scholarly journals Seismic Damage Rapid Assessment of Road Networks considering Individual Road Damage State and Reliability of Road Networks in Emergency Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Jinlong Liu ◽  
Hanxi Jia ◽  
Junqi Lin ◽  
Heng Hu
Keyword(s):  
Network Reliability ◽  
Rapid Assessment ◽  
Road Networks ◽  
Seismic Damage ◽  
Damage State ◽  
Adaboost Algorithm ◽  
The Road ◽  
Traffic Capacity ◽  
Emergency Decision Making ◽  
Emergency Decision

Road networks are one of the vital components of a transportation system that influence the traffic capacity and disaster losses after the earthquakes. The road network reliability is crucial for the postearthquake emergency decision-making. In this study, a method is proposed to assess the seismic damage of road networks considering individual road damage state and reliability of road networks in emergency conditions. First, we assess the importance of the factors that affect seismic road damage using the AdaBoost algorithm. In addition, artificial neural networks are used to evaluate the damage state of an individual road based on the factors that are selected with higher importance. Then, the improved estimation for the reliability of road networks is adopted to assess the damage of road networks. Last, the method is demonstrated using the road networks in Karamay, China.

scholarly journals Suitability of Current Assessment Techniques to Retrodict the Seismic Damage of Buildings: A Case Study in Van, Turkey

2015 ◽  
Vol 9 (1) ◽  
pp. 330-343
Author(s):  
Viorel Popa ◽  
Radu Văcăreanu ◽  
Vasile Oprisoreanu ◽  
Emil Albotă ◽  
Dietlinde Köber
Keyword(s):  
Structural Damage ◽  
Local Community ◽  
Structural Characteristics ◽  
Rapid Assessment ◽  
Seismic Damage ◽  
Seismic Assessment ◽  
Damage State ◽  
Building Stock ◽  
Damage Level ◽  
Assessment Techniques

Two strong earthquakes hit the region of Van (Turkey) in 2012, generating major losses. A large part of the building stock was damaged causing the evacuation of the residents. A post-earthquake investigation team dispatched by the UNESCO through the IPRED platform, six month after the earthquakes, observed the damage state in some still standing buildings. Ten buildings having different structural characteristics were observed. Slight structural damage and severe non-structural damage were observed in three multi-storey apartment buildings, being evacuated at the time of the investigation. Despite the slight structural damage, two multi-storey reinforced concrete shear wall buildings were listed for demolition based on the results of the post-earthquake rapid assessment. These two buildings were recently built based on modern seismic design regulations. The design blueprints were available to the investigation team with the support of the local community of Van. Various rapid post-earthquake investigation techniques applied by the investigation team generated contradictory results. A comprehensive seismic assessment was carried out to retrodict the observed seismic damage. Various methods were applied starting from simple rapid assessment techniques to more elaborated structural analysis based on nonlinear dynamic procedure. In the latter case, strength and stiffness degrading hysteretic models were applied and the non-structural masonry walls were considered in the analytical model. This paper presents the results of these structural analyses in comparison with the observed damage on site. Conclusions regarding the suitability of the applied seismic assessment techniques to retrodict the damage level of the investigated structures are drawn. Some findings of the post-earthquake investigation team are presented as well.

scholarly journals Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method

2019 ◽  
Vol 16 (7) ◽  
pp. 1166 ◽  
Author(s):  
Tianpei Tang ◽  
Senlai Zhu ◽  
Yuntao Guo ◽  
Xizhao Zhou ◽  
Yang Cao
Keyword(s):  
Bayesian Network ◽  
Low Cost ◽  
Road Networks ◽  
Access Point ◽  
Safety Risk ◽  
Crash Data ◽  
Risk Levels ◽  
The Road ◽  
Run Off ◽  
Point Density

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts’ judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015–2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

scholarly journals Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tinggui Chen ◽  
Shiwen Wu ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Sudden Onset ◽  
The Road ◽  
Bee Colony ◽  
Proposed Model ◽  
Effectiveness And Efficiency ◽  
In Transit ◽  
Emergency Supply

It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.

scholarly journals Capacity in municipalities: Infrastructures, maintenance debts and ways of overcoming a run-to-failure mentality

2021 ◽  
pp. 026909422110304
Author(s):  
Jens Alm ◽  
Alexander Paulsson ◽  
Robert Jonsson
Keyword(s):  
Economies Of Scale ◽  
Heavy Traffic ◽  
Road Networks ◽  
Large Degree ◽  
Welfare States ◽  
The Road ◽  
Technical Capacity ◽  
Multidimensional Concept ◽  
Sewage Systems ◽  
Road Segments

There is a growing maintenance debt of ageing and critical infrastructures in many municipalities in European welfare states. In this article, we use the multidimensional concept of local capacity as a point of departure to analyse how and in what ways Swedish municipalities work with the routine maintenance of infrastructures, including municipal road networks as well as water and sewage systems. For the road networks, maintenance is generally outsourced to contractors and there is also a large degree of tolerance for various standards on different road segments within and between the municipalities. Less used road segments are not as prioritised as those with heavy traffic. For the water and sewage systems, in-house technical capacity is needed as differences in water quality are not tolerated. Economies of scale mean that in-house capacity is translated into the creation of inter-municipal bodies. As different forms of capacities tend to reinforce each other, municipal capacity builds up over time in circular movements. These results add knowledge to current research by pointing to the ways municipalities are overcoming a run-to-failure mentality by building capacity to pay off the infrastructural maintenance debt.

scholarly journals Design of Optimal Rainfall Monitoring Network Using Radar and Road Networks

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 378
Author(s):  
Taeyong Kwon ◽  
Seongsim Yoon ◽  
Sanghoo Yoon
Keyword(s):  
Road Networks ◽  
Monitoring Network ◽  
Conditional Entropy ◽  
Radar Data ◽  
Disaster Risk ◽  
Water Levels ◽  
The Road ◽  
Dam Operation ◽  
A Site ◽  
High Degree

Uncertainty in the rainfall network can lead to mistakes in dam operation. Sudden increases in dam water levels due to rainfall uncertainty are a high disaster risk. In order to prevent these losses, it is necessary to configure an appropriate rainfall network that can effectively reflect the characteristics of the watershed. In this study, conditional entropy was used to calculate the uncertainty of the watershed using rainfall and radar data observed from 2018 to 2019 in the Goesan Dam and Hwacheon Dam watersheds. The results identified radar data suitable for the characteristics of the watershed and proposed a site for an additional rainfall gauge. It is also necessary to select the location of the additional rainfall gauged by limiting the points where smooth movement and installation, for example crossing national borders, are difficult. The proposed site emphasized accessibility and usability by leveraging road information and selecting a radar grid near the road. As a practice result, the uncertainty of precipitation in the Goesan and Hwacheon Dam watersheds could be decreased by 70.0% and 67.9%, respectively, when four and three additional gauge sites were installed without any restriction. When these were installed near to the road, with five and four additional gauge sites, the uncertainty in the Goesan Dam and Hwacheon Dam watersheds were reduced by up to 71.1%. Therefore, due to the high degree of uncertainty, it is necessary to measure precipitation. The operation of the rainfall gauge can provide a smooth site and configure an appropriate monitoring network.

An improved multi-criteria emergency decision-making method in environmental disasters

2021 ◽  
Author(s):  
Guang-Jun Jiang ◽  
Hong-Xia Chen ◽  
Hong-Hua Sun ◽  
Mohammad Yazdi ◽  
Arman Nedjati ◽  
...  
Keyword(s):  
Decision Making ◽  
Environmental Disasters ◽  
Emergency Decision Making ◽  
Emergency Decision

scholarly journals A Parallel-Computing Approach for Vector Road-Network Matching Using GPU Architecture

2018 ◽  
Vol 7 (12) ◽  
pp. 472 ◽  
Author(s):  
Bo Wan ◽  
Lin Yang ◽  
Shunping Zhou ◽  
Run Wang ◽  
Dezhi Wang ◽  
...  
Keyword(s):  
Road Network ◽  
Large Scale ◽  
Graphics Processing Unit ◽  
Road Networks ◽  
Processing Unit ◽  
Data Partition ◽  
Matching Method ◽  
The Road ◽  
Central Processing ◽  
Relaxation Matching

The road-network matching method is an effective tool for map integration, fusion, and update. Due to the complexity of road networks in the real world, matching methods often contain a series of complicated processes to identify homonymous roads and deal with their intricate relationship. However, traditional road-network matching algorithms, which are mainly central processing unit (CPU)-based approaches, may have performance bottleneck problems when facing big data. We developed a particle-swarm optimization (PSO)-based parallel road-network matching method on graphics-processing unit (GPU). Based on the characteristics of the two main stages (similarity computation and matching-relationship identification), data-partition and task-partition strategies were utilized, respectively, to fully use GPU threads. Experiments were conducted on datasets with 14 different scales. Results indicate that the parallel PSO-based matching algorithm (PSOM) could correctly identify most matching relationships with an average accuracy of 84.44%, which was at the same level as the accuracy of a benchmark—the probability-relaxation-matching (PRM) method. The PSOM approach significantly reduced the road-network matching time in dealing with large amounts of data in comparison with the PRM method. This paper provides a common parallel algorithm framework for road-network matching algorithms and contributes to integration and update of large-scale road-networks.

scholarly journals Road Networks Winter Risk Estimation Using On-Board Uncooled Infrared Camera for Surface Temperature Measurements over Two Lanes

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
M. Marchetti ◽  
M. Moutton ◽  
S. Ludwig ◽  
L. Ibos ◽  
V. Feuillet ◽  
...  
Keyword(s):  
Data Analysis ◽  
Road Network ◽  
Risk Estimation ◽  
Risk Index ◽  
Road Networks ◽  
Infrared Camera ◽  
Atmospheric Parameters ◽  
The Road ◽  
Measurement Rate

Thermal mapping has been implemented since the late eighties to establish the susceptibility of road networks to ice occurrence with measurements from a radiometer and some atmospheric parameters. They are usually done before dawn during wintertime when the road energy is dissipated. The objective of this study was to establish if an infrared camera could improve the determination of ice road susceptibility, to build a new winter risk index, to improve the measurements rate, and to analyze its consistency with seasons and infrastructures environment. Data analysis obtained from the conventional approved radiometer sensing technique and the infrared camera has shown great similarities. A comparison was made with promising perspectives. The measurement rate to analyse a given road network could be increased by a factor two.

scholarly journals An Emergency Decision-Making Method for Urban Rainstorm Water-Logging: A China Study

2018 ◽  
Vol 10 (10) ◽  
pp. 3453 ◽  
Author(s):  
Jiyong Ding ◽  
Juefang Cai ◽  
Guangxiang Guo ◽  
Chen Chen
Keyword(s):  
Decision Making ◽  
Bayesian Analysis ◽  
Emergency Management ◽  
Utility Theory ◽  
Urban Traffic ◽  
Economic Losses ◽  
Water Logging ◽  
Multi Attribute Utility Theory ◽  
Emergency Decision Making ◽  
Emergency Decision

With the rapid development of the urbanization process, rainstorm water-logging events occur more frequently in big cities in China, which causes great impact on urban traffic safety and brings about severe economic losses. Water-logging has become a hot issue of widespread concern in China. As one kind of natural disasters and emergencies, rainstorm water-logging has the uncertainties of occurrence, development, and evolution. Thus, the emergency decision-making in rainstorm water-logging should be carried out in stages according to its development trend, which is very complicated. In this paper, an emergency decision-making method was proposed for urban water-logging with a hybrid use of dynamic network game technology, Bayesian analysis, and multi-attribute utility theory. The dynamic game process between “rainstorm water-logging” and “decision-making group” was established and the dynamic generation of emergency schemes was analyzed based on Bayesian analysis in various stages of water-logging. In terms of decision-making attributes, this paper mainly considered two goals, i.e., ensuring smooth traffic and controlling emergency cost. The multi-attribute utility theory was used to select the final scheme. An example analysis in Guangzhou of China showed that the method is more targeted and can achieve emergency management objectives more effectively when compared with traditional methods. Therefore, it can provide reference for the scientific decision-making of emergency management in urban rainstorm water-logging.

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