Explore the vast range of titles available.

In the recent times, many studies have been devoted toward rectangular excavations but only a few studies have considered the “corner effect” in the optimized design of soil nail wall-retaining pile-anchor cable supporting systems, especially in large-scale deep foundation pit environments excavated by the central-island technique. Corner effect not only increases the construction costs but also may pose a risk to the safety and stability of such pits. In this paper, changes in the lateral displacement of retaining pile, soil at 1 m away from the foundation pit, crown beam, and the settlement of ground surface and surrounding buildings were extensively investigated based on the field measurements and numerical simulations of a large-scale deep foundation pit in Gaoxin zone, Xi’an, China. In addition, the supporting structure was optimized by considering the lateral influence zone of the corner effect. The optimization scheme proposed in this study not only satisfies the safety requirements of foundation pit supports, but also reduces the construction costs.

There are many strongly developed karsts in South China, which bring great uncertainty to the construction stability of underground projects. This paper takes the deep foundation pit project of a station in a sandy soil area as the background, simulates the deep foundation pit excavation process based on finite element software, and comparatively analyzes the influence of the existence of karst holes on the foundation pit support structure. The results show that the effective treatment of solution holes in the process of foundation pit excavation can reduce the risk of surface settlement around the foundation pit but has less influence on the lateral displacement of the foundation pit support structure. The cavity grouting reinforcement technology is also introduced in detail in the paper, which can provide a reference for the reinforcement of deep foundation pit projects in sandy soil stratum containing strong development of large cavities.

PurposeThe outbreak of COVID-19 pandemic has posed severe challenges to infrastructure construction in China. Particularly, the complex technology and high process uncertainty of deep foundation pit construction make its safety risk identification a challenging issue of general concern. To address these challenges, Building Information Modeling (BIM) can be used as an important tool to enhance communication and decision-making among stakeholders during the pandemic. The purpose of this study is to propose a knowledge management and BIM-integrated safety risk identification method for deep foundation pit construction to improve the management efficiency of project participants.Design/methodology/approachThis paper proposes a risk identification method that integrates BIM and knowledge management for deep foundation pit construction. In the framework of knowledge management, the topological relationships between objects in BIM are extracted and visualized in the form of knowledge mapping. After that, formal expressions of codes are established to realize the structured processing of specification provisions and special construction requirements. A comprehensive plug-in for deep foundation pit construction is designed based on the BIM software.FindingsThe proposed method was verified by taking a sub-project in deep foundation pit project construction as an example. The result showed the new method can make full use of the existing specification and special engineering requirements knowledge. In addition, the developed visual BIM plug-in proves the feasibility and applicability of the proposed method, which can help to increase the risk identification efficiency and refinement.Originality/valueThe deep foundation pit safety risk identification is challenged by the confusion of deep foundation pit construction safety knowledge and the complexity of the BIM model. By establishing the standardized expression of normative knowledge and special construction requirements, the efficiency and refinement of risk identification are improved while ensuring the comprehensiveness of results. Moreover, the topology-based risk identification method focuses on the project objects and their relations in the way of network, eliminating the problem of low efficiency from the direct BIM-based risk identification method due to massive data.

Deep foundation pit support systems are important for reducing construction risks, to ensure the effectiveness and safety of support engineering, so the selection of a suitable support program is the inevitable requirement for the smooth construction of a foundation pit project. In order to improve the rationality of the support scheme, the analytic hierarchy process and the improved Entropy method are comprehensively used to determine the subjective and objective weights of the indexes, and the comprehensive weights are corrected based on the idea of game theory. Subsequently, fuzzy comprehensive evaluation is used for scheme selection, thereby constructing a model for optimizing deep foundation pit support schemes. The model is applied to a municipal pipe gallery project in Area A and the optimal support scheme is determined to be the soil nail wall and supporting piles and anchor ropes. The safety of the support scheme and the effectiveness of the selection model are verified through simulation and construction monitoring. Practice has proved the applicability and superiority of the model in dealing with construction projects characterized by ambiguity and insufficient data. In addition, the advantages and disadvantages of the mainstream evaluation methods of the current deep foundation pit support selection, applicable situations, and the influence mechanism of the geological environment are discussed in this paper, which helps to establish a more comprehensive framework for the selection of the support schemes.

As a key guarantee and cornerstone of building quality, the importance of deformation prediction for deep foundation pits cannot be ignored. However, the deformation data of deep foundation pits have the characteristics of nonlinearity and instability, which will increase the difficulty of deformation prediction. In response to this characteristic and the difficulty of traditional deformation prediction methods to excavate the correlation between data of different time spans, the advantages of variational mode decomposition (VMD) in processing non-stationary series and a gated cycle unit (GRU) in processing complex time series data are considered. A predictive model combining particle swarm optimization (PSO), variational mode decomposition, and a gated cyclic unit is proposed. Firstly, the VMD optimized by the PSO algorithm was used to decompose the original data and obtain the Internet Message Format (IMF). Secondly, the GRU model optimized by PSO was used to predict each IMF. Finally, the predicted value of each component was summed with equal weight to obtain the final predicted value. The case study results show that the average absolute errors of the PSO-GRU prediction model on the original sequence, EMD decomposition, and VMD decomposition data are 0.502 mm, 0.462 mm, and 0.127 mm, respectively. Compared with the prediction mean square errors of the LSTM, GRU, and PSO-LSTM prediction models, the PSO-GRU on the PTB0 data of VMD decomposition decreased by 62.76%, 75.99%, and 53.14%, respectively. The PTB04 data decreased by 70%, 85.17%, and 69.36%, respectively. In addition, compared to the PSO-LSTM model, it decreased by 8.57% in terms of the model time. When the prediction step size increased from three stages to five stages, the mean errors of the four prediction models on the original data, EMD decomposed data, and VMD decomposed data increased by 28.17%, 3.44%, and 14.24%, respectively. The data decomposed by VMD are more conducive to model prediction and can effectively improve the accuracy of model prediction. An increase in the prediction step size will reduce the accuracy of the deformation prediction. The PSO-VMD-GRU model constructed has the advantages of reliable accuracy and a wide application range, and can effectively guide the construction of foundation pit engineering.

This paper aims to investigate the stress and deformation characteristics of double-row piles in deep foundation pit excavation by selecting representative strata in the Changchun area. The changes in bending moment, displacement, and earth pressure of double-row piles during the excavation are established using the FALC 3D software. The findings indicate that the deformation of the front pile is larger than that of the back pile, and the earth pressure distribution of the fornt pile deviates from the conventional Rankine earth pressure theory. Moreover, there are noticeable variations in earth pressure at the soil layer interface of the rear pile.

To ensure the safety of deep foundation pit construction, this paper proposes a settlement calculation model for deep foundation pits in soft soil areas. In this model, factors such as the non-Darcian flow law of soft soil, the varying boundary drainage capacity, and the construction loads are considered. Among them, the Hansbo’s flow and the linear load are used to portray the complicated conditions in real-world engineering, and the continuous drainage boundary is utilized to describe changes in drainage performance of soil boundaries. Comparing the effectiveness of the suggested solution to prior research has confirmed its efficacy. Then, using a number of examples, the consolidation mechanism of soil with continuous drainage boundary is examined in light of Hansbo’s flow law and the linear load. The pore pressure in soil layers with continuous drainage boundaries under linear load exhibits a trend of initially increasing and then dropping, according to numerical research. Furthermore, the peak of the increase in pore pressure is substantially impacted by Hansbo’s flow equation. The bigger the parameters in the Hansbo’s flow law, the longer the linear loading time, and the slower the settlement in the soil layer with the continuous drainage boundary are additional factors.

The goal of this study is to promote the development of high-quality energy and emission reduction measures for super large deep foundation pits applied in metro system construction projects in areas with loess. In this paper, Rhinoceros 6 is first used to model the super large deep foundation pit on both sides of the existing subway. Second, the Mohr‒Coulomb model and the elastic model are used for numerical calculations in FLAC 3D. In-depth analysis of the deformation of the foundation pit and its surrounding environment and optimization of the support system are performed from the perspectives of safety, economy and environmental protection. Finally, the emission factor method is used to analyze the energy consumption level of the support system. The results reveal that the surface settlement, horizontal displacement of support structure, and horizontal and vertical displacements of the lining increase with the number of construction stages (CONS). In addition, there are strong and stable areas of ground settlement. The ground settlement in the strong area exhibits a V-shaped trend. The horizontal displacement of the lining structure is concentrated in the lower 1/5 of the lining structure, and the vertical displacement gradually decreases from the center toward the east and west. Increases in the pile diameter and diagonal steel support stiffness significantly reduce the deformation of the super large deep foundation pit excavation on its sidewalls and surroundings. The optimized support system greatly reduces the project cost and construction difficulty, and the total carbon emissions are reduced by 27.52%.

The hydrodynamic changes and ground settlement induced by engineering dewatering have received much attention, and leakage between different aquifers is often neglected. Obviously, the leakage strength is crucial for the safety of underground engineering in soluble rock distribution areas. In this paper, we examined the Tianfu New Area in Chengdu, China, which contains a paste salt formation, based on numerical simulation techniques, characteristics of hydrodynamic field, leakage strength and ground settlement changes under different combinations of pumping well filter length and waterproof curtain depth were investigated. In the process of optimizing the dewatering scheme for this area, the leakage strength was innovatively included in the evaluation index. We found that as the depth of waterproof curtain increases, the trend of ground settlement and leakage strength caused by dewatering can be divided into a rapid decline phase and a gradual decline phase. However, the critical curtain depths of the two stages of ground settlement and leakage strength are different. The optimization scheme for dewatering engineering was determined under hydrodynamic, leakage strength, and ground settlement constraints. The filter length of the corresponding optimization scheme was 12 m, and the suitable depth of the waterproof curtain was 14–16 m. Our results provide an effective solution and method for optimizing the dewatering scheme in underground engineering projects with gypsum-bearing strata.

Gypseous soils are widely found in arid regions and are known for their high collapsibility when exposed to water. This study investigates the effect of water level inundation on Negative Skin Friction (NSF) and settlement in deep foundations in gypseous soil containing 50% gypsum content. The tests have five water levels starting from 0% up to 100% level of inundation, while being under a constant load of 70 kPa. NSF peaked at 50% saturation due to soil collapse and densification of surrounding soil, while settlement increased and reached its maximum at full saturation. This demonstrates that the nonlinear relationship between water level and pile and soil interaction highlights the need to consider partial saturation in foundation design in gypseous soil.