A systematic review of prediction methods for emergency management

Huang, Di; Wang, Shuaian; Liu, Zhiyuan

doi:10.1016/j.ijdrr.2021.102412

Cited by 71 publications

(22 citation statements)

References 163 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To evaluate the safety of building ruins, seismic rescue experts in China usually refer to "Dangerous Building Appraisal Standards" (JGJ125-99 2004) [20] and "Earthquake Site Work Part II: Building Safety Appraisal" (GB18208.2 2001) [21]. Additionally, a systematic review of prediction methods for emergency management and seismic vulnerability assessment methodologies were published [22,23]. However, the above standards only divide the damage level of collapsed buildings, but the impact factors of the construction of life-saving passages in building ruins are not considered, for example, the infuence of aftershocks on the safety of the life-saving passages.…”

Section: Introductionmentioning

confidence: 99%

Study on the Safety Evaluation Method of Life-Saving Passage in Building Ruins under the Action of Aftershock

Chen

Yang

et al. 2023

Shock and Vibration

View full text Add to dashboard Cite

It is essential to evaluate the safety of the life-saving passage in building ruins and to ensure the “double safety” of rescuers and trapped people during the earthquake rescue; however, there are few studies on the safety evaluation method of life-saving passage. In this paper, the vertical displacement of wood shoring is proposed as an evaluation indicator of the saving-life passage considering the characteristics of building ruins and the size of the living space of the trapped. Taking life-saving passage of the pancake-type building ruins as research object, the evaluation of the safety of the life-saving passage was investigated under the action of aftershock. The vertical bearing capacity test of wood shoring is performed in order to obtain the evaluation indicator of saving-life passage. The restart function of ANSYS/LS-DYNA program is used to re-edit the numerical model of the building ruins to construct the life-saving passage, then, the safety evaluation of life-saving passage of the pancake-type building ruins is investigated under the action of aftershock. The results show that the constructed life-saving passage passed the safety evaluation under the actions of different aftershocks. The possibility of the secondary collapse of the life-saving passage increases exponentially with the increase of rescue time within “72-hour gold rescue,” and the growth is slow after 72 hours when the magnitude of the main earthquake reaches above 7.4; the safety factor K should be increased appropriately if wood shoring is used to construct a life-saving passage when the main earthquake’s magnitude is greater than or equal to 7.5. The safety evaluation method of life-saving passage can provide effective reference for earthquake rescue.

show abstract

Section: Introductionmentioning

confidence: 99%

Study on the Safety Evaluation Method of Life-Saving Passage in Building Ruins under the Action of Aftershock

Chen

Yang

et al. 2023

Shock and Vibration

View full text Add to dashboard Cite

show abstract

“…However, it is still a challenge to determine the extent of the damage and the possible affected assets and populations, if solely utilize the hydrodynamic model. Therefore, with the emerging of geospatial technology, efforts on combining hydrodynamic model with 3S technology (remote sensing, GIS and global positioning system (GPS) have been applied for efficient development and analysis of dam break studies [7]. The availability of open source software and data has offer an advantage of obtaining various data sources for crisis and disaster mapping.…”

Section: Introductionmentioning

confidence: 99%

Dam Break Flood Mapping and Analysis Using Open Source GIS Tool and Data

Samsudin,

Zuhaily,

Setu

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

The impact of climate change may influence on extreme weather conditions and may lead to high intensity precipitation, which will impact on huge structures such as dam. Although risk mitigation and protection of dams from advanced technical expertise have been reviewed regularly, a maximum non-risk guarantee is not achievable, and incidents may occur due to water that usually flows over a spillway and high-speed discharge or unexpected peak discharge. Hence, the immediate impact of dam failure is on the population at risk near the downstream area. This study evaluates the impact of dam break scenario under probable maximum precipitation (PMF) condition at Puah hydropower dam. The aims of this study are to determine the potential risk area at downstream and to assess the flooding impact on population and public facilities due to dam break event. Integration of an open source GIS tool, Google Satellite Image, Open Street Map, and flood hazard map derived from hydrodynamic model has been used to efficiently analyse the impact of dam break flood by using spatial analysis method, and to generate possible evacuation route network. Analysis has estimated that 187,796 people at risk, 3,177 km of road, 2-unit hospital and 76 amenities (mosque and school) will be impacted. This study portrays the possibility of using open source data and tool as an alternative for emergency preparedness application. The method used in this study could be adopted to other area of interest and disaster event, helping the local authorities for disaster emergency preparedness and early warning systems focusing on rescue work if disaster occurs.

show abstract

“…Emergency response is a field that has been widely studied (Huang et al., 2021 ) classifies emergency response activities into three phases: preevent, in‐event and postevent. Among them, emergency response during events is extremely challenging due to psychological and technical reasons.…”

Section: Introductionmentioning

confidence: 99%

A dynamic Bayesian network‐based emergency decision‐making framework highlighting emergency propagations: Illustrated using the Fukushima nuclear accidents and the Covid‐19 pandemic

Cai

Golay

2022

Risk Analysis

View full text Add to dashboard Cite

When facing public emergencies, human societies need to make decisions rapidly in order to mitigate the problems. However, this process can be difficult due to complexity of the emergency scenarios and lack of systematic methods for analyzing them. In the work reported here, we develop a framework based upon dynamic Bayesian networks in order to simulate emergency scenarios and support corresponding decisions. In this framework, we highlight the importance of emergency propagation, which is a critical factor often ignored by decisionmakers. We illustrate that failure of considering emergency propagation can lead to suboptimal mitigation strategies. By incorporating this critical factor, our framework enables decisionmakers to identify optimal response strategies minimizing emergency impacts. Scenarios developed from two public emergencies: the 2011 Fukushima nuclear power plant accidents and the Covid‐19 pandemic, are utilized to illustrate the framework in this paper. Capabilities of the framework in supporting decision making in both events illustrate its generality and adaptability when dealing with complex real‐world situations. Our analysis results reveal many similarities between these two seemingly distinct events. This indicates that seemingly unrelated emergencies can share many common features beyond their idiosyncratic characteristics. Valuable mitigation insights can be obtained by analyzing a broad range of past emergencies systematically.

show abstract

A systematic review of prediction methods for emergency management

Cited by 71 publications

References 163 publications

Study on the Safety Evaluation Method of Life-Saving Passage in Building Ruins under the Action of Aftershock

Study on the Safety Evaluation Method of Life-Saving Passage in Building Ruins under the Action of Aftershock

Dam Break Flood Mapping and Analysis Using Open Source GIS Tool and Data

A dynamic Bayesian network‐based emergency decision‐making framework highlighting emergency propagations: Illustrated using the Fukushima nuclear accidents and the Covid‐19 pandemic

Contact Info

Product

Resources

About