generated fromthe input and output of a given S-box,using the forward search or themeet-in-the-middle strategy.We developed a tool to apply this framework to 4-bit S-boxes.While the 4-bit S-box quantum circuit construction tool LIGHTER-R only finds circuits that can be implemented with four qubits,the proposed tool achieves the circuits with five qubits.The proposed tool can find quantum circuits of 4-bit odd permutations based on the controlled NOT,NOT,and Toffoli gates,whereas LIGHTER-R is unable to perform this task in the same environment.We expect this technique to become a critical step toward optimizing S-box quantum circuits.展开更多
A system model is established to analyze the dynamic performance of an integrated starter and generator （ISG） hybrid power shafting. The model couples the electromechanical coupling shaft dynamics, the bearing hydro...A system model is established to analyze the dynamic performance of an integrated starter and generator （ISG） hybrid power shafting. The model couples the electromechanical coupling shaft dynamics, the bearing hydrodynamic lubrication and the engine block stiffness. The model is com- pared with the model based on ADAMS or the model neglecting the bearing hydrodynamics. The bearing eccentricity and the oil film pressure have been calculated under different hybrid conditions or at the different motor power levels. It＇ s found that the bearing hydrodynamics decreases the cal- culation results of the bearing peak load. Changes of the hybrid conditions or the motor power have no significant effect on the main bearing, but have impact on the motor bearing. A hybrid power sys- tem composed of a 1.6 L engine and a 45 kW ISG motor can operate safely.展开更多
With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.展开更多
The proton exchange membrane fuel cell,as a novel energy device,exhibits a wide array of potential applications.This paper offers a comprehensive review and discussion of modeling and control strategies for fuel cell ...The proton exchange membrane fuel cell,as a novel energy device,exhibits a wide array of potential applications.This paper offers a comprehensive review and discussion of modeling and control strategies for fuel cell systems.It commences with a concise introduction to the structure and principles of fuel cells.Subsequently,it outlines modeling approaches for various fuel cell subsystems,encompassing the fuel cell stack,air supply system,hydrogen supply system,thermal management system,and water management system.Following this,it conducts a comparative analysis and discussion of prevalent control strategies for the aforementioned subsystems.Lastly,the paper outlines future research trends and directions in the modeling and control strategies of fuel cells.The aim of this paper is to provide ideas and inspirations for the design and management of membrane fuel cell systems from control aspects.展开更多
In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the d...In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely correct.Formal verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented correctly.In this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly instructions.The verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.展开更多
As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS...As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.展开更多
This study investigates the application of a support vector machine(SVM)-based model for classifying students’learning abilities in system modeling and simulation courses,aiming at enhancing personalized education.A ...This study investigates the application of a support vector machine(SVM)-based model for classifying students’learning abilities in system modeling and simulation courses,aiming at enhancing personalized education.A small dataset,collected from a pre-course questionnaire,is augmented with integer data to improve model performance.The SVM model achieves an accuracy rate of 95.3%.This approach not only benefits courses at Guizhou Minzu University but also has potential for broader application in similar programs in other institutions.The research provides a foundation for creating personalized learning paths using AI technologies,such as AI-generated content,large language models,and knowledge graphs,offering insights for innovative educational practices.展开更多
In the electric arc furnace （EAF） steel production processes, scrap steel is principally used as a raw material instead of iron ore. In the steelmaking process with EAF, scrap is first melted in the furnace and then...In the electric arc furnace （EAF） steel production processes, scrap steel is principally used as a raw material instead of iron ore. In the steelmaking process with EAF, scrap is first melted in the furnace and then the desired chemical composition of the steel can be obtained in a special furnace such as ladle furnace （LF）. This kind of furnace process is used for the secondary refining of alloy steel. LF furnace offers strong heating fluxes and enables precise temperature control, thereby allowing for the addition of desired amounts of various alloying elements. It also provides outstanding desulfurization at high-temperature treatment by reducing molten steel fluxes and removing deoxidation products. Elemental analysis with mass balance modeling is important to know the precise amount of required alloys for the LF input with respect to scrap composition. In present study, chemical reactions with mass conservation law in EAF and LF were modeled altogether as a whole system and chemical compositions of the final steel alloy output can be obtained precisely according to different scrap compositions, alloying elements ratios, and other input amounts. Besides, it was found that the mass efficiency for iron element in the system is 95.93%. These efficiencies are calculated for all input elements as 8. 45% for C, 30.31% for Si, 46.36% for Mn, 30.64% for P, 41.96% for S, and 69.79% for Cr, etc. These efficiencies provide valuable ideas about the amount of the input materials that are vanished or combusted for 100 kg of each of the input materials in the EAF and LF system.展开更多
In this paper a modeling method of ATC system is developed by using object Petri net. The formalized definition of the senior Petri net is given and illustrated by a practical example.
Heuristic or clustering based time series aggregation methods are often used to reduce temporal complexity of energy system models by selecting representative days.However,these methods potentially neglect relevant in...Heuristic or clustering based time series aggregation methods are often used to reduce temporal complexity of energy system models by selecting representative days.However,these methods potentially neglect relevant information of time series(e.g.,distribution parameters).To identify relevant time series parameters,feature selection algorithms can be applied.The present research contributes by(a)developing a new feature selection approach based on clustering,nested modeling and regression(CNR)which is designed for applications requiring high selectivity and using different data sets,(b)comparing and evaluating CNR with feature selection methods available from the literature(e.g.,LASSO)and(c)identifying relevant information of the time series applied in energy system models,in particular those of demand,photovoltaic and wind.Results show that CNR achieves on average up to 101%lower mean absolute errors when methods are directly compared.Thus,CNR better identifies relevant information when the number of selected features is restricted.The disadvantage of CNR,however,is its high computational effort.A potential remedy to counter this is the combination with another method(e.g.,as pre-feature selection).In terms of relevant information,energy systems including photovoltaic are mainly characterized by the correlation between demand and photovoltaic time series as well as the range and the 35%quantile of demand.When energy systems include wind power,the minimum and mean of wind as well as the correlation between demand and wind time series are relevant characteristics.The implications of these findings are discussed.展开更多
Generally,an accurate model can describe the operating states of a system more effectively and provide a more reliable theoretical basis for the system optimization and control.Different from the traditional intrusive...Generally,an accurate model can describe the operating states of a system more effectively and provide a more reliable theoretical basis for the system optimization and control.Different from the traditional intrusive modeling,a non-intrusive modeling method based on two-stage generative adversarial network(TS-GAN)is proposed for integrated energy system(IES).By using this method,non-intrusive modeling for the IES including photovoltaic,wind power,energy storage,and energy coupling equipment can be carried out.First,the characteristics of IES are analyzed and extracted based on the meteorological data,energy output,and energy price,and then the characteristic database is established.Meanwhile,the loads are classified as uncontrollable loads and schedulable loads based on frequency domain decomposition to facilitate energy management.Furthermore,TS-GAN algorithm based on the Stackelberg game is designed.In the TS-GAN,the first-stage GAN is used to generate the operating data of each equipment identified by non-invasive monitoring,and the second-stage GAN distinguishes the accumulated data generated by first-stage GAN and further modifies the generator models of the first-stage GAN.Finally,the effectiveness and accuracy of the proposed method are verified by the simulation of an energy region.展开更多
The paper presents a new modeling method applied to fault diagnosis for constant linear closed-loop system by taking the impulse response series as the system model, and provides the calculation process of the method ...The paper presents a new modeling method applied to fault diagnosis for constant linear closed-loop system by taking the impulse response series as the system model, and provides the calculation process of the method and output of model. The high frequency part of the pulse series, in the method, is reversed so as not to lose the frequency information of the pulse series in its transfer function. On the other hand, the method can also avoid the disadvantage that the learning results of neural network are uncertain every time. In the last part, the application with random disturbance of digital simulation and practical system shows that the modeling method is high accurate and suitable to be applied in fault diagnosis area.展开更多
Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of ...Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.展开更多
A fuzzy modeling method for complex systems is studied. The notation of general stochastic neural network (GSNN) is presented and a new modeling method is given based on the combination of the modified Takagi and Suge...A fuzzy modeling method for complex systems is studied. The notation of general stochastic neural network (GSNN) is presented and a new modeling method is given based on the combination of the modified Takagi and Sugeno's (MTS) fuzzy model and one-order GSNN. Using expectation-maximization(EM) algorithm, parameter estimation and model selection procedures are given. It avoids the shortcomings brought by other methods such as BP algorithm, when the number of parameters is large, BP algorithm is still difficult to apply directly without fine tuning and subjective tinkering. Finally, the simulated example demonstrates the effectiveness.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
An integrated study on source rock characterization and hydrocarbon generation potential modeling was conducted for the selected Dingo Claystone,Barrow Sub-basin,Australia.In this study,data were collected solely from...An integrated study on source rock characterization and hydrocarbon generation potential modeling was conducted for the selected Dingo Claystone,Barrow Sub-basin,Australia.In this study,data were collected solely from two wells represented by the Bambra-1 and Bambra-2 wells.The collected data include those from bulk geochemical analyses of cuttings and sidewall cores sampled from the Late Jurassic Dingo Claystone.Geochemical data obtained from Rock-Eval pyrolysis and gas chromatography(GC)of extracted organic matter were integrated for source rock characterization and the construction of burial history and hydrocarbon generation in the Dingo Claystone.To improve the accuracy of thermal maturity estimations,only samples with S2 greater than 1 were considered due to potential issues with peak integration and uncertainties of Tmax determination in samples with lower S2 values.Furthermore,Rock-Eval data from the Bambra wells may be unreliable due to the contamination of cuttings and sidewall core(SWC)samples by drilling mud additives and natural hydrocarbons,which could impact the reliability of the data for determining thermal maturity.This study reveals that the Dingo Claystone Formation has total organic carbon(TOC)contents ranging from 0.66%to 8.31%.A poor to good hydrocarbon generation potential is indicated,with a production yield(PY=S_(1)+S_(2))ranging from 1.37 to 10.44 mg HC/g rock.Hydrogen index values vary between 42 and 226 mg HC/g TOC,confirming that the Dingo Claystone is dominantly kerogen TypeⅢ,with minor contributions from typesⅡ/ⅢandⅣ.Thermal maturity ranges from immature to late mature and is mostly in the oil window.This is indicated by T_(max)values of 398-462℃and vitrinite reflectance(Ro,%)of 0.47-1.99.Some samples show suppressed T_(max)and a higher production index,which is typical for samples affected by drilling fluids during drilling operations.Additionally,gas chromatography(GC)analyses are used to interpret the paleodepositional environment showing mixed input between marine and terrestrial origins of the source rocks.One-dimensional basin modeling for the Bambra-1 and Bambra-2 wells was carried out to evaluate the burial and thermal history of the formation.The transformation ratio suggests that hydrocarbon generation has not reached its peak and is still in an ongoing phase.An indication of hydrocarbon migration can be observed in this formation based on the transformation ratio.The effects of contamination warrant further investigation,as it could significantly impact maturity estimates and data reliability.展开更多
In order to speed up and simplify the design of the quadrotor unmanned aerial vehicle(UAV)and carry out experimental simulation and verification of relevant control algorithms,this paper analyzed the system dynamics m...In order to speed up and simplify the design of the quadrotor unmanned aerial vehicle(UAV)and carry out experimental simulation and verification of relevant control algorithms,this paper analyzed the system dynamics model of the mechanical structure and flight principle of the quadrotor aircraft,and used the Newton-Euler method to derive the non-linear dynamic equations.Aiming at improving the modeling accuracy and system integrity of the quadrotor,the physical system modeling was combined with the CAD software and the Matlab/Simscape toolbox.The three-dimensional quadrotor solid model built by CAD software was imported into the Simscape simulation platform to construct the body and power system model of the quadrotor.Based on this,the control algorithm designed by Simulink was added to the simulation platform to facilitate the experiment verification and parameter tuning.The simulation results show that the designed aircraft can achieve hover and tracking well and meet the control performance requirements of the system.展开更多
Research on a hybrid system of a crane is a focus which considers environmental protection and energy saving. A new environmental protection and energy saving hybrid system of tyre crane, which utilizes supercapacitor...Research on a hybrid system of a crane is a focus which considers environmental protection and energy saving. A new environmental protection and energy saving hybrid system of tyre crane, which utilizes supercapacitors as the energy store device, is presented. Analyzing the principle of supercapacitors, the model of the crane＇s hybrid system is set up in this paper, and the model of main blocks are established. Through simulation analyzing, the energy saving result of the new hybrid system is obtained, and the good application value of the new hybrid system is explained.展开更多
Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotiv...Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.展开更多
In this paper, the neural network technology is combined with the fuzzy set theory to model the wave-induced ship motions in irregular seas. This combination makes possible the handling of a non-linear dynamic system ...In this paper, the neural network technology is combined with the fuzzy set theory to model the wave-induced ship motions in irregular seas. This combination makes possible the handling of a non-linear dynamic system with insufficient input information. The numerical results from the strip theory are used to train the networks and to demonstrate the validity of the proposed procedure.展开更多
基金supported by the MSIT(Ministry of Science and ICT),Republic of Korea,under the ITRC(Information Technology Research Center)support program(IITP-2024-RS-2022-00164800)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘Quantum computers accelerate many algorithms based on the superposition principle of quantum mechanics.The Grover algorithm provides significant performance to malicious users attacking symmetric key systems.Since the performance of attacks using quantum computers depends on the efficiency of the quantum circuit of the encryption algorithms,research research on the implementation of quantum circuits is essential.This paper presents a new framework to construct quantum circuits of substitution boxes(S-boxes)using system modeling.We model the quantum circuits of S-boxes using two layers:Toffoli and linear layers.We generate vector spaces based on the values of qubits used in the linear layers and apply them to find quantum circuits.The framework finds the circuit bymatching elements of vector spaces generated fromthe input and output of a given S-box,using the forward search or themeet-in-the-middle strategy.We developed a tool to apply this framework to 4-bit S-boxes.While the 4-bit S-box quantum circuit construction tool LIGHTER-R only finds circuits that can be implemented with four qubits,the proposed tool achieves the circuits with five qubits.The proposed tool can find quantum circuits of 4-bit odd permutations based on the controlled NOT,NOT,and Toffoli gates,whereas LIGHTER-R is unable to perform this task in the same environment.We expect this technique to become a critical step toward optimizing S-box quantum circuits.
基金Supported by the National Natural Science Foundation of China( 51105032)
文摘A system model is established to analyze the dynamic performance of an integrated starter and generator （ISG） hybrid power shafting. The model couples the electromechanical coupling shaft dynamics, the bearing hydrodynamic lubrication and the engine block stiffness. The model is com- pared with the model based on ADAMS or the model neglecting the bearing hydrodynamics. The bearing eccentricity and the oil film pressure have been calculated under different hybrid conditions or at the different motor power levels. It＇ s found that the bearing hydrodynamics decreases the cal- culation results of the bearing peak load. Changes of the hybrid conditions or the motor power have no significant effect on the main bearing, but have impact on the motor bearing. A hybrid power sys- tem composed of a 1.6 L engine and a 45 kW ISG motor can operate safely.
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
基金supported by the National Natural Science Foundation of China(Grant No.62373340).
文摘The proton exchange membrane fuel cell,as a novel energy device,exhibits a wide array of potential applications.This paper offers a comprehensive review and discussion of modeling and control strategies for fuel cell systems.It commences with a concise introduction to the structure and principles of fuel cells.Subsequently,it outlines modeling approaches for various fuel cell subsystems,encompassing the fuel cell stack,air supply system,hydrogen supply system,thermal management system,and water management system.Following this,it conducts a comparative analysis and discussion of prevalent control strategies for the aforementioned subsystems.Lastly,the paper outlines future research trends and directions in the modeling and control strategies of fuel cells.The aim of this paper is to provide ideas and inspirations for the design and management of membrane fuel cell systems from control aspects.
基金supported in part by the Natural Science Foundation of Jiangsu Province in China under grant No.BK20191475the fifth phase of“333 Project”scientific research funding project of Jiangsu Province in China under grant No.BRA2020306the Qing Lan Project of Jiangsu Province in China under grant No.2019.
文摘In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely correct.Formal verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented correctly.In this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly instructions.The verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.
文摘As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.
基金supported by the 2021 Higher Education Teaching Reform Research and Practice Project of SEAC(Grant No.221057)2021 Ministry of Education Industry−University Cooperation Collaborative Education Project(Grant No.202102646007)2022 Guizhou Province Gold Course Construction Project.
文摘This study investigates the application of a support vector machine(SVM)-based model for classifying students’learning abilities in system modeling and simulation courses,aiming at enhancing personalized education.A small dataset,collected from a pre-course questionnaire,is augmented with integer data to improve model performance.The SVM model achieves an accuracy rate of 95.3%.This approach not only benefits courses at Guizhou Minzu University but also has potential for broader application in similar programs in other institutions.The research provides a foundation for creating personalized learning paths using AI technologies,such as AI-generated content,large language models,and knowledge graphs,offering insights for innovative educational practices.
文摘In the electric arc furnace （EAF） steel production processes, scrap steel is principally used as a raw material instead of iron ore. In the steelmaking process with EAF, scrap is first melted in the furnace and then the desired chemical composition of the steel can be obtained in a special furnace such as ladle furnace （LF）. This kind of furnace process is used for the secondary refining of alloy steel. LF furnace offers strong heating fluxes and enables precise temperature control, thereby allowing for the addition of desired amounts of various alloying elements. It also provides outstanding desulfurization at high-temperature treatment by reducing molten steel fluxes and removing deoxidation products. Elemental analysis with mass balance modeling is important to know the precise amount of required alloys for the LF input with respect to scrap composition. In present study, chemical reactions with mass conservation law in EAF and LF were modeled altogether as a whole system and chemical compositions of the final steel alloy output can be obtained precisely according to different scrap compositions, alloying elements ratios, and other input amounts. Besides, it was found that the mass efficiency for iron element in the system is 95.93%. These efficiencies are calculated for all input elements as 8. 45% for C, 30.31% for Si, 46.36% for Mn, 30.64% for P, 41.96% for S, and 69.79% for Cr, etc. These efficiencies provide valuable ideas about the amount of the input materials that are vanished or combusted for 100 kg of each of the input materials in the EAF and LF system.
文摘In this paper a modeling method of ATC system is developed by using object Petri net. The formalized definition of the senior Petri net is given and illustrated by a practical example.
文摘Heuristic or clustering based time series aggregation methods are often used to reduce temporal complexity of energy system models by selecting representative days.However,these methods potentially neglect relevant information of time series(e.g.,distribution parameters).To identify relevant time series parameters,feature selection algorithms can be applied.The present research contributes by(a)developing a new feature selection approach based on clustering,nested modeling and regression(CNR)which is designed for applications requiring high selectivity and using different data sets,(b)comparing and evaluating CNR with feature selection methods available from the literature(e.g.,LASSO)and(c)identifying relevant information of the time series applied in energy system models,in particular those of demand,photovoltaic and wind.Results show that CNR achieves on average up to 101%lower mean absolute errors when methods are directly compared.Thus,CNR better identifies relevant information when the number of selected features is restricted.The disadvantage of CNR,however,is its high computational effort.A potential remedy to counter this is the combination with another method(e.g.,as pre-feature selection).In terms of relevant information,energy systems including photovoltaic are mainly characterized by the correlation between demand and photovoltaic time series as well as the range and the 35%quantile of demand.When energy systems include wind power,the minimum and mean of wind as well as the correlation between demand and wind time series are relevant characteristics.The implications of these findings are discussed.
基金supported by the National Key Research and Development Program of China(2018YFA0702200)National Natural Science Foundation of China(No.62073065).
文摘Generally,an accurate model can describe the operating states of a system more effectively and provide a more reliable theoretical basis for the system optimization and control.Different from the traditional intrusive modeling,a non-intrusive modeling method based on two-stage generative adversarial network(TS-GAN)is proposed for integrated energy system(IES).By using this method,non-intrusive modeling for the IES including photovoltaic,wind power,energy storage,and energy coupling equipment can be carried out.First,the characteristics of IES are analyzed and extracted based on the meteorological data,energy output,and energy price,and then the characteristic database is established.Meanwhile,the loads are classified as uncontrollable loads and schedulable loads based on frequency domain decomposition to facilitate energy management.Furthermore,TS-GAN algorithm based on the Stackelberg game is designed.In the TS-GAN,the first-stage GAN is used to generate the operating data of each equipment identified by non-invasive monitoring,and the second-stage GAN distinguishes the accumulated data generated by first-stage GAN and further modifies the generator models of the first-stage GAN.Finally,the effectiveness and accuracy of the proposed method are verified by the simulation of an energy region.
文摘The paper presents a new modeling method applied to fault diagnosis for constant linear closed-loop system by taking the impulse response series as the system model, and provides the calculation process of the method and output of model. The high frequency part of the pulse series, in the method, is reversed so as not to lose the frequency information of the pulse series in its transfer function. On the other hand, the method can also avoid the disadvantage that the learning results of neural network are uncertain every time. In the last part, the application with random disturbance of digital simulation and practical system shows that the modeling method is high accurate and suitable to be applied in fault diagnosis area.
基金supported by Fundamental Research Funds for the Central Universities (No. N090403005)
文摘Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.
文摘A fuzzy modeling method for complex systems is studied. The notation of general stochastic neural network (GSNN) is presented and a new modeling method is given based on the combination of the modified Takagi and Sugeno's (MTS) fuzzy model and one-order GSNN. Using expectation-maximization(EM) algorithm, parameter estimation and model selection procedures are given. It avoids the shortcomings brought by other methods such as BP algorithm, when the number of parameters is large, BP algorithm is still difficult to apply directly without fine tuning and subjective tinkering. Finally, the simulated example demonstrates the effectiveness.
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.
文摘An integrated study on source rock characterization and hydrocarbon generation potential modeling was conducted for the selected Dingo Claystone,Barrow Sub-basin,Australia.In this study,data were collected solely from two wells represented by the Bambra-1 and Bambra-2 wells.The collected data include those from bulk geochemical analyses of cuttings and sidewall cores sampled from the Late Jurassic Dingo Claystone.Geochemical data obtained from Rock-Eval pyrolysis and gas chromatography(GC)of extracted organic matter were integrated for source rock characterization and the construction of burial history and hydrocarbon generation in the Dingo Claystone.To improve the accuracy of thermal maturity estimations,only samples with S2 greater than 1 were considered due to potential issues with peak integration and uncertainties of Tmax determination in samples with lower S2 values.Furthermore,Rock-Eval data from the Bambra wells may be unreliable due to the contamination of cuttings and sidewall core(SWC)samples by drilling mud additives and natural hydrocarbons,which could impact the reliability of the data for determining thermal maturity.This study reveals that the Dingo Claystone Formation has total organic carbon(TOC)contents ranging from 0.66%to 8.31%.A poor to good hydrocarbon generation potential is indicated,with a production yield(PY=S_(1)+S_(2))ranging from 1.37 to 10.44 mg HC/g rock.Hydrogen index values vary between 42 and 226 mg HC/g TOC,confirming that the Dingo Claystone is dominantly kerogen TypeⅢ,with minor contributions from typesⅡ/ⅢandⅣ.Thermal maturity ranges from immature to late mature and is mostly in the oil window.This is indicated by T_(max)values of 398-462℃and vitrinite reflectance(Ro,%)of 0.47-1.99.Some samples show suppressed T_(max)and a higher production index,which is typical for samples affected by drilling fluids during drilling operations.Additionally,gas chromatography(GC)analyses are used to interpret the paleodepositional environment showing mixed input between marine and terrestrial origins of the source rocks.One-dimensional basin modeling for the Bambra-1 and Bambra-2 wells was carried out to evaluate the burial and thermal history of the formation.The transformation ratio suggests that hydrocarbon generation has not reached its peak and is still in an ongoing phase.An indication of hydrocarbon migration can be observed in this formation based on the transformation ratio.The effects of contamination warrant further investigation,as it could significantly impact maturity estimates and data reliability.
文摘In order to speed up and simplify the design of the quadrotor unmanned aerial vehicle(UAV)and carry out experimental simulation and verification of relevant control algorithms,this paper analyzed the system dynamics model of the mechanical structure and flight principle of the quadrotor aircraft,and used the Newton-Euler method to derive the non-linear dynamic equations.Aiming at improving the modeling accuracy and system integrity of the quadrotor,the physical system modeling was combined with the CAD software and the Matlab/Simscape toolbox.The three-dimensional quadrotor solid model built by CAD software was imported into the Simscape simulation platform to construct the body and power system model of the quadrotor.Based on this,the control algorithm designed by Simulink was added to the simulation platform to facilitate the experiment verification and parameter tuning.The simulation results show that the designed aircraft can achieve hover and tracking well and meet the control performance requirements of the system.
基金This paper is supported by the Youth Chenguang Project of Wuhan under Grant No.20045006071-29
文摘Research on a hybrid system of a crane is a focus which considers environmental protection and energy saving. A new environmental protection and energy saving hybrid system of tyre crane, which utilizes supercapacitors as the energy store device, is presented. Analyzing the principle of supercapacitors, the model of the crane＇s hybrid system is set up in this paper, and the model of main blocks are established. Through simulation analyzing, the energy saving result of the new hybrid system is obtained, and the good application value of the new hybrid system is explained.
基金Project supported by the Centre for Smart Grid and Information Convergence(CeSGIC)at Xi’an Jiaotong-Liverpool University,China
文摘Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.
文摘In this paper, the neural network technology is combined with the fuzzy set theory to model the wave-induced ship motions in irregular seas. This combination makes possible the handling of a non-linear dynamic system with insufficient input information. The numerical results from the strip theory are used to train the networks and to demonstrate the validity of the proposed procedure.
