Prediction and Evaluation of Hardened Concrete Strength

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Bibliographic Details
Title: Prediction and Evaluation of Hardened Concrete Strength
Authors: Xu, Yidong, Mao, Jianghong, Zhuge, Weijie, Yu, Xiaoniu, Wu, Ping
Publisher Information: Singapore: Springer Nature, 2025.
Publication Year: 2025
Collection: Books
Imported or submitted locally
Original Material: 6c6992af-b843-4f46-859c-f6e9998e40d5
Subject Terms: 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
Description: 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.
Document Type: book
File Description: application/pdf
Language: 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
Access URL: https://library.oapen.org/handle/20.500.12657/106067
Rights: URL: http://creativecommons.org/licenses/by-nc-nd/4.0/
Notes: ONIX_20250918T180551_9789819682379_37

https://library.oapen.org/handle/20.500.12657/106067

http://www.Springer.com
Accession Number: edsoap.20.500.12657.106067
Database: OAPEN Library
Description
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.
ISBN:9789819682379
9789819682362
9819682371
9819682363
DOI:10.1007/978-981-96-8237-9