Estimation of ultimate bearing capacity of circular footing resting on recycled construction and demolition waste overlaying on loose sand

Jitendra Singh Yadav1, Anant Saini2, Shaik Hussain3, Vaibhav Sharma4
1Department of Civil Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India
2Department of Civil Engineering, National Institute of Technology Hamirpur, Hamirpur, India
3Trenchless Technology Center, Louisiana Tech University, Ruston, USA
4Department of Civil Engineering, Lovely Professional University, Jalandhar, India

Tóm tắt

Finding soil with suitable geotechnical properties for construction purposes is becoming scarce. Hence, stabilization of soil is obligatory to overcome such a challenging situation. Unfortunately, some of the stabilization techniques are both uneconomical and complex. Therefore, a sustainable and cost-effective remedy is necessary for the time being. Recycled concrete demolition waste (RCDW) obtained from construction and demolition (C&D) waste provides a sustainable and economical way to overcome challenges associated with the loose sand. In this study, the suitability of RCDW to increase the load-carrying capacity of a circular footing placed on RCDW overlaying loose sand was examined using finite-element modelling. The influence of various parameters such as relative density (ID) (ID = 30%, 50%, and 70%), thickness of RCDW layer to diameter of circular footing ratio (u/D) (u/D = 0.4, 0.6, 0.8, 1.0, 1.2), and size of RCDW (i.e. 5 mm and 10.6 mm) on the bearing capacity were assessed. Furthermore, the mathematical expression was developed for evaluation of bearing capacity by using the artificial neural network (ANN) technique. Adding RCDW (5 mm) layer over loose sand increases the load-carrying capacity by 4.96 times and decreases settlement by 5.03 times for u/D = 1.2 and ID = 70% compared to loose sand at ID = 30%. Likewise, for the same instant RCDW layer of size, 10.6 mm leads to increases in the load-carrying capacity by 4.81 times and decreases settlement by 4.75 times. ANN results demonstrated that FANN-SIGMOID model with topology 4-2-1 provided a more precise prediction of ultimate bearing capacity. Further, the sensitivity analysis showed that u/D was the most important parameter affecting the ultimate bearing capacity. The coefficient of determination (R2) for the ANN model is 0.94 and for the MLR model, it is 0.88, indicating that both models successfully predicted the ultimate bearing capacity.

Tài liệu tham khảo

Iqbal MR, Hashimoto K, Tachibana S, Kawamoto K (2019) Geotechnical properties of sludge blended with crushed concrete and incineration ash. Int J GEOMATE 16:116–123. https://doi.org/10.21660/2019.57.8130 Debats JM, Sims M (1997) Vibroflotation in reclamations in Hong Kong. Ground Improv 1:127–145. https://doi.org/10.1680/gi.1997.010301 Mullins G, Winters D, Dapp S (2006) Predicting end bearing capacity of post-grouted drilled shaft in cohesionless soils. J Geotech Geoenvironmental Eng 132:478–487. https://doi.org/10.1061/(asce)1090-0241(2006)132:4(478) Gupta R, Trivedi A (2009) Bearing capacity and settlement of footing resting on confined loose silty sands. Electron J Geotech Eng 14:1–17 Dash SK, Rajagopal K, Krishnaswamy NR (2004) Performance of different geosynthetic reinforcement materials in sand foundations. Geosynth Int 11:35–42. https://doi.org/10.1680/gein.2004.11.1.35 Abid S (2017) Stabilization of soil using chemical methods. Int J Recent Trends Eng Res 3:104–121. https://doi.org/10.23883/ijrter.2017.3436.bnxrm Dutta RK, Yadav JS (2021) The impact of alccofine inclusion on the engineering properties of bentonite. Clean Eng Technol 5:100301. https://doi.org/10.1016/j.clet.2021.100301 Cardoso R, Silva RV, de Brito J, Dhir R (2016) Use of recycled aggregates from construction and demolition waste in geotechnical applications: a literature review. Waste Manag 49:131–145. https://doi.org/10.1016/j.wasman.2015.12.021 Swarna S, Tezeswi TP, Kumar S (2022) Implementing construction waste management in India: An extended theory of planned behaviour approach. Environ Technol Innov 27:102401. https://doi.org/10.1016/j.eti.2022.102401 Ganiron TUJ (2015) Recycling concrete debris from construction and demolition waste. Int J Adv Sci Technol 77:7–24. https://doi.org/10.14257/ijast.2015.77.02 Soni H, Saini A, Yadav JS (2022) Behaviour of square footing over recycled concrete aggregate resting on loose sand: integrated experimental and numerical analyses. Int J Geosynth Gr Eng 8:1–16. https://doi.org/10.1007/s40891-022-00409-8 Jain RK (2013) A study on eco friendly use of recycled rubber tyres. Direct Res J Eng Inf Technol 1:23–37 Ravi M, Murugesan B, Onyelowe KC (2023) Performance evaluation of marine and industrial wastes in cement to envelope low carbon environment in manufacturing process. Int J Low-Carbon Technol 18:986–998. https://doi.org/10.1093/ijlct/ctad082 Kumar P, Nakkeeran G, Onyelowe KC, Krishnaraj L (2023) Comparative study on net-zero masonry walls made of clay and fly ash bricks and grouts/mortars/stuccos with the effect of super fine fly ash blended cement—low carbon cement. Int J Low-Carbon Technol 18:1008–1014. https://doi.org/10.1093/ijlct/ctad087 Onyelowe KC, Kontoni D-PN (2023) The net-zero and sustainability potential of SCC development, production and flowability in concrete structures. Int J Low-Carbon Technol 18:530–541. https://doi.org/10.1093/ijlct/ctad033 Ebid AM, Onyelowe KC, Kontoni D-PN et al (2023) Heat and mass transfer in different concrete structures: a study of self-compacting concrete and geopolymer concrete. Int J Low-Carbon Technol 18:404–411. https://doi.org/10.1093/ijlct/ctad022 Onyelowe KC, Naghizadeh A, Aneke FI et al (2023) Characterization of net-zero pozzolanic potential of thermally-derived metakaolin samples for sustainable carbon neutrality construction. Sci Rep 13:1–11. https://doi.org/10.1038/s41598-023-46362-y Vishnupriyan M, Annadurai R, Onyelowe KC, Ganasen N (2023) Review on electronic waste used as construction materials—a scientometric analysis. Cogent Eng 10:1–18. https://doi.org/10.1080/23311916.2023.2283307 Onyelowe KC, Mojtahedi FF, Azizi S et al (2022) Innovative overview of SWRC application in modeling geotechnical engineering problems. Designs 6:1–54. https://doi.org/10.3390/designs6050069 Onyelowe KC, Ebid AM, Ghadikolaee MR (2023) GRG-optimized response surface powered prediction of concrete mix design chart for the optimization of concrete compressive strength based on industrial waste precursor effect. Asian J Civ Eng. https://doi.org/10.1007/s42107-023-00827-7 Onyelowe KC, Kontoni DPN, Pilla SRM et al (2023) Runtime-based metaheuristic prediction of the compressive strength of net-zero traditional concrete mixed with BFS, FA, SP considering multiple curing regimes. Asian J Civ Eng. https://doi.org/10.1007/s42107-023-00839-3 Arulrajah A, Piratheepan J, Disfani MM, Bo MW (2013) Geotechnical and geoenvironmental properties of recycled construction and demolition materials in pavement subbase applications. J Mater Civ Eng 25:1077–1088. https://doi.org/10.1061/(asce)mt.1943-5533.0000652 Jain A, Chawda A (2016) Apraisal of demolished concrete coarse and fines for stabilization of clayey soil. Int J Eng Sci Res Technol 5:715–719 Henzinger C, Heyer D (2018) Soil improvement using recycled aggregates from demolition waste. Proc Inst Civ Eng Ground Improv 171:74–81. https://doi.org/10.1680/jgrim.17.00031 Cabalar AF, Zardikawi OAA, Abdulnafaa MD (2019) Utilisation of construction and demolition materials with clay for road pavement subgrade. Road Mater Pavement Des 20:702–714. https://doi.org/10.1080/14680629.2017.1407817 Karkush MO, Yassin S (2019) Improvement of geotechnical properties of cohesive soil using crushed concrete. Civ Eng J 5:2110–2119. https://doi.org/10.28991/cej-2019-03091397 Sharma V, Kumar A, Kapoor K (2019) Sustainable deployment of crushed concrete debris and geotextile to improve the load carrying capacity of granular soil. J Clean Prod 228:124–134. https://doi.org/10.1016/j.jclepro.2019.04.306 Sharma A, Sharma RK (2019) Effect of addition of construction–demolition waste on strength characteristics of high plastic clays. Innov Infrastruct Solut 4:1–11. https://doi.org/10.1007/s41062-019-0216-1 Sharma A, Sharma RK (2020) Strength and drainage characteristics of poor soils stabilized with construction demolition waste. Geotech Geol Eng 38:4753–4760. https://doi.org/10.1007/s10706-020-01324-3 Alnunu MZ, Nalbantoglu Z (2019) Performance of loose sand with different waste materials in stone columns in North Cyprus. Environ Geotech 8:318–323. https://doi.org/10.1680/jenge.18.00079 Aljuari KA, Fattah MY, Ali HE (2021) Numerical analysis of treatment of highly expansive soil by partial replacement with crushed concrete. IOP Conf Ser Earth Environ Sci. https://doi.org/10.1088/1755-1315/856/1/012005 Al-Obaydi MA, Abdulnafaa MD, Atasoy OA, Cabalar AF (2022) Improvement in field CBR values of subgrade soil using construction-demolition materials. Transp Infrastruct Geotechnol 9:185–205. https://doi.org/10.1007/s40515-021-00170-x Tabatabaie Shourijeh P, Masoudi Rad A, Heydari Bahman Bigloo F, Binesh SM (2022) Application of recycled concrete aggregates for stabilization of clay reinforced with recycled tire polymer fibers and glass fibers. Constr Build Mater 355:129172. https://doi.org/10.1016/j.conbuildmat.2022.129172 Zhang G, Ding Z, Zhang R et al (2022) Combined utilization of construction and demolition waste and propylene fiber in cement-stabilized soil. Buildings. https://doi.org/10.3390/buildings12030350 Onyelowe KC, Mojtahedi FF, Ebid AM et al (2023) Selected AI optimization techniques and applications in geotechnical engineering. Cogent Eng. https://doi.org/10.1080/23311916.2022.2153419 Onyelowe KC, Jagan J, Kontoni D-PN et al (2023) Utilization of GEP and ANN for predicting the net-zero compressive strength of fly ash concrete toward carbon neutrality infrastructure regime. Int J Low-Carbon Technol 18:902–914. https://doi.org/10.1093/ijlct/ctad081 Onyelowe KC, Ebid AM, Hanandeh S (2023) The influence of nano-silica precursor on the compressive strength of mortar using advanced machine learning for sustainable buildings. Asian J Civ Eng. https://doi.org/10.1007/s42107-023-00832-w Onyelowe KC, Ebid AM, Mahdi HA et al (2023) AI mix design of fly ash admixed concrete based on mechanical and environmental impact considerations. Civ Eng J 9:27–45. https://doi.org/10.28991/CEJ-SP2023-09-03 Onyelowe KC, Ebid AM, Hanandeh S et al (2023) The influence of fines on the hydro-mechanical behavior of sand for sustainable compacted liner and sub-base construction applications. Asian J Civ Eng. https://doi.org/10.1007/s42107-023-00800-4 Onyelowe KC, Ebid AM, Mahdi HA et al (2022) Modeling the confined compressive strength of CFRP-jacketed noncircular concrete columns using artificial intelligence techniques. Cogent Eng 9:1–26. https://doi.org/10.1080/23311916.2022.2122156 Onyelowe KC, Jayabalan J, Ebid AM et al (2022) Evaluation of the compressive strength of CFRP-wrapped circular concrete columns using artificial intelligence techniques. Designs 6:1–20. https://doi.org/10.3390/designs6060112 Onyelowe KC, Fazel Mojtahedi F, Golaghaei Darzi A, Kontoni DPN (2023) Solving large deformation problems in geotechnical and geo-environmental engineering with the smoothed particle hydrodynamics: a state-of-the-art review of constitutive solutions. Springer, Berlin Heidelberg Onyelowe KC, Ebid AM (2023) The influence of fly ash and blast furnace slag on the compressive strength of high-performance concrete (HPC) for sustainable structures. Asian J Civ Eng. https://doi.org/10.1007/s42107-023-00817-9 Onyelowe KC, Sujatha ER, Aneke FI, Ebid AM (2022) Solving geophysical flow problems in Luxembourg: SPH constitutive review. Cogent Eng. https://doi.org/10.1080/23311916.2022.2122158 Onyelowe KC, Ebid AM, Hanandeh S (2023) Advanced machine learning prediction of the unconfined compressive strength of geopolymer cement reconstituted granular sand for road and liner construction applications. Asian J Civ Eng. https://doi.org/10.1007/s42107-023-00829-5 Onyelowe KC, Ebid AM, Ramani Sujatha E et al (2023) Extensive overview of soil constitutive relations and applications for geotechnical engineering problems. Heliyon 9:e14465. https://doi.org/10.1016/j.heliyon.2023.e14465 Onyelowe KC, Ebid AM, Mahdi HA, Baldovino JA (2023) Selecting the safety and cost optimized geo-stabilization technique for soft clay slopes. Civ Eng J 9:453–464. https://doi.org/10.28991/CEJ-2023-09-02-015 Khatti J, Grover KS, Kim HJ et al (2024) Prediction of ultimate bearing capacity of shallow foundations on cohesionless soil using hybrid LSTM and RVM approaches: an extended investigation of multicollinearity. Comput Geotech 165:105912. https://doi.org/10.1016/j.compgeo.2023.105912 Lawal AI, Kwon S (2023) Development of mathematically motivated hybrid soft computing models for improved predictions of ultimate bearing capacity of shallow foundations. J Rock Mech Geotech Eng 15:747–759. https://doi.org/10.1016/j.jrmge.2022.04.005 Nguyen DK, Nguyen TP, Ngamkhanong C et al (2023) Bearing capacity of ring footings in anisotropic clays: FELA and ANN. Neural Comput Appl 35:10975–10996. https://doi.org/10.1007/s00521-023-08278-6 Khatti J, Samadi H, Grover KS (2023) Estimation of settlement of pile group in clay using soft computing techniques. Springer, Berlin Ibrahim AS, Musa AA, Abdulfatah AY, Idris A (2023) Developing soft-computing regression model for predicting soil bearing capacity using soil index properties. Model Earth Syst Environ 9:1223–1232. https://doi.org/10.1007/s40808-022-01541-0 Agbemenou AKH, Motamed R, Talaei-Khoei A (2023) A predictive analytics model for designing deep underground foundations using artificial neural networks. Decis Anal J 7:100220. https://doi.org/10.1016/j.dajour.2023.100220 IS 2720-14 (1983) Methods of test for soils: determination of density index (relative density) of cohesionless soils. Bur Indian Stand New Delhi, India Reaffirmed, pp 1–14 2720-39-1 I (1977) Methods of test for soils, Part 39: Direct shear test for soils containing gravel, Section 1: Laboratory test [CED. Bur Indian Stand New Delhi, India Kim Y, Ahn J, Han W, Gabr M (2009) Experimental evaluation of strength characteristics of stabilized dredged soil. J Mater Civ Eng 22:539–544. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000052CE Tafreshi SNM, Norouzi AH (2012) Bearing capacity of a square model footing on sand reinforced with shredded tire—an experimental investigation. Constr Build Mater 35:547–556. https://doi.org/10.1016/j.conbuildmat.2012.04.092 Boger Z, Guterman H (1997) Knowledge extraction from artificial neural networks models. Proc IEEE Int Conf Syst Man Cybern 4:3030–3035. https://doi.org/10.1109/icsmc.1997.633051 Fakher NA, Fakhruldin MK (2021) Experimental study of relative density effect on bearing capacity of sand reinforced with geogrid. Kufa J Eng 12:46–55. https://doi.org/10.30572/2018/kje/120304 Meyerhof GG (1974) Ultimate bearing capacity of footings on sand layer overlying clay. Can Geotech J 11:223–229 Saini A, Soni H, Yadav JS (2023) Utilization of recycled construction and demolition waste to improve the bearing capacity of loose sand: an integrated experimental and numerical study. Geomech Geoeng. https://doi.org/10.1080/17486025.2023.2288925 Khatti J, Grover KS (2023) Prediction of compaction parameters for fine-grained soil: critical comparison of the deep learning and standalone models. J Rock Mech Geotech Eng 15:3010–3038. https://doi.org/10.1016/j.jrmge.2022.12.034 Khatti J, Grover KS (2023) A scientometrics review of soil properties prediction using soft computing approaches. Springer Netherlands, Dordrecht Khatti J, Grover KS (2023) Prediction of compaction parameters of compacted soil using LSSVM, LSTM, LSBoostRF, and ANN. Innov Infrastruct Solut 8:2023 Garson G (1991) Interpreting neural-network connection weights. AI Expert 6(4):46–51 Olden JD, Jackson DA (2002) Illuminating the “black box”: a randomization approach for understanding variable contributions in artificial neural networks. Ecol Model 154:135–150. https://doi.org/10.1016/S0304-3800(02)00064-9