Prediction and Evaluation of Hardened Concrete Strength
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| Titel: | Prediction and Evaluation of Hardened Concrete Strength |
|---|---|
| Autoren: | Xu, Yidong, Mao, Jianghong, Zhuge, Weijie, Yu, Xiaoniu, Wu, Ping |
| Verlagsinformationen: | Singapore: Springer Nature, 2025. |
| Publikationsjahr: | 2025 |
| Bestand: | Books Imported or submitted locally |
| Original Material: | 6c6992af-b843-4f46-859c-f6e9998e40d5 |
| Schlagwörter: | Open Access, F-P maturity model, Particle Swarm Optimization, Ant Colony Optimization, Artificial Neural Network, Intelligent Prediction Program, Civil engineering, surveying and building, Materials science |
| Beschreibung: | This open access book monitors the development of the temperature field within concrete structures and, based on the Arrhenius equation, constructs F-P maturity equations applicable to different temperature ranges. It investigates the impact of hydration rate on the strength prediction method of the maturity equation. Furthermore, the book employs artificial neural network theory to improve the accuracy of early concrete strength predictions, optimizing the neural network model to develop a more precise and widely applicable prediction model. An intelligent program is developed using MATLAB, facilitating rapid strength prediction and assessment on construction sites using measured parameters. |
| Publikationsart: | book |
| Dateibeschreibung: | application/pdf |
| Sprache: | English |
| ISBN: | 978-981-9682-37-9 978-981-9682-36-2 981-9682-37-1 981-9682-36-3 |
| Relation: | Engineering; Engineering (R0) |
| DOI: | 10.1007/978-981-96-8237-9 |
| Zugangs-URL: | https://library.oapen.org/handle/20.500.12657/106067 |
| Rights: | URL: http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Anmerkungen: | ONIX_20250918T180551_9789819682379_37 https://library.oapen.org/handle/20.500.12657/106067 http://www.Springer.com |
| Dokumentencode: | edsoap.20.500.12657.106067 |
| Datenbank: | OAPEN Library |
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Nájsť tento článok vo Web of Science | Abstract: | This open access book monitors the development of the temperature field within concrete structures and, based on the Arrhenius equation, constructs F-P maturity equations applicable to different temperature ranges. It investigates the impact of hydration rate on the strength prediction method of the maturity equation. Furthermore, the book employs artificial neural network theory to improve the accuracy of early concrete strength predictions, optimizing the neural network model to develop a more precise and widely applicable prediction model. An intelligent program is developed using MATLAB, facilitating rapid strength prediction and assessment on construction sites using measured parameters. |
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| ISBN: | 9789819682379 9789819682362 9819682371 9819682363 |
| DOI: | 10.1007/978-981-96-8237-9 |