Existence of hidden attractors in nonlinear hydro-turbine governing systems and its stability analysis

This work studies the stability and hidden dynamics of the nonlinear hydro-turbine governing system with an output limiting link,and propose a new six-dimensional system,which exhibits some hidden attractors.The parameter switching algorithm is used to numerically study the dynamic behaviors of the system.Moreover,it is investigated that for some parameters the system with a stable equilibrium point can generate strange hidden attractors.A self-excited attractor with the change of its parameters is also recognized.In addition,numerical simulations are carried out to analyze the dynamic behaviors of the proposed system by using the Lyapunov exponent spectra,Lyapunov dimensions,bifurcation diagrams,phase space orbits,and basins of attraction.Consequently,the findings in this work show that the basins of hidden attractors are tiny for which the standard computational procedure for localization is unavailable.These simulation results are conducive to better understanding of hidden chaotic attractors in higher-dimensional dynamical systems,and are also of great significance in revealing chaotic oscillations such as uncontrolled speed adjustment in the operation of hydropower station due to small changes of initial values.

Bursting oscillations in a hydro-turbine governing system with two time scales

A fast-slow coupled model of the hydro-turbine governing system （HTGS） is established by introducing frequency disturbance in this paper. Based on the proposed model, the performances of two time scales for bursting oscillations in the HTGS are investigated and the effect of periodic excitation of frequency disturbance is analyzed by using the bifurcation diagrams, time waveforms and phase portraits. We find that stability and operational characteristics of the HTGS change with the value of system parameter kd. Furthermore, the comparative analyses for the effect of the bursting oscillations on the system with different amplitudes of the periodic excitation a are carried out. Meanwhile, we obtain that the relative deviation of the mechanical torque mt rises with the increase of a. These methods and results of the study, combined with the performance of two time scales and the fast-slow coupled engineering model, provide some theoretical bases for investigating interesting physical phenomena of the engineering system.

Hopf Bifurcation Research of Hydraulic Turbine Governing System with a Saturation Nonlinearity

A nonlinear mathematical model for hydro turbine governing system with saturation nonlinearity in small perturbation has been proposed with all the essential components,i.e. turbine,PID type governor with saturation part and generator included in the model. Existence,stability and direction of Hopf bifurcation of an example HTGS are investigated in detail and presented in forms of bifurcation diagrams and time waveforms. The analysis show that a supercritical Hopf bifurcation may exist in hydraulic turbine systems in some certain conditions. Moreover,the dynamic behavior of system with different parameters such as Tw,Tab,Tyand K are studied extensively. An example with numerical simulations is presented to illustrate the theoretical results. The researches provide a reasonable explanation for the Hopf phenomenon happened in operation of hydroelectric generating unit.

Stability analysis of hydro-turbine governing system based on machine learning

Hydro-turbine governing system is a time-varying complex system with strong non-linearity,and its dynamic characteristics are jointly affected by hydraulic,mechanical,electrical,and other factors.Aiming at the stability of the hydroturbine governing system,this paper first builds a dynamic model of the hydro-turbine governing system through mechanism modeling,and introduces the transfer coefficient characteristics under different load conditions to obtain the stability category of the system.BP neural network is used to perform the machine study and the predictive analysis of the stability of the system under different working conditions is carried out by using the additional momentum method to optimize the algorithm.The test set results show that the method can accurately distinguish the stability category of the hydro-turbine governing system(HTGS),and the research results can provide a theoretical reference for the operation and management of smart hydropower stations in the future.

Terminal Sliding Mode Controllers for Hydraulic Turbine Governing System with Bifurcated Penstocks under Input Saturation

Terminal sliding mode controller method is introduced to enhance the regulation performance of the hydraulic turbine governing system(HTGS).For the purpose of describing the characteristics of controlled system and deducing the control rule,a nonlinear mathematic model of hydraulic turbine governing system with bifurcated penstocks(HTGSBF)under control input saturation is established,and the input/output state linearization feedback approach is used to obtain the relationship between turbine speed and controller output.To address the control input saturation problem,an adaptive assistant system is designed to compensate for controller truncation.Numerical simulations have been conducted under fixed point stabilization and periodic orbit tracking conditions to compare the dynamic performances of proposed terminal sliding mode controllers and conventional sliding mode controller.The results indicate that the proposed terminal sliding mode controllers not only have a faster response and accurate tracking results,but also own a stronger robustness to the system parameter variations.Moreover,the comparisons between the proposed terminal sliding mode controllers and current most often used proportional-integral-differential(PID)controller,as well its variant NPID controller,are discussed at the end of this paper,where the superiority of the terminal sliding mode controllers also have been verified.

Fractional-Order Modeling and Dynamical Analysis of a Francis Hydro-Turbine Governing System with Complex Penstocks

This paper investigates the stability of the Francis hydro-turbine governing system with complex penstocks in the grid-connected mode. Firstly, a novel fractional-order nonlinear mathematical model of a Francis hydro-turbine governing system with complex penstocks is built from an engineering application perspective. This model is described by state-space equations and is composed of the Francis hydro-turbine model, the fractional-order complex penstocks model, the third-order generator model, and the hydraulic speed governing system model. Based on stability theory for a fractional-order nonlinear system, this study discovers a basic law of the bifurcation points of the above system with a change in the fractional-order a. Secondly, the stable region of the governing system is investigated in detail,and nonlinear dynamical behaviors of the system are identified and studied exhaustively via bifurcation diagrams, time waveforms, phase orbits, Poincare maps, power spectrums and spectrograms. Results of these numerical experiments provide a theoretical reference for further studies of the stability of hydropower stations.

On-line Failure Diagnostics for Steam Turbine Hydraulic Governing System

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Data-Driven Modeling of Partially Observed Biological Systems

We present a numerical approach for modeling unknown dynamical systems using partially observed data,with a focus on biological systems with(relatively)complex dynamical behavior.As an extension of the recently developed deep neural network(DNN)learning methods,our approach is particularly suitable for practical situations when(i)measurement data are available for only a subset of the state variables,and(ii)the system parameters cannot be observed or measured at all.We demonstrate that,with a properly designed DNN structure with memory terms,effective DNN models can be learned from such partially observed data containing hidden parameters.The learned DNN model serves as an accurate predictive tool for system analysis.Through a few representative biological problems,we demonstrate that such DNN models can capture qualitative dynamical behavior changes in the system,such as bifurcations,even when the parameters controlling such behavior changes are completely unknown throughout not only the model learning process but also the system prediction process.The learned DNN model effectively creates a“closed”model involving only the observables when such a closed-form model does not exist mathematically.

Bias in Generative AI Systems:A 3-Layer Response and Liability Determination

The risk of bias is widely noticed in the entire process of generative artificial intelligence(generative AI)systems.To protect the rights of the public and improve the effectiveness of AI regulations,feasible measures to address the bias problem in the context of large data should be proposed as soon as possible.Since bias originates in every part and various aspects of AI product lifecycles,laws and technical measures should consider each of these layers and take different causes of bias into account,from data training,modeling,and application design.The Interim Measures for the Administration of Generative AI Service(the Interim Measures),formulated by the Office of the Central Cyberspace Affairs Commission(CAC)and other departments have taken the initiatives to govern AI.However,it lacks specific details on issues such as how to prevent the risk of bias and reduce the effect of bias in decision-making.The Interim Measures also fail to take causes of bias into account,and several principles must be further interpreted.Meanwhile,regulations on generative AI at the global level are still in their early stages.By forming a governance framework,this paper could provide the community with useful experiences and play a leading role.The framework includes at least three parts:first,determining the realm of governance and unifying related concepts;second,developing measures for different layers to identify the causes and specific aspects of bias;third,identifying parties with the skills to take responsibility for detecting bias intrusions and proposing a program for the allocation of liabilities among the large-scale platform developers.

Research on Policy Diffusion Path and Reproduction of River Chief System

The River Chief System (RCS) has evolved from local innovative practices to a national water governance strategy to address the current challenges in China’s water environmental management. In contrast to existing research that focuses on the strengths, weaknesses, and improvements of RCS, this study uses literature study to reveal the dynamic evolution of RCS through three phases, with RCS spreading from developed coastal areas to central and western inland regions. RCS’s diffusion path involves vertical diffusion between central and local levels and horizontal diffusion among local governments. Moreover, RCS has also achieved conceptual spillover, gradually expanding into other governance domains, such as the Lake Chief System, the Field Chief System, the Forestry Chief System, and the integration of multiple chief roles. However, it is essential to scrutinize the phenomenon of applying similar governance mechanisms to different areas, as it may result in challenges such as overburdening local governments, insufficient public participation, oversimplification of differences in natural resource endowments, and limited applicability. This study also provides suggestions on how to address these challenges. The study contributes theoretical insights and policy implications, providing a foundation for practical policy innovation.

A Systematic Review of Blockchain Technology for Government Information Sharing

Government information sharing(GIS)refers to that act of required or provided for duty government information,commercial information and public welfare information,and it is a basic issue of government services.However,the existing GIS has low transparency and is lack of flexibility between different departments.Aiming at such problems,this paper takes blockchain as a solusion,and systematically summarizes the development of digital GIS,the advantages and challenges of blockchain and its theoretical research and practical applications.Specifically,it reviews e-government interactive structure,big data and other solutions,analyses their imperfections,and puts forward blockchain-based solutions.The blockchain improves government service efficiency and data security,meanwhile it faces challenges in throughput and supervision.In order to meet these challenges,researchers propose solutions based on three data exchange scenarios:government-to-government,government-to-enterprise and government-toindividual.In addition to researches,blockchain-based GIS is put into use.The electronic licensing project of Nanjing(China)government is taken as an example to illustrate that blockchain has the ability to openly and securely verify,track,and exchange data,so as to improve management ability and public service level of government agencies.

College Basic Development Status Data Management System Based on Data Governance Framework

In the era of big data, data application based on data governance has become an inevitable trend in the construction of smart campus in higher education. In this paper, a set of data governance system framework covering the whole life cycle of data suitable for higher education is proposed, and based on this, the ideas and methods of data governance are applied to the construction of data management system for the basic development status of faculties by combining the practice of data governance of Donghua University.It forms a closed-loop management of data in all aspects, such as collection, information feedback, and statistical analysis of the basic development status data of the college. While optimizing the management business of higher education, the system provides a scientific and reliable basis for precise decision-making and strategic development of higher education.

Protocol to study the effects of AMPK-mTOR/PINK-Parkin dual signaling pathways on the formation of coronary heart disease showing blood stasis symptom pattern based on traditional Chinese medicine theory of“heart governing blood and vessels”

In this study,we aim to combine gene transfection techniques with the modeling methods previously employed by the research group to deeply investigate the corresponding theories of traditional Chinese medicine regarding“myocardial energy metabolism”and“aortic thrombosis”.Our goal is to elucidate the biological mechanism underlying the occurrence and development of coronary heart disease with blood stasis syndrome from the perspectives of“heart and vessels”and“Qi(in traditional Chinese medicine,it refers to the most fundamental and subtle substances that constitute the human body and maintain life activities.At the same time,it also has the meaning of physiological function.In terms of traditional Chinese medicine,Qi and different words are used together to express different meanings)and blood”.The research content is divided into four modules as follows:1.establishment of an animal model of coronary heart disease with blood stasis syndrome through fibrinogen overexpression.2.Investigation of the mitochondrial quality control system in coronary heart disease with blood stasis syndrome under fibrinogen overexpression.3.Study of platelet autophagy in coronary heart disease with blood stasis syndrome under fibrinogen overexpression.4.Examination of the relationship between the AMPK-mTOR pathway and metabolism in platelet autophagy of coronary heart disease with blood stasis syndrome under fibrinogen overexpression.Ninety-six Sprague Dawley rats will be randomly assigned to the following groups:control group,model group,fibrinogen group and adeno-associated virus group.All rats will undergo a 14-week model construction process,and modern molecular biology methods will be employed to evaluate the model and examine relevant research indicators.The obtained data will be analyzed according to a predefined statistical analysis plan.

Power Distribution System Regulation (A Review)

This article presents a framework and a comprehensive model to optimize the regulation of the electricity distribution system.The regulatory requirements of the electricity distribution system and research gaps in this field are among the important outputs of this review article.In each of the presented parts of the framework,it has reviewed,introduced and listed the regulatory studies of the electricity distribution system.In order to calculate the PDSR(regulation of power distribution system)framework,governance first presents,its goals,and its development plan in the distribution sector,and discusses the regulatory position in it.After that,in the electricity distribution system,it describes the role of the regulator in the goals and plans of the electricity distribution system,and introduces the types of regulation of the electricity distribution system,and finally,discusses about the place of data in the regulation and its requirements,and the effects of regulation in the evolution and stability of the electricity distribution system.

Data Component:An Innovative Framework for Information Value Metrics in the Digital Economy

The increasing dependence on data highlights the need for a detailed understanding of its behavior,encompassing the challenges involved in processing and evaluating it.However,current research lacks a comprehensive structure for measuring the worth of data elements,hindering effective navigation of the changing digital environment.This paper aims to fill this research gap by introducing the innovative concept of“data components.”It proposes a graphtheoretic representation model that presents a clear mathematical definition and demonstrates the superiority of data components over traditional processing methods.Additionally,the paper introduces an information measurement model that provides a way to calculate the information entropy of data components and establish their increased informational value.The paper also assesses the value of information,suggesting a pricing mechanism based on its significance.In conclusion,this paper establishes a robust framework for understanding and quantifying the value of implicit information in data,laying the groundwork for future research and practical applications.

Enhancing transboundary natural tourism resources governance:unveiling the spatial pattern and its influencing factors

Tourism resources that span provincial boundaries in China play a pivotal role in regional development,yet effective governance poses persistent challenges.This study addresses this issue by constructing a comprehensive database of transboundary natural tourism resources(TNTR)through amalgamation of diverse data sources.Utilizing the Getis-Ord Gi^(*),kernel density estimation,and geographical detectors,we scrutinize the spatial patterns of TNTR,focusing on both named and unnamed entities,while exploring the influencing factors.Our findings reveal 7883 identified TNTR in China,with mountain tourism resources emerging as the predominant type.Among provinces,Hunan boasts the highest count,while Shanghai exhibits the lowest.Southern China demonstrates a pronounced clustering trend in TNTR distribution,with the spatial arrangement of biological landscapes appearing more random compared to geological and water landscapes.Western China,characterized by intricate terrain,exhibits fewer TNTR,concurrently unveiling a significant presence of unnamed natural tourism resources.Crucially,administrative segmentation influences TNTR development,generating disparities in regional goals,developmental stages and intensities,and management approaches.In response to these variations,we advocate for strengthening the naming of the unnamed transboundary tourism resources,constructing a geographic database of TNTR for government and establishing a collaborative management mechanism based on TNTR database.Our research contributes to elucidating the intricate landscape of TNTR,offering insights for tailored governance strategies in the realm of cross-provincial tourism resource management.

Research on Risk Identification and Industrial Governance of Digital Education Products Based on Data Annotation Technology

The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.

Do companies influenced by smart cities pay more attention to green governance?Mechanism and optimal spatial correlation

Smart cities are a way for China to construct an innovative and environmentally conscious nation.The paper examines the impact of smart cities on corporate green governance and provides a theoretical foundation for formulating and executing smart city policy in China.Based on panel data from Chinese A-share listed companies in Shanghai and Shenzhen from 2008 to 2020,this study constructs a multiperiod double-difference model to examine the influence of smart cities on corporate green governance.Additionally,it uses a spatial double-difference model to investigate the spatial spillover effect of smart cities on neighboring areas.The findings indicate that smart cities effectively enhance corporate green governance.Analyzing the influencing mechanisms reveals that resource allocation efficiency,technological innovation,management environmental awareness,and regional environmental enforcement efforts act as mediators.Furthermore,the study reveals that the impact of smart cities on promoting corporate green governance is more pronounced in regions with lower levels of marketization and resource-based cities.Moreover,the research explores the spatial spillover effects of smart cities,with an effective radius of approximately 350 km.The optimal spatial correlation zone for green governance of businesses in neighboring areas in relation to smart cities is within a range of 250-350 km.This is manifested by the significant promotion of green governance in neighboring area businesses facilitated by smart cities.

Poverty Reduction in China: Experiences and Measurement of Effects

This study employs the generalized method of moments(GMM)and panel vector autoregression(PVAR)models for a multi-factor quantitative dissection of China’s poverty reduction process across multiple stages,using provincial panel data from 2000 to 2019.According to our research,economic growth and social development are the key drivers of poverty reduction in China,but the trickle-down effect of economic growth is diminishing and marketization is having a lesser pro-poor effect.Public expenditure has failed to provide social protection and income redistribution benefits due to issues such as targeting error and elite capture.Increasing the efficiency of the poverty reduction system calls for adaptive adjustments.Finally,this study highlights China’s poverty reduction experiences and analyzes current challenges,which serve as inspiration for consolidating poverty-reduction achievements,combating relative poverty,and attaining countryside vitalization.

A Brief Introduction to Sichuan Academy of Social Sciences

Sichuan Academy of Social Sciences is the think tank for the People’s Government of Sichuan Province and the Sichuan Provincial Committee of the CPC,with full financial backing of the Party and the government.The Academy consists of 16 institutes,1 graduate school,10 departments of scientific research management services.