• Wind and Structures
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• v.19 no.4
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• pp.421-441
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• 2014

With the assistance of typhoon field data at aerial elevation level observed by meteorological satellites and wind velocity and direction records nearby the ground gathered in Guangzhou Weather Station between 1985 and 2001, some key wind field parameters under typhoon climate in Guangzhou region were calibrated based on Monte-Carlo stochastic algorithm and Meng's typhoon numerical model. By using Peak Over Threshold method (POT) and Generalized Pareto Distribution (GPD), Wind field characteristics during typhoons for various return periods in several typical engineering fields were predicted, showing that some distribution rules in relation to gradient height of atmosphere boundary layer, power-law component of wind profile, gust factor and extreme wind velocity at 1-3s time interval are obviously different from corresponding items in Chinese wind load Codes. In order to evaluate the influence of typhoon field parameters on long-span flexible bridges, 1:100 reduced-scale wind field of type B terrain was reillustrated under typhoon and normal conditions utilizing passive turbulence generators in TJ-3 wind tunnel, and wind-induced performance tests of aero-elastic model of long-span Guangzhou Xinguang arch bridge were carried out as well. Furthermore, aerodynamic admittance function about lattice cross section in mid-span arch lib under the condition of higher turbulence intensity of typhoon field was identified via using high-frequency force-measured balance. Based on identified aerodynamic admittance expressions, Wind-induced stochastic vibration of Xinguang arch bridge under typhoon and normal climates was calculated and compared, considering structural geometrical non-linearity, stochastic wind attack angle effects, etc. Thus, the aerodynamic response characteristics under typhoon and normal conditions can be illustrated and checked, which are of satisfactory response results for different oncoming wind velocities with resemblance to those wind tunnel testing data under the two types of climate modes.

• Geomechanics and Engineering
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• v.33 no.2
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• pp.175-182
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• 2023

In general, the design of structures and its construction processes are fundamentally dependent on their foundation and supporting ground. Thus, it is imperative to understand the behavior of the soil under certain stress and drainage conditions. As it is well known that certain characteristics and behaviors of soils with fines are highly dependent on water content, it is critical to accurately measure and identify the status of the soils in terms of water contents. Liquid limit is one of the important soil index properties to define such characteristics. However, liquid limit measurement can be affected by the proficiency of the operator. On the other hand, dynamic properties of soils are also necessary in many different applications and current testing methods often require special equipment in the laboratory, which is often expensive and sensitive to test conditions. In order to address these concerns and advance the state of the art, this study explores a novel method to determine the liquid limit of cohesive soil by employing video-based vibration analysis. In this research, the modal characteristics of cohesive soil columns are extracted from videos by utilizing phase-based motion estimation. By utilizing the proposed method that analyzes the optical flow in every pixel of the series of frames that effectively represents the motion of corresponding points of the soil specimen, the vibration characteristics of the entire soil specimen could be assessed in a non-contact and non-destructive manner. The experimental investigation results compared with the liquid limit determined by the standard method verify that the proposed method reliably and straightforwardly identifies the liquid limit of clay. It is envisioned that the proposed approach could be applied to measuring liquid limit of soil in practical field, entertaining its simple implementation that only requires a digital camera or even a smartphone without the need for special equipment that may be subject to the proficiency of the operator.

• Journal of the Korean Geotechnical Society
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• v.25 no.1
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• pp.89-99
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• 2009

Compared to standard piling methods, micropile construction can be used in downtown areas since it generates less vibration and noise. Since it only causes less soil disturbance, it is commonly used as reinforcement to existing structures. In this study, a field wherein the bearing capacity and settlement of soil can not support the weight of the superstructure was selected and micropiles were implemented instead of ordinary piles. The deformation modulus of the micropile reinforced ground was determined and was directly reflected in the design. Loading testing was used to check whether or not the allowable bearing capacity satisfies the condition of the designed bearing capacity. The computed deformation modulus based from the test was used in the numerical analysis of soil to investigate the stability of the foundation and analysis method. And a method for controlling the bearing capacity and settlement was recommended.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.