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
This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.W...This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.While focused on representative nanoparticles(nano-TiO₂,nano-Fe₃O₄,and carbon nanotubes)and select energy pollutants,experimental data showed these materials greatly enhanced the movement of pollutants,increasing migration distances from 1.6 to 2.9 times.The carbon nanotubes possessed the greatest carrying effect,increasing the phenanthrene migration distance by 286 percent.The study determined surface properties of nanoparticles,pH of the liquid environment,ionic concentration,and organic matter level as major elements impacting pollutant mobility.Laboratory simulations,while controlled and reproducible,necessarily simplified the complex dynamics of real marine environments.Nanoparticle-sorbate systems were found to be effective in enhancing the deterioration rate of materials used in offshore constructions,with CNTPAHs composites causing carbon steel to corrode by 183% more than if PAHs were used without the composites.This change in corrosion behaviour was shown in other tests to be caused by a change in dynamics of the corrosion products'structural constituents and the various electrochemical properties present on the surface of the material.Samples of concrete showed a spend of 90 days in the composite system resulted in a 26.8% decrease in compressive strength compared to control conditions which had only a 15.3%.Therefore,taking into account the results,strategies were formulated to ensure durability for offshore infrastructure including surface modified anticorrosion coatings,surveillance and alert systems,and integrated protective systems.Future field validation studies are needed to verify these laboratory findings under actual marine conditions.This study helps to comprehend the behaviour of nanoparticles in intricate marine ecosystems,providing support for the sustainable advancement of offshore infrastructure and the protection of the marine environment.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
This research work aims at modelling a framework for Private Cloud infrastructure Deployment for Information and Communication Technology Centres (ICTs) in tertiary institutions in Nigeria. Recent researches have indi...This research work aims at modelling a framework for Private Cloud infrastructure Deployment for Information and Communication Technology Centres (ICTs) in tertiary institutions in Nigeria. Recent researches have indicated that cloud computing will become the mainstream in computing technology and very effective for businesses. All Tertiary Institutions have ICT units, and are generally charged with the responsibilities of deploying ICT infrastructure and services for administration, teaching, research and learning in higher institution at large. The Structured System Analysis and Design Methodology (SSADM) is used in this research and a six-step framework for a cost effective and scalable Private cloud infrastructure using server virtualization is presented as an alternative that can guarantee total and independent control of data flow in the institutions, while ensuring adequate security of vital information.展开更多
Pervasive low levels of education and weak civil society activism in poor rural communities are cited as constraining factors for participatory development (PD), resulting in technical capacity for participation being...Pervasive low levels of education and weak civil society activism in poor rural communities are cited as constraining factors for participatory development (PD), resulting in technical capacity for participation being skewed against the community participants. This paper highlights the outcomes of a research study that examined the applicability of the participatory development concept in conditions characterised by low levels of education and weak civil society. The research was undertaken in two rural villages in the Eastern Cape Province of South Africa, utilising both quantitative and qualitative approaches entailing interviews with 18 key informants followed by two focus group discussions each with seven participants respectively. The research found that rural communities were not aware of the government policy placing people participation at the centre of rural development interventions;and that they would not support it as they believed it was government's role to champion their development. The research also found that the government officials that lead the implementation effort of the rural development programmes did not believe that the participation policy was practical, citing capacity limitations among rural communities. The researcher recommends a moderated rural people participation process, which features creation of a facilitative institutional infrastructure to optimise productive participation of rural people in local development processes.展开更多
No Projects Coopera- Total Invest- Investment Chinese Partners tion Mode ment Predicted Proportion KF3-01 Sewage Treatment Plant J.V. US$30 million Chinese 30% Beijing Economic with land as & Technological investm...No Projects Coopera- Total Invest- Investment Chinese Partners tion Mode ment Predicted Proportion KF3-01 Sewage Treatment Plant J.V. US$30 million Chinese 30% Beijing Economic with land as & Technological investment, 70% Development Zone for foreign partner SZ3-02 Beijing freight transport J.V. US$85 million Through Beijing Traffic Bureau hub of southwest highway negotiation SZ3-03 Beijing southeast international J.V. US$40 million 50% for each ditto container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
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
Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically ...Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically investigates recent advancements in sustainable alternatives,including geopolymer concrete,engineered innovacementitious composites(ECC),bio-concrete,fiber-reinforced polymers(FRPs),and bamboo,stainless steel,and steel-CFRP hybrid bars.Each material is evaluated based on marine durability,mechanical performance,environmental impact,and cost feasibility using life cycle assessment,durability modelling,and a multi-criteria decisionsupport framework.The results reveal that geopolymer concrete and FRP reinforcement’s exhibit superior corrosion resistance and environmental benefits,while ECC and steel-CFRP composites offer structural resilience with moderate environmental trade-offs.However,challenges remain in long-term performance validation,standardization,and market integration.The review concludes that a combined approach involving innovative materials,computational tools,and sustainability assessment is essential for advancing marine infrastructure.Outlook recommendations include focused field studies,development of regulatory guidelines,and interdisciplinary collaboration to drive the practical adoption of eco-efficient materials in coastal and offshore construction.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
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
As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking a...As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking at the long-term costs of infrastructure,traditional lifecycle cost models often fail to account for residual value recovery,material circularity,or environmental externalities.This study creates a unified analytical framework that adds CE strategies to lifecycle cost modelling for offshore wind systems,such as turbines,substructures,moorings,and floating platforms.The method uses multi-objective optimization and system dynamics simulation along with net present value(NPV)modelling,material flow analysis,and carbonadjusted cost accounting.We modelled project-level datasets over 25 years to look at the trade-offs between economic and environmental factors in both linear and circular lifecycle scenarios.We use Python,MATLAB,and OpenLCA to look at key metrics like the Material Circularity Indicator(MCI),estimates of residual value,and internalized carbon costs.The results show that circular infrastructure strategies greatly lower lifecycle costs while also increasing material recovery and carbon efficiency.Scenario simulations showed that CE-based configurations could cut costs by up to 18%and emissions over the life of the product by 22%.Regression and sensitivity analyses showed that MCI,CAPEX,and circular design strategies are good at predicting residual value and long-term economic performance.This study adds a new,evidence-based model for making decisions about infrastructure that takes into account financial,environmental,and material circularity.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
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
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
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
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
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
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This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.While focused on representative nanoparticles(nano-TiO₂,nano-Fe₃O₄,and carbon nanotubes)and select energy pollutants,experimental data showed these materials greatly enhanced the movement of pollutants,increasing migration distances from 1.6 to 2.9 times.The carbon nanotubes possessed the greatest carrying effect,increasing the phenanthrene migration distance by 286 percent.The study determined surface properties of nanoparticles,pH of the liquid environment,ionic concentration,and organic matter level as major elements impacting pollutant mobility.Laboratory simulations,while controlled and reproducible,necessarily simplified the complex dynamics of real marine environments.Nanoparticle-sorbate systems were found to be effective in enhancing the deterioration rate of materials used in offshore constructions,with CNTPAHs composites causing carbon steel to corrode by 183% more than if PAHs were used without the composites.This change in corrosion behaviour was shown in other tests to be caused by a change in dynamics of the corrosion products'structural constituents and the various electrochemical properties present on the surface of the material.Samples of concrete showed a spend of 90 days in the composite system resulted in a 26.8% decrease in compressive strength compared to control conditions which had only a 15.3%.Therefore,taking into account the results,strategies were formulated to ensure durability for offshore infrastructure including surface modified anticorrosion coatings,surveillance and alert systems,and integrated protective systems.Future field validation studies are needed to verify these laboratory findings under actual marine conditions.This study helps to comprehend the behaviour of nanoparticles in intricate marine ecosystems,providing support for the sustainable advancement of offshore infrastructure and the protection of the marine environment.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
文摘This research work aims at modelling a framework for Private Cloud infrastructure Deployment for Information and Communication Technology Centres (ICTs) in tertiary institutions in Nigeria. Recent researches have indicated that cloud computing will become the mainstream in computing technology and very effective for businesses. All Tertiary Institutions have ICT units, and are generally charged with the responsibilities of deploying ICT infrastructure and services for administration, teaching, research and learning in higher institution at large. The Structured System Analysis and Design Methodology (SSADM) is used in this research and a six-step framework for a cost effective and scalable Private cloud infrastructure using server virtualization is presented as an alternative that can guarantee total and independent control of data flow in the institutions, while ensuring adequate security of vital information.
文摘Pervasive low levels of education and weak civil society activism in poor rural communities are cited as constraining factors for participatory development (PD), resulting in technical capacity for participation being skewed against the community participants. This paper highlights the outcomes of a research study that examined the applicability of the participatory development concept in conditions characterised by low levels of education and weak civil society. The research was undertaken in two rural villages in the Eastern Cape Province of South Africa, utilising both quantitative and qualitative approaches entailing interviews with 18 key informants followed by two focus group discussions each with seven participants respectively. The research found that rural communities were not aware of the government policy placing people participation at the centre of rural development interventions;and that they would not support it as they believed it was government's role to champion their development. The research also found that the government officials that lead the implementation effort of the rural development programmes did not believe that the participation policy was practical, citing capacity limitations among rural communities. The researcher recommends a moderated rural people participation process, which features creation of a facilitative institutional infrastructure to optimise productive participation of rural people in local development processes.
文摘No Projects Coopera- Total Invest- Investment Chinese Partners tion Mode ment Predicted Proportion KF3-01 Sewage Treatment Plant J.V. US$30 million Chinese 30% Beijing Economic with land as & Technological investment, 70% Development Zone for foreign partner SZ3-02 Beijing freight transport J.V. US$85 million Through Beijing Traffic Bureau hub of southwest highway negotiation SZ3-03 Beijing southeast international J.V. US$40 million 50% for each ditto container
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.
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.
文摘Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically investigates recent advancements in sustainable alternatives,including geopolymer concrete,engineered innovacementitious composites(ECC),bio-concrete,fiber-reinforced polymers(FRPs),and bamboo,stainless steel,and steel-CFRP hybrid bars.Each material is evaluated based on marine durability,mechanical performance,environmental impact,and cost feasibility using life cycle assessment,durability modelling,and a multi-criteria decisionsupport framework.The results reveal that geopolymer concrete and FRP reinforcement’s exhibit superior corrosion resistance and environmental benefits,while ECC and steel-CFRP composites offer structural resilience with moderate environmental trade-offs.However,challenges remain in long-term performance validation,standardization,and market integration.The review concludes that a combined approach involving innovative materials,computational tools,and sustainability assessment is essential for advancing marine infrastructure.Outlook recommendations include focused field studies,development of regulatory guidelines,and interdisciplinary collaboration to drive the practical adoption of eco-efficient materials in coastal and offshore construction.
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As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking at the long-term costs of infrastructure,traditional lifecycle cost models often fail to account for residual value recovery,material circularity,or environmental externalities.This study creates a unified analytical framework that adds CE strategies to lifecycle cost modelling for offshore wind systems,such as turbines,substructures,moorings,and floating platforms.The method uses multi-objective optimization and system dynamics simulation along with net present value(NPV)modelling,material flow analysis,and carbonadjusted cost accounting.We modelled project-level datasets over 25 years to look at the trade-offs between economic and environmental factors in both linear and circular lifecycle scenarios.We use Python,MATLAB,and OpenLCA to look at key metrics like the Material Circularity Indicator(MCI),estimates of residual value,and internalized carbon costs.The results show that circular infrastructure strategies greatly lower lifecycle costs while also increasing material recovery and carbon efficiency.Scenario simulations showed that CE-based configurations could cut costs by up to 18%and emissions over the life of the product by 22%.Regression and sensitivity analyses showed that MCI,CAPEX,and circular design strategies are good at predicting residual value and long-term economic performance.This study adds a new,evidence-based model for making decisions about infrastructure that takes into account financial,environmental,and material circularity.
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.
