Pub Date : 2024-11-05DOI: 10.1016/j.chaos.2024.115704
Xianwei Rong , Jean Chamberlain Chedjou , Xiaoyan Yu , Makhkamov Bakhtiyor Shukhratovich , Donghua Jiang , Jacques Kengne
This work presents an autonomous hyperjerk type circuit where a generalized memristor consisting of a diode-bridge and an RC filter acts as nonlinear component. The dynamics equations of the proposed circuit are presented in the form of an infinitely differentiable (i.e. smooth) system of order six. A detailed analysis of the model, carried out using classic techniques for studying nonlinear systems, reveals surprising behaviors such as the coexistence of bifurcation modes, non-trivial transient behaviors, offset boosting, torus, chaos, as well as hyperchaos with three positive Lyapunov exponents. These results are obtained by varying both the initial states and the model parameters. This multitude of dynamic properties is verified in the laboratory by carrying out series of measurements on the prototype of the memristive circuit. To the best of our knowledge, the circuit proposed in this article represents the simplest memristor-based circuit known to date in the relevant literature which can generate hyperchaotic signals with three positive Lyapunov exponents.
{"title":"A special memristive diode-bridge-based hyperchaotic hyperjerk autonomous circuit with three positive Lyapunov exponents","authors":"Xianwei Rong , Jean Chamberlain Chedjou , Xiaoyan Yu , Makhkamov Bakhtiyor Shukhratovich , Donghua Jiang , Jacques Kengne","doi":"10.1016/j.chaos.2024.115704","DOIUrl":"10.1016/j.chaos.2024.115704","url":null,"abstract":"<div><div>This work presents an autonomous hyperjerk type circuit where a generalized memristor consisting of a diode-bridge and an RC filter acts as nonlinear component. The dynamics equations of the proposed circuit are presented in the form of an infinitely differentiable (i.e. smooth) system of order six. A detailed analysis of the model, carried out using classic techniques for studying nonlinear systems, reveals surprising behaviors such as the coexistence of bifurcation modes, non-trivial transient behaviors, offset boosting, torus, chaos, as well as hyperchaos with three positive Lyapunov exponents. These results are obtained by varying both the initial states and the model parameters. This multitude of dynamic properties is verified in the laboratory by carrying out series of measurements on the prototype of the memristive circuit. To the best of our knowledge, the circuit proposed in this article represents the simplest memristor-based circuit known to date in the relevant literature which can generate hyperchaotic signals with three positive Lyapunov exponents.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115704"},"PeriodicalIF":5.3,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since 2019, major infectious disease outbreaks have placed tremendous pressure on global public health systems, triggering extensive research on the predictive modeling of infectious diseases. Cellular Automaton (CA) is primarily used in the spatial prediction of infectious diseases to establish a model to for simulating the interaction between different regions and the infection risk to simulate the transmission process of the disease and predict its development trend. However, CA models are governed by initial fixed rules and local interactions, and often fail to capture the complex dynamics of epidemic transmission, which are influenced by factors such as public behavior and government intervention. In view of these limitations, we propose a factorial simulation model for the spatial spread of epidemics, the CA-ABM, which divides agents into three categories–public, government, and hospital agents–to comprehensively express the macro factors that affect the development of epidemics. Agent-Based Modeling (ABM) influences the transition rules of the CA through agent choices, constraints and supporting behaviors. Focusing on the COVID-19 pandemic in mainland China from February 6 to March 20, 2020, we simulate its spread. The results showed an average improvement of 8.4 % in prediction accuracy, with few errors, RMSE under 200, and R2 values over 0.9 in most provinces, demonstrating strong macro-scale stability. This approach helps regions to understand influencing factors and enables targeted infection risk assessment and prevention. In addition, scenario analysis based on CA-ABM model changes epidemic decision-making from “prediction-response” to “scenario-response” and provides theoretical reference for future epidemic management.
{"title":"A novel spatio-temporal prediction model of epidemic spread integrating cellular automata with agent-based modeling","authors":"Peipei Wang , Xinqi Zheng , Yuanming Chen , Yazhou Xu","doi":"10.1016/j.chaos.2024.115709","DOIUrl":"10.1016/j.chaos.2024.115709","url":null,"abstract":"<div><div>Since 2019, major infectious disease outbreaks have placed tremendous pressure on global public health systems, triggering extensive research on the predictive modeling of infectious diseases. Cellular Automaton (CA) is primarily used in the spatial prediction of infectious diseases to establish a model to for simulating the interaction between different regions and the infection risk to simulate the transmission process of the disease and predict its development trend. However, CA models are governed by initial fixed rules and local interactions, and often fail to capture the complex dynamics of epidemic transmission, which are influenced by factors such as public behavior and government intervention. In view of these limitations, we propose a factorial simulation model for the spatial spread of epidemics, the CA-ABM, which divides agents into three categories–public, government, and hospital agents–to comprehensively express the macro factors that affect the development of epidemics. Agent-Based Modeling (ABM) influences the transition rules of the CA through agent choices, constraints and supporting behaviors. Focusing on the COVID-19 pandemic in mainland China from February 6 to March 20, 2020, we simulate its spread. The results showed an average improvement of 8.4 % in prediction accuracy, with few errors, RMSE under 200, and R<sup>2</sup> values over 0.9 in most provinces, demonstrating strong macro-scale stability. This approach helps regions to understand influencing factors and enables targeted infection risk assessment and prevention. In addition, scenario analysis based on CA-ABM model changes epidemic decision-making from “prediction-response” to “scenario-response” and provides theoretical reference for future epidemic management.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115709"},"PeriodicalIF":5.3,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-04DOI: 10.1016/j.chaos.2024.115679
Mengwei Sun , Lu Ren , Jian Liu , Changyin Sun
This article investigates the event-triggered prescribed-time Nash equilibrium seeking problem among multiple coalitions of agents in noncooperative games. Each coalition acts as a virtual player in the noncooperative game, with decisions made by its member agents. Agents lack complete information about others’ decisions and instead estimate them through a communication graph. An event-triggered prescribed-time multi-coalition Nash equilibrium seeking method is developed based on the leader-following consensus protocol, dynamic average consensus protocol, and gradient play. This method ensures the Nash equilibrium of the multi-coalition game is reached within a prescribed time, even when communication between agents only occurs under specific triggering conditions—effectively conserving communication resources. Unlike existing approaches, the proposed algorithm allows precise settling time assignment without prior knowledge of system parameters. This algorithm also prevents Zeno behavior. Lastly, the efficiency of the designed algorithm is demonstrated through simulation experiments.
{"title":"Prescribed-time multi-coalition Nash equilibrium seeking by event-triggered communication","authors":"Mengwei Sun , Lu Ren , Jian Liu , Changyin Sun","doi":"10.1016/j.chaos.2024.115679","DOIUrl":"10.1016/j.chaos.2024.115679","url":null,"abstract":"<div><div>This article investigates the event-triggered prescribed-time Nash equilibrium seeking problem among multiple coalitions of agents in noncooperative games. Each coalition acts as a virtual player in the noncooperative game, with decisions made by its member agents. Agents lack complete information about others’ decisions and instead estimate them through a communication graph. An event-triggered prescribed-time multi-coalition Nash equilibrium seeking method is developed based on the leader-following consensus protocol, dynamic average consensus protocol, and gradient play. This method ensures the Nash equilibrium of the multi-coalition game is reached within a prescribed time, even when communication between agents only occurs under specific triggering conditions—effectively conserving communication resources. Unlike existing approaches, the proposed algorithm allows precise settling time assignment without prior knowledge of system parameters. This algorithm also prevents Zeno behavior. Lastly, the efficiency of the designed algorithm is demonstrated through simulation experiments.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115679"},"PeriodicalIF":5.3,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.chaos.2024.115698
Yuhua Cui , Tao Zeng , Meiling Fan , Rina Wu , Guodong Xu , Xiaohong Wang , Jue Zhao
Functionally graded porous (FGP) materials have significant application potential because they can achieve many specific applications by controlling porosity and material composition. However, most current research has little emphasis on the vibration characteristics of FGP materials with viscoelastic properties. To address this issue, this article presents an improved Bernstein polynomials algorithm to establish the governing equation for analyzing the vibration response of fractional-order viscoelastic FGP beams. This method effectively resolves instability problems associated with boundary conditions. Single step Adams scheme and Newmark-β method are then utilized to solve the governing equation of the viscoelastic FGP beams. The accuracy of the proposed method is confirmed through comparison with the results obtained from the finite element method. A parametric investigation is conducted to explore the impact of porosity and its distribution pattern, power law index, boundary condition, fractional order, and viscoelasticity coefficient on the vibration characteristics of the viscoelastic FGP beams. These findings suggest that desirable dynamic properties for FGP beams can be achieved through tailoring their material gradient and porosity distribution.
{"title":"Dynamic analysis of viscoelastic functionally graded porous beams using an improved Bernstein polynomials algorithm","authors":"Yuhua Cui , Tao Zeng , Meiling Fan , Rina Wu , Guodong Xu , Xiaohong Wang , Jue Zhao","doi":"10.1016/j.chaos.2024.115698","DOIUrl":"10.1016/j.chaos.2024.115698","url":null,"abstract":"<div><div>Functionally graded porous (FGP) materials have significant application potential because they can achieve many specific applications by controlling porosity and material composition. However, most current research has little emphasis on the vibration characteristics of FGP materials with viscoelastic properties. To address this issue, this article presents an improved Bernstein polynomials algorithm to establish the governing equation for analyzing the vibration response of fractional-order viscoelastic FGP beams. This method effectively resolves instability problems associated with boundary conditions. Single step Adams scheme and Newmark-β method are then utilized to solve the governing equation of the viscoelastic FGP beams. The accuracy of the proposed method is confirmed through comparison with the results obtained from the finite element method. A parametric investigation is conducted to explore the impact of porosity and its distribution pattern, power law index, boundary condition, fractional order, and viscoelasticity coefficient on the vibration characteristics of the viscoelastic FGP beams. These findings suggest that desirable dynamic properties for FGP beams can be achieved through tailoring their material gradient and porosity distribution.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115698"},"PeriodicalIF":5.3,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.chaos.2024.115703
Sheng Zhang , Zhen-Qing Wang , Shu-Tao Li , Ye-Qing Chen , Qing Zhu , Jia-Lin Chen
To evaluate the destructive effects of fragment impacts on structures or personnel, it is crucial to assess the velocity, mass, size, and impact location of the fragments, as well as establish the correlation between these factors. This paper presents the experimental measurement of fragment velocities produced by the explosion of a cased charge, the fragments resulting from the explosion are collected and steel plates are used to record the impact locations and sizes of the fragments. Based on the experimental results, the calculation models of fragment velocity, fragment mass distribution and fragment scattering angle are corrected, the spatial distribution models of fragment size and number are established, and the functional relationship between fragment mass and size is constructed. Given the aforementioned research findings, the fragment spatial-mass distribution models based on the size distribution function and based on the mass distribution function are constructed, and the fragment space-mass distributions corresponding to the number of impact regions of 1, 5 and 10 are analyzed, and the effect of the number of impact location divisions on the fragment space-mass distribution is explored. The research results show that, for the current test charge, the fragment spatial-mass distribution model based on the size distribution function aligns most accurately with experimental results when the impact regions is divided into 10. The number of impact locations designated within each region is directly proportional to the number of fragments in that specific region. Notably, the impact location of the largest fragment occurs at 0.8 times the length of the impact region, whereas the peak fragment impact density occurs at 0.743 times the length of the impact region. The spatial-mass distribution model proposed in this paper successfully correlates the velocity, mass, size and impact location of the fragments, providing a realistic theoretical representation of the spatial geometric distribution of the fragments.
{"title":"Construction of a deterministic mathematical model for the spatial-mass distribution of random fragments produced by cased charge explosion","authors":"Sheng Zhang , Zhen-Qing Wang , Shu-Tao Li , Ye-Qing Chen , Qing Zhu , Jia-Lin Chen","doi":"10.1016/j.chaos.2024.115703","DOIUrl":"10.1016/j.chaos.2024.115703","url":null,"abstract":"<div><div>To evaluate the destructive effects of fragment impacts on structures or personnel, it is crucial to assess the velocity, mass, size, and impact location of the fragments, as well as establish the correlation between these factors. This paper presents the experimental measurement of fragment velocities produced by the explosion of a cased charge, the fragments resulting from the explosion are collected and steel plates are used to record the impact locations and sizes of the fragments. Based on the experimental results, the calculation models of fragment velocity, fragment mass distribution and fragment scattering angle are corrected, the spatial distribution models of fragment size and number are established, and the functional relationship between fragment mass and size is constructed. Given the aforementioned research findings, the fragment spatial-mass distribution models based on the size distribution function and based on the mass distribution function are constructed, and the fragment space-mass distributions corresponding to the number of impact regions of 1, 5 and 10 are analyzed, and the effect of the number of impact location divisions on the fragment space-mass distribution is explored. The research results show that, for the current test charge, the fragment spatial-mass distribution model based on the size distribution function aligns most accurately with experimental results when the impact regions is divided into 10. The number of impact locations designated within each region is directly proportional to the number of fragments in that specific region. Notably, the impact location of the largest fragment occurs at 0.8 times the length of the impact region, whereas the peak fragment impact density occurs at 0.743 times the length of the impact region. The spatial-mass distribution model proposed in this paper successfully correlates the velocity, mass, size and impact location of the fragments, providing a realistic theoretical representation of the spatial geometric distribution of the fragments.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115703"},"PeriodicalIF":5.3,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.chaos.2024.115691
Tingyao Hu , Shaohua Luo , Ya Zhang , Guangwei Deng , Hassen M. Ouakad
The DSP (Digital Signal Processing) implementation of two Duffing-type micro-electro-mechanical systems (MEMS) gyros and their event-triggered neural backstepping control with state constraints are investigated in this paper. Initially, we design the two Duffing-type MEMS gyros with a fully decoupled structure and establish a mathematical model based on the Newton's Second Law and the Lagrange equation. Due to the significant differences in the integrated circuit design and engineering application between embedded platforms and computer simulations, we selected the DSP platform to better characterize two Duffing-type MEMS gyros. Based on this, we explore nonlinear dynamic behaviors through phase and time history diagrams from the DSP platform as well as Lyapunov exponents under different coupling and damping coefficients, thereby identifying the existence of harmful chaotic phenomena in such gyros. Subsequently, to address chaotic oscillations along with overcoming the troubles of state constraints, uncertain disturbances and communication burden in the system, we incorporate the integral barrier Lyapunov function (IBLF) to limit the position of the proof mass within the physical limit. Furthermore, a type-2 sequential fuzzy neural network (T2SFNN) is used to approximate unknown nonlinear terms and the switching threshold event-triggered (STET) mechanism is utilized to save communication bandwidth. Then, an event-triggered neural backstepping controller is proposed to successfully achieve safety, high-precision and low resource consumption control of such gyros, ensuring that all signals in the closed-loop system remain bounded. Finally, simulation results and comparative experiments demonstrate the effectiveness and superiority of our proposed control scheme.
{"title":"Dynamical analysis and event-triggered neural backstepping control of two Duffing-type MEMS gyros with state constraints","authors":"Tingyao Hu , Shaohua Luo , Ya Zhang , Guangwei Deng , Hassen M. Ouakad","doi":"10.1016/j.chaos.2024.115691","DOIUrl":"10.1016/j.chaos.2024.115691","url":null,"abstract":"<div><div>The DSP (Digital Signal Processing) implementation of two Duffing-type micro-electro-mechanical systems (MEMS) gyros and their event-triggered neural backstepping control with state constraints are investigated in this paper. Initially, we design the two Duffing-type MEMS gyros with a fully decoupled structure and establish a mathematical model based on the Newton's Second Law and the Lagrange equation. Due to the significant differences in the integrated circuit design and engineering application between embedded platforms and computer simulations, we selected the DSP platform to better characterize two Duffing-type MEMS gyros. Based on this, we explore nonlinear dynamic behaviors through phase and time history diagrams from the DSP platform as well as Lyapunov exponents under different coupling and damping coefficients, thereby identifying the existence of harmful chaotic phenomena in such gyros. Subsequently, to address chaotic oscillations along with overcoming the troubles of state constraints, uncertain disturbances and communication burden in the system, we incorporate the integral barrier Lyapunov function (IBLF) to limit the position of the proof mass within the physical limit. Furthermore, a type-2 sequential fuzzy neural network (T2SFNN) is used to approximate unknown nonlinear terms and the switching threshold event-triggered (STET) mechanism is utilized to save communication bandwidth. Then, an event-triggered neural backstepping controller is proposed to successfully achieve safety, high-precision and low resource consumption control of such gyros, ensuring that all signals in the closed-loop system remain bounded. Finally, simulation results and comparative experiments demonstrate the effectiveness and superiority of our proposed control scheme.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115691"},"PeriodicalIF":5.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.chaos.2024.115699
Zhaohui Li , Xinyu Li , Mindi Li , Kexin Zhang , Xi Zhang , Xiaoxia Zhou
As a powerful framework, higher-order networks have gained significant attention to model the non-pairwise interactions of complex systems. Particularly, simplicial complex is an important mathematical tool which can be used to depict higher-order interactions. However, previous works on simplicial complexes have mainly focused on synthetic data. In this paper, we propose a method based on multivariate phase synchronization to construct simplicial complexes using multichannel stereo-electroencephalography (SEEG) data recorded from epilepsy patients. Furthermore, we examine its ability to describe both global and local characteristics of the higher-order brain network. Specifically, we first introduce the Hodge Laplacian to characterize higher-order interactions and employ the Euler characteristic number to determine the network synchronizability which is a significant global characteristic. Afterwards, we define an improved gravity-based centrality method to identify vital nodes in the higher-order network with simplicial complexes. Additionally, network efficiency based on the higher-order distance between different nodes is adopted to evaluate the effectiveness of this method in distinguishing the important nodes. In particular, we find that the Hippocampus and Fusiform gyrus may promote the synchronization of the epileptic brain network. All in all, we believe that our method paves the way to investigate brain networks with higher-order interactions, which contributes to identifying hubs in the epileptic network and has potential applications in epileptic treatment.
{"title":"Evaluation of human epileptic brain networks by constructing simplicial complexes","authors":"Zhaohui Li , Xinyu Li , Mindi Li , Kexin Zhang , Xi Zhang , Xiaoxia Zhou","doi":"10.1016/j.chaos.2024.115699","DOIUrl":"10.1016/j.chaos.2024.115699","url":null,"abstract":"<div><div>As a powerful framework, higher-order networks have gained significant attention to model the non-pairwise interactions of complex systems. Particularly, simplicial complex is an important mathematical tool which can be used to depict higher-order interactions. However, previous works on simplicial complexes have mainly focused on synthetic data. In this paper, we propose a method based on multivariate phase synchronization to construct simplicial complexes using multichannel stereo-electroencephalography (SEEG) data recorded from epilepsy patients. Furthermore, we examine its ability to describe both global and local characteristics of the higher-order brain network. Specifically, we first introduce the Hodge Laplacian to characterize higher-order interactions and employ the Euler characteristic number to determine the network synchronizability which is a significant global characteristic. Afterwards, we define an improved gravity-based centrality method to identify vital nodes in the higher-order network with simplicial complexes. Additionally, network efficiency based on the higher-order distance between different nodes is adopted to evaluate the effectiveness of this method in distinguishing the important nodes. In particular, we find that the Hippocampus and Fusiform gyrus may promote the synchronization of the epileptic brain network. All in all, we believe that our method paves the way to investigate brain networks with higher-order interactions, which contributes to identifying hubs in the epileptic network and has potential applications in epileptic treatment.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115699"},"PeriodicalIF":5.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.chaos.2024.115685
Shugang Li , Di He , Xiangguo Kong , Haifei Lin , Yankun Ma , Xuelong Li , Mengzhao Zhan , Pengfei Ji , Songrui Yang
The development and utilization of deep formation resources are easily disrupted by impact loads. To investigate what effect of impact on the pore structure and energy evolution of coal, the dynamic compression tests were performed by using the Split Hopkinson Pressure Bar (SHPB) test system. The fractal characteristics of macro cracks were analyzed by box dimension, the micro-pores structure and fractal features of coal samples were studied about nuclear magnetic resonance (NMR), which clarified the intrinsic relationship between fracture structure characteristics and energy dissipation. The results showed that with increasing impact velocity from 1.27 m/s to 4.90 m/s, the dynamic strength and peak strain increased by 85.11 % and 53.76 %, respectively. The fractal dimension of the cracks grew by 26.87 %, and the fractal dimension of pore network and full aperture decreases gradually. With increasing impact velocity, the fracture dissipation energy and energy dissipation rate of coal samples increase exponentially. As the energy dissipation rate increases, the cracks fractal increases in a quadratic function relationship and the pores fractal decreases continuously. Low-velocity impacts induce dislocation plugging between coal matrix crystals, while impact effect causes more dislocations to form stress concentrations at pore tips. When the energy accumulation reaches its maximum value, the content of mesopores and macropores together with the pore connectivity increases. Instantaneous disturbance creates more macroscopic fracture surfaces in the coal, resulting in large-scale fracture instability. This research findings will provide some theoretical foundations to understand the formation mechanism of dynamic disasters in deep mines.
{"title":"Relationship between micro-pores fractal characteristics about NMR T2 spectra and macro cracks fractal laws based on box dimension method of coal under impact load from energy dissipation theory","authors":"Shugang Li , Di He , Xiangguo Kong , Haifei Lin , Yankun Ma , Xuelong Li , Mengzhao Zhan , Pengfei Ji , Songrui Yang","doi":"10.1016/j.chaos.2024.115685","DOIUrl":"10.1016/j.chaos.2024.115685","url":null,"abstract":"<div><div>The development and utilization of deep formation resources are easily disrupted by impact loads. To investigate what effect of impact on the pore structure and energy evolution of coal, the dynamic compression tests were performed by using the Split Hopkinson Pressure Bar (SHPB) test system. The fractal characteristics of macro cracks were analyzed by box dimension, the micro-pores structure and fractal features of coal samples were studied about nuclear magnetic resonance (NMR), which clarified the intrinsic relationship between fracture structure characteristics and energy dissipation. The results showed that with increasing impact velocity from 1.27 m/s to 4.90 m/s, the dynamic strength and peak strain increased by 85.11 % and 53.76 %, respectively. The fractal dimension of the cracks grew by 26.87 %, and the fractal dimension of pore network and full aperture decreases gradually. With increasing impact velocity, the fracture dissipation energy and energy dissipation rate of coal samples increase exponentially. As the energy dissipation rate increases, the cracks fractal increases in a quadratic function relationship and the pores fractal decreases continuously. Low-velocity impacts induce dislocation plugging between coal matrix crystals, while impact effect causes more dislocations to form stress concentrations at pore tips. When the energy accumulation reaches its maximum value, the content of mesopores and macropores together with the pore connectivity increases. Instantaneous disturbance creates more macroscopic fracture surfaces in the coal, resulting in large-scale fracture instability. This research findings will provide some theoretical foundations to understand the formation mechanism of dynamic disasters in deep mines.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115685"},"PeriodicalIF":5.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.chaos.2024.115690
Jingxian Li , Ping Ma , Cong Wang , Shaohua Zhang , Hongli Zhang
New energy sources, such as wind and photovoltaic systems, demonstrate inherent randomness in their power outputs. Additionally, flexible loads, such as electric vehicles at the consumption end further contribute to this variability. These factors result in significant continuous stochastic disturbances on the power system that pose significant threats to the safe and stable operation of the system. Considering continuous stochastic power perturbations, we establish a stochastic differential model of the power system based on Ito stochastic theory. This model analyzes changes in dynamic behavior and oscillation patterns, indicating that stochastic perturbations expand oscillations and reduce the stability boundary. To enhance the system’s security and stability, we propose an adaptive neural network command filter (ANNCF) excitation control method to address stochastic oscillations caused by stochastic power disturbances. Experimental validation using the Real-Time Laboratory (RT-LAB) semi-physical real-time simulation platform shows that the proposed ANNCF excitation method effectively responds to stochastic perturbations, suppresses the stochastic oscillation phenomenon, and significantly improves resistance to stochastic disturbances. Furthermore, this method maintains a superior control effect during sudden power changes and three-phase short circuits, improving the transient stability of the power system.
{"title":"Dynamics analysis and adaptive neural network command filtering excitation control of stochastic power system","authors":"Jingxian Li , Ping Ma , Cong Wang , Shaohua Zhang , Hongli Zhang","doi":"10.1016/j.chaos.2024.115690","DOIUrl":"10.1016/j.chaos.2024.115690","url":null,"abstract":"<div><div>New energy sources, such as wind and photovoltaic systems, demonstrate inherent randomness in their power outputs. Additionally, flexible loads, such as electric vehicles at the consumption end further contribute to this variability. These factors result in significant continuous stochastic disturbances on the power system that pose significant threats to the safe and stable operation of the system. Considering continuous stochastic power perturbations, we establish a stochastic differential model of the power system based on Ito stochastic theory. This model analyzes changes in dynamic behavior and oscillation patterns, indicating that stochastic perturbations expand oscillations and reduce the stability boundary. To enhance the system’s security and stability, we propose an adaptive neural network command filter (ANNCF) excitation control method to address stochastic oscillations caused by stochastic power disturbances. Experimental validation using the Real-Time Laboratory (RT-LAB) semi-physical real-time simulation platform shows that the proposed ANNCF excitation method effectively responds to stochastic perturbations, suppresses the stochastic oscillation phenomenon, and significantly improves resistance to stochastic disturbances. Furthermore, this method maintains a superior control effect during sudden power changes and three-phase short circuits, improving the transient stability of the power system.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115690"},"PeriodicalIF":5.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-01DOI: 10.1016/j.chaos.2024.115695
Liping Chen , Chuang Liu , António M. Lopes , Yong Lin , Yingxiao Liu , YangQuan Chen
This article addresses the synchronization of general variable fractional-order one-sided Lipschitz chaotic systems with norm-bounded time-varying parametric uncertainty. A non-fragile state feedback control scheme is designed to cope with uncertainties in the controller gain fluctuations, and a sufficient condition for master/slave synchronization and determination of the controller gain is derived and expressed as a linear matrix inequality. The new control approach is applicable to fractional-order Lipschitz chaotic systems as well as to integer-order systems. Additionally, compared with other existing schemes, the method is easier and less costly to implement in real-world applications. Three numerical examples are given to show the performance of the non-fragile control approach for synchronizing practical chaotic systems.
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