Research on back analysis of meso-parameters of hydraulic cemented sand and gravel based on Box-Behnken design response surface
Source abstract
Abstract
Abstract Cemented sand and gravel (CSG) is a new type of dam-building material. Aiming at the cumbersome process and long calculation time of traditional methods to invert the meso-parameters, a mesophase parameter inversion method based on Box-Behnken Design response surface was proposed. By constructing a response surface simulation test scheme with different inversion parameters (elastic modulus of aggregates, mortars and interfaces, and interfacial tensile strength), the stochastic aggregate model is used to complete the numerical simulation of the damage process, and different results are obtained. The equation between the response variable (stress at different loading times) and the independent variable (inversion parameter) was verified, and the rationality of the response model was verified; the action mechanism of mesophase parameters at different stages on the mechanical properties of the specimen was analysed. The test results are brought into the response surface model, and the meso-parameters are obtained by inverse analysis. The stress–strain curve obtained by numerical simulation with this parameter has an error of 1.1% at the peak stress and 3.27% at the peak strain. The accuracy is high, the number of test groups is much smaller than other conventional inversion methods, and has feasibility of application in CSG.
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Research context
OpenAlex topics: Dam Engineering and Safety · Rock Mechanics and Modeling · Drilling and Well Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Water Conservancy, North China University of Water Resources and Electric Power , Zhengzhou , 450045 , China
Henan Water Valley Research Institute , Zhengzhou , 450046 , China
Henan Key Laboratory of Water Environment Simulation and Treatment , Zhengzhou , 450002 , China
Fan County Water Conservancy Bureau, Fan County, Puyang City, Henan Province , 457500 , China
References (44)
Show source-provided references
1. Jiang M, Zhang W, Sun Y, Utili S. An investigation on loose cemented granular materials via DEM analyses. Granul Matter. 2013;15:65–84.10.1007/s10035-012-0382-8 ↗
2. D’Addetta GA, Kun F, Ramm E. On the application of a discrete model to the fracture process of cohesive granular materials. Granul Matter. 2002;4:77–90.10.1007/s10035-002-0103-9 ↗
3. Desrues J, Viggiani G. Strain localization in sand: an overview of the experimental results obtained in Grenoble using stereophotogrammetry. Int J Numer Anal Met. 2004;28:279–321.10.1002/nag.338 ↗
4. Drescher A, Vardoulakis I. Geometric softening in triaxial tests on granular material. Geotechnique. 1982;32:291–303.10.1680/geot.1982.32.4.291 ↗
5. Han C. Localization of deformation in sand. University of Minnesota, ProQuest Dissertations Publishing; 1991.
6. Jiang M, Zhu H, Li X. Strain localization analyses of idealized sands in biaxial tests by distinct element method. Front Archit Civ Eng China. 2010;4:208–22.10.1007/s11709-010-0025-2 ↗
7. Mandel J. Conditions de stabilité et postulat de Drucker. Proceedings of IUTAM Symposium on Rheology and Soil Mechanics; 1966. p. 58–68.10.1007/978-3-662-39449-6_5 ↗
8. Pei LZ, Cai ZY. Research review of the cement sand and gravel (CSG) dam. Front Struct Civ Eng. 2012;6:19–24.10.1007/s11709-012-0145-y ↗
9. Dong L, Liu J, Xiuli D. A theoretical study on the influence of aggregate gradation on the tensile strength of 2-dimensional model concrete. Eng Mech. 2017;34:64–72.
10. Xu Y, Chen S. A method for modeling the damage behavior of concrete with a three-phase mesostructure. Constr Build Mater. 2016;102:26–38.10.1016/j.conbuildmat.2015.10.151 ↗
11. Dong L, Liu J, Xiuli D. Analysis theory for size effect of concrete in material-level based on properties and scales of meso structures. J Hydraulic Eng. 2019;102:26–38.
12. Hirose T, Fujisawa T, Yoshida H, Kawasaki H, Hirayama D, Sasaki T. Concept of CSG and its material properties. In Proceedings of the 4th International Symposium on Roller Compacted Concrete Dams. 2018. p. 465–73.
13. Jiang MJ, Sun YG, Li LQ, Zhu HH. Contact behavior of idealized granules bonded in different interparticle distances: an experimental investigation. Mech Mater. 2012;55:1–15.10.1016/j.mechmat.2012.07.002 ↗
14. Batmaz S. Cindere dam–107 m high roller compacted hardfill dam (RCHD) in Turkey. In Proceedings 4th International Symposium on Roller Compacted Concrete Dams. 2003. p. 121–6.
15. Gu C, Li B, Xu G, Yu H. Back analysis of mechanical parameters of roller compacted concrete dam. Sci China Technol Sci. 2010;53:848–53.10.1007/s11431-010-0053-0 ↗
16. Jia JS, Ma FL, Li XY, Chen ZP. Study on material characteristics of cement-sand-gravel dam and engineering application. J Hydraul Eng. 2006;37:578–82.
17. Yang J, Cai X, Guo XW, Zhao JL. Effect of cement content on the deformation properties of cemented sand and gravel material. Appl Sci. 2019;9:2369.10.3390/app9112369 ↗
18. Ren Q, Yin Y, Shen L. Fractal study of random distribution of concrete aggregate and its effect on damage characteristics. J Hydraul Eng. 2020;51:1267–77 and 88.
19. Ince R. Prediction of fracture parameters of concrete by artificial neural networks. Eng Fract Mech. 2004;71:2143–59.10.1016/j.engfracmech.2003.12.004 ↗
20. Wang ZH, Zhu YM, Chen FJ, Yu SP. Back analysis of concrete thermal parameters and its application based on genetic algorithms. J Hunan Univ Sci Technol (Nat Sci Ed). 2007;2:57–61.
21. Li SJ, Liu YX, Chen CL, Li ZG, He X, Zhou Y. Inversion procedure for mechanical parameters of concrete dam with hybrid genetic algorithm. J Dalian Univ Technol. 2004;44:195–9.
22. Jia SP. Inverse analysis for geotechnical engineering based on genetic algorithm and numerical implementation in ABAQUS. Hydrogeol Eng Geol. 2012;39:31–5.
23. Sun QC, Li SJ, Zhao HB, Zheng MZ, He ZY. Probabilistic back analysis of rock mechanical parameters based on displacement and relaxation depth. Chin J Rock Mech Eng. 2019;38:1884–94.
24. Liu DH, Zhao MQ. Meso-structural parameters inversion of PFC model for compaction of asphaltic concrete in core wall. J Hohai Univ. 2020;48:53–9.
25. Jia Y, Chi S. Back-analysis of soil parameters of the Malutang II concrete face rockfill dam using parallel mutation particle swarm optimization. Comput Geotech. 2015;65:87–96.10.1016/j.compgeo.2014.11.013 ↗
26. Li H, Wang G, Wei B, Zhong Y, Zhan L. Dynamic inversion method for the material parameters of a high arch dam and its foundation. Appl Math Model. 2019;71:60–76.10.1016/j.apm.2019.02.008 ↗
27. Box GEP, Wilson KB. On the experimental attainment of optimum conditions. J R Stat Soc Ser B Stat Methodol. 1992;270–310.10.1007/978-1-4612-4380-9_23 ↗
28. Zhang YY, Shen HM. Thin plate’s vibration based on MATLAB software. J Sichuan Univ (Eng Sci Ed). 2012;44:36–40.
29. Jiang BK, Li YH. Response analysis of rotating viscoelastic sandwich beam. J Sichuan Univ. 2012;44:167–70.
30. Pei L, Chen JK, Wu ZY, Li YL, Zhang H. Response surface genetic algorithm of back analysis of concrete thermal parameters. Mater Res Innov. 2015;19:S8-840–5.10.1179/1432891715Z.0000000001817 ↗
31. Li L, Zhi Z, Sai Z, Shuixiu P. Study on technological parameters of the treatment of landfill leachate by MAP method using response surface methodology. Chin J Eng. 2010;4:1289–95.
32. Li D. Parameter inversion of micro constitutive model for concrete materials based on macro experimental data. Dalian University of Technology; 2015.
33. Wang S. Parameter inversion of micro constitutive model for concrete materials based on macro experimental data. Dalian University of Technology; 2015.
34. Roussouly N, Petitjean F, Salaun M. A new adaptive response surface method for reliability analysis. Probabil Eng Mech. 2013;32:103–15.10.1016/j.probengmech.2012.10.001 ↗
35. Lü Q, Low BK. Probabilistic analysis of underground rock excavations using response surface method and SORM. Comput Geotech. 2011;38:1008–21.10.1016/j.compgeo.2011.07.003 ↗
36. Wang Y, Wang C. The application of response surface methodology. J Cent Univ Nat (Nat Sci Ed). 2005;3.
37. Zhouhong Z, Minglin G, Zhanghua X. Finite element model validation of the continuous rigid frame bridge based on structural health monitoring Part I: FE model updating based on the response surface method. Chin Civ Eng J. 2011;44:90–8.
38. Guo L, Zhang Y, Zhong L, Zhang F, Wang M, Li S. CSG elastic modulus model prediction considering meso-components and its effect. Sci Eng Compos Mater. 2020;27:27–271.10.1515/secm-2020-0027 ↗
39. Scrivener KL, Crumbie AK, Laugesen P. The interfacial transition zone (ITZ) between cement paste and aggregate in concrete. Interf Sci. 2004;12:411–21.10.1023/B:INTS.0000042339.92990.4c ↗
40. Zhou S, Chen L, Liu M. Analysis on effect of aggregate on mechanical property of concrete. J Build Mater. 2016;19:143–8.
41. China Academy of Building Research, Tsinghua University, Tongji University, et al. Design specifications for concrete structures. AQSIQ; 2010: 440P; B5.
42. Baktheer A, Chudoba R. Experimental and theoretical evidence for the load sequence effect in the compressive fatigue behavior of concrete. Mater Struct. 2021;54:1–23.10.1617/s11527-021-01667-0 ↗
43. Tian M, Zhou J. New algorithm for parameter inversion in geotechnical engineering. Chin J Rock Mech Eng. 2005;24:1492–6.
44. Jin CY, Ma ZY, Zhang YL, Sha RH, Chen QF. Application of neural network to back analysis of mechanical parameters and initial stress field of rock masses. Rock Soil Mech. 2006;27:1263–6.