The rise in construction activities within mountainous regions has significantly increased the frequency of rockfalls.Statistical models for rockfall hazard assessment often struggle to achieve high precision on a lar...The rise in construction activities within mountainous regions has significantly increased the frequency of rockfalls.Statistical models for rockfall hazard assessment often struggle to achieve high precision on a large scale.This limitation arises primarily from the scarcity of historical rockfall data and the inadequacy of conventional assessment indicators in capturing the physical and structural characteristics of rockfalls.This study proposes a physically based deterministic model designed to accurately quantify rockfall hazards at a large scale.The model accounts for multiple rockfall failure modes and incorporates the key physical and structural parameters of the rock mass.Rockfall hazard is defined as the product of three factors:the rockfall failure probability,the probability of reaching a specific position,and the corresponding impact intensity.The failure probability includes probabilities of formation and instability of rock blocks under different failure modes,modeled based on the combination patterns of slope surfaces and rock discontinuities.The Monte Carlo method is employed to account for the randomness of mechanical and geometric parameters when quantifying instability probabilities.Additionally,the rock trajectories and impact energies simulated using Flow-R software are combined with rockfall failure probability to enable regional rockfall hazard zoning.A case study was conducted in Tiefeng,Chongqing,China,considering four types of rockfall failure modes.Hazard zoning results identified the steep and elevated terrains of the northern and southern anaclinal slopes as areas of highest rockfall hazard.These findings align with observed conditions,providing detailed hazard zoning and validating the effectiveness and potential of the proposed model.展开更多
多变量数据可视化是挖掘多变量数据间内在联系,展现数据特征的重要手段,因此对多变量可视化研究进行系统的梳理,厘清多变量数据可视化的研究脉络、研究现状及热点方向,对领域专家洞察数据所蕴含的关键信息、挖掘变量数据间的潜在规律具...多变量数据可视化是挖掘多变量数据间内在联系,展现数据特征的重要手段,因此对多变量可视化研究进行系统的梳理,厘清多变量数据可视化的研究脉络、研究现状及热点方向,对领域专家洞察数据所蕴含的关键信息、挖掘变量数据间的潜在规律具有重要意义。本文以从中国知网平台(China national knowledge infrastructure,CNKI)和核心合集数据库(web of science,WOS)中检索到的多变量可视化研究文献为数据来源,利用CiteSpace软件对文献进行数据预处理,构建多变量数据可视化研究领域的文献知识图谱。通过对知识图谱的可视化分析,揭示了多变量数据可视化研究的主要方向、前沿主题和研究热点,并指出了未来多变量可视化研究的发展方向。展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42172318 and 42377186)the National Key R&D Program of China(Grant No.2023YFC3007201).
文摘The rise in construction activities within mountainous regions has significantly increased the frequency of rockfalls.Statistical models for rockfall hazard assessment often struggle to achieve high precision on a large scale.This limitation arises primarily from the scarcity of historical rockfall data and the inadequacy of conventional assessment indicators in capturing the physical and structural characteristics of rockfalls.This study proposes a physically based deterministic model designed to accurately quantify rockfall hazards at a large scale.The model accounts for multiple rockfall failure modes and incorporates the key physical and structural parameters of the rock mass.Rockfall hazard is defined as the product of three factors:the rockfall failure probability,the probability of reaching a specific position,and the corresponding impact intensity.The failure probability includes probabilities of formation and instability of rock blocks under different failure modes,modeled based on the combination patterns of slope surfaces and rock discontinuities.The Monte Carlo method is employed to account for the randomness of mechanical and geometric parameters when quantifying instability probabilities.Additionally,the rock trajectories and impact energies simulated using Flow-R software are combined with rockfall failure probability to enable regional rockfall hazard zoning.A case study was conducted in Tiefeng,Chongqing,China,considering four types of rockfall failure modes.Hazard zoning results identified the steep and elevated terrains of the northern and southern anaclinal slopes as areas of highest rockfall hazard.These findings align with observed conditions,providing detailed hazard zoning and validating the effectiveness and potential of the proposed model.
文摘多变量数据可视化是挖掘多变量数据间内在联系,展现数据特征的重要手段,因此对多变量可视化研究进行系统的梳理,厘清多变量数据可视化的研究脉络、研究现状及热点方向,对领域专家洞察数据所蕴含的关键信息、挖掘变量数据间的潜在规律具有重要意义。本文以从中国知网平台(China national knowledge infrastructure,CNKI)和核心合集数据库(web of science,WOS)中检索到的多变量可视化研究文献为数据来源,利用CiteSpace软件对文献进行数据预处理,构建多变量数据可视化研究领域的文献知识图谱。通过对知识图谱的可视化分析,揭示了多变量数据可视化研究的主要方向、前沿主题和研究热点,并指出了未来多变量可视化研究的发展方向。
