A probabilistic seismic loss assessment of RC high-rise(RCHR)buildings designed according to Eurocode 8 and located in the Southern Euro-Mediterranean zone is presented herein.The loss assessment methodology is based ...A probabilistic seismic loss assessment of RC high-rise(RCHR)buildings designed according to Eurocode 8 and located in the Southern Euro-Mediterranean zone is presented herein.The loss assessment methodology is based on a comprehensive simulation approach which takes into account ground motion(GM)uncertainty,and the random effects in seismic demand,as well as in predicting the damage states(DSs).The methodology is implemented on three RCHR buildings of 20-story,30-story and 40-story with a core wall structural system.The loss functions described by a cumulative lognormal probability distribution are obtained for two intensity levels for a large set of simulations(NLTHAs)based on 60 GM records with a wide range of magnitude(M),distance to source(R)and different site soil conditions(SS).The losses expressed in percent of building replacement cost for RCHR buildings are obtained.In the estimation of losses,both structural(S)and nonstructural(NS)damage for four DSs are considered.The effect of different GM characteristics(M,R and SS)on the obtained losses are investigated.Finally,the estimated performance of the RCHR buildings are checked to ensure that they fulfill limit state requirements according to Eurocode 8.展开更多
Stratospheric airships are long-endurance aerostats and have broad applications.All of the energy required for their operation is obtained from solar radiation,which makes accurate calculation of the energy output fro...Stratospheric airships are long-endurance aerostats and have broad applications.All of the energy required for their operation is obtained from solar radiation,which makes accurate calculation of the energy output from the solar array crucial to the design and flight planning of the airships.However,the status of each photovoltaic module in the solar array may differ due to the airship curvature,resulting in mismatch losses and lowered output power,which has not been widely studied.In this paper,an irradiation model and a thermal model are established based on the actual arrangement of the modules.The output power model is established considering the non-uniform radiation in the array.The mismatch losses of the array are analyzed under different flight conditions.The output power of the solar array is decreased by up to 31.6%compared to the ideal state.Moreover,the proportion of mismatch losses increases with latitude,but the maximum mismatch loss power occurs at mid-latitudes.Then,an array reconfiguration method is proposed based on the irradiance dispersion index and position dispersion index.The reconfigured array increases output power by 11.5%and can maintain energy balance in continuous flight.The results can be used to correct the overestimation of the output power during the airship design or to guide the configuration of the solar array.展开更多
Damage detection is a key procedure in maintenance throughout structures′life cycles and post-disaster loss assessment.Due to the complex types of structural damages and the low efficiency and safety of manual detect...Damage detection is a key procedure in maintenance throughout structures′life cycles and post-disaster loss assessment.Due to the complex types of structural damages and the low efficiency and safety of manual detection,detecting damages with high efficiency and accuracy is the most popular research direction in civil engineering.Computer vision(CV)technology and deep learning(DL)algorithms are considered as promising tools to address the aforementioned challenges.The paper aims to systematically summarized the research and applications of DL-based CV technology in the field of damage detection in recent years.The basic concepts of DL-based CV technology are introduced first.The implementation steps of creating a damage detection dataset and some typical datasets are reviewed.CV-based structural damage detection algorithms are divided into three categories,namely,image classification-based(IC-based)algorithms,object detection-based(OD-based)algorithms,and semantic segmentation-based(SS-based)algorithms.Finally,the problems to be solved and future research directions are discussed.The foundation for promoting the deep integration of DL-based CV technology in structural damage detection and structural seismic damage identification has been laid.展开更多
Estimation of economic loss is essential for stakeholders to manage flood risk.Most flooding events are closely related to extreme precipitation,which is influenced by large-scale climate factors.Considering the lagge...Estimation of economic loss is essential for stakeholders to manage flood risk.Most flooding events are closely related to extreme precipitation,which is influenced by large-scale climate factors.Considering the lagged influence of climate factors,we developed a flood-risk assessment framework and used Hunan Province in China as an example to illustrate the risk assessment process.The main patterns of precipitation—as a connection between climate factors and flood economic losses—were extracted by the empirical orthogonal function(EOF)analysis.We identified the correlative climate factors through crosscorrelation analysis and established a multiple stepwise linear regression model to forecast future precipitation patterns.Risk assessment was done based on the main precipitation patterns.Because the economic dataset is limited,a Monte Carlo simulation was applied to simulate 1000-year flood loss events under each precipitation regime(rainy,dry,normal years)to obtain aggregate exceedance probability(AEP)and occurrence exceedance probability(OEP)curves.We found that precipitation has a strong influence on economic loss risk,with the highest risk in rainy years.Regional economic development imbalances are the potential reason for the varying economic loss risks in different regions of Hunan Province.As the climate indices with at least several months prediction lead time are strong indicators in predicting precipitation,the framework we developed can estimate economic loss risk several months in advance.展开更多
Restoring lifeline services to an urban neighborhood impacted by a large disaster is critical to the recovery of the city as a whole.Since cities are comprised of many dependent lifeline systems,the pattern of the res...Restoring lifeline services to an urban neighborhood impacted by a large disaster is critical to the recovery of the city as a whole.Since cities are comprised of many dependent lifeline systems,the pattern of the restoration of each lifeline system can have an impact on one or more others.Due to the often uncertain and complex interactions between dense lifeline systems and their individual operations at the urban scale,it is typically unclear how different patterns of restoration will impact the overall recovery of lifeline system functioning.A difficulty in addressing this problem is the siloed nature of the knowledge and operations of different types of lifelines.Here,a city-wide,multi-lifeline restoration model and simulation are provided to address this issue.The approach uses the Graph Model for Operational Resilience,a data-driven discrete event simulator that can model the spatial and functional cascade of hazard effects and the pattern of restoration over time.A novel case study model of the District of North Vancouver is constructed and simulated for a reference magnitude 7.3 earthquake.The model comprises municipal water and wastewater,power distribution,and transport systems.The model includes 1725 entities from within these sectors,connected through 6456 dependency relationships.Simulation of the model shows that water distribution and wastewater treatment systems recover more quickly and with less uncertainty than electric power and road networks.Understanding this uncertainty will provide the opportunity to improve data collection,modeling,and collaboration with stakeholders in the future.展开更多
文摘A probabilistic seismic loss assessment of RC high-rise(RCHR)buildings designed according to Eurocode 8 and located in the Southern Euro-Mediterranean zone is presented herein.The loss assessment methodology is based on a comprehensive simulation approach which takes into account ground motion(GM)uncertainty,and the random effects in seismic demand,as well as in predicting the damage states(DSs).The methodology is implemented on three RCHR buildings of 20-story,30-story and 40-story with a core wall structural system.The loss functions described by a cumulative lognormal probability distribution are obtained for two intensity levels for a large set of simulations(NLTHAs)based on 60 GM records with a wide range of magnitude(M),distance to source(R)and different site soil conditions(SS).The losses expressed in percent of building replacement cost for RCHR buildings are obtained.In the estimation of losses,both structural(S)and nonstructural(NS)damage for four DSs are considered.The effect of different GM characteristics(M,R and SS)on the obtained losses are investigated.Finally,the estimated performance of the RCHR buildings are checked to ensure that they fulfill limit state requirements according to Eurocode 8.
基金supported by the National Natural Science Foundation of China(No.51775021)the Fundamental Research Funds for the Central Universities,China(Nos.YWF-23-JC-02,YWF-23-JC-09)。
文摘Stratospheric airships are long-endurance aerostats and have broad applications.All of the energy required for their operation is obtained from solar radiation,which makes accurate calculation of the energy output from the solar array crucial to the design and flight planning of the airships.However,the status of each photovoltaic module in the solar array may differ due to the airship curvature,resulting in mismatch losses and lowered output power,which has not been widely studied.In this paper,an irradiation model and a thermal model are established based on the actual arrangement of the modules.The output power model is established considering the non-uniform radiation in the array.The mismatch losses of the array are analyzed under different flight conditions.The output power of the solar array is decreased by up to 31.6%compared to the ideal state.Moreover,the proportion of mismatch losses increases with latitude,but the maximum mismatch loss power occurs at mid-latitudes.Then,an array reconfiguration method is proposed based on the irradiance dispersion index and position dispersion index.The reconfigured array increases output power by 11.5%and can maintain energy balance in continuous flight.The results can be used to correct the overestimation of the output power during the airship design or to guide the configuration of the solar array.
基金National Key R&D Program of China under Grant No.2017YFC1500606,National Natural Science Foundation of China under Grant No.52020105002Heilongjiang Touyan Innovation Team Program。
文摘Damage detection is a key procedure in maintenance throughout structures′life cycles and post-disaster loss assessment.Due to the complex types of structural damages and the low efficiency and safety of manual detection,detecting damages with high efficiency and accuracy is the most popular research direction in civil engineering.Computer vision(CV)technology and deep learning(DL)algorithms are considered as promising tools to address the aforementioned challenges.The paper aims to systematically summarized the research and applications of DL-based CV technology in the field of damage detection in recent years.The basic concepts of DL-based CV technology are introduced first.The implementation steps of creating a damage detection dataset and some typical datasets are reviewed.CV-based structural damage detection algorithms are divided into three categories,namely,image classification-based(IC-based)algorithms,object detection-based(OD-based)algorithms,and semantic segmentation-based(SS-based)algorithms.Finally,the problems to be solved and future research directions are discussed.The foundation for promoting the deep integration of DL-based CV technology in structural damage detection and structural seismic damage identification has been laid.
基金supported by the National Natural Science Foundation of China(grant No.41671503)。
文摘Estimation of economic loss is essential for stakeholders to manage flood risk.Most flooding events are closely related to extreme precipitation,which is influenced by large-scale climate factors.Considering the lagged influence of climate factors,we developed a flood-risk assessment framework and used Hunan Province in China as an example to illustrate the risk assessment process.The main patterns of precipitation—as a connection between climate factors and flood economic losses—were extracted by the empirical orthogonal function(EOF)analysis.We identified the correlative climate factors through crosscorrelation analysis and established a multiple stepwise linear regression model to forecast future precipitation patterns.Risk assessment was done based on the main precipitation patterns.Because the economic dataset is limited,a Monte Carlo simulation was applied to simulate 1000-year flood loss events under each precipitation regime(rainy,dry,normal years)to obtain aggregate exceedance probability(AEP)and occurrence exceedance probability(OEP)curves.We found that precipitation has a strong influence on economic loss risk,with the highest risk in rainy years.Regional economic development imbalances are the potential reason for the varying economic loss risks in different regions of Hunan Province.As the climate indices with at least several months prediction lead time are strong indicators in predicting precipitation,the framework we developed can estimate economic loss risk several months in advance.
文摘Restoring lifeline services to an urban neighborhood impacted by a large disaster is critical to the recovery of the city as a whole.Since cities are comprised of many dependent lifeline systems,the pattern of the restoration of each lifeline system can have an impact on one or more others.Due to the often uncertain and complex interactions between dense lifeline systems and their individual operations at the urban scale,it is typically unclear how different patterns of restoration will impact the overall recovery of lifeline system functioning.A difficulty in addressing this problem is the siloed nature of the knowledge and operations of different types of lifelines.Here,a city-wide,multi-lifeline restoration model and simulation are provided to address this issue.The approach uses the Graph Model for Operational Resilience,a data-driven discrete event simulator that can model the spatial and functional cascade of hazard effects and the pattern of restoration over time.A novel case study model of the District of North Vancouver is constructed and simulated for a reference magnitude 7.3 earthquake.The model comprises municipal water and wastewater,power distribution,and transport systems.The model includes 1725 entities from within these sectors,connected through 6456 dependency relationships.Simulation of the model shows that water distribution and wastewater treatment systems recover more quickly and with less uncertainty than electric power and road networks.Understanding this uncertainty will provide the opportunity to improve data collection,modeling,and collaboration with stakeholders in the future.
