Prediction and Evaluation of Hardened Concrete Strength [electronic resource] : Based on Machine Learning and Mixture Composition / by Yidong Xu, Jianghong Mao, Weijie Zhuge, Xiaoniu Yu, Ping Wu.

За: Інтелектуальна відповідальність: Вид матеріалу: Текст Публікація: Singapore : Springer Nature Singapore : Imprint: Springer, 2026Видання: 1st ed. 2026Опис: IX, 108 p. 32 illus., 25 illus. in color. online resourceТип вмісту:
  • text
Тип засобу:
  • computer
Тип носія:
  • online resource
ISBN:
  • 9789819682379
Тематика(и): Додаткові фізичні формати: Printed edition:: Немає назви; Printed edition:: Немає назви; Printed edition:: Немає назвиДесяткова класифікація Дьюї:
  • 624 23
Класифікація Бібліотеки Конгресу:
  • TA1-2040
Електронне місцезнаходження та доступ:
Вміст:
1. Introduction -- 2. Raw materials and experimental method -- 3. Establishment of maturity equations for different temperature intervals -- 4. Concrete strength prediction based on artificial neural networks -- 5. Development of intelligent concrete strength program -- 6. Conclusions and foresight -- Appendix.
У: Springer Nature eBookЗведення: 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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1. Introduction -- 2. Raw materials and experimental method -- 3. Establishment of maturity equations for different temperature intervals -- 4. Concrete strength prediction based on artificial neural networks -- 5. Development of intelligent concrete strength program -- 6. Conclusions and foresight -- Appendix.

Open Access

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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