Hammer Energy Measurement of Standard Penetration Test in China

Chen, Longwei; Guo, Tingting; Chen, Tong; Liu, Gan; Wang, Yunlong

doi:10.1007/978-3-031-11898-2_168

Cited by 1 publication

(2 citation statements)

References 7 publications

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“…Compared with previous multi-hazard risk assessment studies [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44], our perspective of annual expected direct loss attempts to avoid the disadvantage of being unable to consider the differences in frequency and consequences of disasters when evaluating different disasters one region at the same time. Relative to traditional disaster risk assessment models [27,28] and frameworks [45][46][47][48], our approaches are more adaptive for urban planning purposes with spatial characteristics of facilities.…”

Section: Discussionmentioning

confidence: 99%

“…The research methods of quantitative ex ante disaster risk and loss assessment are mainly based on the induction of historical empirical data and computer numerical simulation. They tend to rely on the application of various types of software, such as the working platforms of ArcGIS, for spatial analysis and visualisation process in the HAZUS [45,46], PAGER [47], and HAZ-China [48] systems, etc. Although disaster casualties are inevitable, few models put loss of human life and economic loss on the same level of disaster risk assessment.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Multi-Hazard Risk Assessment Framework for Urban Disaster Prevention Planning: A Case Study of Xiamen, China

Zhou,

Zhai

2023

Land

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Understanding and measuring the relative risk level of a city facing multi-hazards is fundamental to improving its disaster prevention planning and schemes. A comprehensive risk evaluation approach stands at the intersection of risk management and disaster system theory. It is also an important interdisciplinary field of catastrophology, economics, and urban infrastructure planning. We believe that current attempts to define and measure comprehensive urban natural disaster risks have certain limitations. Therefore, we propose an Urban Multi-hazards Risk Assessment Framework (UMRAF) which draws on definitions, methods, and experience from risk management, evaluation of property, the value of statistical life, and disaster system theory. It contains local disaster identification, place-based risk assessment (taking into account more than one hazard at a time), urban anti-disaster capability assessment, and relative composite risk index measurement. In our case study of Xiamen, China, to check the feasibility of our UMRAF, we examined local multi-hazards risk distribution and urban anti-disaster capacity layout. We then expanded and visualised the spatial distribution of the relative composite risk index of each evaluation unit across the city via our analyst tool, thereby helping to tailor measures that can reduce risk at a local level.

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