Search Results (37)

Significant discrepancies persist between the predicted and measured bearing capacities of Strength Composite (SC) piles in engineering practice, largely due to incomplete consideration of dominant failure modes and the absence of scientifically calibrated adjustment coefficients. Existing design specifications treat side and tip resistance inconsistently and often neglect failures induced by insufficient pile material strength, which compromises accuracy and reliability. To address these limitations, this study systematically analyzed static load test data from 159 SC piles across 44 projects. Statistical evaluation revealed clear dependencies between soil type, pile–soil interface performance, and failure mechanisms, from which stratified adjustment coefficients of side resistance and the unified adjustment coefficient of tip resistance were derived. On this basis, a new calculation method for pile capacity was developed that, for the first time, explicitly integrates material strength limitations and interface failure mechanisms into design. Validation against 112 additional test piles confirmed that over 50% of predicted-to-measured ratios approximated 1.0, and 82.1% fell within ±20%. The study proposes a calculation method for SC pile bearing capacity that is broadly applicable, simple in form, and explicitly accounts for dominant failure modes, thereby providing both theoretical rigor and engineering practicality. Full article

As civil engineering projects grow increasingly complex, ensuring pile integrity is essential for pile bearing capacity and structural safety. Pile integrity testing (PIT) has long been a focal point for researchers and engineers. With the rapid development of industrial-level advancements and artificial intelligence technology, PIT methods have undergone significant technological advancements. This paper reviews traditional PIT techniques, including low-strain integrity testing and thermal integrity profiling. The review covers the principles, advantages, limitations, and recent developments of various testing techniques. Additionally, recent advances in artificial intelligence (AI) techniques, particularly in signal processing and data-driven recognition methods, are discussed. Finally, the advantages, limitations, and potential future research directions of existing methods are summarized. This paper aims to offer a systematic reference for researchers and engineers in PIT, synthesizing technical details of traditional methods and their AI-enabled advancements. Furthermore, it explores potential directions for integrating AI with PIT, with a focus on key challenges such as noisy signal interpretation and regulatory barriers in applications. Full article

The safety associated with the bearing capacity of pile foundations is intrinsically linked to the overall safety, stability, and economic viability of structural systems. In response to the need for rapid and precise predictions of pile bearing capacity, this study introduces a kernel extreme learning machine (KELM) prediction model optimized through a multi-strategy improved beetle optimization algorithm (IDBO), referred to as the IDBO-KELM model. The model utilizes the pile length, pile diameter, average effective vertical stress, and undrained shear strength as input variables, with the bearing capacity serving as the output variable. Initially, experimental data on pile bearing capacity was gathered from the existing literature and subsequently normalized to facilitate effective integration into the model training process. A detailed introduction of the multi-strategy improved beetle optimization algorithm (IDBO) is provided, with its superior performance validated through 23 benchmark functions. Furthermore, the Wilcoxon rank sum test was employed to statistically assess the experimental outcomes, confirming the IDBO algorithm’s superiority over other prevalent metaheuristic algorithms. The IDBO algorithm was then utilized to optimize the hyperparameters of the KELM model for predicting pile bearing capacity. In conclusion, the statistical metrics for the IDBO-KELM model demonstrated a root mean square error (RMSE) of 4.7875, a coefficient of determination (R²) of 0.9313, and a mean absolute percentage error (MAPE) of 10.71%. In comparison, the baseline KELM model exhibited an RMSE of 6.7357, an R² of 0.8639, and an MAPE of 18.47%. This represents an improvement exceeding 35%. These findings suggest that the IDBO-KELM model surpasses the KELM model across all evaluation metrics, thereby confirming its superior accuracy in predicting pile bearing capacity. Full article

Detecting stored-grain pests on the surface of the grain pile plays an important role in integrated pest management (IPM), which is crucial for grain security. Recently, numerous deep learning-based pest detection methods have been proposed. However, a critical limitation of existing methods is their inability to detect out-of-distribution (OOD) categories that are unseen during training. When encountering such objects, these methods often misclassify them as in-distribution (ID) categories. To address this challenge, we propose a one-stage framework named PestOOD for out-of-distribution stored-grain pest detection via flow-based feature reconstruction. Specifically, we propose a novel Flow-Based OOD Feature Generation (FOFG) module that generates OOD features for detector training via feature reconstruction. This helps the detector learn to recognize OOD objects more effectively. Additionally, to prevent network overfitting that may lead to an excessive focus on ID feature extraction, we propose a Noisy DropBlock (NDB) module and integrate it into the backbone network. Finally, to ensure effective network convergence, a Stage-Wise Training Strategy (STS) is proposed. We conducted extensive experiments on our previously established multi-class stored-grain pest dataset. The results show that our proposed PestOOD demonstrates superior performance over state-of-the-art methods, providing an effective AI-enabled solution to ensure grain security. Full article

The rapid proliferation of electric vehicles necessitates accurate forecasting of charging pile capacity for urban power system planning, yet existing methods for medium- to long-term prediction lack effective mechanisms to capture complex multi-factor relationships. To address this gap, a hybrid cointegration–BiLSTM framework is proposed for medium- to long-term load forecasting. Cointegration theory is leveraged to identify long-term equilibrium relationships between EV charging capacity and socioeconomic factors, effectively mitigating spurious regression risks. The extracted cointegration features and error correction terms are integrated into a bidirectional LSTM network to capture complex temporal dependencies. Validation using data from 14 cities in Hunan Province demonstrated that cointegration analysis surpassed linear correlation methods in feature preprocessing effectiveness, while the proposed model achieved enhanced forecasting accuracy relative to conventional temporal convolutional networks, support vector machines, and gated recurrent units. Furthermore, a 49% reduction in MAE and RMSE was observed when ECT-enhanced features were adopted instead of unenhanced groups, confirming the critical role of comprehensive feature engineering. Compared with the GRU baseline, the BiLSTM model yielded a 26% decrease in MAE and a 24% decrease in RMSE. The robustness of the model was confirmed through five-fold cross-validation, with ECT-enhanced features yielding optimal results. This approach provides a scientifically grounded framework for EV charging infrastructure planning, with potential extensions to photovoltaic capacity forecasting. Full article

Bridges are assets in every society, and their deterioration can have severe economic, social, and environmental consequences. Therefore, implementing effective asset management strategies is crucial to ensure bridge infrastructure’s long-term performance and safety. Roadmaps can serve as valuable tools for bridge asset managers, helping bridge engineers make informed decisions that enhance bridge safety while maintaining controlled life cycle costs. Although some bridge asset management roadmaps exist, such as the one published by the United States Federal Highway Administration (FHWA), there is a lack of structured research roadmaps that are both region-specific and adaptable as guiding frameworks for similar studies. For instance, the FHWA roadmap cannot be universally applied across diverse regional contexts. This study addresses this critical gap by developing a research roadmap tailored to Idaho, USA. The roadmap was developed using a three-phase methodological approach: (1) a comprehensive analysis of past and ongoing Department of Transportation (DOT)-funded research projects over the last five years, (2) a nationwide survey of DOT funding and research practices, and (3) a detailed assessment of Idaho Transportation Department (ITD) deficiently rated bridge inventory, including individual element condition states. In the first phase, three filtering stages were implemented to identify the top 25 state projects. A literature review was conducted for each project to provide ITD’s Technical Advisory Committee (TAC) members with insights into research undertaken by various state DOTs. Moreover, in the second phase, approximately six questionnaires were designed and distributed to other state DOTs. These questionnaires primarily covered topics related to bridge research priorities and funding allocation. In the final phase, a condition state analysis was conducted using data-driven methods. Key findings from this three-phase methodological approach highlight that ultra-high-performance concrete (UHPC), bridge deck preservation, and maintenance strategies are high-priority research areas across many DOTs. Furthermore, according to the DOT responses, funding is most commonly allocated to projects related to superstructure and deck elements. Finally, ITD found that the most deficient elements in Idaho bridges are reinforced concrete abutments, reinforced concrete pile caps and footings, reinforced concrete pier walls, and movable bearing systems. These findings were integrated with insights from ITD’s TAC to generate a prioritized list of 23 high-impact research topics aligned with Idaho’s specific needs and priorities. From this list, the top six topics were selected for further investigation. By adopting this strategic approach, ITD aims to enhance the efficiency and effectiveness of its bridge-related research efforts, ultimately contributing to safer and more resilient transportation infrastructure. This paper could be a helpful resource for other DOTs seeking a systematic approach to addressing their bridge research needs. Full article

The energy pile integrates shallow geothermal energy extraction with underground structural engineering, thereby expanding the functional applications and scope of pile foundations. Due to its widespread adoption, research on energy pile analysis theory has advanced significantly. Among existing analytical methods, the load transfer method is widely employed owing to its computational simplicity and readily obtainable parameters. However, current load transfer models for energy piles remain imperfect, primarily because their results often fail to accurately reflect real-world loading conditions. This study investigates the underlying causes of this discrepancy and proposes an iterative method to eliminate unbalanced forces at the pile head, based on the displacement coordination algorithm for energy pile load transfer. The calculated results at the pile head show an 18% reduction in error compared to previous studies. The average error compared with field test results is within 20%, with consistent trend patterns, confirming the feasibility of the proposed method. Computational results demonstrate that the proposed method effectively captures the combined effects of mechanical load and temperature variations on the bearing behavior of energy piles. It should be noted that this paper focuses specifically on improving the temperature-dependent load transfer method for energy piles. Consequently, the conventional load transfer method and results under purely mechanical loading are not discussed herein. Full article

In recent years, the frequent collapse of bridges has underscored the severe threats posed by ship collisions and seismic forces to bridge pile foundations, particularly under scour conditions. Scour significantly increases bending moments, weakens foundation stability, and exacerbates damage under ship impacts and seismic loading. This review systematically examines the dynamic responses of bridge pile foundations subjected to multi-hazard scenarios, focusing on how scour-induced degradation exacerbates the impacts of ship collisions and seismic events. The synthesis covers experimental studies, numerical simulations, and theoretical approaches, providing a comprehensive evaluation of methodologies and findings. Advanced bibliometric tools, such as CiteSpace and VOSviewer, are employed to identify research trends, hotspots, and collaborations in this domain. Additionally, the review highlights the integration of intelligent technologies for mitigating ship collision risks and improving bridge safety management in scour-prone environments. By consolidating existing knowledge, this paper can serve as a critical reference for understanding the compounded effects of scour and other hazards on bridge pile foundations, offering guidance for future research and engineering practices. Full article

This study systematically investigates the plastic deformation behavior and load-bearing mechanisms of micropiles through integrated scaled physical modeling and nonlinear finite element analysis, with particular emphasis on quantifying plastic hinge characteristics. The development of plastic deformation in laterally loaded micropiles was analytically described using plastic hinge theory, complemented by experimental-numerical validation. The key findings demonstrate the following points. (1) Existing empirical formulas for plastic hinge length, based on sectional parameters, show significant discrepancies, with experimental calibration establishing an optimized length of 2D. (2) Parametric FEM studies of three diameter groups (3–7% longitudinal reinforcement ratio) reveal that cross-sectional geometry and reinforcement configuration collectively govern nonlinear ultimate capacity, where ≤0.1% reinforcement ratio variation induces <5% bearing capacity deviation. (3) Square sections exhibit 12–18% higher capacity than circular equivalents of the equivalent dimensions, with this advantage amplifying with increasing pile size. (4) While excessive reinforcement ratios (>6%) impair structural performance, emergent scale effects effectively mitigate associated capacity reduction. These findings provide critical insights for optimizing micropile design in geotechnical applications through coordinated consideration of geometric, material, and scale parameters. Full article

This paper presents a comprehensive on-site decision-making framework for assessing the structural integrity of a jacket-type offshore platform in the Gulf of Mexico, installed at a water depth of 50 m. Six critical analyses—(i) static operation and storm, (ii) dynamic storm, (iii) strength-level seismic, (iv) seismic ductility (pushover), (v) maximum wave resistance (pushover), and (vi) spectral fatigue—are performed using SACS V16 software to capture both linear and nonlinear interactions among the soil, piles, and superstructure. The environmental conditions include multi-directional wind, waves, currents, and seismic loads. In the static linear analyses (i, ii, and iii), the overall results confirm that the unity checks (UCs) for structural members, tubular joints, and piles remain below allowable thresholds (UC < 1.0), thus meeting API RP 2A-WSD, AISC, IMCA, and Pemex P.2.0130.01-2015 standards for different load demands. However, these three analyses also show hydrostatic collapse due to water pressure on submerged elements, which is mitigated by installing stiffening rings in the tubular components. The dynamic analyses (ii and iii) reveal how generalized mass and mass participation factors influence structural behavior by generating various vibration modes with different periods. They also include a load comparison under different damping values, selecting the most unfavorable scenario. The nonlinear analyses (iv and v) provide collapse factors (Cr = 8.53 and RSR = 2.68) that exceed the minimum requirements; these analyses pinpoint the onset of plasticization in specific elements, identify their collapse mechanism, and illustrate corresponding load–displacement curves. Finally, spectral fatigue assessments indicate that most tubular joints meet or exceed their design life, except for one joint (node 370). This joint’s service life extends from 9.3 years to 27.0 years by applying a burr grinding weld-profiling technique, making it compliant with the fatigue criteria. By systematically combining linear, nonlinear, and fatigue-based analyses, the proposed framework enables robust multi-hazard verification of marine platforms. It provides operators and engineers with clear strategies for reinforcing existing structures and guiding future developments to ensure safe long-term performance. Full article

The poultry industry plays a pivotal role in global agriculture, with poultry serving as a major source of protein and contributing significantly to economic growth. However, the sector faces challenges associated with labor-intensive tasks that are repetitive and physically demanding. Automation has emerged as a critical solution to enhance operational efficiency and improve working conditions. Specifically, robotic manipulation and handling of objects is becoming ubiquitous in factories. However, challenges exist to precisely identify and guide a robot to handle a pile of objects with similar textures and colors. This paper focuses on the development of a vision system for a robotic solution aimed at automating the chicken rehanging process, a fundamental yet physically strenuous activity in poultry processing. To address the limitation of the generic instance segmentation model in identifying overlapped objects, a cost-effective, dual-active laser scanning system was developed to generate precise depth data on objects. The well-registered depth data generated were integrated with the RGB images and sent to the instance segmentation model for individual chicken detection and identification. This enhanced approach significantly improved the model’s performance in handling complex scenarios involving overlapping chickens. Specifically, the integration of RGB-D data increased the model’s mean average precision (mAP) detection accuracy by 4.9% and significantly improved the center offset—a customized metric introduced in this study to quantify the distance between the ground truth mask center and the predicted mask center. Precise center detection is crucial for the development of future robotic control solutions, as it ensures accurate grasping during the chicken rehanging process. The center offset was reduced from 22.09 pixels (7.30 mm) to 8.09 pixels (2.65 mm), demonstrating the approach’s effectiveness in mitigating occlusion challenges and enhancing the reliability of the vision system. Full article

Integral abutment bridges (IABs) have been widely applied in bridge engineering because of their excellent seismic performance, long service life, and low maintenance cost. The superstructure and substructure of an IAB are integrally connected to reduce the possibility of collapse or girders falling during an earthquake. The soil behind the abutment can provide a damping effect to reduce the deformation of the structure under a seismic load. Girders have not been considered in some of the existing published experimental tests on integral abutment–reinforced-concrete (RC) pile (IAP)–soil systems, which may not accurately represent real conditions. A pseudo-static low-cycle test on a girder–integral abutment–RC pile (GIAP)–soil system was conducted for an IAB in China. The experiment’s results for the GIAP specimen were compared with those of the IAP specimen, including the failure mode, hysteretic curve, energy dissipation capacity, skeleton curve, stiffness degradation, and displacement ductility. The test results indicate that the failure modes of both specimens were different. For the IAP specimen, the pile cracked at a displacement of +2 mm, while the abutment did not crack during the test. For the GIAP specimen, the pile cracked at a displacement of −8 mm, and the abutment cracked at a displacement of 50 mm. The failure mode of the specimen changed from severe damage to the pile top under a small displacement to damage to both the abutment and pile top under a large displacement. Compared with the IAP specimen, the initial stiffness under positive horizontal displacement (39.2%), residual force accumulation (22.6%), residual deformation (12.6%), range of the elastoplastic stage in the skeleton curve, and stiffness degradation of the GIAP specimen were smaller; however, the initial stiffness under negative horizontal displacement (112.6%), displacement ductility coefficient (67.2%), average equivalent viscous damping ratio (30.8%), yield load (20.4%), ultimate load (7.8%), and range of the elastic stage in the skeleton curve of the GIAP specimen were larger. In summary, the seismic performance of the GIAP–soil system was better than that of the IAP–soil system. Therefore, to accurately reflect the seismic performance of GIAP–soil systems in IABs, it is suggested to consider the influence of the girder. Full article

The use of the Vertical Shaft Sinking Machine (VSM) for shaft construction marks a significant advancement in modern technology and is recognized as one of the leading techniques in the field. However, much of the existing research focuses on mechanical and technical challenges, often overlooking the effects on surrounding soil and the structural integrity of shafts. This study demonstrates that increasing pile diameter by 20% improves load-bearing capacity by 15% and reduces soil settlement by 12%, though these improvements come with higher construction costs. Additionally, larger diameters improve lateral stability, but excessively long piles lead to diminishing returns. To address the limited research on reinforcement design in soft soils, a series of numerical models were employed to investigate the effects of pile spacing, length, and diameter on surrounding soil behavior. This in-depth analysis aims to provide a scientific foundation for optimizing VSM technology in caisson pile foundations, particularly in soft-soil conditions. Full article

As the foundation of marine infrastructure, pile groups are subjected to extreme wave loads. Existing research primarily focuses on regular waves and wave forces. There is limited research on the pressure distribution of pile bodies under extreme waves. This paper describes a wave flume experiment where waves of a self-proposed extreme wave type were generated. The experiment considers three water depths (25/35/45 cm), three wave-pushing velocities (20/30/40 cm/s), and two clear distances (D, 2D). A total of 216 measuring points equipped with digital pressure sensors captured the vertical and circumferential pressure distribution and wave positive force. The results show that (1) the vertical and circumferential pressure distribution patterns of each component pile and the single pile are similar in various loading scenarios and clear distances. (2) The measuring point pressure, pressure after circumferential integration, and wave positive force are positively correlated with wave-pushing velocity. (3) The wave pressure is positively correlated with the water depth, while the pressure after circumferential integration is negatively correlated with the water depth. (4) When the clear distance is D, the wave positive force coefficient of each component pile is less than 1.0. Full article

In urban metro construction, shield tunneling often needs to pass through building and bridge pile foundations, potentially affecting the stability of existing structures. Therefore, accurately assessing the impact of shield tunneling on bridges and buildings is crucial. This study presents a comprehensive prediction method combining numerical simulation and empirical formulas, taking the underpass project of the Shijiazhuang–Wuhan High-Speed Railway Bridge by Zhengzhou Metro Line 5 as a case study. Three-dimensional numerical model calculations were performed using finite element software to analyze the displacement and stress changes of buildings and tunnel structures at different construction stages, revealing the deformation patterns of buildings adjacent to the tunnel during shield tunneling. In particular, the ground settlement caused by twin-tunnel excavation was compared with Peck’s empirical formula to verify the reliability of the numerical simulation. The results show that twin-tunnel excavation exacerbates the horizontal displacement, uplift, and settlement of the ground, with maximum deformation rates increasing by 7.10%, 20%, and 11.4%, respectively. Comparing the ground deformation results of Peck’s empirical formulas with numerical calculations revealed similar trends in the settlement curves, with a maximum deviation of 6.67%. It can be concluded that using Peck’s empirical formula to calculate ground deformation characteristics complements the limitations of numerical simulations, making the assessment results more reliable. The findings of this study demonstrate that integrating numerical simulation with empirical formulas significantly enhances the reliability of deformation predictions in complex tunneling scenarios. This research not only offers a comprehensive safety assessment method for shield tunneling construction but also provides valuable guidance for the design and construction of similar projects, serving as a theoretical reference for future engineering endeavors. Full article