基于机器学习的SHAP和PDP分析对UHPC流变性能的研究

doi:10.11896/cldb.24100237

Abstract
Figure/Table
References
Related Citation (15)

Download:

Full Text ( PDF ) (9756KB)
Export: BibTeX | EndNote (RIS)

Abstract In this study, machine learning methods combined with interpretable tools SHAP (Shapley Additive exPlanations) and PDP (Partial Depen-dence Plot) were used to accurately predict the rheology of ultra-high performance concrete (UHPC). By collecting a large amount of UHPC rheological parameter data and input variables including water consumption, mineral admixture content and admixture content, four kinds of machine learning prediction models were constructed. The optimal models were selected by R², MAE, RMSE and other evaluation indicators, and SHAP and PDP analysis were carried out. The experimental results show that the optimal machine learning model combined with SHAP and PDP can effectively predict the rheology of UHPC. Moreover, the interpretability of the method helps to better understand the prediction process and results of the model, and provides a basis for further optimizing the mix ratio of UHPC.

Key words： SHAP PDP ultra-high performance concrete (UHPC) machine learning rheological property

Published: 25 January 2026 Online: 2026-01-27

CLC number:

TU528.01

	Service
	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	ZHOU Xiangxu
	DUAN Feng
	ZHU Bo

Cite this article:

ZHOU Xiangxu,DUAN Feng,ZHU Bo. Machine Learning-based Study on Rheological Properties of UHPC by SHAP and PDP Analysis[J]. Materials Reports, 2026, 40(2): 24100237-8.

URL:

https://www.mater-rep.com/EN/10.11896/cldb.24100237 OR https://www.mater-rep.com/EN/Y2026/V40/I2/24100237

1 Ding Q F, Jin Y Z, Meng X F. Construction and Building Materials, 2023, 385, 56.
2 Nguyen T, Tran T, Hoang N. Advanced Engineering Informatics, 2020, 44, 101057.
3 Bo Y C, Liu M, Wu I L, et al. Construction and Building Materials, 2023, 399, 132522.
4 Şahin H G, Altun O B, Eser M. Construction and Building Materials, 2024, 411, 134633.
5 Charrier M, et al. Cement and Concrete Research, 2022, 156, 106761.
6 Hatice G Ş, Öznur B A, Murat E, et al. Construction and Building Materials, 2024, 411, 134633.
7 Ekanayake I, Meddage D, Rathnayake U. Construction Materials, 2022, 16, e01059.
8 Amin M N, Iqbal M, Khan K, et al. Polymers, 2022, 14, 1303.
9 Rezaul K, Hamidul I, Shuvo D D, et al. Case Studies in Construction Materials, 2024, 20, e02828.
10 Abul K, Rezaul K, Somir C M, et al. Case Studies in Construction Materials, 2024, 24, e02991.
11 Tran M V, Cu Y T H, Le C V H. Journal of Building Engineering, 2021, 44, 103400.
12 Arunothayan A R, Nematollahi B, Khayat K H, et al. Cement and Concrete Composites, 2023, 136, 104854.
13 Zhang Q Q, Zhang L H, Ran Q P. Journal of Building Materials, 2019, 22(5), 680 (in Chinese).
张倩倩, 张丽辉, 冉千平. 建筑材料学报, 2019, 22(5), 680.
14 Shang T T, Wang H X, Sun D A. China Concrete and Cement Products, 2023(9), 7 (in Chinese).
商涛平, 王洪新, 孙德安. 混凝土与水泥制品, 2023(9), 7.
15 Wu Z, Khayat H K, Shi C. Cement and Concrete Research, 2019, 123, 105786.
16 Rui Y, Fengjiao Z, Tianyi Y, et al. Construction and Building Materials, 2021, 271, 121500.
17 Wang R, Gao X, Huang H, et al. Construction and Building Materials, 2017, 73, 14465.
18 Zhang C, Wang J, Zhang X, et al. Case Studies in Construction Materials, 2024, 20, e03036.
19 Li K, Leng Y, Xu L, et al. Construction and Building Materials, 2022, 349, 128793.
20 Cao R Z, Zhou M R, Zhou Q. Materials Reports, 2019, 33(16), 2684 (in Chinese).
曹润倬, 周茗如, 周群. 材料导报, 2019, 33(16), 2684.
21 Mehdipour I, Khayat H K. Construction and Building Materials, 2018, 161, 340.
22 Zhang C. Rheological properties of ultra-high performance concrete and their effects on steel fiber distribution. Master’s Thesis, Jinan University, China, 2023 (in Chinese).
张冲. 超高性能混凝土流变性能及其对钢纤维分布特性的影响. 硕士学位论文, 济南大学, 2023.
23 Jinyang C, Zhen H, Guozhi Z, et al. Construction and Building Materials, 2022, 321, 126154.
24 Chen F X, Yang R H, Wang Z Y, et al. Journal of Building Engineering, 2023, 68, 106167.
25 Wakjira G T, Kutty A A, Alam S M. Construction and Building Materials, 2024, 416, 135114.
26 Friedman H J. The Annals of Statistics, 2001, 29, 1189.
27 Safhi M E, Dabiri H, Soliman A, et al. Powder Technology, 2024, 438, 119623.
28 Chen T, Gao X, Ren M. Construction and Building Materials, 2018, 158, 864.
29 Liu L X, Ding Q F, Kang N L, et al. Expert Systems with Applications, 2024, 242, 122790.
30 Pal A, Ahmed S K, Mangalathu S. Construction and Building Materials, 2024, 417, 135369.
31 Kovler K, Roussel N. Cement and Concrete Research, 2011, 41, 775.
32 Liu Z Y. Rheological property control and mechanical properties characterization of 3D printed cement-based materials. Master’s Thesis, China Building Materials Science Research Institute, China, 2019 (in Chinese).
刘致远. 3D打印水泥基材料流变性能调控及力学性能表征. 硕士学位论文, 中国建筑材料科学研究总院, 2019.
33 Song Y G, Qi L L, Kun L, et al. Case Studies in Construction Materials, 2023, 18, e01952.
34 Gelardi G, Flatt R J. In:Science and Technology of Concrete Admixtures, UK, Woodhead Publishing, 2016, pp. 257.
35 Huang H. Study on rheological properties of fly ash concrete. Master’s Thesis, Wuhan University of Technology, China, 2011 (in Chinese).
黄浩. 粉煤灰混凝土流变性能研究. 硕士学位论文, 武汉理工大学, 2011.
36 Boulekbache B, Hamrat M, Chemrouk M, et al. Construction and Building Materials, 2010, 24, 1664.