Search Results (984)

In predictive maintenance frameworks, risk curves are used as interpretable, real-time indicators of equipment degradation. However, existing approaches generally assume a monotonically increasing trend and neglect the corrective effect of maintenance, resulting in unrealistic or overly conservative risk estimations. This paper addresses this limitation by introducing a novel method that dynamically corrects risk curves through a quantitative measure of maintenance effectiveness. The method adjusts the evolution of risk to reflect the actual impact of preventive and corrective interventions, providing a more realistic and traceable representation of asset condition. The approach is validated with case studies on critical feedwater pumps in a combined-cycle power plant. First, individual maintenance actions are analyzed for a single failure mode to assess their direct effectiveness. Second, the cross-mode impact of a corrective intervention is evaluated, revealing both direct and indirect effects. Third, corrected risk curves are compared across two redundant pumps to benchmark maintenance performance, showing similar behavior until 2023, after which one unit accumulated uncontrolled risk while the other remained stable near zero, reflected in their overall performance indicators (0.67 vs. 0.88). These findings demonstrate that maintenance-corrected risk curves enhance diagnostic accuracy, enable benchmarking between comparable assets, and provide a missing piece for the development of realistic, risk-informed predictive maintenance strategies. Full article

While methods like cyclic triaxial testing and p-y model updating theory exist in geotechnical and offshore wind engineering, they have not been systematically applied to solve the specific deformation problems of offshore PV piles. This study investigates a specific offshore photovoltaic (PV) project in Qinhuangdao City, Hebei Province. Initially, field tests of horizontal static load on steel pipe pile foundations were conducted. A finite element model (FEM) of single piles was subsequently developed and validated. Further analysis examined the failure modes, initial stiffness, and ultimate resistance of offshore PV single piles in sandy soil foundations under varying pile diameters and embedment depths. The hyperbolic p-y curve model was modified by incorporating pile diameter size effects and embedment depth considerations. Key findings reveal the following: (1) The predominant failure mechanism of fixed offshore PV monopiles manifests as wedge-shaped failure in shallow soil layers. (2) Conventional API specifications and standard hyperbolic models demonstrate significant deviations in predicting p-y (horizontal soil resistance-pile displacement) curves, whereas the modified hyperbolic model shows good agreement with field measurements and numerical simulations. This research provides critical data support and methodological references for calculating the horizontal bearing capacity of offshore PV steel pipe pile foundations. Full article

Predictive maintenance of semi-autogenous grinding (SAG) mills reduces unplanned downtime and improves throughput. This study develops a data-driven prognostic model for production SAG mill using four years of operational data (temperature, voltage, current, motor speed, etc.). We follow a MATLAB (R2025a)-based prognostics and health management (PHM) workflow: data cleaning and synchronization; feature engineering in time and frequency domains (statistical moments, spectral power, bandwidth); normalization and clustering to separate operating regimes; and labeling of run-to-failure sequences for a recurring electrical failure mode. A health indicator is derived by scoring candidate features for monotonicity, trendability, and prognosability and fusing them into a condition index. Using MATLAB Predictive Maintenance Toolbox, we train and validate multiple Remaining Useful Life (RUL) learners including similarity-based, regression, and survival models on run-to-failure histories, selecting the best via cross-validated error and prediction stability. On held-out sets, the selected model forecasts RUL consistent with observed failure dates, providing actionable lead time for maintenance planning. The results highlight the practicality of deploying a PHM pipeline for SAG mills using existing plant data and commercial toolchains. Full article

To evaluate the creep and fatigue fracture lives of structural acrylic spliced components fabricated via bulk polymerization, and to elucidate the associated fracture mechanisms, this study conducted creep and fatigue tests on spliced coupons annealed at 85 °C and 65 °C, as well as base material coupons. The experimental life data were fitted using log-log linear regression models. Based on statistical analysis, a simple yet robust statistical framework was established for life prediction, featuring three design curves: 97.7% survival curves, improved 95% confidence interval lower bounds, and one-sided tolerance curves. Fractographic examination using scanning electron microscopy (SEM) was performed to characterize macroscopic failure modes. The results indicate distinct threshold behavior between stress levels and both creep and fatigue life. The creep threshold stresses are 25 MPa for the base material, 29 MPa for the spliced coupons annealed at 85 °C, and 17 MPa for the spliced coupons annealed at 65 °C. Corresponding fatigue threshold stress amplitudes are 21 MPa, 22 MPa, and 31 MPa, respectively. Failure in the base material is primarily initiated by randomly distributed internal defects, whereas failure in the spliced coupons is mainly caused by defects within the seam or interfacial tearing. Full article

This study investigates the axial performance of continuous helix screw piles compared to helical piles through full-scale compression and tension load testing in layered soils. Twenty-three piles were installed and tested. The results demonstrate that screw piles can achieve considerable axial capacity with lower installation torque than helical piles, particularly under tensile loading. The capacity-torque relationship for screw piles was more consistent across both compression and tension, likely due to reduced soil disturbance from the smaller helix projection. Strain gauge measurements indicated that screw piles act primarily as friction piles with the threaded shaft carrying most of the load, especially in stiff clay. On the other hand, the smooth portion of the pile shaft contributed only marginally to resistance in compression and none in tension. The calculated capacity based on theoretical equations aligned well with field results in compression, with screw piles best represented by cylindrical shear failure in sand and a combination of cylindrical shear and individual bearing failure in clay. However, there is greater variability between calculated and measured uplift capacity, possibly due to soil disturbance effects. Additionally, the commonly used helix spacing ratio (S/D) was found to be less applicable to screw piles in predicting failure mode due to their smaller shaft-to-helix diameter difference. Full article

Vibration loads during deep drilling are one of the main causes of reduced service life of drilling tools and emergency failure of downhole motors. This work investigates the adaptive operation of an original elastic element based on an open cylindrical shell used as part of a drilling shock absorber. The vibration protection device contains an adjustable radial clearance between the load-bearing shell and the rigid housing, which provides the effect of structural nonlinearity. This allows effective combination of two operating modes of the drilling shock absorber: normal mode, when the clearance does not close and the elastic element operates with increased compliance; and emergency mode, when the clearance closes and gradual load redistribution and increase in device stiffness occur. A nonconservative problem concerning the contact interaction of an elastic filler with a coaxially installed shaft and an open shell is formulated, and as the load increases, contact between the shell and the housing, installed with a radial clearance, is taken into account. Numerical finite element modeling is performed considering dry friction in contact pairs. The distributions of radial displacements, contact stresses, and equivalent stresses are examined, and deformation diagrams are presented for two loading modes. The influence of different cycle asymmetry coefficients on the formation of hysteresis loops and energy dissipation is analyzed. It is shown that with increasing load, clearance closure begins from local sectors and gradually covers almost the entire outer surface of the shell. This results in deconcentration of contact pressure between the shell and housing and reduction of peak concentrations of equivalent stresses in the open shell. The results confirm the effectiveness of the adaptive approach to designing shell shock absorbers capable of reliably withstanding emergency overloads, which is important for deep drilling where the exact range of external impacts is difficult to predict. Full article

The long-term stability of grout-reinforced fractured rock masses in acidic groundwater environments after tunnel fires is critical for the safe operation of underground engineering. In this study, grouting reinforcement tests were performed on fractured diorite specimens using a high-strength fast-anchoring agent (HSFAA), and their mechanical degradation and microstructural evolution mechanisms were investigated under coupled high-temperature (25–1000 °C) and acidic corrosion (pH = 2) conditions. Multi-scale characterization techniques, including uniaxial compression strength (UCS) tests, X-ray computed tomography (CT), scanning electron microscopy (SEM), three-dimensional (3D) topographic scanning, and X-ray diffraction (XRD), were employed systematically. The results indicated that the synergistic thermo-acid interaction accelerated mineral dissolution and induced structural reorganization, resulting in surface whitening of specimens and decomposition of HSFAA hydration products. Increasing the prefabricated fracture angles (0–60°) amplified stress concentration at the grout–rock interface, resulting in a reduction of up to 69.46% in the peak strength of the specimens subjected to acid corrosion at 1000 °C. Acidic corrosion suppressed brittle disintegration observed in the uncorroded specimens at lower temperature (25–600 °C) by promoting energy dissipation through non-uniform notch formation, thereby shifting the failure modes from shear-dominated to tensile-shear hybrid modes. Quantitative CT analysis revealed a 34.64% reduction in crack volume (V_ca) for 1000 °C acid-corroded specimens compared to the control specimens at 25 °C. This reduction was attributed to high-temperature-induced ductility, which transformed macroscale crack propagation into microscale coalescence. These findings provide critical insights for assessing the durability of grouting reinforcement in post-fire tunnel rehabilitation and predicting the long-term stability of underground structures in chemically aggressive environments. Full article

This study investigated the structural behavior of slab-on-grade (SOG) specimens constructed using two materials: conventional concrete reinforced with steel mesh and high-ductility fiber-reinforced cement composites (HDFRCC) containing 1.2% polyethylene (PE) fiber without steel reinforcement. The compressive strengths of conventional concrete and HDFRCC were 37 MPa and 54 MPa, respectively. The average flexural tensile strength of HDFRCC was 3.9 MPa at first cracking and 9.7 MPa at peak load. Punching shear tests were performed under three loading configurations: internal (center), edge, and corner loading. Crack patterns and load–displacement responses were analyzed for both material types. Under center loading, the experimentally measured load-bearing capacities were 174.52 kN for conventional concrete and 380.82 kN for HDFRCC, with both materials exhibiting reduced capacities under edge and corner loading. Analytical predictions demonstrated close agreement with the experimental results for conventional concrete but significantly underestimated the load capacity of HDFRCC SOG. This discrepancy is attributed to the strain-hardening and crack-bridging mechanisms inherent in HDFRCC, which contribute to enhanced strength beyond conventional analytical predictions. In terms of failure mode, the conventional concrete SOG exhibited the expected flexural failure. In contrast, the HDFRCC SOG experienced either flexural failure or a combination of flexural and punching failure, in contradiction to the analytical prediction of exclusive punching shear failure. These findings indicate that the punching shear resistance of the HDFRCC SOG is substantially higher than predicted. Full article

The waviness defect, a common manufacturing flaw in composite structures, can significantly impact the mechanical performance. This study investigates the effects of wrinkles on the ultimate load and failure modes of two Carbon Fiber Reinforced Composite (CFRC) laminates through compressive experiments and simulation analyses. The laminates have stacking sequences of [0]_10S and [45/0/−45/90/45/0/−45/0/45/0]_S. Each laminate includes four different waviness ratios (the ratio of wrinkle amplitude to laminate thickness) of 0%, 10%, 20% and 30%. In the simulation, a novel multiaxial progressive damage model is implemented via the user material (UMAT) subroutine to predict the compressive failure behavior of wrinkled composite laminates. This multiscale analysis framework innovatively features a 7 × 7 generalized method of cells coupled with stress-based multiaxial Hashin failure criteria to accurately analyze the impact of wrinkle defects on structural performance and efficiently transfer macro-microscopic damage variables. When any microscopic subcell within the representative unit cell (RUC) satisfies a failure criterion, its stiffness matrix is reduced to a nominal value, and the corresponding failure modes are tracked through state variables. When more than 50% fiber subcells fail in the fiber direction or more than 50% matrix subcells fail in the transverse or thickness direction, it indicates that the RUC has experienced the corresponding failure modes, which are the tensile or compressive failure of fibers, matrix, or delamination in the three axial directions. This multiscale model accurately predicted the load–displacement curves and failure modes of wrinkled composites under compressive load, showing good agreement with experimental results. The analysis results indicate that wrinkle defects can reduce the ultimate load-carrying capacity and promote local buckling deformation at the wrinkled region, leading to changes in damage distribution and failure modes. Full article

The growing demand for lightweight and reliable structures across aerospace, automotive, marine, and civil engineering has driven significant advances in polymer adhesive technology. These materials serve dual roles, functioning as matrices in composites and as structural bonding agents, where they must balance strength, toughness, durability, and sometimes sustainability. Recent review efforts have greatly enriched understanding, yet most approach the topic from specialized angles—whether emphasizing nanoscale toughening, multifunctional formulations, sustainable alternatives, or microscopic failure processes in bonded joints. While such perspectives provide valuable insights, they often remain fragmented, leaving open questions about how nanoscale mechanisms translate into macroscopic reliability, how durability evolves under realistic service conditions, and how mechanical responses interact across different loading modes. To address this, the present review consolidates knowledge on the performance of polymer adhesives under tension, shear, fracture, fatigue, creep, and impact. By integrating experimental findings with computational modeling and emerging data-driven approaches, it situates localized mechanisms within a broader structure–performance framework. This unified perspective not only highlights persistent gaps—such as predictive modeling of complex failure, scalability of nanomodified systems, and long-term durability under coupled environments—but also outlines strategies for developing next-generation adhesives capable of delivering reliable, high-performance bonding solutions for demanding applications. Full article

Lithium-ion batteries (LIBs) are critical components in safety-critical systems such as electric vehicles, aerospace, and grid-scale energy storage. Their degradation over time can lead to catastrophic failures, including thermal runaway and uncontrolled combustion, posing severe threats to human safety and infrastructure. Developing a robust AI framework for degradation prognostics in safety-critical systems is essential to mitigate these risks and ensure operational safety. However, sensor noise, dynamic operating conditions, and the multi-scale nature of degradation processes complicate this task. Traditional denoising and modeling approaches often fail to preserve informative temporal features or capture both abrupt fluctuations and long-term trends simultaneously. To address these limitations, this paper proposes a hybrid data-driven framework that combines Sample Entropy-guided Variational Mode Decomposition (SE-VMD) with K-means clustering for adaptive signal preprocessing. The SE-VMD algorithm automatically determines the optimal number of decomposition modes, while K-means separates high- and low-frequency components, enabling robust feature extraction. A dual-branch architecture is designed, where Gated Recurrent Units (GRUs) extract short-term dynamics from high-frequency signals, and Transformers model long-term trends from low-frequency signals. This dual-branch approach ensures comprehensive multi-scale degradation feature learning. Additionally, experiments with varying sliding window sizes are conducted to optimize temporal modeling and enhance the framework’s robustness and generalization. Benchmark dataset evaluations demonstrate that the proposed method outperforms traditional approaches in prediction accuracy and stability under diverse conditions. The framework directly contributes to Artificial Intelligence for Security by providing a reliable solution for battery health monitoring in safety-critical applications, enabling early risk mitigation and ensuring operational safety in real-world scenarios. Full article

Scaffolds are temporary structures that workers usually use during building or repair work. These structures can be built in different shapes and types depending on the type of joints to which the beams and columns of the scaffolds are connected. Due to their temporary nature, they are very sensitive to vibration under dynamic or static actions, and this causes many accidents and unstable behaviours in them. This unstable behaviour has different reasons, including bracing conditions and slenderness of the columns, stiffness of joints and anchors, imperfections in the construction, damage and corrosion due to climate change, etc. This article aims to reanalyse the mechanical properties of scaffold joints and anchors and obtain some critical factors in the overall stability of the mentioned structures, including load-bearing capacity, initial stiffness, energy absorption, and ductility. To this aim, some recent research on scaffolds has been summarised and discussed, and then the failure mode and mechanical behaviour of the scaffolds in different types of scaffold joints and anchors have been estimated and considered from previous studies. Moreover, some mechanical properties, including ductility, initial stiffness, and energy absorption, have been estimated and developed based on the force-displacement curves of previous studies. The results highlight the crucial importance of the mechanical properties and behaviour of anchors and joints in estimating the behaviour and stability of scaffolds. The results also revealed that determining the mechanical characteristics of the mentioned elements can have a significant influence on the optimisation and design of scaffolds more accurately and predictably. Moreover, determining the mechanical properties of the anchors and joints can enhance our insights and understanding of how the mentioned parameters can improve the behaviour, stability, and safety of the scaffold structures. Full article

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

Induction motors (IM) play essential tasks in distinct production sectors because of their low cost and robustness. Considering that most of the energy demand in industry is allocated for powering up IM, recent research has focused on detecting and predicting faults to avoid severe disturbances. Broken rotor bars (BRB) in IM cause a significant deficit of energy, above all in those applications where constant changes in speed are required, increasing the probability of a catastrophic failure. Variable speed drives (VSD) introduce harmonic components to the power supply current controlling the IM rotating speed, which make it difficult to identify BRB. Therefore, in this work, an innovative methodology is proposed for detecting BRB in VSD-fed IM with a wide rotating-speed bandwidth during their start-up transient. The introduced procedure performs a statistical analysis for computing the mean, median, mode, variance, skewness, and kurtosis, to identify slight changes on the acquired current signal. These values are fed into an artificial neural network (ANN), which carries out the IM operational condition classification as healthy (HLT) or with BRB. Experimentally obtained results corroborate the effectiveness of the proposed approach to detecting BRB even for dynamically varying rotating speed, reaching a high accuracy of 99%, similar to recently reported techniques. Full article

Accurately identifying surrounding rock failure modes and designing matching support systems are critical to the safety of deep-earth and underground space engineering. We develop a graded classification scheme based on the rock strength-to-stress ratio and the Stress Reduction Factor (SRF) to quantify failure types and guide support design. Within the convergence–confinement method (CCM) framework, we establish analytical models for shotcrete, rock bolts, steel arches, and composite support systems, enabling parameterized calculations of stiffness, load-bearing capacity, and equilibrium conditions. We conduct single-factor sensitivity analyses to reveal how the Geological Strength Index (GSI), burial depth (H), and equivalent tunnel radius (R₀) govern the evolution of surrounding rock pressure and deformation. We propose targeted reinforcement strategies that address large-deformation and high-stress instabilities in practice by linking observed or predicted failure modes to specific support schemes. A large-deformation case study verifies that the proposed parameterized design method accurately predicts the equilibrium support pressure and radial deformation, and the designed support scheme markedly reduces convergence. Accordingly, this study provides a practical tool for tunnel support parameter design and an analytical platform for safe, reliable, and efficient decision making for initial support. Full article