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Analysis of ground vibrations due to underground trains by 2.5D finite/infinite element approach

Earthquake Engineering and Engineering Vibration 2010年第3期9卷 327-335页

作者： Hsiao-Hui Hung Y. B. Yang Center for Research on Earthquake Engineering （NCREE） Taipei 10617 Chinese Taipei Yunlin University of Science and Technology Douliu Yunlin 64002 Chinese Taipei

The 2.5D finite/infinite element approach is adopted to study wave propagation problems caused by underground moving trains. The irregularities of the near field, including the tunnel structure and parts of the soil, are modeled by the finite elements, and the wave propagation properties of the far field extending to infinity are modeled by the infinite elements. One particular feature of the 2.5D approach is that it enables the computation of the three-dimensional response of the half-space, taking into account the load-moving effect, using only a two-dimensional profile. Although the 2.5D finite/infinite element approach shows a great advantage in studying the wave propagation caused by moving trains, attention should be given to the calculation aspects, such as the rules for mesh establishment, in order to avoid producing inaccurate or erroneous results. In this paper, some essential points for consideration in analysis are highlighted, along with techniques to enhance the speed of the calculations. All these observations should prove useful in making the 2.5D finite/infinite element approach an effective one.

关键词： ground vibrations 2.5D finite/infinite element underground train wave number wave propagation

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Artificial neural network with a cross-validation approach to blast-induced ground vibration propagation modeling

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Underground Space 2021年第3期6卷 281-289页

作者： Gustavo Paneiro Manuel Rafael DECivil/CERENA Tecnico LisboaULisboaPortugal Orica Mining Services Portugal Portugal

Given their technical and economic advantages,the application of explosive substances to rock mass excavation is widely ***,because of serious environmental restraints,there has been an increasing need to use complex tools to control environmental effects due to blast-induced ground *** the present study,an artificial neural network(ANN)with k-fold cross-validation was applied to a dataset containing 1114 observations that was obtained from published results;furthermore,quantitative and qualitative parameters were considered for ground vibration amplitude *** best ANN model obtained has a maximum coefficient of determination of 0.840 and a mean absolute error of 5.59 and it comprises 17 input parameters,12 neurons in a one-layer hidden layer,and a sigmoid transfer *** with the traditional models,the model obtained using the proposed methodology demonstrated better generalization ***,the proposed methodology offers an ANN model with higher prediction ability.

关键词： Rock blasting Excavation ground vibrations Artificial neural network K-fold cross-validation Modeling

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