Foundation Pit Research Articles

Optimization of a deep foundation pit dewatering scheme in gypsum-bearing strata

Optimization of a deep foundation pit dewatering scheme in gypsum-bearing strata

Evaluation of the dynamic additional impact about foundation pit construction on the existing adjacent subway station with the PBA method

In this paper, relying on the Tianhe East Station project of Guangzhou Subway Line 11, the deformation and mechanical evolution rules about the existing adjacent stations with the pile-beam-arch (PBA) method in the all excavation stages about the new foundation pit is evaluated through numerical calculation method. It was revealed that that the largest displacement about the existing station’s side wall and the middle column reaches 2.1mm and 1.5mm respectively during the excavation about the foundation pit. Due to the impact about construction of the foundation pit, the uplifting phenomenon occurs on the side of the foundation pit, and the maximum uplifting value reaches 0.4mm. When the construction about foundation pit is finished, the whole station floor shows a deformation form of “left lower torsion”, and the largest compressive stresses as well as tensile stresses about the side wall and the bottom plate do not reach the standard limiting value, and the whole is being a relative safe status. With the increase about the excavation depths, the axial forces about the middle column gradually increase to 7016kN, and the incremental axial forces about the middle column after the construction is completed accounts for about 11.7% of the axial force of initial construction. Therefore, the disturbance effect about foundation pit construction on the adjacent station with the PBA method can not be ignored. The research result in this paper may offer some important references for the construction and design of similar cases.

Deformation prediction of large-scale civil structures using spatiotemporal clustering and empirical mode decomposition-based long short-term memory network

Structural deformation prediction is important for maintaining the serviceability and safety of civil infrastructure. However, current deep learning-based single prediction models face difficulties in accurately tracking deformation evolution of large-scale civil structures with numerous diverse monitoring data. In this study, a novel deformation prediction framework is proposed based on a spatiotemporal clustering algorithm and an empirical mode decomposition (EMD)-based long short-term memory (LSTM) network. Experiments on a large excavated foundation pit show that the proposed framework has a prediction error of RMSE less than 0.4 mm, outperforming LSTM models without using spatiotemporal clustering or EMD. Such high-precision predictions at many different monitoring locations demonstrate its promising application on large-scale structures. More deformation prediction experiments are required in the future to further validate the capability and performance of the proposed framework.

Retracted: Field Test and Data Simulation of Foundation Pit Support System Based on BP Neural Network

Retracted: Field Test and Data Simulation of Foundation Pit Support System Based on BP Neural Network

3D Simulation and Leakage Detection Technique for Deep Foundation Pits Based on Electric Field

To solve the problems of poor accuracy, poor anti-interference ability and unclear distribution of leakage electric field response characteristics of the traditional ground DC method for leakage detection of underground diaphragm walls in foundation pits, this paper proposes a deep foundation pit leakage detection technology based on the electric field. Secondly, it constructed the multi-field coupling equations and boundary conditions of the leakage electric field coupled with the leakage flow field and ion diffusion field, and then realized the three-dimensional forward evolution of the leakage electric field of the pit using the nonstructural mesh dissection method and the finite-element-infinite-element discretization method. Finally, physical model experiments and numerical simulations are used to confirm the reliability and accuracy of the foundation pit leakage detection technology and system. The results shows that monitoring the continuous change of the electric field for a period of time, the electric field detection technology for foundation pit leakage can effectively identify the location of hidden leakage and overcome the site’s strong industrial interference, resulting in a new technical solution for foundation pit leakage detection.

Prediction of deformation and damage of foundation support system based on BP neural network

The pit in the ground that needs to be excavated during the construction of a building is known as a foundation pit. In this paper, a MATLAB neural network toolbox is proposed to establish a three-layer BP neural network to predict building settlement. The relative error of the predicted values obtained after training is between -2% and 1%, and the maximum absolute error is 0.049 mm. this error is acceptable for rock-on-rock engineering problems. It shows that the building settlement prediction using artificial neural network method is feasible and the prediction results are credible. It automatically identifies the complex nonlinear relationships between the dependent and independent variables through self-learning of the optimal operation strategy, and considers the interactions among the factors in a comprehensive and integrated manner, which has good application prospects for solving nonlinear problems in the field of geotechnical engineering.

The sensitivity and timeliness of a variation correlation between structures in close proximity and located in the delta region

Typical geotechnical structures in the delta region include slopes, foundation pits, and embankments. An analysis of their interrelationships is essential for the overall safety and security of the delta region. At present, these structures are mainly studied by the manual analysis of single monitoring points and by inspection patrols performed by researchers in the field. However, this method is inefficient, costly, and risky to undertake. Furthermore, it is mainly through a time series that the respective states of a single-structure single monitoring point are successfully identified. This makes it difficult to present the correlation between structures and monitoring points, and makes it impossible to truly assess their overall safety patterns. To this end, this study proposes an intelligent analysis method based on feedforward neural networks to associate multiple monitoring points for multiple structures. It uses the correlation between the monitoring values of multiple geotechnical structures and multiple monitoring points for modeling. Then, key coefficients, the gray correlation theory, and degree of importance are introduced to assess the correlation and sensitivity factors of the changes occurring between different structures. The response time and duration between them were also analyzed. Finally, it was applied to a close, typical geotechnical structure system in South China, and the example application was good (R2: 0.91 ∼ 0.95, GR: 0.805 ∼ 0.981). The combined response time and duration of the M index of the foundation pit was optimal for the embankment S (Tr = 0, Tc = 3 ∼ 7) and the JM (Tr = 0, Tc = 4) index of the slope. The multi-correlation model established in this study provides new guidance for accurately revealing the latent hazard potential of typical geotechnical structural systems in the delta region in close proximity. It can also be used as a relevant implication for correlating changes between geotechnical structures in close proximity in other areas.

Numerical Simulation of Artificial Recharge Groundwater Effect on Overlying Soft Clay Compression Control

Soil deformation is prone to occur in the process of the foundation pit dewatering. A large number of metro existing tunnels are located in soft soil layers. The compression of soft soil poses a threat to metro existing tunnels. Previously, plenty of research on foundation pit dewatering is focused on the hydraulic head and deformation characteristics of the aquifer. However, the law of water releasing and compression deformation of overlying soft soil has not been taken seriously. In order to study the artificial recharge groundwater effect on overlying soft clay, a three-dimensional seepage–soil deformation coupling numerical model was established. The theoretical basis of the model is Darcy’s law and the principle of effective stress. A foundation pit located in Nanjing, China was selected as an example. The numerical model was used to simulate the hydraulic head and soil deformation caused by foundation pit dewatering and artificial recharge groundwater outside. The result shows that, due to the difference of hydraulic head between the aquifer and the aquitard reducing, it also has a good control effect on the deformation of the soft soil by recharging water into the aquifer. The location of recharge wells around the metro existing tunnel can control the soil deformation effectively, which could help to reduce the impact on the metro existing tunnel.

Research on Shear Strength Parameters of the Silty Fine Sand and the Rounded Gravel Layers in Nanning City

The silty fine sand and rounded gravel layers are widely distributed in Nanning City, China. Due to the low clay content, the silty fine sand and rounded gravel layers are prone to disturbance during sampling and transportation, which affects the shear strength test results. The reasonable determination of their shear strength is significant and imperative to the project. The rail transit project in Nanning is under large-scale construction. This work obtained the shear strength of the silty fine sand and the rounded gravel layers by conducting laboratory tests on undisturbed samples from deep foundation pits, combined with large-scale direct shear in situ tests. In addition, geotechnical investigation reports for typical projects in Nanning City were compiled, and the test data for the silty fine sand and the rounded gravel layers were comparatively analyzed using the empirical value. The results show that the shear strength test values of the fine sand layer are consistent with the current standard empirical values, and empirical values can be used for reference. The shear strength test value of the rounded gravel layer has significantly improved compared to the current standard empirical value, with a cohesion (c) value of 0–6.8 kPa and an increase in internal friction angle (φ) of 0%–12.5%. It is recommended to determine the shear strength of the rounded gravel layer based on the actual situation.

Sensitivity analysis of counterweight double-row pile deformation to weak stratum parameters

In order to investigate the sensitivity of weak soil parameters on the deformation of balanced double-row piles, a case study was conducted in a deep foundation pit project in Shenzhen City. A variety of analysis methods, including numerical simulation, field measurements, orthogonal experiments, and theoretical analysis, were employed to analyze the impact of three weak soil parameters on the deformation of balanced double-row piles. The research results showed that the deformation of the front and back rows of piles exhibited overturning deformation, gradually decreasing with depth and reaching the maximum at the pile top due to the constraint effect of the balance platform. The numerical simulation results of horizontal displacements for the front and rear piles were in good agreement with the field measurements, confirming the accuracy and reasonableness of the numerical analysis model and parameter selection. Through a series of orthogonal numerical simulation experiments, it was determined that the cohesive strength (C) of soft layers, such as rockfill and silt, is a key factor, the internal friction angle (φ) is an important influencing factor, and the elastic modulus (E) is a general influencing factor. Theoretical analysis was employed to establish the relationship curve between each parameter and the maximum pile deformation, as well as the sensitivity factors, further verifying the impact of these weak soil parameters. The research findings presented in this paper can provide valuable guidance for geotechnical engineers when selecting geological parameters for similar deep excavation projects.

System reliability-based robust design of deep foundation pit considering multiple failure modes

Recently, reliability-based design is a universal method to quantify negative influence of uncertainty in geotechnical engineering. However, for deep foundation pit, evaluating the system safety of retaining structures and finding cost-effective design points are main challenges. To address this, this study proposes a novel system reliability-based robust design method for retaining system of deep foundation pit and illustrated this method via a simplified case history in Suzhou, China. The proposed method included two parts: system reliability model and robust design method. Back Propagation Neural Network (BPNN) is used to fit limit state functions and conduct efficient reliability analysis. The common source random variable (CSRV) model are used to evaluate correlation between failure modes and determine the system reliability. Furthermore, based on the system reliability model, a robust design method is developed. This method aims to find cost-effective design points. To solve this problem, the third generation non-dominated genetic algorithm (NSGA-III) is adopted. The efficiency and accuracy of whole computations are improved by involving BPNN models and NSGA-III algorithm. The proposed method has a good performance in locating the balanced design point between safety and construction cost. Moreover, the proposed method can provide design points with reasonable stiffness distribution.

Transformer based neural network for daily ground settlement prediction of foundation pit considering spatial correlation.

Deep foundation pit settlement prediction based on machine learning is widely used for ensuring the safety of construction, but previous studies are limited to not fully considering the spatial correlation between monitoring points. This paper proposes a transformer-based deep learning method that considers both the spatial and temporal correlations among excavation monitoring points. The proposed method creates a dataset that collects all excavation monitoring points into a vector to consider all spatial correlations among monitoring points. The deep learning method is based on the transformer, which can handle the temporal correlations and spatial correlations. To verify the model's accuracy, it was compared with an LSTM network and an RNN-LSTM hybrid model that only considers temporal correlations without considering spatial correlations, and quantitatively compared with previous research results. Experimental results show that the proposed method can predict excavation deformations more accurately. The main conclusions are that the spatial correlation and the transformer-based method are significant factors in excavation deformation prediction, leading to more accurate prediction results.

A novel technique for constructing prefabricated subway stations under open excavation

Prefabricated construction is essential for realising green, efficient and sustainable development of rail transit. However, limited space in foundation pits and cross-interference with inner struts mean that the advantages of existing prefabrication technology cannot be leveraged effectively to build subway stations under open excavation with inner support. In this paper, this problem is addressed by introducing a modular design method and two novel connection technologies. The proposed modular design method is sufficiently adaptable to balance the use of space between the station structure and the inner struts. The two proposed connection technologies provide efficient ways to assemble different concrete segments with two newly developed joints – namely, a CHC joint (comprising two C-shaped and one H-shaped steel members) and a flexible lock joint – in the circumferential and longitudinal directions, respectively. The first application of this fully prefabricated scheme in the Shenzhen Metro shows the huge potential of this technology for constructing subway stations under open-cut conditions, and its advantages in technical, economic and social aspects reveal wide application prospects in rail transit.

Numerical Analysis of the Influence of Deep Excavation on Nearby Pile Foundation Building

In this paper, a numerical simulation is used to establish a three-dimensional model, which considers the height of buildings, the relative position between buildings, and foundation pits. These were studied in detail to investigate the changes in settlement of adjacent buildings and the displacement and internal force of piles caused by deep foundation pit excavation. The results indicate that the number of floors in the building, along with the angle and distance between the building and the excavation pit, have a significant impact on the settlement of the building and the deformation and internal force variation in the piles. For example, when D = 0.1 H, with the increase in the number of floors, the increase in the bending moment of pile 1 at the pile shaft is 62.63 kN·m, and the increase in the bending moment at the pile head is 224.72 kN·m. At this point, the maximum horizontal displacement of the pile shaft occurs at approximately 1.27 H. When θ = 45∘, the maximum difference between the maximum and minimum deformations of the building is 9.71 mm. When D ≤ 1.0 H, the majority of the building is in the primary influence range of surface settlement behind the wall, and the building undergoes a combined deformation of ‘upper convex’ and ‘concave’. When D > 1.0 H, the building predominantly resides in the secondary influence range, and the building undergoes a deformation of ‘upper convex’.

Measurement and Analysis of Deformation of Underlying Tunnel Induced by Foundation Pit Excavation

The excavation of a foundation pit can exert a notable impact on the underlying tunnel. This research paper aims to analyze and synthesize measured deformation outcomes caused by foundation pit excavation on the underlying tunnel. The paper employs a two-stage analysis approach to derive the calculation formula for additional stress and the deformation control equation of the adjacent tunnel under the influence of foundation pit excavation. Subsequently, the Hermite spectrum method is applied to transform the deformation control equation of the underlying tunnel into a set of linear equations, enabling the determination of the deformation curve. To verify the precision of the theoretical calculation method, a comparative study is conducted between theoretical results and actual measurements. Moreover, a sensitivity analysis of crucial project factors is performed. The research findings reveal minimal disparity between theoretical calculation outcomes and measured deformation of the underlying tunnel, thus affirming the accuracy and rationality of the theoretical calculation formula. The excavation of the foundation pit leads to an uplift deformation in the underlying tunnel, resulting in an “n”-shaped deformation profile. Notably, the stiffness of the foundation soil and the depth at which the tunnel is buried emerge as pivotal factors influencing the deformation of the underlying tunnel. As the stiffness of the foundation soil and the depth of tunnel burial increase, the uplift deformation gradually diminishes, albeit within a restricted range of reduction.

Monitoring and numerical simulation analysis of a pit-in-pit excavation of the first branch line of Lanzhou Metro

Abstract Based on the pit excavation project in a station of Lanzhou Metro, the horizontal displacement of bored piles, the ground settlement around the foundation pit, and the supporting axial force in the foundation pit were tested on site. The changing rules and influencing factors of horizontal displacement of external and internal bracing piles during foundation pit construction are analyzed. Comparing the measured results with the numerical simulation results, the results show that the finite element calculation results can meet the engineering needs, the pile-support system can effectively control the deformation of the foundation pit, and the bottom of the outer pit has an obvious uplift. The numerical simulation is used to study the influence of different working conditions on the deformation of the foundation pit. The results show that the inner support of the foundation pit can control soil deformation more effectively than the outer support of the foundation pit. The study can provide a reference for the construction of such foundation pit in Lanzhou in the future.

Experimental Study of Hardening Small Strain Model Parameters for Strata Typical of Zhengzhou and Their Application in Foundation Pit Engineering

The hardening small strain (HSS) model, which considers the non-linear characteristics of the shear modulus of soil in the small strain range, is commonly utilized in the numerical analysis of excavations in sensitive environments. In order to ascertain the parameters of an HSS model for strata typical of Zhengzhou, an extensive series of laboratory tests was executed. Subsequently, a statistical analysis was utilized to establish the relationships between the principal parameters. A three-dimensional finite element model was established based on the excavation of representative strata in Zhengzhou. The accuracy and applicability of the model parameters were verified using the field measurement data. In addition, an analysis of the sensitivity of the main HSS model parameters to the foundation pit deformation was also carried out. The results show that the HSS model can analyze excavation deformation with greater precision than the hardening soil (HS) model or the Mohr–Coulomb (MC) model. The small strain parameters G0ref and γ0.7 have a great influence on the horizontal displacement of the support and the vertical displacement of soil behind the wall, respectively. The research results serve as a reliable foundation for both the analysis of excavation deformation and the determination of HSS model parameters for strata typical of Zhengzhou.

Prediction of retaining structure deformation of ultra-deep foundation pit by empirical mode decomposition with recurrent neural networks

Prediction of retaining structure deformation of ultra-deep foundation pit by empirical mode decomposition with recurrent neural networks

Stability Analysis of Trench Wall for Diaphragm Wall in Ultra-Deep Circular Foundation Pit: A Comprehensive Investigation

Circular diaphragm walls are increasingly being used in ultra-deep foundation pits due to their arch-shaped bearing system, which provides reasonable structural support. The trench walls that form the circular ground connection wall are typically double-angled in shape, and their stability analysis remains a challenge. In this paper, an instability model for double-angled trench walls based on 3D sliding body analysis is proposed. The objective of this paper is to determine the minimum amount of slurry needed to maintain the integrity of the trench wall. The results show that the center of symmetry on the inside of the wall is the most vulnerable to damage, followed by the inside corner, and then the center and corner on the outside. The consideration of sliding bodies in overall and local stability calculations for double-angled trench wall shapes can provide a reasonable stability assessment.

Numerical analysis for supporting and deformation of complex foundation pit groups in unstable areas of karst strata

Due to the extensive karst development zone in karst areas, the stability of the underground soil layer is poor. The support of foundation pits in this area will be affected by complex environmental factors, and if not handled properly, it will cause significant safety hazards and economic losses. In this paper, the three-dimensional finite element model of the complex foundation pit and adjacent foundation pit group was established with the help of Midas GTS NX numerical software, and numerical simulation was carried out for the whole foundation pit excavation and construction process, and the deformation results of the adjacent foundation pit support structure of the complex foundation pit group and the soil outside the foundation pit were obtained. The results show that the underground wall of the complex foundation pit shifted to the north under the action of buttresses, with a similar “cantilever” displacement pattern on the south side of the underground wall in the center, a “push-back displacement” on the north side of the underground wall in the center, and a “ventral” displacement pattern at the corners of the grounded wall and on the east and west sides. Combined with the field measurement data, the support piles in the internal support system have a “cantilever” displacement pattern under the condition of massive soil unloading in the vicinity of the foundation pit, while the supporting piles show a “parabolic” displacement pattern under the action of the corner internal support. The deformation characteristics of the foundation pit in the presence of adjacent pits are significantly different from the results based on empirical laws. The results of the above study will provide useful technical guidance for the safety of excavation support for foundation pit groups in complex environments and the reasonable control of the surrounding environment.