A DDDAS framework for volcanic ash propagation and hazard analysis

A. Patra; M. Bursik; J. Dehn; M. Jones; M. Pavolonis; E. B. Pitman; T. Singh; P. Singla; P. Webley

doi:10.1016/j.procs.2012.04.118

A DDDAS framework for volcanic ash propagation and hazard analysis

A. Patra
, M. Bursik
, J. Dehn
, M. Jones
, M. Pavolonis
, E. B. Pitman
, T. Singh
, P. Singla
, P. Webley

Aerospace Engineering

Research output: Contribution to journal › Conference article › peer-review

16 Scopus citations

Abstract

In this paper we will present early work on using a DDDAS based approach to the construction of probabilistic estimates of volcanic ash transport and dispersal. Our primary modeling tools will be a combination of a plume eruption model BENT and the ash transport model PUFF. Data from satellite imagery, observation of vent parameters and windfields will drive our simulations. We will use uncertainty quantification methodology - polynomial chaos quadrature in combination with data integration to complete the DDDAS loop.

Original language	English (US)
Pages (from-to)	1090-1099
Number of pages	10
Journal	Procedia Computer Science
Volume	9
DOIs	https://doi.org/10.1016/j.procs.2012.04.118
State	Published - 2012
Event	12th Annual International Conference on Computational Science, ICCS 2012 - Omaha, NB, United States Duration: Jun 4 2012 → Jun 6 2012

All Science Journal Classification (ASJC) codes

General Computer Science

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10.1016/j.procs.2012.04.118

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@article{3b0246f3b69e42998db32bc30d14276a,

title = "A DDDAS framework for volcanic ash propagation and hazard analysis",

abstract = "In this paper we will present early work on using a DDDAS based approach to the construction of probabilistic estimates of volcanic ash transport and dispersal. Our primary modeling tools will be a combination of a plume eruption model BENT and the ash transport model PUFF. Data from satellite imagery, observation of vent parameters and windfields will drive our simulations. We will use uncertainty quantification methodology - polynomial chaos quadrature in combination with data integration to complete the DDDAS loop.",

author = "A. Patra and M. Bursik and J. Dehn and M. Jones and M. Pavolonis and Pitman, \{E. B.\} and T. Singh and P. Singla and P. Webley",

note = "Funding Information: The work reported here was supported by AFOSR contract number FA9550-11-1-0336.; 12th Annual International Conference on Computational Science, ICCS 2012 ; Conference date: 04-06-2012 Through 06-06-2012",

year = "2012",

doi = "10.1016/j.procs.2012.04.118",

language = "English (US)",

volume = "9",

pages = "1090--1099",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - A DDDAS framework for volcanic ash propagation and hazard analysis

AU - Patra, A.

AU - Bursik, M.

AU - Dehn, J.

AU - Jones, M.

AU - Pavolonis, M.

AU - Pitman, E. B.

AU - Singh, T.

AU - Singla, P.

AU - Webley, P.

N1 - Funding Information: The work reported here was supported by AFOSR contract number FA9550-11-1-0336.

PY - 2012

Y1 - 2012

N2 - In this paper we will present early work on using a DDDAS based approach to the construction of probabilistic estimates of volcanic ash transport and dispersal. Our primary modeling tools will be a combination of a plume eruption model BENT and the ash transport model PUFF. Data from satellite imagery, observation of vent parameters and windfields will drive our simulations. We will use uncertainty quantification methodology - polynomial chaos quadrature in combination with data integration to complete the DDDAS loop.

AB - In this paper we will present early work on using a DDDAS based approach to the construction of probabilistic estimates of volcanic ash transport and dispersal. Our primary modeling tools will be a combination of a plume eruption model BENT and the ash transport model PUFF. Data from satellite imagery, observation of vent parameters and windfields will drive our simulations. We will use uncertainty quantification methodology - polynomial chaos quadrature in combination with data integration to complete the DDDAS loop.

UR - https://www.scopus.com/pages/publications/84893044639

UR - https://www.scopus.com/pages/publications/84893044639#tab=citedBy

U2 - 10.1016/j.procs.2012.04.118

DO - 10.1016/j.procs.2012.04.118

M3 - Conference article

AN - SCOPUS:84893044639

SN - 1877-0509

VL - 9

SP - 1090

EP - 1099

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 12th Annual International Conference on Computational Science, ICCS 2012

Y2 - 4 June 2012 through 6 June 2012

ER -

A DDDAS framework for volcanic ash propagation and hazard analysis

Abstract

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