Application Strategy of Digital Comprehensive Management and Maintenance System for Bridges

Effective application of digital integrated management and maintenance systems is essential for successful operation and maintenance management of bridge projects.This article analyzes the application strategy of such systems.It provides an overview of comprehensive digital management and maintenance of bridges,an analysis of the basic components of the integrated management and maintenance system,and its application strategies.This study aims to offer guidance for the application of the system and to improve the quality of modern bridge engineering management and maintenance work.

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.

Exploration of Operation and Maintenance Management Mode and Innovation Mechanism of Pilot Base of Chemical Park

Based on the current situation of the operation and maintenance management of the pilot base in many chemical parks in China,this paper conducts an in-depth exploration of the operation and maintenance management and innovation mode of the pilot base from the aspects of the evaluation of the pilot project entering the park,safety and environmental protection supervision,pilot mode,and industrialization mode of the pilot test results,so as to provide solutions for accelerating the process and industrialization of the pilot project and realizing the innovation value of the pilot base.

Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

Continuous wave and active Q-switched operation of Watt-level LED-pumped two-rod Nd,Ce:YAG laser

A high-performance LED-side-pumped two-rod Nd,Ce:YAG laser with continuous-wave(CW) and acousto–optical(A-O) Q-switched operation is demonstrated in this work. A symmetrically shaped flat–flat cavity with two identical LEDside-pumped laser modules is employed for power scalability. In the CW regime, the maximum output average power of laser at 1064 nm is 4.41 W, corresponding to a maximum optical conversion efficiency of 5.3% and a slope efficiency is 12.4%. In the active Q-switched regime, the pulse energy of laser reaches as high as 0.89 m J at a repetition rate of 800 Hz with a pulse width of 457.2 ns, the corresponding highest peak output power is 1.94 k W and the M~2 factor is measured to be about 8.8. To the best of the authors' knowledge, this is the first demonstration and the highest performance of a CW LED-side-pumped two-rod laser Nd,Ce:YAG with Watt-level output reported so far.

Mediating role of social support in dysphoria,despondency,and quality of life in patients undergoing maintenance hemodialysis

BACKGROUND Dysphoria and despondency are prevalent psychological issues in patients undergoing Maintenance Hemodialysis(MHD)that significantly affect their quality of life(QOL).High levels of social support can significantly improve the physical and mental well-being of patients undergoing MHD.Currently,there is limited research on how social support mediates the relationship between dysphoria,despondency,and overall QOL in patients undergoing MHD.It is imperative to investigate this mediating effect to mitigate dysphoria and despondency in patients undergoing MHD,ultimately enhancing their overall QOL.AIM To investigate the mediating role of social support in relationships between dysphoria,despondency,and QOL among patients undergoing MHD.METHODS Participants comprised 289 patients undergoing MHD,who were selected using a random sampling approach.The Social Support Rating Scale,Self-Rating Anxiety Scale,Self-Rating Depression Scale,and QOL Scale were administered.Correlation analysis was performed to examine the associations between social support,dysphoria,despondency,and QOL in patients undergoing MHD.To assess the mediating impact of social support on dysphoria,despondency,and QOL in patients undergoing MHD,a bootstrap method was applied.RESULTS Significant correlations among social support,dysphoria,despondency,and quality in patients undergoing MHD were observed(all P<0.01).Dysphoria and despondency negatively correlated with social support and QOL(P<0.01).Dysphoria and despondency had negative predictive impacts on the QOL of patients undergoing MHD(P<0.05).The direct effect of dysphoria on QOL was statistically significant(P<0.05).Social support mediated the relationship between dysphoria and QOL,and this mediating effect was significant(P<0.05).Similarly,the direct effect of despondency on QOL was significant(P<0.05).Moreover,social support played a mediating role between despondency and QOL,with a significant mediating effect(P<0.05).CONCLUSION These findings suggest that social support plays a significant mediating role in the relationship between dysphoria,despondency,and QOL in patients undergoing MHD.

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.

Key Issues for Modelling, Operation, Management and Diagnosis of Lithium Batteries: Current States and Prospects

1 Introduction.With the continuous growth of the global population,the energy demand continues to increase.However,due to the dominance of fossil fuels in global energy and fossil fuels are non-renewable,it has led to the global energy crisis[1].Besides,the use of fossil fuels will generate a mass of air pollutants(e.g.,carbon dioxide,sulfur dioxide,etc.),which will cause serious environmental pollution,climate change[2],etc.To resolve the aforementioned issues,countries around the world have implemented a variety of measures hoping to fundamentally adjust the global energy structure and achieve sustainable development.Thereinto,“Paris Agreement”reached in 2015 under the framework of“United Nations Framework Convention on Climate Change”aims to control the increase in the average temperature of the globe to within 2°C below preindustrial levels,and thereafter to peak global greenhouse gas emissions as soon as possible,continuously decreasing thereafter[3].United Kingdom plans to reduce the average exhaust emissions of“new cars”to approximately 50–70 g/km by 20230,which is roughly half of what it is now[4].In addition,China proposed a plan at“United Nations General Assembly”in 2020 to peak carbon dioxide emissions by 2030 and strive to achieve carbon neutrality by 2060.It is a fact that the whole world is committed to changing the current energy structure,protecting the Earth’s ecology,and achieving global sustainable development[5].

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Translation Theory and Techniques in Optometry Literature: A Case Study of the “Optoform 80 Installation and Maintenance Manual”

Translation of specialized documents in optometry presents unique challenges,requiring a deep understanding of the professional context,terminology,and adherence to specific translation styles.This paper delves into the translation theory and techniques employed in the English-to-Chinese translation of the“Optoform 80 Installation and Maintenance Manual”,serving as a case study.Emphasizing Nida’s theory of functional equivalence,the paper explores the complexities of translating professional optometry literature,focusing on key points and common issues in translating installation and maintenance manuals for optometric devices.Special attention is given to the translation of professional terminology,employing methods such as addition,omission,conversion,and repetition.The translation process aims to meet specific requirements,ensuring accuracy and coherence while aligning with Chinese language conventions.The paper also analyzes translation methods and techniques concerning terminology,prepositions,conjunctions,and handling parallel elements based on practical insights from the Optoform 80 Manual.

Current status and prospects of research on safety situation awareness of high speed railway operation environment

Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.

Analysis of Detection and Monitoring Technology in the Construction and Maintenance of Large Bridges

Currently,there is significant attention placed on the construction,management,and maintenance of large service bridges.Within the realm of bridge maintenance management,the utilization of detection and monitoring technology is indispensable.By employing these technologies,we can effectively identify any structural defects within the bridge,promptly uncover unknown risks,proactively establish maintenance strategies,and prevent the rapid deterioration of bridge conditions.This article aims to explore the advantages of applying bridge monitoring and testing technology and to discuss various methods for implementing detection and monitoring technology throughout the construction,management,and maintenance phases of large bridges.Ultimately,this will contribute to ensuring the safe operation of large bridges.

Research and Practice of the Blended Teaching Model of BOPPPS Teaching Method Under the Background of Digital Education: Taking Operations Research Course as an Example

The rapid development of digital education provides new opportunities and challenges for teaching model innovation.This study aims to explore the application of the BOPPPS(Bridge-in,Objective,Pre-assessment,Participatory learning,Post-assessment,Summary)teaching method in the development of a blended teaching model for the Operations Research course under the background of digital education.In response to the characteristics of the course and the needs of the student group,the teaching design is reconstructed with a student-centered approach,increasing practical teaching links,improving the assessment and evaluation system,and effectively implementing it in conjunction with digital educational technology.This teaching model has shown significant effectiveness in the context of digital education,providing valuable experience and insights for the innovation of the Operations Research course.

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.

Timing of surgical operation for patients with intra-abdominal infection:A systematic review and meta-analysis

BACKGROUND Intra-abdominal infections(IAIs)is the most common type of surgical infection,with high associated morbidity and mortality rates.In recent years,due to the use of antibiotics,various drug-resistant bacteria have emerged,making the treatment of abdominal infections more challenging.Early surgical exploration can reduce the mortality of patients with abdominal infection and the occurrence of complications.However,available evidence regarding the optimal timing of IAI surgery is still weak.In study,we compared the effects of operation time on patients with abdominal cavity infection and tried to confirm the best timing of surgery.AIM To assess the efficacy of early vs delayed surgical exploration in the treatment of IAI,in terms of overall mortality.METHODS A systematic literature search was performed using PubMed,EMBASE,Cochrane Central Register of Controlled Trials,Ovid,and ScienceDirect.The systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analyses method.Based on the timing of the surgical operation,we divided the literature into two groups:Early surgery and delayed surgery.For the early and delayed surgery groups,the intervention was performed with and after 12 h of the initial surgical intervention,respectively.The main outcome measure was the mortality rate.The literature search was performed from May 5 to 20,2021.We also searched the World Health Organization International Clinical Trials Registry Platform search portal and ClinicalTrials.gov on May 20,2021,for ongoing trials.This study was registered with the International Prospective Register of Systematic Reviews.RESULTS We identified nine eligible trial comparisons.Early surgical exploration of patients with IAIs(performed within 12 h)has significantly reduced the mortality and complications of patients,improved the survival rate,and shortened the hospital stay.CONCLUSION Early surgical exploration within 12 h may be more effective for the treatment of IAIs relative to a delayed operation.

Ergonomic Reliability Assessment of VDT Systemfor Operation Design Based on Improved BPNN and HCR under Special Circumstances

Ergonomic reliability plays a significant role in the safe operation of devices.With the spread of infectious diseases around the world,in work environments with high loads and high infection rates,medical staff work in a state of high self-protection.The use of visual display terminal(VDT)for medical equipment has undergone fundamental changes,and the traditional medical equipment human-machine interface design needs to be improved.After the completion of design and development,a VDT design enters the experimental testing stage,which has significant limitations for simulating the work of medical staff in the high-load and high-infection environments.The testing cost is high,and subjects face harsh conditions;thus,an ergonomic reliability model that can predict the use of VDT in such special high-infection and high-load circumstances must be established.An ergonomic reliability model based on an improved backpropagation neural network(BPNN)and human cognition reliability(HCR)is proposed for predicting and evaluating operation flows according tomedical equipment VDTs.Firstly,a small data sample can be used to train BPNN to generate a network that can ensure suitable accuracy.To prevent the model from falling into local optimal solutions,the bat algorithm is introduced to improve the BPNN.Compared to a traditional BPNN,the superiority of the improved BPNN is clearly demonstrated.Secondly,the HCR method is used to analyze and highlight changes in the human factor reliability of VDTs for medical equipment in different time processes and operating processes according to BPNN prediction results,to provide a reference for selecting the optimalmethod.Finally,the validity and availability of the proposedmethod are verified through an eye tracker experiment and statistical analysis results.

Analysis on Operational Safety and Efficiency of FAO System in Urban Rail Transit

This paper discusses two urgent problems that need to be solved in fully automatic operation(FAO)for urban rail transit.The first is the analysis of safety in FAO,while another is the analysis of efficiency in FAO.Firstly,this paper establishes an operational safety evaluation index system from the perspective of operation for the unique or typical risk sources of the FAO system,and uses the analytic hierarchy process(AHP)to evaluate the indicators,analyzes various factors that affect the safe operation of FAO,and provides safety management recommendations for FAO lines operation to maintain the FAO system specifically.Secondly,taking the Yanfang Line as an example,this paper uses OpenTrack software to analyze the efficiency of FAO operation,and conducts simulation calculations for key links such as the mainline tracking interval,train entry and exit,and return limit interval.The fault impact surface of the FAO trains is simulated and discussed to verify whether FAO can meet the long-term operation requirements of Yanfang Line.Finally,this paper compares the simulation data of FAO on the Yanfang Line with manual operation(MO)to verify the advantages of FAO and guide the engineering construction of subsequent fully automated driving lines.

Management System Activities of the Operation and Utilization of GHARR-1

The Ghana Research Reactor-1 (GHARR-1) is a 34 kW low enriched uranium (LEU) Miniature Neutron Source Reactor (MNSR), tank-in-pool type and cooled by natural circulation under atmospheric pressure operating conditions. GHARR-1 is owned by Ghana Atomic Energy Commission (GAEC) and operated by National Nuclear Research Institute (NNRI), one of the institutes of GAEC. GHARR-1 is housed by Nuclear Reactors Research Centre (NRRC), one of the Centres of NNRI. Management/Administration, Radiation protection, Reactor operation and maintenance, Reactor utilization and Physical protection are the various systems/units that integrate to manage the activities of operation and utilization of GHARR-1 in addition to the quality assurance and quality control management system of the research reactor facility. The GHARR-1 which is currently in operation follows a robust maintenance culture adopted by the management system and this has made it possible to keep the reactor in operation with minimal interruption. The management system activities adopted at the Centre to ensure safety of the workers, public and the research reactor facility include authorization of the operation of the reactor for any experiments/modifications;providing material and financial resources for maintaining the research reactor facility;following standard procedures while carrying out Neutron Activation Analysis;participation in IAEA proficiency test;irradiation sites/positions characterization;following standard procedures while carrying out reactor operation and maintenance including reactor and pool water purification and other related activities;monitoring radiation levels in the controlled, supervised and uncontrolled areas of the research reactor facility as well as during reactor operation and maintenance;controlling the physical entry of the workers and public into the research reactor facility;and ensuring that the security structures provided to protect the reactor facility are functioning properly. The thorough knowledge on the functions of the various components that make up the electrical/electronic and control systems of the reactor has been observed to be important for continuous successful maintenance of the research reactor to keep the reactor in operation. This work provides some management system activities adopted to monitor the activities of the research reactor operation and utilization to guarantee safety of workers, public and the environment as well as to safeguard a continuous operation of the research reactor. These management system activities adopted among others, are in the form of Monitoring Forms provided for monitoring the activities of the research reactor operation and utilization in order to ensure standard procedures and specifications are followed and quality services are rendered to the public.

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.

A Multi-Objective Optimization for Locating Maintenance Stations and Operator Dispatching of Corrective Maintenance

In this study,we introduce a novel multi-objective optimization model tailored for modern manufacturing,aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance.Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel,addressing a crucial gap in the integration of maintenance personnel dispatching and station selection.Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness.The core of our methodology is the NSGA Ⅲ+Dispatch,an advanced adaptation of the Non-Dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ),meticulously designed for the selection of maintenance stations and effective operator dispatching.This method integrates a comprehensive coding process,crossover operator,and mutation operator to efficiently manage multiple objectives.Rigorous empirical testing,including a detailed analysis from a taiwan region electronic equipment manufacturer,validated the effectiveness of our approach across various scenarios of machine failure frequencies and operator configurations.The findings reveal that the proposed model significantly outperforms current practices by reducing response times by up to 23%in low-frequency and 28.23%in high-frequency machine failure scenarios,leading to notable improvements in efficiency and cost reduction.Additionally,it demonstrates significant improvements in oper-ational efficiency,particularly in selective high-frequency failure contexts,while ensuring substantial manpower cost savings without compromising on operational effectiveness.This research significantly advances maintenance strategies in production environments,providing the manufacturing industry with practical,optimized solutions for diverse machine malfunction situations.Furthermore,the methodologies and principles developed in this study have potential applications in various other sectors,including healthcare,transportation,and energy,where maintenance efficiency and resource optimization are equally critical.