Jiu-jiang Wu

Bio: Jiu-jiang Wu is an academic researcher from Southwest University of Science and Technology. The author has contributed to research in topics: Pile & Bearing capacity. The author has an hindex of 3, co-authored 7 publications receiving 17 citations.

A load transfer approach to rectangular closed diaphragm walls

Abstract: As a new type of bridge foundation, rectangular closed diaphragm walls (RCDWs) provide an efficient solution to controlling the settlement of high-speed railway bridges. However, the scant research on settlement prediction for RCDWs has hindered their application in practical engineering. This paper attempts to establish a simplified approach for predicting the settlement of RCDWs. First, a simplified analytical model of an RCDW is established in accordance with the load transfer approach. Then, the load transfer curves and related coefficients of skin friction and foot resistance are discussed, and special attention is given to the determination of inner skin friction based on the results of a model test. In addition, an iterative procedure is applied to facilitate the solution process; moreover, a program named SPFRCDW, written in Matlab, is developed to estimate the settlement of RCDWs based on the proposed approach. Finally, a case study is conducted to verify the calculation results of SPFRCDW. The r...

Comparison on the Horizontal Behaviors of Lattice-Shaped Diaphragm Wall and Pile Group under Static and Seismic Loads

Abstract: Lattice-shaped diaphragm wall (hereafter referring to LSDW) is a new type of bridge foundation, and the relevant investigation on its horizontal behaviors is scant. This paper is devoted to the numerical study of the comparison on the static and seismic responses of LSDW and pile group under similar material quantity in soft soil. It can be found that the horizontal bearing capacity of LSDW is considerably larger than that of pile group, and the deformation pattern of LSDW basically appears to be an overall toppling while pile group clearly shows a local bending deformation pattern during the static loading process. The acceleration response and the acceleration amplification effects of LSDW are slightly greater than that of pile group due to the existing of soil core and the difference on the ability of energy dissipation. The horizontal displacement response of pile group is close to that of LSDW at first and becomes stronger than that of LSDW due to the generation of plastic soil deformation near the pile-soil interface at last. The pile body may be broken in larger potential than LSDW especially when its horizontal displacement is notable. Compared with pile group, LSDW can be a good option for being served as a lateral bearing or an earthquake-proof foundation in soft soil.

Seismic Behavior of Rectangular Closed Diaphragm Walls in Gently Sloping Liquefiable Deposit: Dynamic Centrifuge Testing

Abstract: Rectangular closed diaphragm walls (RCDWs) are often used as bridge foundations because of their advantageous properties such as high stiffness and construction efficiency, low cost, and mi...

Settlement calculation method of grid-type diaphragm wall bridge foundation in soft soil foundation

Abstract: The invention provides a settlement calculation method of a grid-type diaphragm wall bridge foundation in a soft soil foundation. According to the method, the structural characteristics of the grid-type diaphragm wall foundation itself in the soft soil foundation are taken into account; based on the foundation settlement characteristics, calculation of the frictional resistance on the outer side of a wall body is deduced, meanwhile the concept of equivalent shear stiffness is put forward and used for calculating the frictional resistance on the inner side of the wall body, and finally based ona load transfer method, the foundation settlement amount under various levels of load can be calculated by means of iterative calculation. According to the method, it is unnecessary to conduct special geotechnical engineering investigation, and the method provides a scientific basis for engineering design and construction of the soft soil foundation to which the novel grid-type diaphragm wall bridge foundation are applied.

Closure to “Load Transfer for Axially Loaded Piles in Clay”

Abstract: An analytical method for developing a theoretical load-settlement curve for axially loaded piles in clay is presented. The method is based on the correlation of the ratio of load transfer to soil shear strength as a function of pile movement. The results of studies of field tests of instrumented piles and laboratory tests of small piles in clay are used to obtain the desired correlation. The correlation is presented in the form of a family of curves that are obtained when the ratios of load transfer to soil shear strength versus pile movement are plotted as a function of depth. The validity of the family of correlation curves is checked by comparing computed and actual load-settlement curves for some typical field tests. Results obtained by this method indicate that the method may be used effectively to determine load-carrying capacity for axially loaded piles in clay.

Optimized functional linked neural network for predicting diaphragm wall deflection induced by braced excavations in clays

Abstract: Deep excavation during the construction of underground systems can cause movement on the ground, especially in soft clay layers. At high levels, excessive ground movements can lead to severe damage to adjacent structures. In this study, finite element analyses (FEM) and the hardening small strain (HSS) model were performed to investigate the deflection of the diaphragm wall in the soft clay layer induced by braced excavations. Different geometric and mechanical properties of the wall were investigated to study the deflection behavior of the wall in soft clays. Accordingly, 1090 hypothetical cases were surveyed and simulated based on the HSS model and FEM to evaluate the wall deflection behavior. The results were then used to develop an intelligent model for predicting wall deflection using the functional linked neural network (FLNN) with different functional expansions and activation functions. Although the FLNN is a novel approach to predict wall deflection; however, in order to improve the accuracy of the FLNN model in predicting wall deflection, three swarm-based optimization algorithms, such as artificial bee colony (ABC), Harris’s hawk’s optimization (HHO), and hunger games search (HGS), were hybridized to the FLNN model to generate three novel intelligent models, namely ABC-FLNN, HHO-FLNN, HGS-FLNN. The results of the hybrid models were then compared with the basic FLNN and MLP models. They revealed that FLNN is a good solution for predicting wall deflection, and the application of different functional expansions and activation functions has a significant effect on the outcome predictions of the wall deflection. It is remarkably interesting that the performance of the FLNN model was better than the MLP model with a mean absolute error (MAE) of 19.971, root-mean-squared error (RMSE) of 24.574, and determination coefficient (R2) of 0.878. Meanwhile, the performance of the MLP model only obtained an MAE of 20.321, RMSE of 27.091, and R2 of 0.851. Furthermore, the results also indicated that the proposed hybrid models, i.e., ABC-FLNN, HHO-FLNN, HGS-FLNN, yielded more superior performances than those of the FLNN and MLP models in terms of the prediction of deflection behavior of diaphragm walls with an MAE in the range of 11.877 to 12.239, RMSE in the range of 15.821 to 16.045, and R2 in the range of 0.949 to 0.951. They can be used as an alternative tool to simulate diaphragm wall deflections under different conditions with a high degree of accuracy.

Optimized functional linked neural network for predicting diaphragm wall deflection induced by braced excavations in clays

Abstract: Deep excavation during the construction of underground systems can cause movement on the ground, especially in soft clay layers. At high levels, excessive ground movements can lead to severe damage to adjacent structures. In this study, finite element analyses (FEM) and the hardening small strain (HSS) model were performed to investigate the deflection of the diaphragm wall in the soft clay layer induced by braced excavations. Different geometric and mechanical properties of the wall were investigated to study the deflection behavior of the wall in soft clays. Accordingly, 1090 hypothetical cases were surveyed and simulated based on the HSS model and FEM to evaluate the wall deflection behavior. The results were then used to develop an intelligent model for predicting wall deflection using the functional linked neural network (FLNN) with different functional expansions and activation functions. Although the FLNN is a novel approach to predict wall deflection; however, in order to improve the accuracy of the FLNN model in predicting wall deflection, three swarm-based optimization algorithms, such as artificial bee colony (ABC), Harris’s hawk’s optimization (HHO), and hunger games search (HGS), were hybridized to the FLNN model to generate three novel intelligent models, namely ABC-FLNN, HHO-FLNN, HGS-FLNN. The results of the hybrid models were then compared with the basic FLNN and MLP models. They revealed that FLNN is a good solution for predicting wall deflection, and the application of different functional expansions and activation functions has a significant effect on the outcome predictions of the wall deflection. It is remarkably interesting that the performance of the FLNN model was better than the MLP model with a mean absolute error (MAE) of 19.971, root-mean-squared error (RMSE) of 24.574, and determination coefficient (R2) of 0.878. Meanwhile, the performance of the MLP model only obtained an MAE of 20.321, RMSE of 27.091, and R2 of 0.851. Furthermore, the results also indicated that the proposed hybrid models, i.e., ABC-FLNN, HHO-FLNN, HGS-FLNN, yielded more superior performances than those of the FLNN and MLP models in terms of the prediction of deflection behavior of diaphragm walls with an MAE in the range of 11.877 to 12.239, RMSE in the range of 15.821 to 16.045, and R2 in the range of 0.949 to 0.951. They can be used as an alternative tool to simulate diaphragm wall deflections under different conditions with a high degree of accuracy.