Search Results (78)

Under the adverse geological conditions of silty soft soil in coastal, lakeside, and river areas of countries worldwide, safety and quality during deep foundation pit construction are research challenges that researchers must overcome. Through 3D simulation, micro-finite element coupling modeling and construction site monitoring tests, this paper comprehensively analyzes the formation mechanism and causes of deep foundation pit foundation quality defects and diseases under the most unfavorable environment and multi-factor interference and puts forward scientific treatment suggestions. The research process accurately applies multidisciplinary coupling model research such as computer science, instrument science and technology, and material mechanics to solve the impact of multi-factor and uncertain environments on construction. The final research results provide sufficient theoretical and physical cases for improving the safety and stability of deep foundation pits under soft foundation conditions and provide rich practical specifications for the testing, monitoring and construction of similar projects; it provides a strong guarantee for the global deep foundation pit monitoring and early warning system under soft foundation conditions. Full article

Seismic risk assessment is pivotal for ensuring the reliability of prefabricated subway stations, where selecting optimal intensity measures (IMs) critically enhances probabilistic seismic demand models and fragility analysis. While peak ground acceleration (PGA) is widely adopted for above-ground structures, its suitability for underground systems remains debated due to distinct dynamic behaviors. This study identifies the most appropriate IMs for soft soil-embedded prefabricated subway stations at varying depths through nonlinear finite element modeling and develops corresponding fragility curves. A soil–structure interaction model was developed to systematically compare seismic responses of shallow-buried, medium-buried, and deep-buried stations under diverse intensities. Incremental dynamic analysis was employed to construct probabilistic demand models, while candidate IMs (PGA, PGV, and v_rms) were evaluated using a multi-criteria framework assessing correlation, efficiency, practicality, and proficiency. The results demonstrate that burial depth significantly influences IM selection: PGA performs optimally for shallow depths, peak ground velocity (PGV) excels for medium depths, and root mean square velocity (v_rms) proves most effective for deep-buried stations. Based on these optimized IMs, seismic fragility curves were generated, quantifying damage probability characteristics across burial conditions. The study provides a transferable IM selection methodology, advancing seismic risk assessment accuracy for prefabricated underground infrastructure. Through a systematic investigation of the correlation between IM applicability and burial depth, coupled with the development of fragility relationships, this study establishes a robust technical framework for enhancing the seismic performance of subway stations, and provides valuable insights for seismic risk assessment methodologies in underground infrastructure systems. Full article

The development of underground spaces is crucial for modern urban environments, particularly in coastal cities with prevalent soft soil conditions. Deep foundation excavation works in such areas present technical challenges due to complex deformation phenomena including soil settlement and the lateral displacement of supporting structures. This study analyzes deformation patterns associated with deep foundation pit excavations in Ningbo’s soft soil areas by examining 10 cases of subway station projects. This study evaluated the relationship between the maximum surface settlement and various engineering parameters using statistical and comparative analyses and also compared the results of each relationship with those of other regional studies. The results indicate that multiple coupled parameters—the excavation depth, diaphragm-wall-embedded depth ratio, support system stiffness, and pit aspect ratio—significantly shape the deformation patterns. The average ratio of the maximum surface settlement to the excavation depth is 0.64%, notably higher than in regions such as Hangzhou and Shanghai. The maximum lateral displacement in this study averaged 0.37% of the excavation depth. The maximum lateral displacement of the diaphragm walls in this study averaged 0.37% of the depth of excavation and, in addition, the average positive correlation between the depth at which the maximum lateral displacement occurred and the depth of pit excavation was $h_{\delta \mathrm{h}\mathrm{m}\mathrm{a}\mathrm{x}}=H_e$ + 1.46. A positive correlation also emerged between the maximum ground settlement and lateral displacement of the diaphragm walls. But the influence of the shape of the pit on the deformation will show different types of relationships depending on the area and geotechnical conditions, which need to be further investigated. Full article

To the aim of this paper is to study the structural and environmental deformation characteristics caused by the excavation of a very large deep foundation pit in the sandy soil area of Beijing. This paper is based on numerical simulation and field monitoring results and these results are compared with the deformation data of a soft soil foundation pit in the Shanghai area. The results show that the influence of the environment surrounding the super-large deep foundation pit project studied in this paper is obviously too great. With the progress of construction, the deformation rate and deformation amount of the column at the side of the foundation pit are obviously higher than that of the column in the middle area. Due to the “hysteresis” of stress transfer in the sand, the settlement of the roof of the north wall is delayed and the deformation range is smaller than that of the south wall. Compared with the conventional foundation pit, the influence area of the surrounding surface is larger, reaching 4 He (He is the depth of the foundation pit). Δvmax (the maximum surface settlement) is between 0.2~2.3% He, and the relationship between δvmax = 1.43% Vwm. Through orthogonal experiments and numerical simulation, it is concluded that the deformation of foundation pit structure and its surrounding environment is more sensitive to excavation unloading, precipitation amplitude, and column spacing. It is also concluded that the strong, medium, and weak influence areas of the bottom uplift after foundation pit construction are (0~0.07) × L, (0.07~0.14) × L, and (0.14~0.5) × L, respectively (L is the width of foundation pit). When the embedment ratio is between 1.8~2.4, the displacement mode of the parapet structure is T mode; when the embedment ratio is between 2.4~3.4, the displacement mode of the parapet structure is RB mode. Full article

As foundation pit engineering is developing towards larger and deeper designs, the requirements for controlling excavation-induced deformation are becoming increasingly stringent, particularly in complex urban environments and soft soil areas. In recent years, numerous foundation pit projects have incorporated Hydraulic Servo Steel Support (HSSS) to actively manage the axial forces of the internal supports, which has achieved significant reductions in the displacement of the retaining structures (δ_D). An investigation of engineering cases in soft soil areas revealed that the average ratios of the δ_D to the excavation depth (H) for foundation pits with and without servo control systems were 0.11% and 0.38%, respectively. This study analyzed the monitoring data related to the δ_D, the deformation of the soil outside the foundation pit, and the changes in the axial force of the internal supports in a deep foundation pit located in Hangzhou City, China. The results indicated that employing the zoned excavation and HSSS effectively controlled the δ_D. During the excavation stage, the HSSS ensured that the δ_D remained below the design threshold, although some deformation persisted during the dismantling stage. Additionally, adjustments to the axial force of the internal supports affected the axial force of the adjacent supports, with a common occurrence of reverse pulling force in the first-layer supports due to the action of the HSSS. Therefore, further optimization of the HSSS is necessary to enhance control effectiveness. Full article

With the ongoing urbanization and densification of cities worldwide, the planning and utilization of urban underground space (UUS) have become crucial for developing urban underground infrastructure. Given the limited construction space within dense urban areas and the influence of declining groundwater levels, technologies such as open caissons and various vertical shaft methods have been introduced for UUS development. However, the dissemination of these technologies remains fragmented across different domains, lacking systematic summarization. A comprehensive, up-to-date overview of open caisson and vertical shaft technologies is essential for their effective application. In the manuscript, a systematic analysis of vertical shaft technologies, specifically focusing on their use in soft ground conditions, is conducted. The analysis is based on an extensive literature review and case study evaluation. It addresses the unique challenges posed by high compressibility, low bearing capacity, and groundwater sensitivity. Conventional shaft technologies and mechanized systems, including open caissons, drilled shafts, and the novel pressed-in ultra-deep assembled shafts (PIAUS), are evaluated systematically. Key aspects such as design principles, construction techniques, and stability in soft soils are discussed. The limitations of conventional methods in soft UUS are highlighted, while the advantages of advanced mechanized systems—such as rapid construction, reduced environmental impact, and improved safety—are emphasized. A detailed comparison of case studies demonstrates that PIAUS construction technology is particularly efficient in urban areas with confined spaces, dense building conditions, and ground conditions up to 200 MPa, with shaft diameters up to 12.8 m and depths of 115.2 m. Additionally, its suitability for rapid construction in soft and medium ground conditions is supported by undrained excavation with parallel excavation and liner sinking techniques. The PIAUS technology shows considerable potential for future projects, including shield construction shafts, ventilation shafts for tunnels, underground parking garages, and stormwater storage wells. This manuscript also highlights emerging mechanized methods in underground space development, their advantages, limitations, and areas for future research and improvement. Full article

The issue of geotechnical hazards induced by excavation in soft soil areas has become increasingly prominent. However, the retaining structure and surface settlement deformation induced by the creep of soft soil and spatial effect of the excavation sequence are not fully considered where only elastic–plastic deformation is used in design. To understand the spatiotemporal effects of excavation-induced deformation in soft soil pits, a case study was performed with the Huaxi Park Station of the Suzhou Metro Line S1, Jiangsu Province, China, as an example. Field monitoring was conducted, and a three-dimensional numerical model was developed, taking into account the creep characteristics of mucky clay and spatiotemporal response of retaining structures induced by excavations. The spatiotemporal effects in retaining structures and ground settlement during excavation processes were analyzed. The results show that as the excavation depth increased, the horizontal displacement of the diaphragm walls increased linearly and tended to exhibit abrupt changes when approaching the bottom of the pit. The maximum horizontal displacement of the wall at the west end well was close to 70 mm, and the maximum displacement of the wall at the standard section reached approximately 80 mm. The ground settlement on both pit sides showed a “trough” distribution pattern, peaking at about 12 m from the pit edge, with a settlement rate of −1.9 mm/m per meter of excavation depth. The excavation process directly led to the lateral deformation of the diaphragm walls, resulting in ground settlement, which prominently reflected the time-dependent deformation characteristics of mucky soft soil during the excavation process. These findings provide critical insights for similar deep excavation projects in mucky soft soil, particularly regarding excavation-induced deformations, by providing guidance on design standards and monitoring strategies for similar geological conditions. Full article

The highway network is densely distributed in the southeast coast of China. Highway subgrades passing through soft soil areas often produce large settlements, resulting in pavement cracking, bridgehead jumping, and other diseases. In order to study the effect of three trenchless treatment technologies of oblique jet grouting pile (JGP), lateral displacement limiting pile (LDLP), and load reducing pipe (LRP), centrifugal model tests were carried out under three treated conditions and without treatment. Based on the data of pore water pressure and settlement in the range of the half embankment model and outside the embankment, the settlement characteristics of highway soft soil foundation during the test simulation were studied, and the characteristics of different treatment methods were compared. The high level of pore water pressure corresponds to the rapid development of settlement. The average settlement during the existing operation period accounts for 96.7% of the total settlement of the simulation period, and the settlement does not converge. The methods can effectively inhibit the development of settlement, and each has its own characteristics: the LRP method does not involve foundation treatment, so its settlement characteristics are closest to that without treatment. The LDLP method can obviously limit the settlement within the embankment range and the pore water dissipation. The JGP method enhances the synergistic deformation ability of the embankment and significantly decreases the differential settlement. Full article

The hardening soil model with small-strain stiffness (HSS model) is widely applied in deep foundation pit engineering in coastal soft-soil areas, yet it is characterized by a multitude of parameters that are relatively cumbersome to acquire. In this study, we incorporate a genetic algorithm and a back-propagation neural network (BPNN) model into an inversion analysis for HSS model parameters, with the objective of facilitating a more streamlined and accurate determination of these parameters in practical engineering. Utilizing horizontal displacement monitoring data from retaining structures, combined with local engineering, both a BPNN model and a BPNN optimized by a genetic algorithm (GA-BPNN) model were established to invert the stiffness modulus parameters of the HSS model for typical strata. Subsequently, numerical simulations were conducted based on the inverted parameters to analyze the deformation characteristics of the retaining structures. The performances of the BPNN and GA-BPNN models were evaluated using statistical metrics, including R², MAE, MSE, WI, VAF, RAE, RRSE, and MAPE. The results demonstrate that the GA-BPNN model achieves significantly lower prediction errors, higher fitting accuracy, and predictive performance compared to the BPNN model. Based on the parameters inverted by the GA-BPNN model, the average compression modulus $E_{s1-2}$, the reference tangent stiffness modulus $E_{oed}^{ref}$, the reference secant stiffness modulus $E_{50}^{ref}$, and the reference unloading–reloading stiffness modulus $E_{ur}^{ref}$ for gravelly cohesive soil were determined as $E_{oed}^{ref}=0.83E_{s1-2}$ and $E_{ur}^{ref}={8.14E}_{50}^{ref}$; for fully weathered granite, $E_{oed}^{ref}=1.54E_{s1-2}$ and $E_{ur}^{ref}={5.51E}_{50}^{ref}$. Numerical simulations conducted with these stiffness modulus parameters show excellent agreement with monitoring data, effectively describing the deformation characteristics of the retaining structures. In situations where relevant mechanical tests are unavailable, the application of the GA-BPNN model for the inversion analysis of HSS model parameters is both rational and effective, offering a reference for similar engineering projects. Full article

In soft soil foundations, the utilization of box-type retaining walls as a support method represents a novel approach. This study focuses on investigating the key factors influencing lateral wall deflection and ground settlement behind the wall in deep excavation projects supported by box-type retaining walls. Based on a practical engineering case in Shanghai, the large deformation Lagrangian numerical simulation software FLAC-3D is employed to simulate the displacement of box-type retaining walls as well as the surface settlement surrounding the excavation pit during the excavation process of deep-foundation pits. This research encompasses aspects such as the box size, the filling material within the box, and the constituent materials of the retaining wall. Ultimately, it is concluded that variations in the size of the box-retaining wall have a significant impact on wall deflection and surrounding ground settlement, while the filling material and constituent materials have relatively minor effects. This study provides a theoretical basis and scientific reference for the design and construction of box-type retaining walls in deep-foundation pit engineering. Full article

In forest ecosystems, the application of hyperspectral (HS) imagery offers unprecedented opportunities for refined identification and classification. The diversity and complexity of forest cover make it challenging for traditional remote-sensing techniques to capture subtle spectral differences. Hyperspectral imagery, however, can reveal the nuanced changes in different tree species, vegetation health status, and soil composition through its nearly continuous spectral information. This detailed spectral information is crucial for the monitoring, management, and conservation of forest resources. While Convolutional Neural Networks (CNNs) have demonstrated excellent local context modeling capabilities in HS image classification, their inherent network architecture limits the exploration and representation of spectral feature sequence properties. To address this issue, we have rethought HS image classification from a sequential perspective and proposed a hybrid model, the Spectral Weaver, which combines CNNs and Transformers. The Spectral Weaver replaces the traditional Multi-Head Attention mechanism with a Channel Attention mechanism (MCA) and introduces Centre-Differential Convolutional Layers (Conv2d-cd) to enhance spatial feature extraction capabilities. Additionally, we designed a cross-layer skip connection that adaptively learns to fuse “soft” residuals, transferring memory-like components from shallow to deep layers. Notably, the proposed model is a highly flexible backbone network, adaptable to both hyperspectral and multispectral image inputs. In comparison to traditional Visual Transformers (ViT), the Spectral Weaver innovates in several ways: (1) It introduces the MCA mechanism to enhance the mining of spectral feature sequence properties; (2) It employs Centre-Differential Convolutional Layers to strengthen spatial feature extraction; (3) It designs cross-layer skip connections to reduce information loss; (4) It supports both multispectral and hyperspectral inputs, increasing the model’s flexibility and applicability. By integrating global and local features, our model significantly improves the performance of HS image classification. We have conducted extensive experiments on the Gaofen dataset, multispectral data, and multiple hyperspectral datasets, validating the superiority of the Spectral Weaver model in forest hyperspectral image classification. The experimental results show that our model achieves 98.59% accuracy on multispectral data, surpassing ViT’s 96.30%. On the Jilin-1 dataset, our proposed algorithm achieved an accuracy of 98.95%, which is 2.17% higher than ViT. The model significantly outperforms classic ViT and other state-of-the-art backbone networks in classification performance. Not only does it effectively capture the spectral features of forest vegetation, but it also significantly improves the accuracy and robustness of classification, providing strong technical support for the refined management and conservation of forest resources. Full article

The pre-stressed high-strength concrete (PHC) nodular pile is a type of PHC pile with a variable cross-section of the pile shaft, and it has normally been applied in ground treatment projects in recent years. The PHC nodular pile shaft consists of nodules, which introduce differences for the load transfer mechanism of the PHC nodular pile compared to the conventional PHC pipe pile. In this paper, the load transfer mechanism and influencing factors of the bearing capacity of the PHC nodular pile were investigated based on a group of field tests and numerical simulations. The following conclusions were obtained based on the analysis of the field test and simulation results: the nodules along the pile could effectively increase the ultimate capacity of the PHC nodular pile, and the field test results showed that the ultimate capacity of 450 (500) mm PHC nodular piles was about 1.23–1.38 times of the 450 mm PHC pipe pile after being cured for 40 days, which can be used for the design of PHC nodular pile. The simulation results showed that the bearing capacity of the PHC nodular pile would decrease with the increase in nodular spacing and nodular length along the pile shaft, while increasing with the increase in nodular diameter, and the diameter of the nodule can be increased moderately to improve the ultimate capacity of the PHC nodular pile. Full article

This research develops and evaluates a recyclable corrugated cardboard vibration isolation box reinforced with balsa wood as an alternative to traditional open trench methods for mitigating ground-borne environmental body waves. This study includes designing and testing scaled prototypes, laboratory analyses, prototype fabrication, and full-scale field experiments. In soft ground conditions, ensuring slope stability during deep excavations is a key engineering challenge for open trenches. For this purpose, scaled prototypes were subjected to laboratory tests to assess the resistance of the wave barrier’s wall surface. Numerical analyses were also conducted to evaluate the strength of the internal lattice structure under various loads. A prototype was fabricated for on-site experiments simulating real-world conditions. Field experiments evaluated the vibration isolation performance of the proposed barrier. Accelerometer sensors were strategically placed to gather data, analyzing ground surface vibrations for free field motions to assess the vibration shielding efficiency of both the open trench method and the corrugated vibration isolation box, with and without Styrofoam infill. This study concludes that the recyclable corrugated vibration isolation box is a viable alternative, offering comparable or improved vibration isolation efficiency in soft soil conditions while promoting environmental sustainability using recyclable materials. Full article

The overall reinforcement of soft soil foundation has the disadvantages of large engineering quantity and high cost. When the pile foundation bears horizontal loads in the soil, the mechanical properties of the soil near the surface have a greater impact on it compared to the deep soil. Therefore, studying the influence of shallow soil reinforcement on the horizontal bearing capacity of pile foundations has important engineering significance. Studying the influence of shallow soft soil reinforcement around piles on the horizontal bearing performance of piles is of great significance for improving the economic efficiency of pile foundation reinforcement technology in soft soil areas. In this paper, seven pile-soil finite element models are established based on ABAQUS 2022 software to study the influence of shallow reinforcement on the horizontal bearing capacity of single pile. The models were established on the basis of a field test and its validity was verified. The influence of different reinforcement degrees on the horizontal bearing capacity of piles is analyzed by taking the reinforcement width and reinforcement depth as variables. The results indicate that shallow ground improvement significantly enhances the horizontal bearing capacity of the pile. The horizontal bearing capacity of the pile is increased by 83.0%, 104.3%, and 224.4%, respectively, corresponding to a reinforcement width of 2 times, 3 times, and 4 times the diameter of the pile, respectively. With the increase of the reinforcement width, the bending moment and deformation of the pile under the same horizontal load decrease significantly, while it has no significant effect on the location of the maximum bending moment of the pile. The bearing capacity of the pile foundation gradually increases with the increase of the reinforcement depth. Compared with the unreinforced situation, the horizontal bearing capacity of the pile body is increased by 224.4%, 361.3%, and 456.8%, respectively, corresponding to a reinforcement depth of 0.1 times, 0.2 times, and 0.3 times the pile length. As the reinforcement depth increases, the corresponding increase in bearing capacity does not increase linearly, but gradually decreases. This indicates that blindly carrying out deep soil reinforcement without comprehensive evaluation is not advisable. Full article

Artificial intelligence (AI) has enabled several optimization techniques for structural design, including machine learning, evolutionary algorithms, as in the case of genetic algorithms, reinforced learning, deep learning, etc. Although the use of AI for weight optimization in steel and concrete buildings has been extensively studied in recent decades, multi-objective optimization for reinforced concrete (RC) and steel buildings remains challenging due to the difficulty in establishing independent objective functions and obtaining Pareto fronts. The well-known Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is an efficient genetic algorithm approach for multi-objective optimization. In this work, the NSGA-II approach is considered for the multi-objective structural optimization of three-dimensional RC buildings subjected to earthquakes. For the objective of this study, two function objectives are considered: minimizing total cost and the probability of structural failure, which are obtained via several nonlinear seismic analyses of the RC buildings. Beams and columns’ cross-sectional dimensions are selected as design variables, and the Mexican Building Code (MBC) specifications are imposed as design constraints. Pareto fronts are obtained for two RC-framed buildings located in Mexico City (soft soil sites), which demonstrate the efficiency and accuracy of NSGA-II for structural optimization. Full article