Linganisha mbinu

	Fragility Curve Estimation	Uchanganuzi wa Uhatarishaji wa Kutetemeka kwa Uwezekano (PSHA)
Nyanja	Disaster Studies	Uhandisi wa Ujenzi
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2015	1968
Mwanzilishi	Jack W. Baker; Tiziana Rossetto & Amr Elnashai	C. Allin Cornell
Aina	Statistical estimation pipeline for conditional damage probability	Quantitative probabilistic framework
Chanzo asilia	Baker, J. W. (2015). Efficient Analytical Fragility Function Fitting Using Dynamic Structural Analysis. Earthquake Spectra, 31(1), 579-599.	Cornell, C. A. (1968). Engineering seismic risk analysis. Bulletin of the Seismological Society of America, 58(5), 1583–1606.
Majina mbadala	Seismic Fragility Functions, Fragility Function Fitting, Conditional Damage Probability Curves, Lognormal Fragility Modeling	PSHA, seismic hazard analysis, probabilistic earthquake hazard assessment, Cornell-McGuire method
Zinazohusiana	4	1
Muhtasari	Fragility curve estimation produces a function that gives the probability that an asset reaches or exceeds a defined damage state as a function of a hazard intensity measure, such as peak ground acceleration or spectral acceleration. It is the central conditional-probability link in disaster risk assessment, sitting between hazard (how strong the shaking is) and loss (what the damage costs), and is almost always parameterized as a lognormal cumulative distribution defined by a median intensity and a logarithmic standard deviation. Tiziana Rossetto and Amr Elnashai's 2003 work derived empirical fragility and vulnerability functions for European reinforced-concrete buildings from large post-earthquake damage databases, while Jack Baker's 2015 paper formalized efficient maximum-likelihood fitting of fragility functions from dynamic structural analyses. The method spans empirical fitting to observed damage, analytical fitting to simulated response, and expert-based judgment when data are scarce. Its output, a small set of curves indexed by damage state, is the reusable vulnerability building block consumed by loss-estimation and catastrophe-modeling pipelines. Estimating these curves well is what makes downstream risk numbers credible rather than arbitrary.	Probabilistic Seismic Hazard Analysis (PSHA) is a quantitative engineering framework used in civil and geotechnical engineering to estimate the likelihood that ground shaking will exceed a specified intensity level at a site within a given time window. By combining earthquake source geometry, recurrence statistics, and ground-motion attenuation models, PSHA produces hazard curves and maps that inform seismic design codes, infrastructure planning, and risk management decisions.