Porosity/Cement Index and Machine Learning Models for Predicting Tensile and Compressive Strength of Cemented Silt in Varying Compaction Conditions.
- DOI
- 10.3390/ma19030498
- Published
- 2026 Jan 27
- Container
- Materials (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/ma19030498,
title = {Porosity/Cement Index and Machine Learning Models for Predicting Tensile and Compressive Strength of Cemented Silt in Varying Compaction Conditions.},
author = {Baldovino JA and Coronado-Hernández OE and Nuñez de la Rosa YE},
year = {2026},
journal = {Materials (Basel, Switzerland)},
doi = {10.3390/ma19030498},
url = {https://doi.org/10.3390/ma19030498}
}RIS
TY - JOUR TI - Porosity/Cement Index and Machine Learning Models for Predicting Tensile and Compressive Strength of Cemented Silt in Varying Compaction Conditions. AU - Baldovino JA AU - Coronado-Hernández OE AU - Nuñez de la Rosa YE PY - 2026 JO - Materials (Basel, Switzerland) DO - 10.3390/ma19030498 UR - https://doi.org/10.3390/ma19030498 ER -
APA
JA, B., OE, C., & YE, N. D. L. R. (2026). Porosity/Cement Index and Machine Learning Models for Predicting Tensile and Compressive Strength of Cemented Silt in Varying Compaction Conditions.. Materials (Basel, Switzerland). https://doi.org/10.3390/ma19030498
Source records
- pubmed · retrieved 2026-09-27T07:28:59.281Z