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    Wyświetlanie 1-2 z 2
    Tytuł:
    Reviews on Finite Element Modeling Practices of Stone Columns for Soft Soil Stabilization Beneath an Embankment Dam
    Autorzy:
    Teshager, Daniel Kefelegn
    Belayneh, Henok Lemma
    Powiązania:
    https://bibliotekanauki.pl/articles/2172888.pdf
    Data publikacji:
    2022
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    embankment
    soft soil
    settlement
    stone column
    slope stability
    consolidation
    Opis:
    This article reviews the numerical approach in stone column practices and presents the benefits of stone columns as a ground improvement of soft soil to support an embankment dam. In this article, the methodological approaches to numerically modeling stone columns in both 2D and 3D studies, as well as the selection of an appropriate constitutive model are discussed. The numerical practices for the installation of the stone column and the validation procedures used to ensure the accuracy of the numerical analysis are also explained. In addition to that, the study also presents the benefits of stone columns in improving settlement behavior, slope stability, and decreasing the end time of consolidation. Parameters that influence the performance of the stone column with their respective results are also assessed.
    Źródło:
    Studia Geotechnica et Mechanica; 2022, 44, 4; 343--353
    0137-6365
    2083-831X
    Pojawia się w:
    Studia Geotechnica et Mechanica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Deep neural network and ANN ensemble for slope stability prediction
    Autorzy:
    Gupta, A.
    Aggarwal, Y.
    Aggarwal, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/24200566.pdf
    Data publikacji:
    2022
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    upper clay
    lower clay
    peat
    angle of internal friction
    embankment
    factor of safety
    slope stability
    deep neural network
    ensemble
    glina górna
    glina dolna
    torf
    kąt tarcia wewnętrznego
    nasyp
    współczynnik bezpieczeństwa
    stabilność zbocza
    głęboka sieć neuronowa
    zespół
    Opis:
    Purpose: Application of deep neural networks (DNN) and ensemble of ANN with bagging for estimating of factor of safety (FOS) of soil stability with a comparative performance analysis done for all techniques. Design/methodology/approach: 1000 cases with different geotechnical and similar Geometrical properties were collected and analysed using the Limit Equilibrium based Morgenstern-Price Method with input variables as the strength parameters of the soil layers, i.e., Su (Upper Clay), Su (Lower Clay), Su (Peat), angle of internal friction (φ), Su (Embankment) with the factor of safety (FOS) as output. The evaluation and comparison of the performance of predicted models with cross-validation having ten folds were made based on correlation-coefficient (CC), Nash-Sutcliffe-model efficiency-coefficient (NSE), root-mean-square-error (RMSE), mean-absolute-error (MAE) and scattering-index (S.I.). Sensitivity analysis was conducted for the effects of input variables on FOS of soil stability based on their importance. Findings: The results showed that these techniques have great capability and reflect that the proposed model by DNN can enhance performance of the model, surpassing ensemble in prediction. The Sensitivity analysis outcome demonstrated that Su (Lower Clay) significantly affected the factor of safety (FOS), trailed by Su (Peat). Research limitations/implications: This paper sets sight on use of deep neural network (DNN) and ensemble of ANN with bagging for estimating of factor of safety (FOS) of soil stability. The current approach helps to understand the tangled relationship of various inputs to estimate the factor of safety of soil stability using DNN and ensemble of ANN with bagging. Practical implications: A dependable prediction tool is provided, which suggests that model can help scientists and engineers optimise FOS of soil stability. Originality/value: Recently, DNN and ensemble of ANN with bagging have been used in various civil engineering problems as reported by several studies and has also been observed to be outperforming the current prevalent modelling techniques. DNN can signify extremely changing and intricate high-dimensional functions in correlation to conventional neural networks. But on a detailed literature review, the application of these techniques to estimate factor of safety of soil stability has not been observed.
    Źródło:
    Archives of Materials Science and Engineering; 2022, 116, 1; 14--27
    1897-2764
    Pojawia się w:
    Archives of Materials Science and Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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