Search Results (70)

This paper presents a comprehensive study of torsional stick–slip vibrations in rotary drilling systems through a comparison between two lumped parameter models with differing complexity: a simple two-degree-of-freedom (2-DOF) model and a complex high-degree-of-freedom (high-DOF) model. The two models are developed under identical boundary conditions and consider an identical nonlinear friction torque dynamic involving the Stribeck effect and dry friction phenomena. The high-DOF model is calculated with the Finite Element Method (FEM) to enable accurate simulation of the dynamic behavior of the drill string and accurate representation of wave propagation, energy build-up, and torque response. Field data obtained from an Algerian oil well with Measurement While Drilling (MWD) equipment are used to guide modeling and determine simulations. According to the findings, the FEM-based high-DOF model demonstrates better performance in simulating basic stick–slip dynamics, such as drill bit velocity oscillation, nonlinear friction torque formation, and transient bit-to-surface contacts. On the other hand, the 2-DOF model is not able to represent these effects accurately and can lead to inappropriate control actions and mitigation of vibration severity. This study highlights the importance of robust model fidelity in building reliable real-time rotary drilling control systems. From the performance difference measurement between low-resolution and high-resolution models, the findings offer valuable insights to optimize drilling efficiency further, minimize non-productive time (NPT), and improve the rate of penetration (ROP). This contribution points to the need for using high-fidelity models, such as FEM-based models, in facilitating smart and adaptive well control strategies in modern petroleum drilling engineering. Full article

Predicting wave run-up on seawalls is essential for assessing coastal flood risk and guiding resilient design. In this study, we combine physical model experiments with a hybrid data driven method to forecast wave run-up distance. Laboratory tests generated a nonlinear data set spanning a wide range of wave amplitudes, wavelengths, Froude numbers. To capture the underlying physical regimes, the records were first classified using a Gaussian Mixture Model (GMM), which automatically grouped waves of similar hydrodynamic character. Within each cluster a Gradient Boosting Regressor (GBR) was then trained, allowing the model to learn tailored input–output relationships instead of forcing a single global fit. Results demonstrate that the GMM-GBR combined model achieves a coefficient of determination $R^2$ greater than 0.91, outperforming a conventional, non-clustered GBR model. This approach offers a reliable tool for predicting seawall performance under varying wave conditions, contributing to better coastal management and resilience strategies. Full article

FWI is a nonlinear optimization problem; significant discrepancies between the initial and true velocity models can lead to solutions converging to local optima. To address this issue, we proposed a PIRNN-based FWI method with first-arrival time constraints. Physics-informed recurrent neural networks (PIRNNs) integrate the physical processes of seismic wave propagation into recurrent neural networks, offering a novel approach for full-waveform inversion (FWI). First, the physical processes of seismic wave propagation were embedded into the recurrent neural network, enabling finite-difference solutions of the wave equation through forward propagation. Second, first-arrival time differences between synthetic and observed records were calculated, which then guided the selection of appropriate seismic traces for FWI loss computation. Additionally, the spatiotemporal gradient information recorded during the forward propagation of the recurrent neural network was utilized for backpropagation, enabling nonlinear optimization of FWI. This method avoids the local optima caused by waveform mismatches between the observed and synthetic records resulting from inaccurate initial velocity models. Numerical experiments on the BP and Marmousi velocity models demonstrated that the proposed method accurately reconstructed subsurface velocity structures even when the initial model significantly deviated from the true model, and maintained a degree of reconstruction accuracy in the presence of considerable noise, thereby validating its low sensitivity to the initial model and its robustness against noise. 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

In the field of nondestructive evaluation (NDE) using ultrasonic guided waves, accurately assessing the aging failure of insulation coatings remains a challenging and prominent research topic. While the application of ultrasonic guided waves in material testing has been extensively explored in the existing literature, there is still a significant gap in quantitatively evaluating the aging failure of insulation coatings. This study innovatively proposes an NDE method for assessing insulation coating aging failure by integrating signal processing and machine learning technologies, thereby effectively addressing both theoretical and practical gaps in this domain. The proposed method not only enhances the accuracy of detecting insulation coating aging failure but also introduces new approaches to non-destructive testing technology in related fields. To achieve this, an accelerated aging experiment was conducted to construct a cable database encompassing various degrees of damage. The effects of aging time, temperature, mechanical stress, and preset defects on coating degradation were systematically investigated. Experimental results indicate that aging time exhibits a three-stage nonlinear evolution pattern, with 50 days marking the critical inflection point for damage accumulation. Temperature significantly influences coating damage, with 130 °C identified as the critical threshold for performance mutation. Aging at 160 °C for 100 days conforms to the time-temperature superposition principle. Additionally, mechanical stress concentration accelerates coating failure when the bending angle is ≥90°. Among preset defects, cut defects were most destructive, increasing crack density by 5.8 times compared to defect-free samples and reducing cable life to 40% of its original value. This study employs Hilbert–Huang Transform (HHT) for noise reduction in ultrasonic guided wave signals. Compared to Fast Fourier Transform (FFT), HHT demonstrates superior performance in feature extraction from ultrasonic guided wave signals. By combining HHT with machine learning techniques, we developed a hybrid prediction model—HHT-LightGBM-PSO-SVM. The model achieved prediction accuracies of 94.05% on the training set and 88.36% on the test set, significantly outperforming models constructed with unclassified data. The LightGBM classification model exhibited the highest classification accuracy and AUC value (0.94), highlighting its effectiveness in predicting coating aging damage. This research not only improves the accuracy of detecting insulation coating aging failure but also provides a novel technical means for aviation cable health monitoring. Furthermore, it offers theoretical support and practical references for nondestructive testing and life prediction of complex systems. Future studies will focus on optimizing model parameters, incorporating additional environmental factors such as humidity and vibration to enhance prediction accuracy, and exploring lightweight algorithms for real-time monitoring. Full article

The vulnerability curve serves as a precise evaluation metric for structural seismic performance and a critical component in earthquake loss assessment. In this study, the orthogonal expansion method for random ground motion generation is integrated with the probability density evolution method (PDEM) to address the dynamic reliability and vulnerability of general Multi-Degree of Freedom (MDOF) nonlinear structures. By employing dynamic reliability as a constraint and vulnerability as an evaluation index, the guided firework algorithm (GFWA) is introduced to optimize the design of viscoelastic damper (VED) structure systems. To validate the proposed methods, several examples are presented, including the generation of artificial waves, the vulnerability analysis of a five-story reinforced concrete (RC) structure, and a comparative study of GFWA and genetic algorithm (GA) optimization for VED parameters to assess the optimization efficiency. The results demonstrate that the proposed vulnerability method achieves satisfactory accuracy and is well suited for evaluating damper structure optimization designs. Furthermore, GFWA outperforms GA significantly in terms of efficiency and feasibility, offering a promising approach for optimization design in architectural structures. Full article

In this study, a detection method utilizing nonlinear ultrasonic guided waves is presented to tackle the difficulties in detecting localized damage and weakening in bonded composite structures. For a three-layer structure made of polystyrene, acrylic resin, and aluminum plate, dispersion equations for ultrasonic guided waves were developed using the spring model and wave equation. The A1-S1 mode was selected by examining the material parameters’ influence on the adhesive layer’s dispersion curves. The finite element method was employed to simulate the propagation characteristics of ultrasonic guided waves within the composite structure. The error between the theoretically calculated and simulated group velocities was less than 5.15%. As the propagation distance increased, both the nonlinearity coefficient and the amplitude of the second-order harmonic showed an upward trend. This indicates a significant accumulation effect at the second harmonic of nonlinear guided waves. Compared to without adhesive layer weakening, localized and overall weakening resulted in higher amplitudes of the second-order harmonic. Experimental testing of ultrasonic guided waves was conducted to investigate the nonlinear properties of the composite structure. The error between the experimentally measured and theoretically calculated group velocities was less than 6.96%. The experimental results corroborated the propagation accumulation effect of the second-order harmonic amplitude. Full article

The technologically advanced learning ocean system—wave energy converter (TALOS-WEC) project addresses the urgent need for sustainable and efficient energy solutions by leveraging the vast potential of wave energy. This project presents a pioneering approach to wave energy capture through its unique multi-axis and omnidirectional point absorber design. Featuring a fully enclosed power take-off (PTO) system, the TALOS-WEC harnesses energy across six degrees of freedom (DoFs) using an innovative internal reaction mass (IRM) mechanism. This configuration enables efficient energy extraction from the relative motion between the IRM and the hull, aiming for energy conversion efficiencies ranging between 75–80% under optimal conditions, while ensuring enhanced durability in harsh marine environments. The system’s adaptability is reflected in its versatile geometric configurations, including triangular, octagonal, and circular designs, customised for diverse marine conditions. Developed at Lancaster University, UK, and supported by international collaborations, the TALOS-WEC project emphasises cutting-edge advancements in hydrodynamic modelling, geometric optimisation, and control systems. Computational methodologies leverage hybrid frequency-time domain models and advanced panel codes (WAMIT, HAMS, and NEMOH) to address non-linearities in the PTO system, ensuring precise simulations and optimal performance. Structured work packages (WPs) guide the project, addressing critical aspects such as energy capture optimisation, reliability enhancement, and cost-effectiveness through innovative monitoring and control strategies. This paper provides a comprehensive overview of the TALOS-WEC, detailing its conceptual design, development, and validation. Findings demonstrate TALOS’s potential to achieve scalable, efficient, and robust wave energy conversion, contributing to the broader advancement of renewable energy technologies. The results underscore the TALOS-WEC’s role as a cutting-edge solution for harnessing oceanic energy resources, offering perspectives into its commercial viability and future scalability. Full article

Thermal barrier coatings (TBCs) and air film-cooling technology have been extensively utilized in nickel-based, single-crystal turbine blades to enhance their heat resistance. However, structural complexity and material property mismatches between layers can affect residual stresses and potentially lead to coating failure. In this study, a three-dimensional finite element model with atmospheric plasma-spraying thermal barrier coatings (APS-TBCs) deposited on air-cooled, nickel-based, single-crystal blades was established to investigate residual stress character under centrifugal load, considering the effect of temperature, crystal orientation deviation angle, oxide layer thickness, and the number of cycles. The results show that when the centrifugal load is increased from 300 MPa to 700 MPa, the absolute value of the residual stress at the crest of the interface between Top Coat (TC) and Thermally Grown Oxide (TGO) increases by only 8.5%, whereas in the region of compressive to tensile stress conversion, residual stress decreases by 100.9%. As the crystal orientation deviation angle increases, the absolute value of the residual compressive stress increases and the absolute value of the residual tensile stress decreases, but the performance is more special in the valley region, where the absolute value of the residual stress increases with the increase in the deviation angle. Special attention is required, as the increase in temperature leads to a rise in the absolute value of residual stress. For example, at the trough of the TC–TGO interface, when the temperature increases from 910 °C to 1100 °C, the residual stress increases by 9.8%. The effect of the number of cycles on residual stress is relatively weak. For instance, at the wave crest of the TC–TGO interface, the residual stress differs by only 0.6 MPa between one cycle and three cycles. The effect of oxide layer thickness on residual stress in the TBCs after a single cycle is nonlinear. When the oxide layer thickness is 0, 4, and 7 μm, the residual stress undergoes a transition between tensile and compressive directions at different locations. The exploration of these results has yielded some valuable laws that can provide a reference for the study of the damage mechanism of TBCs, as well as a guide for the optimization of nickel-based turbine blades in the manufacturing and use processes. Full article

The anti-corrosion layer of the pipe provides corrosion resistance and extends the lifespan of the whole pipeline. Heat-shrinkable tape is primarily used as the pipeline joint coating material bonded to the pipeline weld connection position after heating. Delineating the bonding strength and assessing the quality of the bonded structure is crucial for pipeline safety. A detection technology based on nonlinear ultrasound is presented to quantitatively evaluate the bonding strength of a steel-EVA-polyethylene three-layer annulus bonding structure. Using the Floquet boundary condition, the dispersion curves of phase velocity and group velocity for a three-layer annulus bonding structure are obtained. Additionally, wave structure analysis is employed in theoretical study to choose guided wave modes that are appropriate for detection. In this paper, guided wave amplitude, frequency attenuation, and nonlinear harmonics are used to evaluate the structural bonding strength. The results reveal that the detection method based on amplitude and frequency attenuation can be used to preliminarily screen the poor bonding, while the acoustic nonlinear coefficient is sensitive to bonding strength changes. This study introduces a comprehensive and precise pipeline joint bonding strength detection system leveraging ultrasonic-guided wave technology for pipeline coating applications. The detection system determines the bonding strength of bonded structures with greater precision than conventional ultrasonic inspection methods. Full article

Structural health monitoring (SHM) is essential for ensuring the safety and longevity of laminated composite structures. Their favorable strength-to-weight ratio renders them ideal for the automotive, marine, and aerospace industries. Among various non-destructive testing (NDT) methods, ultrasonic techniques have emerged as robust tools for detecting and characterizing internal flaws in composites, including delaminations, matrix cracks, and fiber breakages. This review concentrates on recent developments in ultrasonic NDT techniques for the SHM of laminated composite structures, with a special focus on guided wave methods. We delve into the fundamental principles of ultrasonic testing in composites and review cutting-edge techniques such as phased array ultrasonics, laser ultrasonics, and nonlinear ultrasonic methods. The review also discusses emerging trends in data analysis, particularly the integration of machine learning and artificial intelligence for enhanced defect detection and characterization through guided waves. This review outlines the current and anticipated trends in ultrasonic NDT for SHM in composites, aiming to aid researchers and practitioners in developing more effective monitoring strategies for laminated composite structures. Full article

This is a comprehensive overview on our research work to link interdisciplinary modeling and simulation techniques to improve the predictability and reliability simulations (PARs) of compressible turbulence with shock waves for general audiences who are not familiar with our nonlinear approach. This focused nonlinear approach is to integrate our “nonlinear dynamical approach” with our “newly developed high order entropy-conserving, momentum-conserving and kinetic energy-preserving methods” in the quantification of numerical uncertainty in highly nonlinear flow simulations. The central issue is that the solution space of discrete genuinely nonlinear systems is much larger than that of the corresponding genuinely nonlinear continuous systems, thus obtaining numerical solutions that might not be solutions of the continuous systems. Traditional uncertainty quantification (UQ) approaches in numerical simulations commonly employ linearized analysis that might not provide the true behavior of genuinely nonlinear physical fluid flows. Due to the rapid development of high-performance computing, the last two decades have been an era when computation is ahead of analysis and when very large-scale practical computations are increasingly used in poorly understood multiscale data-limited complex nonlinear physical problems and non-traditional fields. This is compounded by the fact that the numerical schemes used in production computational fluid dynamics (CFD) computer codes often do not take into consideration the genuinely nonlinear behavior of numerical methods for more realistic modeling and simulations. Often, the numerical methods used might have been developed for weakly nonlinear flow or different flow types other than the flow being investigated. In addition, some of these methods are not discretely physics-preserving (structure-preserving); this includes but is not limited to entropy-conserving, momentum-conserving and kinetic energy-preserving methods. Employing theories of nonlinear dynamics to guide the construction of more appropriate, stable and accurate numerical methods could help, e.g., (a) delineate solutions of the discretized counterparts but not solutions of the governing equations; (b) prevent numerical chaos or numerical “turbulence” leading to FALSE predication of transition to turbulence; (c) provide more reliable numerical simulations of nonlinear fluid dynamical systems, especially by direct numerical simulations (DNS), large eddy simulations (LES) and implicit large eddy simulations (ILES) simulations; and (d) prevent incorrect computed shock speeds for problems containing stiff nonlinear source terms, if present. For computation intensive turbulent flows, the desirable methods should also be efficient and exhibit scalable parallelism for current high-performance computing. Selected numerical examples to illustrate the genuinely nonlinear behavior of numerical methods and our integrated approach to improve PARs are included. Full article

This paper presents an innovative approach to high-temperature health monitoring of aircraft structures utilizing an ultrasonic guided wave transmission and reception system integrated with a zirconia heat buffer layer. Aiming to address the challenges posed by environmental thermal noise and the installation of heat buffers, which can introduce structural nonlinearities into guided wave signals, a composite guided wave consisting of longitudinal and Lamb waves was proposed for online damage detection within thermal protection systems. To effectively analyze these complex signals, a hybrid damage monitoring technique combining variational mode decomposition (VMD) and fuzzy entropy (FEN) was introduced. The VMD was employed to isolate the principal components of the guided wave signals, while the fuzzy entropy of these components served as a quantitative damage factor, characterizing the extent of the structural damage. Furthermore, this study validated the feasibility of piezoelectric probes equipped with heat buffer layers for both exciting and receiving ultrasonic guided wave signals in a dual heat buffer layer, a one-transmit-one-receive configuration. The experimental results demonstrated the efficacy of the proposed VMD-FEN damage factor for real-time monitoring of damage in aircraft thermal protection systems, both at ambient and elevated temperatures (up to 150 °C), showcasing its potential for enhancing the safety and reliability of aerospace structures operating under extreme thermal conditions. Full article

The Grain for Green Program (GFGP) plays a critical role in enhancing watershed vegetation cover. Analyzing changes in vegetation cover provides significant practical value in guiding ecological conservation and restoration in vulnerable regions. This study utilizes MOD13Q1 NDVI data to construct the Kernel Normalized Difference Vegetation Index (kNDVI) and analyzes the spatiotemporal evolution and future trends of vegetation cover from 2000 to 2020, covering key periods of the GFGP. The study innovatively combines the optimal parameter geographic detector with constraint lines to comprehensively reveal the nonlinear constraints, intensities, and critical thresholds imposed by various driving factors on the kNDVI. The results indicate that the following: (1) The vegetation cover of the Luo River Basin increased significantly between 2000 and 2020, with a noticeable increase in the percentage of high-quality vegetation. Spatially, the vegetation cover followed a pattern of being “high in the southwest and low in the northeast”, with 73.69% of the region displaying improved vegetation conditions. Future vegetation degradation is predicted to threaten 59.40% of the region, showing a continuous or future declining trend. (2) The primary driving factors for changes in the vegetation cover are evapotranspiration, elevation, population density, and geomorphology type, with temperatures and GDP being secondary factors. Dual-factor enhancement or nonlinear enhancement was observed in interactions among the factors, with evapotranspiration and population density having the largest interaction (q = 0.76). (3) The effects of driving factors on vegetation exhibited various patterns, with thresholds existing for the hump-shaped and concave-waved types. The stability of the kNDVI in 40.23% of the areas showed moderate to high fluctuations, with the most significant fluctuations observed in low-altitude and high-temperature areas, as well as those impacted by dense human activities. (4) By overlaying the kNDVI classifications on the GFGP areas, priority reforestation areas totaling 68.27 km² were identified. The findings can help decisionmakers optimize the next phase of the GFGP and in effective regional ecological management. Full article

Freak waves have caused numerous accidents resulting in the collapse of ship structures due to structural plasticity, buckling, and instability, leading to the loss of life and property. Consequently, there is a growing academic interest in understanding ship structural collapsed responses induced by freak waves. This paper presents both numerical and experimental investigations on the structural collapse response of a ship model caused by freak waves. The study uses the Peregrine breather solution theory based on the Nonlinear Schrödinger (NLS) equation to generate a theoretical freak wave, and the nonlinear time-domain wave elevation and velocity field are obtained. The theoretical history of wave elevation is transferred into the wave maker of the wave tank to create experimental freak waves, and the velocity field of the freak wave is defined in a Computational Fluid Dynamics (CFD) solver to generate 3D numerical freak waves. A similar hydroelasto-plastic model is designed, and a hydroelasto-plastic experiment is conducted to observe experimental freak waves and large rotational deformations. The theoretical velocity field from the Peregrine breather solution theory, based on the NLS equation, is defined in a CFD platform to generate 3D numerical freak waves. A two-way Fluid-Structure Interaction (FSI) numerical hydroelasto-plastic approach coupling of CFD with a nonlinear Finite Element Method (FEM) solver is applied. Co-simulation of wave pressures and the structural collapsed response of the ship model caused by freak waves is performed. The wave elevation of experimental and numerical freak waves and the large rotational deformation of the buckling hinge are analyzed and compared, revealing a good agreement between the experiment and calculation. The maximum simulation rotational angle is 38.9°, while the maximum experimental rotational angle is equal to 42.3° for a typical wave case H2, which means numerical model accuracy and performance are acceptable for the simulating hydroelasto-plastic problem. The findings demonstrate that the numerical approach proposed in this study can effectively solve the hydroelasto-plastic response of ship structures in freak waves, offering a valuable tool for evaluating ship strength in these conditions and guiding future ship structural design. Full article