Many uncertain factors in the excavation process may lead to excessive lateral displacement or over-limited internal force of the piles, as well as inordinate settlement of soil surrounding the existing bridge foundation. Safety control is pivotal to ensuring the safety of adjacent structures. In this paper, an innovative method is proposed that combines an analytic hierarchy process (AHP) with a finite element method (FEM) to reveal the potential impact risk of uncertain factors on the surrounding environment. The AHP was adopted to determine key influencing factors based on the weight of each influencing factor. The FEM was used to quantify the impact of the key influencing factors on the surrounding environment. In terms of the AHP, the index system of uncertain factors was established based on an engineering investigation. A matrix comparing the lower index layer to the upper index layer, and the weight of each influencing factor, were calculated. It was found that the excavation depth and the distance between the foundation pit and the bridge foundation were fundamental factors. For the FEM, the FE baseline model was calibrated based on the case of no bridge surrounding the foundation pit. The consistency between the monitoring data and the numerical simulation data for a ground settlement was analyzed. FE simulations were then conducted to quantitatively analyze the degree of influence of the key influencing factors on the bridge foundation. Furthermore, the lateral displacement of the bridge pile foundation, the internal force of the piles, and the settlement of the soil surrounding the pile foundation were emphatically analyzed. The most hazardous construction condition was also determined. Finally, two safety control measures for increasing the numbers of support levels and the rooted depths of the enclosure structure were suggested. A novel method for combining AHP with FEM can be used to determine the key influencing aspects among many uncertain factors during a construction, which can provide some beneficial references for engineering design and construction.

Shuangxi FENG ,   Huayang LEI   et al.
Twelve ECC beams with three different fiber types, along with four normal concrete beams, were tested in this study to evaluate the influence of cross-sectional hollowing on their flexural performance. The fiber types used were nylon monofilament (NM), low-cost untreated polyvinyl alcohol (PVA), and polypropylene (PP). Three different square hole sizes of 60, 80, and 100 mm with cross-sectional hollowing ratios of 0.16, 0.28, and 0.44, respectively, were adopted for each group of beams in addition to a solid beam. All beams were tested under four-point loading using a displacement-controlled testing machine. The test results showed that ECC beams can mostly withstand higher cracking and ultimate loads compared to their corresponding normal concrete versions. The results also showed that both the ductility and toughness of the ECC beams are higher than those of the normal concrete beams and that the ductility values of the hollow beams with a hole size of 60 mm are higher than those of the corresponding solid beams. Moreover, hollow ECC beams with hole sizes of 60 and 80 mm exhibited a higher ductility than a solid normal concrete beam.

This study aims to improve the unconfined compressive strength of soils using additives as well as by predicting the strength behavior of stabilized soils using two artificial-intelligence-based models. The soils used in this study are stabilized using various combinations of cement, lime, and rice husk ash. To predict the results of unconfined compressive strength tests conducted on soils, a comprehensive laboratory dataset comprising 137 soil specimens treated with different combinations of cement, lime, and rice husk ash is used. Two artificial-intelligence-based models including artificial neural networks and support vector machines are used comparatively to predict the strength characteristics of soils treated with cement, lime, and rice husk ash under different conditions. The suggested models predicted the unconfined compressive strength of soils accurately and can be introduced as reliable predictive models in geotechnical engineering. This study demonstrates the better performance of support vector machines in predicting the strength of the investigated soils compared with artificial neural networks. The type of kernel function used in support vector machine models contributed positively to the performance of the proposed models. Moreover, based on sensitivity analysis results, it is discovered that cement and lime contents impose more prominent effects on the unconfined compressive strength values of the investigated soils compared with the other parameters.

Ensuring a safe foundation design in soft clay is always a challenging task to engineers. In the present study, the effectiveness of under-reamed piles in soft clay underlaid by stiff clay is numerically studied using the lower-bound finite element limit analysis (LB FELA). The bearing and uplift capacities of under-reamed piles are estimated through non-dimensional factors and , respectively. These factors increased remarkably and marginally compared to and of the piles without bulbs when the bulb is placed in stiff and soft clay, respectively. For a given ratio of undrained cohesion of stiff to soft clay ( / ), the factors and moderately increased with the increase in the length-to-shaft-diameter ratio ( / ) and adhesion factors in soft clay ( ) and stiff clay ( ). The variation of radial stress along the pile–soil interface, distribution of axial force in the under-reamed piles, and state of plastic shear failure in the soil are also studied under axial compression and tension. The results of this study are expected to be useful for the estimation of the bearing and uplift capacities of under-reamed piles in uniform clay and soft clay underlaid by stiff clay.

Most Popular