住宅区地震伤亡概率评估

IF 4.2 1区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY International journal of disaster risk reduction Pub Date : 2024-10-15 DOI:10.1016/j.ijdrr.2024.104902
Yuanyuan Ren , Donghui Ma , Wei Wang , Ziyi Wang , Xingde Zhao , Menghua Zhu
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引用次数: 0

摘要

准确合理地评估地震伤亡对于地震灾害规划和政府决策至关重要。然而,目前关于地震伤亡评估的研究往往缺乏对地震场景和影响因素不确定性的充分考虑。为了提高伤亡评估的真实性和可靠性,本研究提出了一种能够同时考虑多种影响因素的地震伤亡评估模型。该模型对各影响因素进行了定量评估,并综合考虑了地震发生时间、建筑物损坏状态和居住人数等相关不确定性特征。研究以住宅区为例,比较了考虑和不考虑公寓布局和居民年龄结构的伤亡评估结果。研究还解释了量化伤亡和构建住宅区地震事件脆弱性模型的概率方法。此外,还提出了适用于北京砌体结构住宅区地震伤亡概率评估的简化分析方法。研究结果表明,建筑物内的公寓布局对住宅区伤亡评估结果的影响相对较小,而居民的年龄结构对地震伤亡估算的影响较大。考虑到这三个因素的不确定性,住宅区的伤亡率大致呈对数正态分布。地震烈度从Ⅵ度(0.05g)到Ⅸ度(0.40g),不同地震烈度下的伤亡率标准偏差超过 0.4。本研究提出的概率分析方法完善了现有的地震伤亡评估模型,弥补了概率评估研究的不足。
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Probabilistic assessment of earthquake casualties in residential areas
Accurately and reasonably assessing earthquake casualties is crucial for seismic disaster planning and governmental decision-making. However, current research on earthquake casualty assessments often lacks sufficient consideration of the uncertainties related to seismic scenarios and influencing factors. To enhance the authenticity and reliability of casualty assessments, this study proposes a seismic casualty assessment model capable of simultaneously considering multiple influencing factors. It quantitatively evaluates each influencing factor and comprehensively integrates the uncertainty characteristics associated with seismic occurrence time, building damage states, and the number of occupants. Using a residential area as an example, the research compares casualty assessment results with and without considering apartment layouts and the age structure of residents. It also explains the probabilistic method for quantifying casualties and constructing vulnerability models for seismic events in the residential area. Additionally, a simplified analytical method applicable to probabilistic assessment of earthquake casualties in masonry residential areas in Beijing is proposed. The research findings indicate that the apartment layouts within buildings have a relatively minor impact on the assessment results of casualties in the residential area, while the age structure of residents significantly affects earthquake casualty estimates. Casualty rates in the residential area, considering uncertainties in the three factors, approximately follow a log-normal distribution. For seismic intensities ranging from VI(0.05g) to IX(0.40g), the standard deviation of casualty rates across different seismic intensities exceeds 0.4. The probabilistic analysis method proposed in this study enhances existing models for earthquake casualty assessments and addresses the shortcomings in probabilistic evaluation research.
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来源期刊
International journal of disaster risk reduction
International journal of disaster risk reduction GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
8.70
自引率
18.00%
发文量
688
审稿时长
79 days
期刊介绍: The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international. Key topics:- -multifaceted disaster and cascading disasters -the development of disaster risk reduction strategies and techniques -discussion and development of effective warning and educational systems for risk management at all levels -disasters associated with climate change -vulnerability analysis and vulnerability trends -emerging risks -resilience against disasters. The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.
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