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Application of visualization modeling technology in the determination of reinforcement range of deep soft soil foundation

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A Correction to this article was published on 22 April 2022

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Abstract

Visualization modeling technology usually obtains the stratum land information through exploration and abstractly understands the soil layer distribution of the building site by means of 3D drawing. The introduction of 3D stratum visualization technology in foundation design can show the distribution of stratum more vividly and comprehensively. The visualization process and realization method of 3D stratum are studied in depth, and the technology is successfully applied to the foundation design, which provides convenience for the foundation layout and the checking of foundation elevation system, and also reduces the complexity of foundation design.

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References

  • Alizamir M, Kim S, Zounemat-Kermani M et al (2020) Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model. Artif Intell Rev 8(10):1–28

    Google Scholar 

  • Amin A, Zuecco G, Geris J et al (2020) Depth distribution of soil water sourced by plants at the global scale: a new direct inference approach. Ecohydrology 13(2):e2177

    Article  Google Scholar 

  • Borchard N, Bulusu M, Meyer N et al (2019) Deep soil carbon storage in tree-dominated land use systems in tropical lowlands of Kalimantan. Geoderma 354(10):113864–113866

    Article  Google Scholar 

  • Dong HN, Horpibulsuk S, Suddeepong A et al (2020) Compressibility of ultra-soft soil in the Mae Moh Mine, Thailand. Eng Geol 271:105594

    Article  Google Scholar 

  • Gissawong N, Mukdasai S, Boonchiangma S et al (2020) A rapid and simple method for the removal of dyes and organophosphorus pesticides from water and soil samples using deep eutectic solvent embedded sponge. Chemosphere 260(5):127590

    Article  Google Scholar 

  • Hong Z, Liu W, Xu B (2021) Research on the pipeline walking caused by cyclic increasing soil friction for free deep-sea submarine pipelines laid on even seabed. Mar Struct 75(12):102873

    Article  Google Scholar 

  • Hou X, Ding T, Cao K et al (2019) Research on multi-pipe drilling and pneumatic sampling technology for deep Martian soil. Adv Space Res 64(1):211–222

    Article  Google Scholar 

  • Huang W, Wu Q, Dey N, Ashour A, Fong SJ, González-Crespo R (2020) Adjectives grouping in a dimensionality affective clustering model for fuzzy perceptual evaluation. Int J Interact Multimedia Artif Intell 6(2):10

    Google Scholar 

  • Jose R, Carvalho DD, Kassouf R et al (2019) Behavior of laterally top-loaded deep foundations in highly porous and collapsible soil. J Mater Civ Eng 31(2):04018373.1-04018373.9

    Google Scholar 

  • Liu S, Pan Z, Cheng X (2017) A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface. Fractals 25(4):1740004

    Article  Google Scholar 

  • Liu S, Bai W, Liu G et al (2018) Parallel fractal compression method for big video data. Complexity 2018:2016976

    Google Scholar 

  • Liu T, Zhou J, Liang L et al (2021) A novel torque analysis method for drilling deep lunar soil by DEM. J Terrramech 94(5):23–37

    Article  Google Scholar 

  • Morente-Molinera J, Aguilar SR, González-Crespo R, Herrera-Viedma E (2019) Using clustering methods to deal with high number of alternatives on group decision making. Procedia Comput Sci 162:316–323

    Article  Google Scholar 

  • Rabbani P, Tolooiyan A, Lajevardi SH et al (2019) The effect of the depth of cutter soil mixing on the compressive behavior of soft clay treated by alkali-activated slag. KSCE J Civ Eng 23(10):4237–4249

    Article  Google Scholar 

  • Ramadan O, Mehanny S, Kotb AM (2020) Assessment of seismic vulnerability of continuous bridges considering soil-structure interaction and wave passage effects. Eng Struct 206(11):110161–110165

    Article  Google Scholar 

  • Samuel RDJ, Kanna BR (2018) Cybernetic microbial detection system using transfer learning. Multimedia Tools Appl 79(7–8):5225–5242

    Google Scholar 

  • Singh N, Kumar S, Udawatta RP et al (2021) X-ray micro-computed tomography characterized soil pore network as influenced by long-term application of manure and fertilizer. Geoderma 385(5):114872

    Article  Google Scholar 

  • Soundrapandiyan R, Dutta P, Trivedi A (2018) Adaptive infrared images enhancement using fuzzy-based concepts.

  • Stephan T, Sharma K, Shankar A, Punitha S, Varadarajan V, Liu P (2020) Fuzzy-logic-inspired zone-based clustering algorithm for wireless sensor networks. Int J Fuzzy Syst. https://doi.org/10.1007/s40815-020-00929-3

    Article  Google Scholar 

  • Vivekananda G, Reddy PC (2021) Efficient video transmission technique using clustering and optimization algorithms in MANETs. Int J Adv Intell Paradigms 19(1–2):1

    Article  Google Scholar 

  • Wang L, Liu Y, Pan Y et al (2019) Measure for reducing the tensile stress in cement-treated soil layer in deep excavation in soft clay. KSCE J Civ Eng 23(9):3924–3934

    Article  Google Scholar 

  • Yang WQ, Ma J et al (2019) Application of post-grouting in bridge foundation reinforcement: a case study. J GeoEngineering 14(3):155–165

    Google Scholar 

  • Zhang WX, Li B, Hwang HJ et al (2019a) Punching shear strength of reinforced concrete column footings under eccentric compression: experiment and analysis. Eng Struct 198:109509

    Article  Google Scholar 

  • Zhang M, Xu B, Li X et al (2019b) Deep neural network-based soft-failure detection and failure aware routing and spectrum allocation for elastic optic networks. Optic Eng 58(6):066107.1-0666107.9

    Google Scholar 

  • Zhang Z, Ye G et al (2019c) Centrifugal and numerical modeling of stiffened deep mixed column-supported embankment with slab over soft clay. Can Geotechn J 56(10):1418–1432

    Article  Google Scholar 

  • Zhao G, Liu J, Cui J et al (2019a) Revealing the mechanism of the force dragging the soft bag in the dynamic process of deep soil coring. Powder Technol 344:251–259

    Article  Google Scholar 

  • Zhao Y, Guindo ML et al (2019b) Deep learning associated with laser-induced breakdown spectroscopy (libs) for the prediction of lead in soil. Appl Spectrosc 73(5):565–573

    Article  Google Scholar 

  • Zhou DQ, Feng CX (2019) Engineering characteristics and reinforcement program of inclined pre-stressed concrete pipe piles. KSCE J Civ Eng 23(9):3907–3923

    Article  Google Scholar 

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No funds and grants were received by any of the authors.

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JL: methodology, project administration, and manuscript editing; DZ: software and validation; LW: visualization, and manuscript review and editing; FW: design framework, and resources.

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Correspondence to Jianfeng Li.

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This article is part of a Topical Collection in Environmental Earth Sciences on Deep learning for earth resource and environmental remote sensing, guest edited by Carlos Enrique Montenegro Marin, Xuyun Zhang and Nallappan Gunasekaran.

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Li, J., Zheng, D., Wu, L. et al. Application of visualization modeling technology in the determination of reinforcement range of deep soft soil foundation. Environ Earth Sci 81, 215 (2022). https://doi.org/10.1007/s12665-022-10268-1

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