Composition prediction of pore solution in hardened concrete materials based on machine learning
The pore solution composition (OH−, Na+, K+, Ca2+ and SO42-, S2O32-, S2- concentrations) of hardened concrete materials, including binary systems of PC mixed with a single SCM and with two SCMs, was investigated. Based on database comprising more than 400 entries with more than 80 parameters, machin...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-12-01
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| Series: | Developments in the Built Environment |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666165923001679 |