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dc.contributor.authorShahedan, Noor Fifinatasha Binti
dc.contributor.supervisorTony Hadibarataen_US
dc.contributor.supervisorMuhammad Noor Hazwan Bin Jusohen_US
dc.date.accessioned2025-07-04T02:03:11Z
dc.date.available2025-07-04T02:03:11Z
dc.date.issued2025en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/98031
dc.description.abstract

OPC for marine infrastructure. Optimized mixes demonstrated a significant 65-70% reduction in chloride migration by 56–90 days, validating long-term durability despite higher early-age porosity. An Artificial Neural Network (ANN) model, with a precision of RMSE 0.007899, effectively predicted chloride migration trends, enhancing corrosion management. These findings highlight geopolymer concrete's eco-friendly durability, reduced maintenance costs, and suitability for sustainable marine structures in harsh environments.

en_US
dc.publisherCurtin Universityen_US
dc.titleDevelopment of An Artificial Neural Network (ANN) Model for Improved Corrosion Management using Fly Ash Geopolymer Concrete (FAGC) in Marine Infrastructure Applicationsen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentCurtin Malaysiaen_US
curtin.accessStatusOpen accessen_US
curtin.facultyCurtin Malaysiaen_US
curtin.contributor.orcidShahedan, Noor Fifinatasha Binti [0000-0001-5390-4829]en_US


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