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      Multi-angle property analysis and stress–strain curve prediction of cementitious sand gravel based on triaxial test

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          Abstract

          In order to further promote the application of cementitious sand gravel (CSG), the mechanical properties and variation rules of CSG material under triaxial test were studied. Considering the influence of fly ash content, water-binder ratio, sand rate and lateral confining pressure, 81 cylinder specimens were designed and made for conventional triaxial test, and the influence laws of stress–strain curve, failure pattern, elastic modulus, energy dissipation and damage evolution of specimens were analyzed. The results showed that the peak of stress–strain curve increased with the increase of confining pressure, and the peak stress, peak strain and energy dissipation all increased significantly, but the damage variable D decreased with the increase of confining pressure. Under triaxial compression, the specimen was basically sheared failure from the bonding surface, and the aggregate generally did not break. Sand rate had a significant effect on the peak stress of CSG, and decreased with the increase of sand rate. Under the conditions of the same cement content, fly ash content and confining pressure, the optimal water-binder ratio 1.2 existed when the sand rate was 0.2 and 0.3. After analyzing and processing the stress–strain curve of triaxial test, a Cuckoo Search-eXtreme Gradient Boosting (CS-XGBoost) curve prediction model was established, and the model was evaluated by evaluation indexes R 2, RMSE and MAE. The average R 2 of the XGBoost model based on initial parameters under 18 different output features was 0.8573, and the average R 2 of the CS-XGBoost model was 0.9516, an increase of 10.10%. Moreover, the prediction curve was highly consistent with the test curve, indicating that the CS algorithm had significant advantages. The CS-XGBoost model could accurately predict the triaxial stress–strain curve of CSG.

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              Combining Principal Component Analysis, Discrete Wavelet Transform and XGBoost to trade in the financial markets

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                Author and article information

                Contributors
                gh3646@126.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                16 July 2024
                16 July 2024
                2024
                : 14
                : 16400
                Affiliations
                North China University of Water Resources and Electric Power, ( https://ror.org/03acrzv41) Zhengzhou, 450046 China
                Article
                62345
                10.1038/s41598-024-62345-z
                11252373
                39013923
                690999b7-15d1-4015-9b16-49a5401b3e51
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 December 2023
                : 15 May 2024
                Funding
                Funded by: Research on key technologies of operation and maintenance of long-distance, multi-type and complex terrain water supply projects
                Award ID: XYSSTZXCSGS-KY-02
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                cementitious sand gravel,cuckoo search,damage analysis,energy dissipation,stress–strain curve,extreme gradient boosting,failure characteristics,civil engineering,software

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