Quantitative assessment of subgrade settlement in soil-rock mixtures using intelligent compaction

Abstract

This study conducts a series of vibratory compaction tests on soil-rock mixture fillers, focusing on how rock size and content influence settlement. Using models and parameters validated by unconfined compression tests and numerical simulations, a surface vibration compaction model was developed to monitor real-time settlement. Results show that final settlement decreases with increasing rock size and content. PFC3D simulations reveal void ratio variations during compaction, which correlate closely with settlement and overall compaction quality. Notably, the settlement at the compacted state follows the same trend as final settlement when rock size and content vary. The study also finds that simulated final settlement is inversely proportional to excitation frequency and directly proportional to rock content. A parameter sensitivity analysis highlights the roles of soil-rock ratio and excitation frequency, leading to a settlement prediction model. Field validation confirms the model’s high accuracy in estimating compaction quality from settlement data.

Keywords

Soil-rock mixture fillers / Vibration compaction / Direct settlement assessment / PFC3D simulation / Settlement prediction model

References

[1] Zhao L, Xie Z, Li L, Huang D, Zhang Z, Zhou J. Investigation of effect of rock content on dynamic response and failure characteristics of soil–rock mixture slope using large-scale shaking table test. Eng Fail Anal, 2024

[2] Liu Z-R, Ye W-M, Zhang Z, Wang Q, Chen Y-G, Cui Y-J. A nonlinear particle packing model for multi-sized granular soils. Constr Build Mater, 2019, 221: 274-282

[3] Gong J, Liu J. Analysis on the mechanical behaviors of soil-rock mixtures using discrete eement method. Procedia Eng, 2015, 102: 1783-1792

[4] Xu WJ, Hu RL, Tan RJ. Some geomechanical properties of soil–rock mixtures in the Hutiao Gorge area, China. Géotechnique, 2007, 57(3): 255-264

[5] Afifipour M, Moarefvand P. Mechanical behavior of bimrocks having high rock block proportion. Int J Rock Mech Min Sci, 2014, 65: 40-48

[6] Napoli ML, Barbero M, Scavia C. Effects of block shape and inclination on the stability of melange bimrocks. Bull Eng Geol Environ, 2021, 80(10): 7457-7466

[7] Sonmez H, Ercanoglu M, Kalender A, Dagdelenler G, Tunusluoglu C. Predicting uniaxial compressive strength and deformation modulus of volcanic bimrock considering engineering dimension. Int J Rock Mech Min Sci, 2016, 86: 91-103

[8] Sonmez H, Gokceoglu C, Medley EW, Tuncay E, Nefeslioglu HA. Estimating the uniaxial compressive strength of a volcanic bimrock. Int J Rock Mech Min Sci, 2006, 43(4): 554-561

[9] Sonmez H, Tuncay E, Gokceoglu C. Models to predict the uniaxial compressive strength and the modulus of elasticity for Ankara agglomerate. Int J Rock Mech Min Sci, 2004, 41(5): 717-729

[10] Wang Y, Li CH, Hu YZ. Use of X-ray computed tomography to investigate the effect of rock blocks on meso-structural changes in soil-rock mixture under triaxial deformation. Constr Build Mater, 2018, 164: 386-399

[11] Wen-Jie X, Qiang X, Rui-Lin H (2011) Study on the shear strength of soil-rock mixture by large scale direct shear test. Int J Rock Mech Min Sci 48(8):1235–1247. https://doi.org/10.1016/j.ijrmms.2011.09.018

[12] Zhang S, Tang H, Zhan H, Lei G, Cheng H. Investigation of scale effect of numerical unconfined compression strengths of virtual colluvial–deluvial soil–rock mixture. Int J Rock Mech Min Sci, 2015, 77: 208-219

[13] Zhang Z, Sheng Q, Fu X, Zhou Y, Huang J, Du Y. An approach to predicting the shear strength of soil-rock mixture based on rock block proportion. Bull Eng Geol Env, 2019, 79(5): 2423-2437

[14] He Z, Zhang J, Sun T, He X (2020) Influence of maximum particle diameter on the mechanical behavior of soil‐rock mixtures. Adv Civil Eng. https://doi.org/10.1155/2020/8850221

[15] Zhao Y, Liu Z, Wang D (2018) Study of material composition effects on the mechanical properties of soil‐rock mixtures. Adv Civil Eng. https://doi.org/10.1155/2018/3854727

[16] Tu Y, Chai H, Liu X, Wang J, Zeng B, Fu X, Yu J. An experimental investigation on the particle breakage and strength properties of soil-rock mixture. Arab J Geosci, 2021

[17] Yan X, Zhan W, Hu Z, Yu Y, Xiao D, de Oliveira Correia JAF (2021) Experimental study on the effect of compaction work and defect on the strength of soil‐rock mixture subgrade. Adv Mater Sci Eng. https://doi.org/10.1155/2021/5533590

[18] Liu F, Gao C, Xu J, Yang J (2024) Cyclic shear behavior and bobilstm-based model for soil-rock mixture-concrete interfaces. Construct Build Mater 426. https://doi.org/10.1016/j.conbuildmat.2024.136031

[19] Li S, Yang Z, Gao Y, Liu H, Liu X, Jin X. Wetting deformation characteristics of soil–rock mixture considering the water-disintegration of red stratum soft rock. Acta Geotech, 2023, 19(7): 4381-4397

[20] Sun Y, Kwok C Y, Duan K (2024) Size effects on crystalline rock masses: insights from grain-based dem modeling. Comput Geotech 171. https://doi.org/10.1016/j.compgeo.2024.106376

[21] Zhai Q, Zhang R, Rahardjo H, Satyanaga A, Dai G, Gong W, Zhao X, Chua YS. A new mathematical model for the estimation of shear modulus for unsaturated compacted soils. Can Geotech J, 2024, 61(10): 2124-2137

[22] Zhai Q, Rahardjo H, Satyanaga A, Dai G. Estimation of unsaturated shear strength from soil–water characteristic curve. Acta Geotech, 2019, 14(6): 1977-1990

[23] Zhao Y, Liu Z, Mazzotti C (2019) Numerical experiments on triaxial compression strength of soil‐rock mixture. Adv Civil Eng. https://doi.org/10.1155/2019/8763569

[24] Wang S, Ji T, Xue Q, Shen Z, Zhang Q. Deformation and failure characteristics of soil-rock mixture considering material composition and random structure. Adv Mater Sci Eng, 2019, 2019: 1-13

[25] Qi Q, Nie Y, Wang X, Liu S (2023) Exploring the effects of size ratio and fine content on vibration compaction behaviors of gap-graded granular mixtures via calibrated dem models. Powder Technol 415. https://doi.org/10.1016/j.powtec.2022.118156

[26] Eichler C, Pietsch-Braune S, Dosta M, Schmidt A, Heinrich S (2022) Micromechanical analysis of roller compaction process with dem. Powder Technol 398. https://doi.org/10.1016/j.powtec.2022.117146

[27] Chang W, Xing A, Wang P. Initiation mechanism of an earthquake-triggered loess-mudstone interface landslide: insights from DEM numerical simulation. Bull Eng Geol Env, 2024

[28] Hu Y, Lu Y (2024) A novel framework for calibrating dem parameters: a case study of sand and soil-rock mixture. Comput Geotech 174. https://doi.org/10.1016/j.compgeo.2024.106619

[29] Peng J, Wong LNY, Teh CI. Effects of grain size-to-particle size ratio on micro-cracking behavior using a bonded-particle grain-based model. Int J Rock Mech Min Sci, 2017, 100: 207-217

[30] Shi C, Chen Y, Zhang L, Zhang X, Qiu L (2024) Numerical study on mechanical characteristics of gabion mixed media with discrete element method. Construct Build Mater 438. https://doi.org/10.1016/j.conbuildmat.2024.137108

[31] Wang T, Tang CS, Liu WJ, Cheng Q, Shen ZT, Pan XH (2024) Insight into the initiation and propagation mechanism of desiccation cracking in clayey soil from dem simulations. Comput Geotech 175. https://doi.org/10.1016/j.compgeo.2024.106694

[32] Zheng Z, Tang H, Zhang Q, Pan P, Zhang X, Mei G, Liu Z, Wang W (2023) True triaxial test and pfc3d-gbm simulation study on mechanical properties and fracture evolution mechanisms of rock under high stresses. Comput Geotech 154. https://doi.org/10.1016/j.compgeo.2022.105136

[33] Wang X, Cheng C, Li J, Zhang J, Ma G, Jin J (2023) Automated monitoring and evaluation of highway subgrade compaction quality using artificial neural networks. Auto Construct 145. https://doi.org/10.1016/j.autcon.2022.104663

[34] Thurner HF. Method and a device for ascertaining the degree of compaction of a bed of material with a vibratory compacting device. J Acoust Soc Am, 1979, 65(5): 1356-1357

[35] Xu Q, Chang GK. Evaluation of intelligent compaction for asphalt materials. Autom Constr, 2013, 30: 104-112

[36] Mooney MA, Rinehart RV. Field monitoring of roller vibration during compaction of subgrade soil. J Geotech Geoenviron Eng, 2007, 133(3): 257-265

[37] White DJ, Vennapusa PKR, Gieselman HH. Field assessment and specification review for roller-integrated compaction monitoring technologies. Adv Civ Eng, 2011, 2011: 1-15

[38] Wang X, Dong X, Zhang Z, Zhang J, Ma G, Yang X (2022) Compaction quality evaluation of subgrade based on soil characteristics assessment using machine learning. Transport Geotech 32. https://doi.org/10.1016/j.trgeo.2021.100703

[39] Wang X, Dong X, Li J, Zhang Z, Zhang J, Ma G (2023) Developing an advanced ann-based approach to estimate compaction characteristics of highway subgrade. Adv Eng Inform 56. https://doi.org/10.1016/j.aei.2023.102023

[40] Wang S, Li Y, Gao X, Xue Q, Zhang P, Wu Z (2020) Influence of volumetric block proportion on mechanical properties of virtual soil-rock mixtures. Eng Geol 278. https://doi.org/10.1016/j.enggeo.2020.105850

[41] Ministry of Transport of the People's Republic of China. (2021). Test Methods of Soils for Highway Engineering (JTG 3430—2020). China Communications Press.

[42] Rahman S, Khattak M J, Adhikari B, Adhikari S (2021) Discrete element modeling of bonded soil mixtures under uniaxial compression and indirect tension test. Transport Geotech 26. https://doi.org/10.1016/j.trgeo.2020.100438

[43] Acquah K, Chen Y. Discrete element modelling of soil compaction of a press-wheel. AgriEngineering, 2021, 3(2): 278-293

[44] Zhu Y, Gong J, Nie Z. Shear behaviours of cohesionless mixed soils using the DEM: the influence of coarse particle shape. Particuology, 2021, 55: 151-165

[45] Garcia B, Villard P, Richefeu V, Daudon D (2022) Comparison of full-scale rockfall tests with 3d complex-shaped discrete element simulations. Eng Geol 310. https://doi.org/10.1016/j.enggeo.2022.106855

[46] Benvenuti L, Kloss C, Pirker S. Identification of DEM simulation parameters by artificial neural networks and bulk experiments. Powder Technol, 2016, 291: 456-465

[47] Shan P, Lai X. Mesoscopic structure PFC∼2D model of soil rock mixture based on digital image. J Vis Commun Image Represent, 2019, 58: 407-415

[48] Widuliński Ł, Tejchman J, Kozicki J, Leśniewska D. Discrete simulations of shear zone patterning in sand in earth pressure problems of a retaining wall. Int J Solids Struct, 2011, 48(7–8): 1191-1209

[49] Wu M, Zhou F, Wang J (2023) DEM modeling of mini-triaxial test on soil-rock mixture considering particle shape effect. Comput Geotech 153. https://doi.org/10.1016/j.compgeo.2022.105110

[50] Yang Y, Chen T, Zheng H. Mathematical cover refinement of the numerical manifold method for the stability analysis of a soil-rock-mixture slope. Eng Anal Bound Elem, 2020, 116: 64-76

[51] Zhang T, Yu L, Wei J, Pu H, Zhang Q, Hu L, Mi X (2024) Stress evolution in rocks around tunnel under uniaxial loading: insights from pfc3d-gbm modelling and force chain analysis. Theor Appl Fract Mech 134. https://doi.org/10.1016/j.tafmec.2024.104728

[52] Wang X, Lu W, Li J, Zhang J, Ma G (2024) Multi-domain adaptive analysis of intelligent compaction measurement value for subgrade construction. Autom Constr 163. https://doi.org/10.1016/j.autcon.2024.105413

[53] Yu S, Shen S. Compaction prediction for asphalt mixtures using wireless sensor and machine learning algorithms. IEEE Trans Intell Transp Syst, 2023, 24(1): 778-786

[54] Yu S, Shen S, Steger R, Wang X. Effect of warm mix asphalt additive on the workability of asphalt mixture: from particle perspective. Constr Build Mater, 2022, 360 129548

[55] Yu S, Musazay JA, Zhang C, Hu P, Shen S. Workability of low-density polyethylene modified asphalt mixtures: a statistical analysis of particle kinematics. J Clean Prod, 2024, 447 141564

[56] Qing-Fu H, Mei-Li Z, Jin-Chang S, Yu-Long LUO, Xia Z (2015) Numerical method to generate granular assembly with any desired relative density based on DEM. Chin J Geotech Eng 37(3):537–543. https://doi.org/10.11779/CJGE201503019

Funding

National Natural Science Foundation of China(52278342)

RIGHTS & PERMISSIONS

The Author(s)