The national grid and other life-sustaining critical infrastructures face an unprecedented threat from prolonged blackouts,which could last over a year and pose a severe risk to national security.Whether caused by phy...The national grid and other life-sustaining critical infrastructures face an unprecedented threat from prolonged blackouts,which could last over a year and pose a severe risk to national security.Whether caused by physical attacks,EMP(electromagnetic pulse)events,or cyberattacks,such disruptions could cripple essential services like water supply,healthcare,communication,and transportation.Research indicates that an attack on just nine key substations could result in a coast-to-coast blackout lasting up to 18 months,leading to economic collapse,civil unrest,and a breakdown of public order.This paper explores the key vulnerabilities of the grid,the potential impacts of prolonged blackouts,and the role of AI(artificial intelligence)and ML(machine learning)in mitigating these threats.AI-driven cybersecurity measures,predictive maintenance,automated threat response,and EMP resilience strategies are discussed as essential solutions to bolster grid security.Policy recommendations emphasize the need for hardened infrastructure,enhanced cybersecurity,redundant power systems,and AI-based grid management to ensure national resilience.Without proactive measures,the nation remains exposed to a catastrophic power grid failure that could have dire consequences for society and the economy.展开更多
Scientific and technological advancements are rapidly transforming underground engineering,shifting from labor-intensive,time-consuming methods to automated,real-time systems.This timely and comprehensive review cover...Scientific and technological advancements are rapidly transforming underground engineering,shifting from labor-intensive,time-consuming methods to automated,real-time systems.This timely and comprehensive review covers in-situ testing,intelligent monitoring,and geophysical testing methods,highlighting fundamental principles,testing apparatuses,data processing techniques,and engineering applications.The state-of-the-art summary emphasizes not only cutting-edge innovations for complex and harsh environments but also the transformative role of artificial intelligence and machine learning in data interpretations.The integration of big data and advanced algorithms is particularly impactful,enabling the identification,prediction,and mitigation of potential risks in underground projects.Key aspects of the discussion include detection capabilities,method integration,and data convergence of intelligent technologies to drive enhanced safety,operational efficiency,and predictive reliability.The review also examines future trends in intelligent technologies,emphasizing unified platforms that combine multiple methods,real-time data,and predictive analytics.These advancements are shaping the evolution of underground construction and maintenance,aiming for risk-free,high-efficiency underground engineering.展开更多
In this work,we present a parallel implementation of radiation hydrodynamics coupled with particle transport,utilizing software infrastructure JASMIN(J Adaptive Structured Meshes applications INfrastructure)which enca...In this work,we present a parallel implementation of radiation hydrodynamics coupled with particle transport,utilizing software infrastructure JASMIN(J Adaptive Structured Meshes applications INfrastructure)which encapsulates high-performance technology for the numerical simulation of complex applications.Two serial codes,radiation hydrodynamics RH2D and particle transport Sn2D,have been integrated into RHSn2D on JASMIN infrastructure,which can efficiently use thousands of processors to simulate the complex multi-physics phenomena.Moreover,the non-conforming processors strategy has ensured RHSn2D against the serious load imbalance between radiation hydrodynamics and particle transport for large scale parallel simulations.Numerical results show that RHSn2D achieves a parallel efficiency of 17.1%using 90720 cells on 8192 processors compared with 256 processors in the same problem.展开更多
Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions mu...Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions must be carefully considered throughout their life cycle.Recent advancements in science and technology have enabled more effective structural monitoring of railway systems,largely driven by the adoption of intelligent strategies for inspection,maintenance,monitoring,and risk management.Research continues to expand and deepen the knowledge in this area;however,it remains a challenging field due to factors such as the complexity of railway systems,the high cost of implementation,and the need for reliable long-term data.展开更多
The efficient transportation of goods is vital for the economic growth of communities,making developing and maintaining seaport infrastructure an essential component of the marine transportation system.Given their geo...The efficient transportation of goods is vital for the economic growth of communities,making developing and maintaining seaport infrastructure an essential component of the marine transportation system.Given their geographic locations,ports are consistently at risk from natural hazards,making the resilience of port infrastructure an essential goal.Despite considerable progress in resilience research,there remains a gap in methods tailored explicitly to assessing port resilience,particularly under extreme wind events.Current approaches often do not capture the full complexity of port systems,as they tend to focus on isolated aspects,such as structural resilience.This paper introduces the PORT Resilience Framework,addressing these gaps by evaluating resilience through a comprehensive list of indicators gathered from various legitimate sources.The indicators are then organized under four comprehensive resilience dimensions:Physical Infrastructure,ICT(i.e.,Information and Communication Technology)and Equipment;Organization and Business Management;Resources and Economic Development;and Territory,Environment,and Stakeholders.This classification is summarized under the acronym"PORT."This paper also introduces a method for aggregating resilience indicators by considering their performance before and after a specific hazard,transforming the data into a quantifiable Loss of Resilience index.The approach is applied to a case study,assessing the resilience of a real Terminal against wind action using real data sourced from the port management.The case study analysis revealed that human resources and quay operations were the most critical factors affecting recovery,with insufficient staffing leading to prolonged recovery periods.The study further demonstrated that post-disruption activity surges,captured by different serviceability function methodologies,often created operational bottlenecks,challenging the port's overall recovery.展开更多
Structural health monitoring technology uses advanced sensors to collect structural state data in real time,evaluate its integrity and residual life,and make maintenance decisions accordingly.The key of structural hea...Structural health monitoring technology uses advanced sensors to collect structural state data in real time,evaluate its integrity and residual life,and make maintenance decisions accordingly.The key of structural health monitoring is to obtain structural data accurately.With the development of new sensor technology,sensors and data acquisition devices for structural health monitoring are constantly emerging,and the performance of these devices is developing rapidly.The latest developments of fiber optic sensors,piezoelectric material sensors and self-diagnostic sensors for structural health monitoring are summarized.The basic working principle of each sensor and its application in structural health monitoring are introduced,and the challenges and opportunities faced by sensors in structural health monitoring are prospected.展开更多
Quantifying material use in infrastructure development and analyzing its relationship with economic growth is essential for enhancing resource efficiency and steering regional resource management toward sustainable de...Quantifying material use in infrastructure development and analyzing its relationship with economic growth is essential for enhancing resource efficiency and steering regional resource management toward sustainable development.This study systematically assessed infrastructure related material use in 30 provinces,autonomous regions,and municipalities in China during 1978-2022.The result indicated that material stock has experienced significant growth,increasing from 16.91×10^(9)t in 1978 to 103.60×10^(9)t in 2022,with an average annual growth rate of 4.20%.However,from 1978 to 2015,material input followed a strong upward trend but saturated after 2015.At the national level,material input peaked in 2015,after which it began to decline.The central region reached its peak earlier in 2013,while the eastern and western regions peaked in 2015.Using a decoupling analysis framework,this study revealed that nationally,the elasticity value between material stock and gross domestic product(GDP)remained near or above 1.0,reflecting continued reliance on stock accumulation.Regionally,the elasticity value between material stock and GDP has increased in the central and western regions during 1978-2022,whereas elasticity value between material stock and GDP in the eastern region showed a slower growth rate but still struggled to achieve absolute decoupling.Moreover,the elasticity value between material input and GDP has declined at the national level,presenting a relative decoupling,with some regions already achieving absolute decoupling.The eastern region was closer to absolute decoupling,while the central and western regions,though still intensive in material input,exhibited faster declines in elasticity.Accelerating the transition from linear to circular economy is an essential step for China to achieve absolute decoupling and long-term sustainability.Finally,this research recommends promoting the adoption of renewable energy,driving industrial upgrading,implementing compact urban design,and extending the lifespan of infrastructure to reduce material dependency and achieve sustainable infrastructure transformation at the national level.展开更多
The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber ris...The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber risks. Although comprehensive, the complexity of the NIST CSF can be overwhelming, especially for those lacking extensive cybersecurity resources. Current implementation tools often cater to larger companies, neglecting the specific needs of SMEs, which can be vulnerable to cyber threats. To address this gap, our research proposes a user-friendly, open-source web platform designed to simplify the implementation of the NIST CSF. This platform enables organizations to assess their risk exposure and continuously monitor their cybersecurity maturity through tailored recommendations based on their unique profiles. Our methodology includes a literature review of existing tools and standards, followed by a description of the platform’s design and architecture. Initial tests with SMEs in Burkina Faso reveal a concerning cybersecurity maturity level, indicating the urgent need for improved strategies based on our findings. By offering an intuitive interface and cross-platform accessibility, this solution aims to empower organizations to enhance their cybersecurity resilience in an evolving threat landscape. The article concludes with discussions on the practical implications and future enhancements of the tool.展开更多
On 13 December 2024,liquefied natural gas(LNG)company Venture Global LNG(Arlington,VA,USA)commenced commercial production of the super-chilled fuel at its partially completed Plaquemines LNG export terminal in Louisia...On 13 December 2024,liquefied natural gas(LNG)company Venture Global LNG(Arlington,VA,USA)commenced commercial production of the super-chilled fuel at its partially completed Plaquemines LNG export terminal in Louisiana(Fig.1)[1].In terms of dollars invested,the 21 billion USD plant is the fourth largest infrastructure project in the world[2].Venture Global initially expected the terminal to produce and ship 20 million tonnes of LNG annually[3].An 18 billion USD expansion of the terminal approved in February 2025 will bring its maximum annual produc-tion capacity to 45 million tonnes[4].When fully operational in 2027,the facility,located in Plaquemines Parish on the Mississippi River about 32 km south of New Orleans,will be among the largest in the world,further contributing to the US position as the world’s biggest LNG exporter[1].展开更多
The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the si...The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the sig-nificant potential of natural language processing(NLP)to analyze unstructured human language during disasters,thereby facilitating the uncovering of disruptions and providing situational awareness supporting various aspects of resilience regarding CISs.Despite this potential,few studies have systematically mapped the global research on NLP applications with respect to supporting various aspects of resilience of CISs.This paper contributes to the body of knowledge by presenting a review of current knowledge using the scientometric review technique.Using 231 bibliographic records from the Scopus and Web of Science core collections,we identify five key research areas where researchers have used NLP to support the resilience of CISs during natural disasters,including sentiment analysis,crisis informatics,data and knowledge visualization,disaster impacts,and content analysis.Furthermore,we map the utility of NLP in the identified research focus with respect to four aspects of resilience(i.e.,preparedness,absorption,recovery,and adaptability)and present various common techniques used and potential future research directions.This review highlights that NLP has the potential to become a supplementary data source to support the resilience of CISs.The results of this study serve as an introductory-level guide designed to help scholars and practitioners unlock the potential of NLP for strengthening the resilience of CISs against natural disasters.展开更多
Since its inception,the Belt and Road Initiative(BRI)has emerged as a global platform for international cooperation,with infrastructure connectivity at its core.Infrastructure,often referred to as the“lifeblood”of e...Since its inception,the Belt and Road Initiative(BRI)has emerged as a global platform for international cooperation,with infrastructure connectivity at its core.Infrastructure,often referred to as the“lifeblood”of economic and social development,plays a pivotal role in breaking bottlenecks,bridging regional gaps,and driving inclusive growth-particularly in developing regions where inadequate infrastructure has long hindered progress.展开更多
The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challe...The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.展开更多
This article is adapted from a speech delivered by Dato’Norman Muhamad,Ambassador of Malaysia to China,at the ASEAN-China(Beijing Municipal Administrative Center)Trade and Investment Promotion Conference.The text has...This article is adapted from a speech delivered by Dato’Norman Muhamad,Ambassador of Malaysia to China,at the ASEAN-China(Beijing Municipal Administrative Center)Trade and Investment Promotion Conference.The text has been edited for clarity and length.展开更多
With the continuous development of digital technology,urban management and urban construction have undergone tremendous changes,exerting a profound impact on people’s lives.As a vital component of cities,urban road i...With the continuous development of digital technology,urban management and urban construction have undergone tremendous changes,exerting a profound impact on people’s lives.As a vital component of cities,urban road infrastructure is closely related to the daily lives of citizens.The application of digital twin technology can provide more support for the full lifecycle operation and maintenance management of urban road infrastructure,effectively improving the quality and efficiency of operation and maintenance management,ensuring the effectiveness of urban road infrastructure,and building a higher-quality urban life.Based on urban road infrastructure,this paper analyzes the application value of digital twin technology,proposes strategies for full lifecycle operation and maintenance management,and offers more references for urban construction.展开更多
With the continuous advancement of the country’s urbanization process,many cities are simultaneously carrying out the renovation of old urban areas while building new urban areas,which involves the demolition of many...With the continuous advancement of the country’s urbanization process,many cities are simultaneously carrying out the renovation of old urban areas while building new urban areas,which involves the demolition of many buildings and municipal infrastructures.To ensure the smooth progress of demolition projects,related safety management work is crucial.This article will discuss the safety management measures for demolition projects based on the basic principles of safety management for municipal infrastructure demolition projects,taking the demolition of gas storage tanks as an example.展开更多
Purpose–This paper aims to systematically review the evolution of inspection technologies and equipment for heavy-haul railway infrastructure,with a focus on China’s Shuohuang Railway and Daqin Railway.It summarizes...Purpose–This paper aims to systematically review the evolution of inspection technologies and equipment for heavy-haul railway infrastructure,with a focus on China’s Shuohuang Railway and Daqin Railway.It summarizes the technological progression from traditional manual inspections to integrated and intelligent inspection systems,analyzes their practical application outcomes and outlines future research directions to support the safe,efficient and sustainable operation of heavy-haul railways.Design/methodology/approach–The study employs a combination of historical and empirical analysis,primarily drawing on academic literature and operational data from Shuohuang Railway.The development of inspection technologies is categorized into two distinct phases:traditional inspection and integrated inspection.The comprehensive effectiveness of these technologies is evaluated based on actual inspection efficiency,defect detection capability,cost savings and other relevant data.Findings–The adoption of integrated inspection vehicles has significantly improved inspection efficiency and accuracy.In 2014,the world’s first heavy-haul integrated inspection vehicle enabled synchronous multidisciplinary inspections,greatly reducing reliance on manual labor.By 2024,the intelligent heavy-haul integrated inspection vehicle further enhanced detection precision by 30%.Practical applications demonstrate that the annual number of track defects decreased from 25,000 to 3,800,while the track quality index(TQI)remained stable below 6 mm.Additionally,annual maintenance costs were reduced by more than 40 m yuan.Originality/value–This paper provides the first systematic review of the development of inspection technologies for heavy-haul railway infrastructure,highlighting China’s leading achievements in integrated and intelligent inspection.It clarifies the practical value of these technologies in enhancing safety,reducing costs and optimizing maintenance operations.Furthermore,it proposes future directions for development,including system integration,onboard computing capabilities and unmanned operations,offering valuable insights for technological innovation and policymaking in the field.展开更多
Artificial intelligence(Al)has emerged as a key arena in major country competition.Recognizing the potential of artificial intelligence as a strategic asset to redefine the United States'global technological leade...Artificial intelligence(Al)has emerged as a key arena in major country competition.Recognizing the potential of artificial intelligence as a strategic asset to redefine the United States'global technological leadership and geopolitical influence,the Trump administration announced the Stargate project in January 2025.Trump's Al infrastructure policy is characterized by government-led connections to technology capital,loose technological regulation,security priorities,and the pursuit of political achievements.His policy goals are to achieve economic growth and job creation internally to serve the political goal of American revival,win the global AI competition,and ensure US global technological leadership.However,the policy implementation of AI infrastructure faces a few challenges,such as industrial path dependency,energy supply constraints,and ethical risks of Al.Guided by techno-nationalism,the US would continue to regard China as its primary strategic competitor.展开更多
The increasing incidence of global warming and frequent heavy precipitation events presents a significant challenge for urban areas in managing extreme precipitation.Strengthening the resilience of communities to clim...The increasing incidence of global warming and frequent heavy precipitation events presents a significant challenge for urban areas in managing extreme precipitation.Strengthening the resilience of communities to climate change is a crucial strategy for fostering sustainable urban development.Green infrastructure offers an ecologically system for rainwater management and ecological restoration,and plays a significant role in adapting to climate risks.This study focuses on climate resilience by examining the implementation of green rainwater infrastructure within the context of climate-adapted green infrastructure in the High Point community of Seattle,USA,and proposes renewal planning strategies,methods,and implementation concepts at the community level.The research indicates that the High Point community has effectively mitigated the issue of waterlogging and enhanced the local microclimate through the implementation of green infrastructure systems,including permeable pavement,rain gardens,bioretention pools,and vegetative buffer zones.It is proposed that the collaborative design of green infrastructure should adhere to principles of systematization,alignment with natural processes,adaptation to the local environment,and engagement of multiple stakeholders,while considering various functions,diverse communities,and differing social contexts.Furthermore,it should be developed in consideration of the unique spatial characteristics,landscape structures,and social needs of each community.展开更多
This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing...This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing the index system from the perspectives of functionality,economy,social impact,environmental impact,and sustainability.The paper also discusses the application of the optimized index system in practical evaluation and the measures to ensure its effectiveness.The research aims to enhance the evaluation mechanism for the value of transportation infrastructure assets,providing a more scientific basis for decision-making,addressing challenges in asset management,improving the level of asset management in transportation infrastructure,and meeting the demands of high-quality development in the transportation sector in the new era.展开更多
The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station pe...The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station performance by analyzing power consumption efficiency,station utilization rates,no-power session occurrences,and CO_(2)reduction metrics.A dataset of 17,500 charging sessions from 305 stations across a regional network was analyzed to identify operational inefficiencies and opportunities for infrastructure optimization.Results indicate a strong correlation between station utilization and energy efficiency,highlighting the importance of strategic station placement.The findings also emphasize the impact of no-power sessions on network inefficiency and the need for real-time station monitoring.CO_(2)reduction analysis demonstrates that optimizing EV charging performance can significantly contribute to sustainability goals.Based on these insights,this study recommends the implementation of predictive maintenance strategies,real-time user notifications,and diversified provider networks to improve station availability and efficiency.The proposed data-driven framework offers actionable solutions for policymakers,charging network operators,and urban planners to enhance EV infrastructure reliability and sustainability.展开更多
文摘The national grid and other life-sustaining critical infrastructures face an unprecedented threat from prolonged blackouts,which could last over a year and pose a severe risk to national security.Whether caused by physical attacks,EMP(electromagnetic pulse)events,or cyberattacks,such disruptions could cripple essential services like water supply,healthcare,communication,and transportation.Research indicates that an attack on just nine key substations could result in a coast-to-coast blackout lasting up to 18 months,leading to economic collapse,civil unrest,and a breakdown of public order.This paper explores the key vulnerabilities of the grid,the potential impacts of prolonged blackouts,and the role of AI(artificial intelligence)and ML(machine learning)in mitigating these threats.AI-driven cybersecurity measures,predictive maintenance,automated threat response,and EMP resilience strategies are discussed as essential solutions to bolster grid security.Policy recommendations emphasize the need for hardened infrastructure,enhanced cybersecurity,redundant power systems,and AI-based grid management to ensure national resilience.Without proactive measures,the nation remains exposed to a catastrophic power grid failure that could have dire consequences for society and the economy.
基金supported by Ministry of Education of Singapore,under Academic Research Fund Tier 1(Grant Number RG143/23).
文摘Scientific and technological advancements are rapidly transforming underground engineering,shifting from labor-intensive,time-consuming methods to automated,real-time systems.This timely and comprehensive review covers in-situ testing,intelligent monitoring,and geophysical testing methods,highlighting fundamental principles,testing apparatuses,data processing techniques,and engineering applications.The state-of-the-art summary emphasizes not only cutting-edge innovations for complex and harsh environments but also the transformative role of artificial intelligence and machine learning in data interpretations.The integration of big data and advanced algorithms is particularly impactful,enabling the identification,prediction,and mitigation of potential risks in underground projects.Key aspects of the discussion include detection capabilities,method integration,and data convergence of intelligent technologies to drive enhanced safety,operational efficiency,and predictive reliability.The review also examines future trends in intelligent technologies,emphasizing unified platforms that combine multiple methods,real-time data,and predictive analytics.These advancements are shaping the evolution of underground construction and maintenance,aiming for risk-free,high-efficiency underground engineering.
基金National Natural Science Foundation of China(12471367)。
文摘In this work,we present a parallel implementation of radiation hydrodynamics coupled with particle transport,utilizing software infrastructure JASMIN(J Adaptive Structured Meshes applications INfrastructure)which encapsulates high-performance technology for the numerical simulation of complex applications.Two serial codes,radiation hydrodynamics RH2D and particle transport Sn2D,have been integrated into RHSn2D on JASMIN infrastructure,which can efficiently use thousands of processors to simulate the complex multi-physics phenomena.Moreover,the non-conforming processors strategy has ensured RHSn2D against the serious load imbalance between radiation hydrodynamics and particle transport for large scale parallel simulations.Numerical results show that RHSn2D achieves a parallel efficiency of 17.1%using 90720 cells on 8192 processors compared with 256 processors in the same problem.
文摘Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions must be carefully considered throughout their life cycle.Recent advancements in science and technology have enabled more effective structural monitoring of railway systems,largely driven by the adoption of intelligent strategies for inspection,maintenance,monitoring,and risk management.Research continues to expand and deepen the knowledge in this area;however,it remains a challenging field due to factors such as the complexity of railway systems,the high cost of implementation,and the need for reliable long-term data.
文摘The efficient transportation of goods is vital for the economic growth of communities,making developing and maintaining seaport infrastructure an essential component of the marine transportation system.Given their geographic locations,ports are consistently at risk from natural hazards,making the resilience of port infrastructure an essential goal.Despite considerable progress in resilience research,there remains a gap in methods tailored explicitly to assessing port resilience,particularly under extreme wind events.Current approaches often do not capture the full complexity of port systems,as they tend to focus on isolated aspects,such as structural resilience.This paper introduces the PORT Resilience Framework,addressing these gaps by evaluating resilience through a comprehensive list of indicators gathered from various legitimate sources.The indicators are then organized under four comprehensive resilience dimensions:Physical Infrastructure,ICT(i.e.,Information and Communication Technology)and Equipment;Organization and Business Management;Resources and Economic Development;and Territory,Environment,and Stakeholders.This classification is summarized under the acronym"PORT."This paper also introduces a method for aggregating resilience indicators by considering their performance before and after a specific hazard,transforming the data into a quantifiable Loss of Resilience index.The approach is applied to a case study,assessing the resilience of a real Terminal against wind action using real data sourced from the port management.The case study analysis revealed that human resources and quay operations were the most critical factors affecting recovery,with insufficient staffing leading to prolonged recovery periods.The study further demonstrated that post-disruption activity surges,captured by different serviceability function methodologies,often created operational bottlenecks,challenging the port's overall recovery.
文摘Structural health monitoring technology uses advanced sensors to collect structural state data in real time,evaluate its integrity and residual life,and make maintenance decisions accordingly.The key of structural health monitoring is to obtain structural data accurately.With the development of new sensor technology,sensors and data acquisition devices for structural health monitoring are constantly emerging,and the performance of these devices is developing rapidly.The latest developments of fiber optic sensors,piezoelectric material sensors and self-diagnostic sensors for structural health monitoring are summarized.The basic working principle of each sensor and its application in structural health monitoring are introduced,and the challenges and opportunities faced by sensors in structural health monitoring are prospected.
基金supported by the Shanghai Committee of Science and Technology Fund(22ZR1419300)the Academic Year 2025 Ritsumeikan Asia Pacific University Academic Research Subsidy(Grants-in-Aid Reapplication Type).
文摘Quantifying material use in infrastructure development and analyzing its relationship with economic growth is essential for enhancing resource efficiency and steering regional resource management toward sustainable development.This study systematically assessed infrastructure related material use in 30 provinces,autonomous regions,and municipalities in China during 1978-2022.The result indicated that material stock has experienced significant growth,increasing from 16.91×10^(9)t in 1978 to 103.60×10^(9)t in 2022,with an average annual growth rate of 4.20%.However,from 1978 to 2015,material input followed a strong upward trend but saturated after 2015.At the national level,material input peaked in 2015,after which it began to decline.The central region reached its peak earlier in 2013,while the eastern and western regions peaked in 2015.Using a decoupling analysis framework,this study revealed that nationally,the elasticity value between material stock and gross domestic product(GDP)remained near or above 1.0,reflecting continued reliance on stock accumulation.Regionally,the elasticity value between material stock and GDP has increased in the central and western regions during 1978-2022,whereas elasticity value between material stock and GDP in the eastern region showed a slower growth rate but still struggled to achieve absolute decoupling.Moreover,the elasticity value between material input and GDP has declined at the national level,presenting a relative decoupling,with some regions already achieving absolute decoupling.The eastern region was closer to absolute decoupling,while the central and western regions,though still intensive in material input,exhibited faster declines in elasticity.Accelerating the transition from linear to circular economy is an essential step for China to achieve absolute decoupling and long-term sustainability.Finally,this research recommends promoting the adoption of renewable energy,driving industrial upgrading,implementing compact urban design,and extending the lifespan of infrastructure to reduce material dependency and achieve sustainable infrastructure transformation at the national level.
文摘The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber risks. Although comprehensive, the complexity of the NIST CSF can be overwhelming, especially for those lacking extensive cybersecurity resources. Current implementation tools often cater to larger companies, neglecting the specific needs of SMEs, which can be vulnerable to cyber threats. To address this gap, our research proposes a user-friendly, open-source web platform designed to simplify the implementation of the NIST CSF. This platform enables organizations to assess their risk exposure and continuously monitor their cybersecurity maturity through tailored recommendations based on their unique profiles. Our methodology includes a literature review of existing tools and standards, followed by a description of the platform’s design and architecture. Initial tests with SMEs in Burkina Faso reveal a concerning cybersecurity maturity level, indicating the urgent need for improved strategies based on our findings. By offering an intuitive interface and cross-platform accessibility, this solution aims to empower organizations to enhance their cybersecurity resilience in an evolving threat landscape. The article concludes with discussions on the practical implications and future enhancements of the tool.
文摘On 13 December 2024,liquefied natural gas(LNG)company Venture Global LNG(Arlington,VA,USA)commenced commercial production of the super-chilled fuel at its partially completed Plaquemines LNG export terminal in Louisiana(Fig.1)[1].In terms of dollars invested,the 21 billion USD plant is the fourth largest infrastructure project in the world[2].Venture Global initially expected the terminal to produce and ship 20 million tonnes of LNG annually[3].An 18 billion USD expansion of the terminal approved in February 2025 will bring its maximum annual produc-tion capacity to 45 million tonnes[4].When fully operational in 2027,the facility,located in Plaquemines Parish on the Mississippi River about 32 km south of New Orleans,will be among the largest in the world,further contributing to the US position as the world’s biggest LNG exporter[1].
基金financial support from the National Science Foundation(NSF)EPSCoR R.I.I.Track-2 Program,awarded under the NSF grant number 2119691.
文摘The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the sig-nificant potential of natural language processing(NLP)to analyze unstructured human language during disasters,thereby facilitating the uncovering of disruptions and providing situational awareness supporting various aspects of resilience regarding CISs.Despite this potential,few studies have systematically mapped the global research on NLP applications with respect to supporting various aspects of resilience of CISs.This paper contributes to the body of knowledge by presenting a review of current knowledge using the scientometric review technique.Using 231 bibliographic records from the Scopus and Web of Science core collections,we identify five key research areas where researchers have used NLP to support the resilience of CISs during natural disasters,including sentiment analysis,crisis informatics,data and knowledge visualization,disaster impacts,and content analysis.Furthermore,we map the utility of NLP in the identified research focus with respect to four aspects of resilience(i.e.,preparedness,absorption,recovery,and adaptability)and present various common techniques used and potential future research directions.This review highlights that NLP has the potential to become a supplementary data source to support the resilience of CISs.The results of this study serve as an introductory-level guide designed to help scholars and practitioners unlock the potential of NLP for strengthening the resilience of CISs against natural disasters.
文摘Since its inception,the Belt and Road Initiative(BRI)has emerged as a global platform for international cooperation,with infrastructure connectivity at its core.Infrastructure,often referred to as the“lifeblood”of economic and social development,plays a pivotal role in breaking bottlenecks,bridging regional gaps,and driving inclusive growth-particularly in developing regions where inadequate infrastructure has long hindered progress.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.
文摘This article is adapted from a speech delivered by Dato’Norman Muhamad,Ambassador of Malaysia to China,at the ASEAN-China(Beijing Municipal Administrative Center)Trade and Investment Promotion Conference.The text has been edited for clarity and length.
文摘With the continuous development of digital technology,urban management and urban construction have undergone tremendous changes,exerting a profound impact on people’s lives.As a vital component of cities,urban road infrastructure is closely related to the daily lives of citizens.The application of digital twin technology can provide more support for the full lifecycle operation and maintenance management of urban road infrastructure,effectively improving the quality and efficiency of operation and maintenance management,ensuring the effectiveness of urban road infrastructure,and building a higher-quality urban life.Based on urban road infrastructure,this paper analyzes the application value of digital twin technology,proposes strategies for full lifecycle operation and maintenance management,and offers more references for urban construction.
文摘With the continuous advancement of the country’s urbanization process,many cities are simultaneously carrying out the renovation of old urban areas while building new urban areas,which involves the demolition of many buildings and municipal infrastructures.To ensure the smooth progress of demolition projects,related safety management work is crucial.This article will discuss the safety management measures for demolition projects based on the basic principles of safety management for municipal infrastructure demolition projects,taking the demolition of gas storage tanks as an example.
基金supported by 2020 Science and Technology Innovation Project of Shuo-Huang Railway Development Company(SHTL-20-12).
文摘Purpose–This paper aims to systematically review the evolution of inspection technologies and equipment for heavy-haul railway infrastructure,with a focus on China’s Shuohuang Railway and Daqin Railway.It summarizes the technological progression from traditional manual inspections to integrated and intelligent inspection systems,analyzes their practical application outcomes and outlines future research directions to support the safe,efficient and sustainable operation of heavy-haul railways.Design/methodology/approach–The study employs a combination of historical and empirical analysis,primarily drawing on academic literature and operational data from Shuohuang Railway.The development of inspection technologies is categorized into two distinct phases:traditional inspection and integrated inspection.The comprehensive effectiveness of these technologies is evaluated based on actual inspection efficiency,defect detection capability,cost savings and other relevant data.Findings–The adoption of integrated inspection vehicles has significantly improved inspection efficiency and accuracy.In 2014,the world’s first heavy-haul integrated inspection vehicle enabled synchronous multidisciplinary inspections,greatly reducing reliance on manual labor.By 2024,the intelligent heavy-haul integrated inspection vehicle further enhanced detection precision by 30%.Practical applications demonstrate that the annual number of track defects decreased from 25,000 to 3,800,while the track quality index(TQI)remained stable below 6 mm.Additionally,annual maintenance costs were reduced by more than 40 m yuan.Originality/value–This paper provides the first systematic review of the development of inspection technologies for heavy-haul railway infrastructure,highlighting China’s leading achievements in integrated and intelligent inspection.It clarifies the practical value of these technologies in enhancing safety,reducing costs and optimizing maintenance operations.Furthermore,it proposes future directions for development,including system integration,onboard computing capabilities and unmanned operations,offering valuable insights for technological innovation and policymaking in the field.
文摘Artificial intelligence(Al)has emerged as a key arena in major country competition.Recognizing the potential of artificial intelligence as a strategic asset to redefine the United States'global technological leadership and geopolitical influence,the Trump administration announced the Stargate project in January 2025.Trump's Al infrastructure policy is characterized by government-led connections to technology capital,loose technological regulation,security priorities,and the pursuit of political achievements.His policy goals are to achieve economic growth and job creation internally to serve the political goal of American revival,win the global AI competition,and ensure US global technological leadership.However,the policy implementation of AI infrastructure faces a few challenges,such as industrial path dependency,energy supply constraints,and ethical risks of Al.Guided by techno-nationalism,the US would continue to regard China as its primary strategic competitor.
文摘The increasing incidence of global warming and frequent heavy precipitation events presents a significant challenge for urban areas in managing extreme precipitation.Strengthening the resilience of communities to climate change is a crucial strategy for fostering sustainable urban development.Green infrastructure offers an ecologically system for rainwater management and ecological restoration,and plays a significant role in adapting to climate risks.This study focuses on climate resilience by examining the implementation of green rainwater infrastructure within the context of climate-adapted green infrastructure in the High Point community of Seattle,USA,and proposes renewal planning strategies,methods,and implementation concepts at the community level.The research indicates that the High Point community has effectively mitigated the issue of waterlogging and enhanced the local microclimate through the implementation of green infrastructure systems,including permeable pavement,rain gardens,bioretention pools,and vegetative buffer zones.It is proposed that the collaborative design of green infrastructure should adhere to principles of systematization,alignment with natural processes,adaptation to the local environment,and engagement of multiple stakeholders,while considering various functions,diverse communities,and differing social contexts.Furthermore,it should be developed in consideration of the unique spatial characteristics,landscape structures,and social needs of each community.
文摘This paper focuses on the optimization of the evaluation index system for the value of transportation infrastructure assets.It analyzes the shortcomings of the current system and explores the directions for optimizing the index system from the perspectives of functionality,economy,social impact,environmental impact,and sustainability.The paper also discusses the application of the optimized index system in practical evaluation and the measures to ensure its effectiveness.The research aims to enhance the evaluation mechanism for the value of transportation infrastructure assets,providing a more scientific basis for decision-making,addressing challenges in asset management,improving the level of asset management in transportation infrastructure,and meeting the demands of high-quality development in the transportation sector in the new era.
文摘The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station performance by analyzing power consumption efficiency,station utilization rates,no-power session occurrences,and CO_(2)reduction metrics.A dataset of 17,500 charging sessions from 305 stations across a regional network was analyzed to identify operational inefficiencies and opportunities for infrastructure optimization.Results indicate a strong correlation between station utilization and energy efficiency,highlighting the importance of strategic station placement.The findings also emphasize the impact of no-power sessions on network inefficiency and the need for real-time station monitoring.CO_(2)reduction analysis demonstrates that optimizing EV charging performance can significantly contribute to sustainability goals.Based on these insights,this study recommends the implementation of predictive maintenance strategies,real-time user notifications,and diversified provider networks to improve station availability and efficiency.The proposed data-driven framework offers actionable solutions for policymakers,charging network operators,and urban planners to enhance EV infrastructure reliability and sustainability.
