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    Tytuł:
    Sensitivity Analysis for Influence Parameters of Rail Corrugation Characteristics in Metro Straight Section
    Autorzy:
    Wang, Z.
    Lei, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/2023447.pdf
    Data publikacji:
    2021
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    sensitivity analysis
    metro
    rail corrugation
    friction self-excitation
    stochastic finite element
    analiza wrażliwości
    pofałdowanie szyn
    samowzbudzenie tarcia
    stochastyczny element skończony
    Opis:
    Based on the theory of friction self-excited vibration and the measured data of rail corrugation, the cause of rail corrugation in metro straight section was analyzed. Then, using the stochastic finite element method, the sensitivity of each parameter to rail corrugation was studied by selecting the elastic modulus E1 and density ρ1 of the wheel-rail material, the elastic modulus E2 and density ρ2 of the track slab material, the wheel-rail coefficient of friction f, the fastener vertical stiffness K and vertical damping C, the wheel-rail longitudinal relative slip s as the random parameters. The results show that under the support of Cologne egg fastener track, the characteristic frequency of friction self-excited vibration of wheel-rail system is close to the characteristic frequency of measured corrugation, indicating that the occurrence of rail corrugation is related to the friction self-excited vibration of wheel-rail system under the condition of saturated creep force. The parameter sensitivity analysis illustrates that the influence degree of each random parameter on the real part αi of complex eigenvalue is E1>ρ1>C>E2>ρ2>f>K>s in turn. E1, C and s are positively correlated with the real part αi of complex eigenvalue, while the remaining 5 parameters are negatively correlated with the real part αi of complex eigenvalue. Therefore, appropriate decrease of E1, C and s, and increase of ρ1, E2, ρ2, f and K can play a positive role in the control of rail corrugation.
    Źródło:
    Advances in Science and Technology. Research Journal; 2021, 15, 4; 110-117
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Soft computing based prediction of friction angle of clay
    Autorzy:
    Dutta, R. K.
    Gnananandarao, T.
    Ladol, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/1818506.pdf
    Data publikacji:
    2020
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    artificial neural network
    sensitivity analysis
    M5P model tree
    multiregression analysis
    friction angle of clay
    sztuczna sieć neuronowa
    analiza wrażliwości
    drzewo modelu M5P
    analiza wielokrotnej regresji
    Opis:
    Purpose: This article uses soft computing-based techniques to elaborate a study on the prediction of the friction angle of clay. Design/methodology/approach: A total of 30 data points were collected from the literature to predict the friction angle of the clay. To achieve the friction angle, the independent parameters sand content, silt content, plastic limit and liquid limit were used in the soft computing techniques such as artificial neural networks, M5P model tree and multi regression analysis. Findings: The major findings from this study are that the artificial neural networks are predicting the friction angle of the clay accurately than the M5P model and multi regression analysis. The sensitivity analysis reveals that the clay content is the major influencing independent parameter to predict the friction angle of the clay followed by sand content, liquid limit and plastic limit. Research limitations/implications: The proposed expressions can used to predict the friction angle of the clay accurately but can be further improved using large data for a wider range of applications. Practical implications: The proposed equations can be used to calculate the friction angle of the clay based on sand content, silt content, plastic limit and liquid limit. Originality/value: There is no such expression available in the literature based on soft computing techniques to calculate the friction angle of the clay.
    Źródło:
    Archives of Materials Science and Engineering; 2020, 104, 2; 58--68
    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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