近断层脉冲式地震动的自动分类

IF 8.5 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-12-24 DOI:10.1111/mice.13408
Hongwu Yang, Yingmin Li, Weihao Pan, Lei Hu, Shuyan Ji
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引用次数: 0

摘要

本研究提出了一种自动的、定量的近断层脉冲式地震动分类方法,区分了前向性和飞步(FS)震动。该方法引入了两个新的参数——脉冲速度比和脉冲面积比,将分类标准从定性的框架转变为定量的框架。结合增强的脉冲提取技术(捕获永久位移特征),这些参数显著提高了分类效率和可重复性。这种自动化方法克服了人工分类的局限性,提供了可重复的结果。识别出的FS地震动可用于跨断层结构的动力分析,提高地震危险性评估的可靠性。
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Automatic classification of near-fault pulse-like ground motions
This study presents an automated, quantitative classification method for near-fault pulse-like ground motions, distinguishing between forward-directivity and fling-step (FS) motions. The method introduces two novel parameters—the pulse velocity ratio and pulse area ratio—which transform the classification standard from a qualitative to a quantitative framework. Combined with an enhanced pulse extraction technique that captures permanent displacement characteristics, these parameters significantly improve classification efficiency and repeatability. This automated approach overcomes the limitations of manual classification, providing reproducible results. The identified FS ground motions can be applied to the dynamic analysis of cross-fault structures, enhancing the reliability of seismic hazard assessments.
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来源期刊
CiteScore
17.60
自引率
19.80%
发文量
146
审稿时长
1 months
期刊介绍: Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms. Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.
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