کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6388179 | 1627765 | 2014 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Uncertainty quantification and inference of Manning's friction coefficients using DART buoy data during the TÅhoku tsunami
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علم هواشناسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Tsunami computational models are employed to explore multiple flooding scenarios and to predict water elevations. However, accurate estimation of water elevations requires accurate estimation of many model parameters including the Manning's n friction parameterization. Our objective is to develop an efficient approach for the uncertainty quantification and inference of the Manning's n coefficient which we characterize here by three different parameters set to be constant in the on-shore, near-shore and deep-water regions as defined using iso-baths. We use Polynomial Chaos (PC) to build an inexpensive surrogate for the GeoClaw model and employ Bayesian inference to estimate and quantify uncertainties related to relevant parameters using the DART buoy data collected during the TÅhoku tsunami. The surrogate model significantly reduces the computational burden of the Markov Chain Monte-Carlo (MCMC) sampling of the Bayesian inference. The PC surrogate is also used to perform a sensitivity analysis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean Modelling - Volume 83, November 2014, Pages 82-97
Journal: Ocean Modelling - Volume 83, November 2014, Pages 82-97
نویسندگان
Ihab Sraj, Kyle T. Mandli, Omar M. Knio, Clint N. Dawson, Ibrahim Hoteit,