Sensitivity of solidification hydration model in estimating carbonation of fly ash cement system

Yu, Y; Zhang, T; Wang, Q; Chen, X; Wu, D; Gao, W; Liu, A

Sensitivity of solidification hydration model in estimating carbonation of fly ash cement system

Yu, Y Zhang, T Wang, Q Chen, X Wu, D

Gao, W Liu, A

Permalink

Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Construction and Building Materials, 2021, 282, pp. 1-18
Issue Date:: 2021-05-03

Closed Access

	Filename	Description	Size
	1-s2.0-S0950061821003421-main (1).pdf	Published version	5.73 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Yu, Y
dc.contributor.author	Zhang, T
dc.contributor.author	Wang, Q
dc.contributor.author	Chen, X
dc.contributor.author	Wu, D https://orcid.org/0000-0002-7284-5024
dc.contributor.author	Gao, W
dc.contributor.author	Liu, A
dc.date.accessioned	2022-05-26T03:02:16Z
dc.date.available	2022-05-26T03:02:16Z
dc.date.issued	2021-05-03
dc.identifier.citation	Construction and Building Materials, 2021, 282, pp. 1-18
dc.identifier.issn	0950-0618
dc.identifier.uri	http://hdl.handle.net/10453/157717
dc.description.abstract	The system containing ordinary Portland cement and fly ash (FA) tends to be vulnerable against carbonation, where hydration estimation is crucial for assessing the carbonation resistance of the system. To date, few available models targeting FA-cement hydration are free from empirical or epistemic parameters, leading to unresolved issues of model sensitivity in estimating carbonation. In this study, a well-acclaimed hydration model is coupled with chemophysical modelling to numerically interpret the time-dependent mechanisms of system decay under carbonation. Furthermore, leveraging the power of extended support vector regression method, a robust and efficient framework is proposed for the investigation of hydration model sensitivity in carbonation assessment. The developed method is extensively validated against experimental studies and a carefully crafted benchmark test. Through sensitivity analyses, key findings on the propagation of hydration model sensitivity as well as the detailed levels of impact from respective model parameters are unravelled.
dc.language	en
dc.publisher	Elsevier
dc.relation	http://purl.org/au-research/grants/arc/IH150100006
dc.relation	http://purl.org/au-research/grants/arc/IH200100010
dc.relation.ispartof	Construction and Building Materials
dc.relation.isbasedon	10.1016/j.conbuildmat.2021.122582
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0905 Civil Engineering, 1202 Building
dc.subject.classification	Building & Construction
dc.title	Sensitivity of solidification hydration model in estimating carbonation of fly ash cement system
dc.type	Journal Article
utslib.citation.volume	282
utslib.for	0905 Civil Engineering
utslib.for	1202 Building
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-05-26T03:01:27Z
pubs.publication-status	Published
pubs.volume	282

Abstract:

The system containing ordinary Portland cement and fly ash (FA) tends to be vulnerable against carbonation, where hydration estimation is crucial for assessing the carbonation resistance of the system. To date, few available models targeting FA-cement hydration are free from empirical or epistemic parameters, leading to unresolved issues of model sensitivity in estimating carbonation. In this study, a well-acclaimed hydration model is coupled with chemophysical modelling to numerically interpret the time-dependent mechanisms of system decay under carbonation. Furthermore, leveraging the power of extended support vector regression method, a robust and efficient framework is proposed for the investigation of hydration model sensitivity in carbonation assessment. The developed method is extensively validated against experimental studies and a carefully crafted benchmark test. Through sensitivity analyses, key findings on the propagation of hydration model sensitivity as well as the detailed levels of impact from respective model parameters are unravelled.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/157717