Stochastic reduced order models for uncertainty quantification of intergranular corrosion rates
Publication
, Journal Article
Sarkar, S; Warner, JE; Aquino, W; Grigoriu, MD
Published in: Corrosion Science
March 1, 2014
We present a stochastic reduced order model (SROM) approach for quantifying uncertainty in systems undergoing corrosion. A SROM is a simple random element with a small number of samples that approximates the statistics of another target random element. The parameters of a SROM are selected through an optimization problem. SROMs can be used to propagate uncertainty through a mathematical model of a corroding system in the same way as in Monte Carlo methods. We use SROMs to estimate the statistics of corrosion current density, considering randomness in anode-cathode sizes. We compare the performance of SROMs against the more common Monte-Carlo approach. © 2013 Elsevier Ltd.
Duke Scholars
Published In
Corrosion Science
DOI
ISSN
0010-938X
Publication Date
March 1, 2014
Volume
80
Start / End Page
257 / 268
Related Subject Headings
- Energy
- 4017 Mechanical engineering
- 4016 Materials engineering
- 4005 Civil engineering
- 0913 Mechanical Engineering
- 0912 Materials Engineering
- 0905 Civil Engineering
Citation
APA
Chicago
ICMJE
MLA
NLM
Sarkar, S., Warner, J. E., Aquino, W., & Grigoriu, M. D. (2014). Stochastic reduced order models for uncertainty quantification of intergranular corrosion rates. Corrosion Science, 80, 257–268. https://doi.org/10.1016/j.corsci.2013.11.032
Sarkar, S., J. E. Warner, W. Aquino, and M. D. Grigoriu. “Stochastic reduced order models for uncertainty quantification of intergranular corrosion rates.” Corrosion Science 80 (March 1, 2014): 257–68. https://doi.org/10.1016/j.corsci.2013.11.032.
Sarkar S, Warner JE, Aquino W, Grigoriu MD. Stochastic reduced order models for uncertainty quantification of intergranular corrosion rates. Corrosion Science. 2014 Mar 1;80:257–68.
Sarkar, S., et al. “Stochastic reduced order models for uncertainty quantification of intergranular corrosion rates.” Corrosion Science, vol. 80, Mar. 2014, pp. 257–68. Scopus, doi:10.1016/j.corsci.2013.11.032.
Sarkar S, Warner JE, Aquino W, Grigoriu MD. Stochastic reduced order models for uncertainty quantification of intergranular corrosion rates. Corrosion Science. 2014 Mar 1;80:257–268.
Published In
Corrosion Science
DOI
ISSN
0010-938X
Publication Date
March 1, 2014
Volume
80
Start / End Page
257 / 268
Related Subject Headings
- Energy
- 4017 Mechanical engineering
- 4016 Materials engineering
- 4005 Civil engineering
- 0913 Mechanical Engineering
- 0912 Materials Engineering
- 0905 Civil Engineering