Framework for Aleatory Variability and Epistemic Uncertainty for the Ground-Motion Characterization Based on the Level of Simplification

不确定度量化 参数统计 不确定性传播 概率逻辑 不确定度分析 地震动 数学 计算机科学 统计 工程类 结构工程
作者
Irene Liou,Norman A. Abrahamson
出处
期刊:Bulletin of the Seismological Society of America [Seismological Society of America]
标识
DOI:10.1785/0120240141
摘要

ABSTRACT Aleatory variability and epistemic uncertainty are commonly used concepts in probabilistic seismic hazard analysis (PSHA); however, separating uncertainty into aleatory variability and epistemic uncertainty is often seen as arbitrary. As part of the ground-motion characterization, we present a clarifying framework for defining aleatory variability and epistemic uncertainty for ground-motion models (GMMs). Aleatory variability is mainly due to unmodeled physical behaviors affecting ground motion. In contrast, epistemic uncertainty refers to the scientific uncertainty that the earthquake effects included in the model are modeled correctly. What is treated as aleatory variability and epistemic uncertainty depends on the level of model simplification. Simple models have larger aleatory variability and smaller epistemic uncertainty than complex models that model more physical behaviors. The framework has two parts: the method component, related to the algorithm and basic formulation for computing the ground motion, and the parametric component, which captures the effect of inputs to the GMM that are not included in the hazard integral. Each part has three components: aleatory variability, epistemic uncertainty in the median ground motion, and epistemic uncertainty in the size of the aleatory variability. The six terms provide a framework to ensure that all parts of the aleatory variability and epistemic uncertainty are included once and only once in the hazard calculation. The framework is especially beneficial as a guide for incorporating more complex GMMs into PSHA; it clarifies the separation of aleatory variability and epistemic uncertainty for nonergodic GMMs and numerical simulations.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
英俊的铭应助Sia采纳,获得20
刚刚
Wendy发布了新的文献求助10
1秒前
飘飘完成签到,获得积分10
1秒前
天天快乐应助wrr采纳,获得10
1秒前
我一定会毕业的完成签到,获得积分10
1秒前
1秒前
李爱国应助函王采纳,获得10
3秒前
何pengda发布了新的文献求助10
4秒前
英姑应助蔬菜人采纳,获得10
5秒前
5秒前
飘飘发布了新的文献求助10
5秒前
量子星尘发布了新的文献求助10
6秒前
liangha16完成签到,获得积分10
6秒前
TheBugsss完成签到,获得积分10
6秒前
7秒前
张华完成签到,获得积分10
7秒前
8秒前
Sia完成签到,获得积分10
8秒前
111完成签到,获得积分10
9秒前
科研通AI2S应助好好看文献采纳,获得10
9秒前
刘璐瑶完成签到,获得积分10
10秒前
young_lifestyle应助落寞妍采纳,获得10
10秒前
Wendy完成签到,获得积分10
10秒前
杨888完成签到,获得积分10
11秒前
个性太英发布了新的文献求助10
12秒前
13秒前
14秒前
14秒前
14秒前
wsy完成签到,获得积分20
14秒前
何pengda完成签到,获得积分10
16秒前
函王完成签到,获得积分10
16秒前
卡卡西应助科研通管家采纳,获得10
16秒前
爆米花应助科研通管家采纳,获得10
16秒前
16秒前
ED应助科研通管家采纳,获得10
16秒前
卡卡西应助科研通管家采纳,获得10
16秒前
wangling2333应助科研通管家采纳,获得10
16秒前
ED应助科研通管家采纳,获得10
16秒前
卡卡西应助科研通管家采纳,获得10
17秒前
高分求助中
The Mother of All Tableaux Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 2400
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
Cognitive Neuroscience: The Biology of the Mind 1000
Cognitive Neuroscience: The Biology of the Mind (Sixth Edition) 1000
Optimal Transport: A Comprehensive Introduction to Modeling, Analysis, Simulation, Applications 800
Official Methods of Analysis of AOAC INTERNATIONAL 600
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 588
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3958282
求助须知:如何正确求助?哪些是违规求助? 3504444
关于积分的说明 11118494
捐赠科研通 3235770
什么是DOI,文献DOI怎么找? 1788433
邀请新用户注册赠送积分活动 871211
科研通“疑难数据库(出版商)”最低求助积分说明 802582