Development of An Artificial Neural Network (ANN) Model for Improved Corrosion Management using Fly Ash Geopolymer Concrete (FAGC) in Marine Infrastructure Applications
dc.contributor.author | Shahedan, Noor Fifinatasha Binti | |
dc.contributor.supervisor | Tony Hadibarata | en_US |
dc.contributor.supervisor | Muhammad Noor Hazwan Bin Jusoh | en_US |
dc.date.accessioned | 2025-07-04T02:03:11Z | |
dc.date.available | 2025-07-04T02:03:11Z | |
dc.date.issued | 2025 | en_US |
dc.identifier.uri | http://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.publisher | Curtin University | en_US |
dc.title | Development of An Artificial Neural Network (ANN) Model for Improved Corrosion Management using Fly Ash Geopolymer Concrete (FAGC) in Marine Infrastructure Applications | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | PhD | en_US |
curtin.department | Curtin Malaysia | en_US |
curtin.accessStatus | Open access | en_US |
curtin.faculty | Curtin Malaysia | en_US |
curtin.contributor.orcid | Shahedan, Noor Fifinatasha Binti [0000-0001-5390-4829] | en_US |