Risk assessment and mitigation programs have been carried out over the last decades in the attempt to reduce transportation infrastructure downtime and post-disaster recovery costs.Recently,the concept of resilience g...Risk assessment and mitigation programs have been carried out over the last decades in the attempt to reduce transportation infrastructure downtime and post-disaster recovery costs.Recently,the concept of resilience gained increasing importance in design,assessment,maintenance,and rehabilitation structures and infrastructure systems,particularly bridges and transportation networks,exposed to natural and man-made hazards.In the field of disaster mitigation,frameworks have been proposed to provide a basis for development of qualitative and quantitative models quantifying the functionality and resilience at various scales,including components,groups and systems within infrastructure networks and communities.In these frameworks,the effects of aging and environmental aggressiveness must be explicitly considered,affecting the structural performance and functionality of civil infrastructure systems.Significant efforts have been made to incorporate risk and resilience assessment frameworks into informed decision making to decide how to best use resources to minimize the impact of hazards on civil infrastructure systems.This review paper is part of these efforts.It presents an overview of the main principles and concepts,methods and strategies,advances and accomplishments in the field of life-cycle reliability,risk and resilience of structures and infrastructure systems,with emphasis on seismic resilience of bridges and road networks.展开更多
With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and powe...With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and power distribution systems.Supporting these applications,an important family of methods are based on graphs.For DT applications in modeling and managing smart cities,large-scale knowledge graphs(KGs)are necessary to represent the complex interdependencies and model the urban infrastructure as a system of systems.To this end,this paper develops a conceptual framework:Automated knowledge Graphs for Complex Systems(AutoGraCS).In contrast to existing KGs developed for DTs,AutoGraCS can support KGs to account for interdependencies and statistical correlations across complex systems.The established KGs from AutoGraCS can then be easily turned into Bayesian networks for probabilistic modeling,Bayesian analysis,and adaptive decision supports.Besides,AutoGraCS provides flexibility in support of users’need to implement the ontology and rules when constructing the KG.With the user-defined ontology and rules,AutoGraCS can automatically generate a KG to represent a complex system consisting of multiple systems.The bridge network in Miami-Dade County,FL is used as an illustrative example to generate a KG that integrates multiple layers of data from the bridge network,traffic monitoring facilities,and flood water watch stations.展开更多
The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience modeling.These data enable and inform mitigation and recovery planning decisions prior to...The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience modeling.These data enable and inform mitigation and recovery planning decisions prior to and following damaging events such as earthquakes.This paper presents a multi-disciplinary seismic resilience mod-eling methodology to assess the vulnerability of the built environment and economic systems.This methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of com-munities.Two complementary modeling strategies are designed to examine the impacts of scenario earthquakes from a combined engineering and economic perspective.The engineering model is developed using a probabilis-tic fragility-based modeling approach and is analyzed using Monte Carlo(MC)simulations subject to seismic multi-hazard,including simulated ground shaking and resulting liquefaction of the soil,to quantify the physical damage to buildings and electric power substations(EPS).The outcome of the analysis is subsequently used as input to repair and recovery models to quantify repair cost and recovery time metrics for buildings and as input to functionality models to estimate the functionality of individual buildings and substations by accounting for their interdependency.The economic model consists of a spatial computable general equilibrium(SCGE)model that aggregates commercial buildings into sectors for retail,manufacturing,services,etc.,and aggregates residential buildings into a wide range of household groups.The SCGE model employs building functionality estimates to quantify the economic losses.The outcomes of this integrated modeling consist of engineering and economic impact metrics,which are used to investigate mitigation actions to help inform a community on approaches to achieve its resilience goals.An illustrative case study of Salt Lake County(SLC),Utah,developed through an extensive collaborative partnership and engagement with SLC officials,is presented.The results demonstrate the effectiveness of the proposed methodology in quantifying the loss and functional recovery of infrastructure systems,the impacts on capital stock,employment,and household income and the effect of various mitigation strategies in reducing the losses and functional recovery time subject to earthquakes with varying intensities.展开更多
Identity management has been ripe for disruption over the past few years due to recurring incidents of data breaches that have led to personal information leaks and identity theft.The rise of blockchain technology has...Identity management has been ripe for disruption over the past few years due to recurring incidents of data breaches that have led to personal information leaks and identity theft.The rise of blockchain technology has paved the way for the development of self-sovereign identity(SSI)—a new class of user-controlled resilient identity management systems that are enabled by distributed ledger technology.This paper examines how SSI management can be used in a public transportation sector that spans different operators in multiple countries.Specifically,the paper explores how a blockchain-based decentralized identity management system can draw on the SSI framework to provide high-level security and transparency for all involved parties in public transportation ecosystems.Accordingly,building on analyses of the existing public transportation ticketing solutions,we elicited requirements of a comparable system based on the SSI principles.Next,we developed a low-fidelity prototype to showcase how passengers can utilize standardized travel credentials that are valid across different transportation networks in Europe.The proposed system eliminates the need for multiple travel cards(i.e.,one for each transportation provider)and empowers individuals to have better control over the use of their identities while they utilize interoperable ticketing systems across Europe.Overall,building on the public transportation case,we offer a proof-of-concept that shows how individuals can better manage their identity credentials via the SSI framework.展开更多
Municipal wastewater consists of a downstream collection of flushed sewage(without solid waste),other household runoffs,industrial runoffs,hospital runoffs and agricultural runoffs through an underground pipe before t...Municipal wastewater consists of a downstream collection of flushed sewage(without solid waste),other household runoffs,industrial runoffs,hospital runoffs and agricultural runoffs through an underground pipe before treatment.A runoff collection system called the wastewater treatment plant(WWTPs)treats such wastewater before release into environment following specific regulatory standards.This years-long practice has been improved upon by adding end-to-end pipe technologies with a view to enhancing the quality of effluent released.However,effluents released into the environment from design/application of WWTPs appear to contain emerging contaminants of both biotic and abiotic nature.The observation of chemical contaminants,antibiotic resistant bacteria(ARB),antibiotic resistant genes(ARGs)and diverse pathogenic bacteria genera in wastewater works release further affirm the abundance of such emerging contaminants.As a result,the government and water regulatory organizations in various part of the world are considering the removal of water reuse act from recycling policy/process.Current global debate is focused on questions about sustenance of any improved additional treatment level;effect of energy consumption by added treatment stage and its impact on the environmental wellness as contaminants borne wastewater is consistently released.Technological advancement/research suggests implementation of newer innovative infrastructural systems(NIIS)such as Mobbing Bed Biofilm Rector(MBBR),for wastewater effluent management which involve addition of newer wastewater treatment stages.This review addressed current pitfalls including wastewater microbiota of high epidemiological/public health relevance and affirms the need for such improvement which requires modification of ongoing institutional framework with a view to encourage implementation of NIIS for an improved effluent release.Exploiting the advances of microbial biofilming and the potentials of microbial biofueling as discussed in various section promises a future of robust environmental system,stable operational standard,release of quality effluent and sustainable management of wastewater works.Application of the aforementioned would enhance qualityWWTPs release and in-defacto reduces spread of ARB/ARGs as well as impacts both the environment wellness and public health.展开更多
文摘Risk assessment and mitigation programs have been carried out over the last decades in the attempt to reduce transportation infrastructure downtime and post-disaster recovery costs.Recently,the concept of resilience gained increasing importance in design,assessment,maintenance,and rehabilitation structures and infrastructure systems,particularly bridges and transportation networks,exposed to natural and man-made hazards.In the field of disaster mitigation,frameworks have been proposed to provide a basis for development of qualitative and quantitative models quantifying the functionality and resilience at various scales,including components,groups and systems within infrastructure networks and communities.In these frameworks,the effects of aging and environmental aggressiveness must be explicitly considered,affecting the structural performance and functionality of civil infrastructure systems.Significant efforts have been made to incorporate risk and resilience assessment frameworks into informed decision making to decide how to best use resources to minimize the impact of hazards on civil infrastructure systems.This review paper is part of these efforts.It presents an overview of the main principles and concepts,methods and strategies,advances and accomplishments in the field of life-cycle reliability,risk and resilience of structures and infrastructure systems,with emphasis on seismic resilience of bridges and road networks.
基金support received from US Department of Transportation Tier 1 University Transportation Center CREATE Award No.69A3552348330.
文摘With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and power distribution systems.Supporting these applications,an important family of methods are based on graphs.For DT applications in modeling and managing smart cities,large-scale knowledge graphs(KGs)are necessary to represent the complex interdependencies and model the urban infrastructure as a system of systems.To this end,this paper develops a conceptual framework:Automated knowledge Graphs for Complex Systems(AutoGraCS).In contrast to existing KGs developed for DTs,AutoGraCS can support KGs to account for interdependencies and statistical correlations across complex systems.The established KGs from AutoGraCS can then be easily turned into Bayesian networks for probabilistic modeling,Bayesian analysis,and adaptive decision supports.Besides,AutoGraCS provides flexibility in support of users’need to implement the ontology and rules when constructing the KG.With the user-defined ontology and rules,AutoGraCS can automatically generate a KG to represent a complex system consisting of multiple systems.The bridge network in Miami-Dade County,FL is used as an illustrative example to generate a KG that integrates multiple layers of data from the bridge network,traffic monitoring facilities,and flood water watch stations.
基金funded through a cooperative agreement between the U.S.National Institute of Standards and Technology and Colorado State University(NIST Financial Assistance Award Numbers:70NANB15H044 and 70NANB20H008).
文摘The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience modeling.These data enable and inform mitigation and recovery planning decisions prior to and following damaging events such as earthquakes.This paper presents a multi-disciplinary seismic resilience mod-eling methodology to assess the vulnerability of the built environment and economic systems.This methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of com-munities.Two complementary modeling strategies are designed to examine the impacts of scenario earthquakes from a combined engineering and economic perspective.The engineering model is developed using a probabilis-tic fragility-based modeling approach and is analyzed using Monte Carlo(MC)simulations subject to seismic multi-hazard,including simulated ground shaking and resulting liquefaction of the soil,to quantify the physical damage to buildings and electric power substations(EPS).The outcome of the analysis is subsequently used as input to repair and recovery models to quantify repair cost and recovery time metrics for buildings and as input to functionality models to estimate the functionality of individual buildings and substations by accounting for their interdependency.The economic model consists of a spatial computable general equilibrium(SCGE)model that aggregates commercial buildings into sectors for retail,manufacturing,services,etc.,and aggregates residential buildings into a wide range of household groups.The SCGE model employs building functionality estimates to quantify the economic losses.The outcomes of this integrated modeling consist of engineering and economic impact metrics,which are used to investigate mitigation actions to help inform a community on approaches to achieve its resilience goals.An illustrative case study of Salt Lake County(SLC),Utah,developed through an extensive collaborative partnership and engagement with SLC officials,is presented.The results demonstrate the effectiveness of the proposed methodology in quantifying the loss and functional recovery of infrastructure systems,the impacts on capital stock,employment,and household income and the effect of various mitigation strategies in reducing the losses and functional recovery time subject to earthquakes with varying intensities.
文摘Identity management has been ripe for disruption over the past few years due to recurring incidents of data breaches that have led to personal information leaks and identity theft.The rise of blockchain technology has paved the way for the development of self-sovereign identity(SSI)—a new class of user-controlled resilient identity management systems that are enabled by distributed ledger technology.This paper examines how SSI management can be used in a public transportation sector that spans different operators in multiple countries.Specifically,the paper explores how a blockchain-based decentralized identity management system can draw on the SSI framework to provide high-level security and transparency for all involved parties in public transportation ecosystems.Accordingly,building on analyses of the existing public transportation ticketing solutions,we elicited requirements of a comparable system based on the SSI principles.Next,we developed a low-fidelity prototype to showcase how passengers can utilize standardized travel credentials that are valid across different transportation networks in Europe.The proposed system eliminates the need for multiple travel cards(i.e.,one for each transportation provider)and empowers individuals to have better control over the use of their identities while they utilize interoperable ticketing systems across Europe.Overall,building on the public transportation case,we offer a proof-of-concept that shows how individuals can better manage their identity credentials via the SSI framework.
文摘Municipal wastewater consists of a downstream collection of flushed sewage(without solid waste),other household runoffs,industrial runoffs,hospital runoffs and agricultural runoffs through an underground pipe before treatment.A runoff collection system called the wastewater treatment plant(WWTPs)treats such wastewater before release into environment following specific regulatory standards.This years-long practice has been improved upon by adding end-to-end pipe technologies with a view to enhancing the quality of effluent released.However,effluents released into the environment from design/application of WWTPs appear to contain emerging contaminants of both biotic and abiotic nature.The observation of chemical contaminants,antibiotic resistant bacteria(ARB),antibiotic resistant genes(ARGs)and diverse pathogenic bacteria genera in wastewater works release further affirm the abundance of such emerging contaminants.As a result,the government and water regulatory organizations in various part of the world are considering the removal of water reuse act from recycling policy/process.Current global debate is focused on questions about sustenance of any improved additional treatment level;effect of energy consumption by added treatment stage and its impact on the environmental wellness as contaminants borne wastewater is consistently released.Technological advancement/research suggests implementation of newer innovative infrastructural systems(NIIS)such as Mobbing Bed Biofilm Rector(MBBR),for wastewater effluent management which involve addition of newer wastewater treatment stages.This review addressed current pitfalls including wastewater microbiota of high epidemiological/public health relevance and affirms the need for such improvement which requires modification of ongoing institutional framework with a view to encourage implementation of NIIS for an improved effluent release.Exploiting the advances of microbial biofilming and the potentials of microbial biofueling as discussed in various section promises a future of robust environmental system,stable operational standard,release of quality effluent and sustainable management of wastewater works.Application of the aforementioned would enhance qualityWWTPs release and in-defacto reduces spread of ARB/ARGs as well as impacts both the environment wellness and public health.
