Computational Experiments for Complex Social Systems:Integrated Design of Experiment System

Powered by advanced information industry and intelligent technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).And human factors have become crucial in the operations of complex social systems.Traditional mechanical analysis and social simulations alone are powerless for analyzing complex social systems.Against this backdrop,computational experiments have emerged as a new method for quantitative analysis of complex social systems by combining social simulation(e.g.,ABM),complexity science,and domain knowledge.However,in the process of applying computational experiments,the construction of experiment system not only considers a large number of artificial society models,but also involves a large amount of data and knowledge.As a result,how to integrate various data,model and knowledge to achieve a running experiment system has become a key challenge.This paper proposes an integrated design framework of computational experiment system,which is composed of four parts:generation of digital subject,generation of digital object,design of operation engine,and construction of experiment system.Finally,this paper outlines a typical case study of coal mine emergency management to verify the validity of the proposed framework.

A general Boolean semantic modelling approach for complex and intelligent industrial systems in the framework of DES

Discrete event system(DES)models promote system engineering,including system design,verification,and assessment.The advancement in manufacturing technology has endowed us to fabricate complex industrial systems.Consequently,the adoption of advanced modeling methodologies adept at handling complexity and scalability is imperative.Moreover,industrial systems are no longer quiescent,thus the intelligent operations of the systems should be dynamically specified in the model.In this paper,the composition of the subsystem behaviors is studied to generate the complexity and scalability of the global system model,and a Boolean semantic specifying algorithm is proposed for generating dynamic intelligent operations in the model.In traditional modeling approaches,the change or addition of specifications always necessitates the complete resubmission of the system model,a resource-consuming and error-prone process.Compared with traditional approaches,our approach has three remarkable advantages:(i)an established Boolean semantic can be fitful for all kinds of systems;(ii)there is no need to resubmit the system model whenever there is a change or addition of the operations;(iii)multiple specifying tasks can be easily achieved by continuously adding a new semantic.Thus,this general modeling approach has wide potential for future complex and intelligent industrial systems.

Optimal scheduling of a township integrated-energy system using the adjustable heat-electricity ratio model

With the expansion and implementation of rural revitalization strategies,there is a constant need for new energy sources for the construction of new townships.Consequently,integrated energy systems with the interconnection and interaction of multiple energy sources are developing rapidly.Biomass energy,a renewable green energy source with low pollution and wide distribution,has significant application potential in integrated energy systems.Considering the application of biomass energy in townships,this study established an integrated biomass energy system and proposed a model to optimize its operation.Lowest economic cost and highest clean energy utilization rate were considered as the objective functions.In addition,a plan was suggested to adjust the heat-electricity ratio based on the characteristics of the combined heat and power of the biomass.Finally,a simulation analysis conducted for a town in China was discussed,demonstrating that the construction of a township integrated-energy system and the use of biomass can significantly reduce operating costs and improve the energy utilization rate.Moreover,by adjusting the heat-electricity ratio,the economic cost was further reduced by 6.70%,whereas the clean energy utilization rate was increased by 5.14%.

A lightweight symmetric image encryption cryptosystem in wavelet domain based on an improved sine map

In the era of big data,the number of images transmitted over the public channel increases exponentially.As a result,it is crucial to devise the efficient and highly secure encryption method to safeguard the sensitive image.In this paper,an improved sine map(ISM)possessing a larger chaotic region,more complex chaotic behavior and greater unpredictability is proposed and extensively tested.Drawing upon the strengths of ISM,we introduce a lightweight symmetric image encryption cryptosystem in wavelet domain(WDLIC).The WDLIC employs selective encryption to strike a satisfactory balance between security and speed.Initially,only the low-frequency-low-frequency component is chosen to encrypt utilizing classic permutation and diffusion.Then leveraging the statistical properties in wavelet domain,Gaussianization operation which opens the minds of encrypting image information in wavelet domain is first proposed and employed to all sub-bands.Simulations and theoretical analysis demonstrate the high speed and the remarkable effectiveness of WDLIC.

Double quantum images encryption scheme based on chaotic system

This paper explores a double quantum images representation(DNEQR)model that allows for simultaneous storage of two digital images in a quantum superposition state.Additionally,a new type of two-dimensional hyperchaotic system based on sine and logistic maps is investigated,offering a wider parameter space and better chaotic behavior compared to the sine and logistic maps.Based on the DNEQR model and the hyperchaotic system,a double quantum images encryption algorithm is proposed.Firstly,two classical plaintext images are transformed into quantum states using the DNEQR model.Then,the proposed hyperchaotic system is employed to iteratively generate pseudo-random sequences.These chaotic sequences are utilized to perform pixel value and position operations on the quantum image,resulting in changes to both pixel values and positions.Finally,the ciphertext image can be obtained by qubit-level diffusion using two XOR operations between the position-permutated image and the pseudo-random sequences.The corresponding quantum circuits are also given.Experimental results demonstrate that the proposed scheme ensures the security of the images during transmission,improves the encryption efficiency,and enhances anti-interference and anti-attack capabilities.

Dual-salt poly(tetrahydrofuran) electrolyte enables quasi-solid-state lithium metal batteries to operate at -30 ℃

The stable operation of solid-state lithium metal batteries at low temperatures is plagued by severe restrictions from inferior electrolyte-electrode interface compatibility and increased energy barrier for Li^(+)migration.Herein,we prepare a dual-salt poly(tetrahydrofuran)-based electrolyte consisting of lithium hexafluorophosphate and lithium difluoro(oxalato)borate(LiDFOB).The Li-salt anions(DFOB−)not only accelerate the ring-opening polymerization of tetrahydrofuran,but also promote the formation of highly ion-conductive and sustainable interphases on Li metal anodes without sacrificing the Li^(+)conductivity of electrolytes,which is favorable for Li^(+)transport kinetics at low temperatures.Applications of this polymer electrolyte in Li||LiFePO_(4)cells show 82.3%capacity retention over 1000 cycles at 30℃and endow stable discharge capacity at−30℃.Remarkably,the Li||LiFePO4 cells retain 52%of their room-temperature capacity at−20℃and 0.1 C.This rational design of dual-salt polymer-based electrolytes may provide a new perspective for the stable operation of quasi-solid-state batteries at low temperatures.

Optimizing near-carbon-free nuclear energy systems:advances in reactor operation digital twin through hybrid machine learning algorithms for parameter identification and state estimation

Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.

A coordinated operation method of wind-PV-hydrogenstorage multi-agent energy system

Wind-photovoltaic(PV)-hydrogen-storage multi-agent energy systems are expected to play an important role in promoting renewable power utilization and decarbonization.In this study,a coordinated operation method was proposed for a wind-PVhydrogen-storage multi-agent energy system.First,a coordinated operation model was formulated for each agent considering peer-to-peer power trading.Second,a coordinated operation interactive framework for a multi-agent energy system was proposed based on the theory of the alternating direction method of multipliers.Third,a distributed interactive algorithm was proposed to protect the privacy of each agent and solve coordinated operation strategies.Finally,the effectiveness of the proposed coordinated operation method was tested on multi-agent energy systems with different structures,and the operational revenues of the wind power,PV,hydrogen,and energy storage agents of the proposed coordinated operation model were improved by approximately 59.19%,233.28%,16.75%,and 145.56%,respectively,compared with the independent operation model.

Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption algorithm.Initially,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent operations.Subsequently,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random sequences.These chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image pixels.Furthermore,the complexity of the encryption process is enhanced through improved Joseph block scrambling.Thorough experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as 7.999.Additionally,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.

PERIODIC SYSTEMS WITH TIME DEPENDENT MAXIMAL MONOTONE OPERATORS

We consider a first order periodic system in R^(N),involving a time dependent maximal monotone operator which need not have a full domain and a multivalued perturbation.We prove the existence theorems for both the convex and nonconvex problems.We also show the existence of extremal periodic solutions and provide a strong relaxation theorem.Finally,we provide an application to nonlinear periodic control systems.

Market Operation of Energy Storage System in Smart Grid:A Review

As a flexible resource,energy storage plays an increasingly significant role in stabilizing and supporting the power system,while providing auxiliary services.Still,the current high demand for energy storage contrasts with the fuzzy lack of market-oriented mechanisms for energy storage,the principle of market-oriented operation has not been embodied,and there is no unified and systematic analytical framework for the business model.However,the dispatch management model of energy storage in actual power system operation is not clear.Still,the specific scheduling process and energy storage strategy on the source-load-network side could be more specific,and there needs to be a greater understanding of the collaborative scheduling process of the multilevel scheduling center.On this basis,this paper reviews the energy storage operation model and market-based incentive mechanism,For different functional types and installation locations of energy storage within the power system,the operational models and existing policies for energy storage participation in the market that are adapted to multiple operating states are summarized.From the point of view of the actual scheduling and operation management of energy storage in China,an energy storage regulation and operation management model based on“national,provincial,and local”multilevel coordination is proposed,as well as key technologies in the interactive scenarios of source-load,network and storage.

Clinical effect of operative vs nonoperative treatment on humeral shaft fractures:Systematic review and meta-analysis of clinical trials

BACKGROUND Whether operation is superior to non-operation for humeral shaft fracture remains debatable.We hypothesized that operation could decrease the nonunion and reintervention rates and increase the functional outcomes.AIM To compare the clinical efficacy between operative and nonoperative approaches for humeral shaft fractures.METHODS We searched the PubMed,Web of Science,ScienceDirect,and Cochrane databases from 1990 to December 2023 for clinical trials and cohort studies comparing the effects of operative and conservative methods on humeral shaft fractures.Two investigators independently extracted data from the eligible studies,and the other two assessed the methodological quality of each study.The quality of the included studies was assessed using the Cochrane risk bias or Newcastle-Ottawa Scale.The nonunion,reintervention and the overall complications and functional scores were pooled and analyzed using Review Manager software(version 5.3).RESULTS A total of four randomized control trials and 13 cohort studies were included,with 1285 and 1346 patients in the operative and nonoperative groups,respectively.Patients in the operative group were treated with a plate or nail,whereas those in the conservative group were managed with splint or functional bracing.Four studies were assessed as having a high risk of bias,and the other 13 were of a low risk of bias according to the Newcastle-Ottawa Scale or Cochrane risk bias tool.The operative group had a significantly decreased rate of nonunion[odds ratio(OR)0.30;95%CI:0.23 to 0.40,reintervention(OR:0.33;95%CI:0.24 to 0.47),and overall complications(OR:0.62;95%CI:0.49 to 0.78)].The pooled effect of the Disabilities of Arm,Shoulder,and Hand score showed a significant difference at 3[mean difference(MD)-8.26;95%CI:-13.60 to-2.92],6(MD:-6.72;95%CI:-11.34 to-2.10),and 12 months(MD:-2.55;95%CI:-4.36 to-0.74).The pooled effect of Visual Analog Scale scores and the Constant-Murley score did not significantly differ between the two groups.CONCLUSION This systematic review and meta-analysis revealed a trend of rapid functional recovery and decreased rates of nonunion and reintervention after operation for humeral shaft fracture compared to conservative treatment.

Modeling,Simulation,and Risk Analysis of Battery Energy Storage Systems in New Energy Grid Integration Scenarios

Energy storage batteries can smooth the volatility of renewable energy sources.The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system(BESS).However,the current modeling of grid-connected BESS is overly simplistic,typically only considering state of charge(SOC)and power constraints.Detailed lithium(Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions.Additionally,there is a lack of real-time batteries risk assessment frameworks.To address these issues,in this study,we establish a thermal-electric-performance(TEP)coupling model based on a multitime scale BESS model,incorporating the electrical and thermal characteristics of Li-ion batteries along with their performance degradation to achieve detailed simulation of grid-connected BESS.Additionally,considering the operating characteristics of energy storage batteries and electrical and thermal abuse factors,we developed a battery pack operational riskmodel,which takes into account SOCand charge-discharge rate(Cr),using amodified failure rate to represent the BESS risk.By integrating detailed simulation of energy storage with predictive failure risk analysis,we obtained a detailed model for BESS risk analysis.This model offers a multi-time scale integrated simulation that spans month-level energy storage simulation times,day-level performance degradation,minutescale failure rate,and second-level BESS characteristics.It offers a critical tool for the study of BESS.Finally,the performance and risk of energy storage batteries under three scenarios—microgrid energy storage,wind power smoothing,and power grid failure response—are simulated,achieving a real-time state-dependent operational risk analysis of the BESS.

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

Purpose-The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approach-The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle.Based on data mechanism models,it predicts the lifespan of key components,evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.Findings-The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system,which helps operators to monitor the operation of vehicle online,predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.Originality/value-This system improves the efficiency of rail vehicle operation,scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.

Systemic immune-inflammation index combined with pediatric appendicitis score in assessing the severity and prognosis for paediatric appendicitis

BACKGROUND Pediatric appendicitis is a common cause of abdominal pain in children and is recognized as a significant surgical emergency.A prompt and accurate diagnosis is essential to prevent complications such as perforation and peritonitis.AIM To investigate the predictive value of the systemic immune-inflammation index(SII)combined with the pediatric appendicitis score(PAS)for the assessment of disease severity and surgical outcomes in children aged 5 years and older with appendicitis.METHODS Clinical data of 104 children diagnosed with acute appendicitis were analyzed.The participants were categorized into the acute appendicitis group and chronic appendicitis group based on disease presentation and further stratified into the good prognosis group and poor prognosis group based on prognosis.The SII and PAS were measured,and a joint model using the combined SII and PAS was constructed to predict disease severity and surgical outcomes.RESULTS Significant differences were observed in the SII and PAS parameters between the acute appendicitis group and chronic appendicitis group.Correlation analysis showed associations among the SII,PAS,and disease severity,with the combined SII and PAS model demonstrating significant predictive value for assessing disease severity[aera under the curve(AUC)=0.914]and predicting surgical outcomes(AUC=0.857)in children aged 5 years and older with appendicitis.CONCLUSION The study findings support the potential of integrating the SII with the PAS for assessing disease severity and predicting surgical outcomes in pediatric appendicitis,indicating the clinical utility of the combined SII and PAS model in guiding clinical decision-making and optimizing surgical management strategies for pediatric patients with appendicitis.

Construction of Regional Ecological Capital Operation Mechanism System from the Perspective of Green Economy Development

Green development has gradually become the main theme of the current world economic development.Green transformation development and cracking the contradiction between ecology and economy need to build an effective ecological capital operation system and mechanism to support,encourage the effective operation of regional ecological capital,promote the appreciation and preservation of ecological capital,and escort the operation.This paper constructs a four-in-one regional ecological capital operation mechanism system,in which the"accumulation mechanism"is the prerequisite,the"conversion mechanism"is the key link,the"compensation mechanism"is an important supplement,and the"incentive mechanism"is the safeguard measure,which aims to ensure the smooth progress of the construction of beautiful China in the new era and realize the socialist modern power.

Research on a Comprehensive Monitoring System for Tunnel Operation based on the Internet of Things and Artificial Intelligence Identification Technology

This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.

Study on Independent Supervision Function of Design Assurance System

The effective operation of a design assurance system cannot be achieved without the effective performance of the independent supervision function.As one of the core functions of the design assurance system,the purpose of the independent supervision function is to ensure that the system operates within the scope of procedures and manuals.At present,the function of independent supervision is a difficult and confusing issue for various original equipment manufacturers as well as suppliers,and there is an urgent requirement to put forward relevant requirements and form relevant methods.Based on the above mentioned objective,the basic requirements of the independent supervision function of design assurance system were studied,the problems and deficiencies in the organization,staffing,and methods existing in the current independent supervision function were analyzed,the improvement suggestions and measures for the performance of the independent supervision function from the aspects of the organization,staffing,procedures,and suppliers were put forward.The present work and conclusions provide guidance and direction for the effective operation of the design assurance system.

Mission reliability modeling and evaluation for reconfigurable unmanned weapon system-of-systems based on effective operation loop

The concept of unmanned weapon system-of-systems(UWSoS)involves a collection of various unmanned systems to achieve or accomplish a specific goal or mission.The mission reliability of UWSoS is represented by its ability to finish a required mission above the baselines of a given mission.However,issues with heterogeneity,cooperation between systems,and the emergence of UWSoS cannot be effectively solved by traditional system reliability methods.This study proposes an effective operation-loop-based mission reliability evaluation method for UWSoS by analyzing dynamic reconfiguration.First,we present a new connotation of an effective operation loop by considering the allocation of operational entities and physical resource constraints.Then,we propose an effective operationloop-based mission reliability model for a heterogeneous UWSoS according to the mission baseline.Moreover,a mission reliability evaluation algorithm is proposed under random external shocks and topology reconfiguration,revealing the evolution law of the effective operation loop and mission reliability.Finally,a typical 60-unmanned-aerial-vehicle-swarm is taken as an example to demonstrate the proposed models and methods.The mission reliability is achieved by considering external shocks,which can serve as a reference for evaluating and improving the effectiveness of UWSoS.

Study on the Characteristics of A New Hybrid Mooring System for DualPlatform Joint Operations

As the sustainable exploitation of marine resources develops,dual-platform joint operation has caught increasing attention.Dual-platform joint operation requires smaller relative motion between the two sub-platforms,which is normally difficult to be satisfied by the traditional mooring system.Therefore,a new hybrid mooring system is developed and studied in this article.To ensure safety during platform movements,both the number of anchor chains and the relative motion between the two sub-platforms are reduced in the new hybrid mooring system.By performing numerical simulations based on three-dimensional potential flow theory in AQWA and physical experiments,the performances of both the new hybrid and traditional mooring systems under two different wave conditions(i.e.,working wave and freak wave conditions) are systematically investigated.Regarding the new hybrid mooring system,the relative stability between the two sub-platforms of the new system is better,and the platforms can restore stability faster when affected by freak waves.