Search Results (109)

The damage status of shield machine disc cutters directly impacts the safety and efficiency of tunnelling projects. Current manual inspection methods involve high risks and low efficiency, while existing detection methods suffer from low accuracy and poor real-time performance in complex environments, often lacking quantitative analysis capabilities. To address these issues, this paper proposes an intelligent identification and quantitative assessment method for disc cutter damage based on the Deep Forest (DF) model. First, an eddy current sensor calibration platform was established, and a mapping relationship between output voltage and actual wear was developed through piecewise fitting to achieve precise wear quantification. In the data preprocessing stage, signal quality was improved via filtering, and typical damage features such as edge chipping, cracks, and eccentric wear were extracted using pulse edge detection. These feature segments were then resampled to construct the model training dataset. The DF model utilizes a hierarchical ensemble structure to mine data correlations, enabling accurate identification of four states: normal, edge chipping, eccentric wear, and cracks. Simultaneously, a DF regression model was employed to provide continuous quantitative predictions of damage size. Experimental results show that the classification model achieved accuracies of 98%, 96%, and 96% on the training, validation, and test sets, respectively, with weighted average F1-scores exceeding 0.96. The regression model achieved a coefficient of determination (R²) of 0.9940 and a root mean square error (RMSE) of 0.4051 on the test set. Both models demonstrate excellent performance and generalization, achieving full coverage from “qualitative state identification” to “quantitative wear assessment,” thereby providing reliable decision support for cutter maintenance and replacement. Full article

Droughts are one of the most significant hazards that affect human life due to the imbalanced distribution of water across the world. Some parts of the world are usually dry, and meteorological conditions affect these regions rapidly. In water-scarce regions, droughts significantly put at risk socio-economic stability and food security, which may cause a major challenge to sustainable development. Therefore, a precise definition of drought and the identification of early warning signals can help to minimize the negative effects of droughts, especially in terms of agriculture. In this study, drought signals of three major agricultural provinces of Turkey, namely Antalya, Şanlıurfa, and Konya, were investigated. For this purpose, the Standard Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Evaporative Demand Drought Index (EDDI), and Vegetation Condition Index (VCI) were computed for each province. A composite score index was proposed for the evaluation of multiple indices together. All datasets were obtained from remote-sensing products to ensure reproducibility. A dataset for the 2003–2023 period was used. The monthly precipitation derived from CHIRPS data and potential evaporation (PEV) data were obtained from the ERA5-Land. Therefore, the SPEI and EDDI values were calculated by using ERA5-Land PEV values but not the evapotranspiration. The Normalized Difference Vegetation Index (NDVI) values for each province were obtained from the MODIS/Terra MOD13A3 v061. The Mann–Kendall test and Sen’s slope were applied to the computed time series to detect the trends. As a result, the dry and wet periods were identified for each province individually. The VCI was found to have an increasing trend for all tested provinces. Overall, from a future perspective, the most vulnerable province in terms of meteorological drought was indicated to be Antalya. Full article

This paper presents a minimally intrusive experimental methodology for identifying and modeling power losses in the electric powertrain of a battery electric vehicle, including the inverter, electric motor and speed reducer. Measurements are performed on a roller test bench equipped with an eddy current brake, using two complementary approaches to determine the mechanical power at the wheel: (i) a direct measurement based on an onboard rotary torque sensor integrated into a driveshaft; (ii) an indirect estimation derived from brake power measurements corrected for bench losses and tire longitudinal slip. The two approaches are systematically compared in order to quantify the accuracy loss associated with brake-based measurements and to identify the operating conditions under which they can reliably substitute direct torque measurements. The experimental results show that brake-based estimations provide acceptable accuracy at moderate–high torque levels, while significant deviations occur at low torque. Based on the experimental dataset, an overall power loss model is identified using a polynomial function of motor torque and speed. Two fitting strategies are investigated: an unconstrained least-squares approach, allowing all coefficients to vary freely, and a constrained formulation enforcing physically admissible (non-negative) loss terms; while the unconstrained method slightly improves the numerical fit, it may lead to non-physical coefficients and invalid efficiency predictions. In contrast, the constrained approach preserves physical interpretability and ensures consistent loss and efficiency maps. Finally, a step-by-step practical guide is provided to facilitate the implementation of the proposed methodology for powertrain loss identification on electric vehicles without extensive mechanical disassembly. Full article

Magnetorheological (MR) dampers exhibit significant hysteretic nonlinearities, particularly under dynamic operating conditions, where accurately modeling the complex coupling between magnetic flux density and excitation current remains challenging. To overcome the limitations of the conventional static Jiles–Atherton (JA) model in capturing dynamic hysteresis responses, a dynamic JA model incorporating multiple loss mechanisms (LS-DJAM) is proposed for MR dampers. Building on loss separation theory, the model integrates eddy current and excess loss mechanisms to more accurately represent the dynamic hysteresis behavior of MR dampers. By coupling the Bingham mechanical model, a magneto-mechanical constitutive relation for MR dampers is established. Furthermore, to enhance the accuracy of LS-DJAM parameter identification, a hybrid particle swarm optimization–genetic algorithm (PSO–GA) is developed. Genetic operators are embedded within the PSO framework to strengthen the global search capability and mitigate premature convergence, thereby enabling efficient LS-DJAM parameter identification. The proposed LS-DJAM, identified via the PSO–GA, significantly enhances the modeling of MR damper output forces. PSO–GA parameter estimation improves accuracy by over 60%, and the LS-DJAM reduces the maximum modeling error by 87.5% compared with the conventional JA model. It accurately captures the dynamic hysteresis characteristics of MR dampers, providing a robust theoretical basis and practical framework for high-performance control and engineering optimization. Full article

To investigate the spatiotemporal dynamics and wall shear stress patterns of a PVC (precessing vortex core) within a bounded swirling flow for agricultural irrigation, LES (Large Eddy Simulation) simulations based on a guide-vane hydro-cyclone were conducted and validated by physical experiments. Coherent structures were extracted through flow modal decomposition, and a reduced-order model was established. The modal analysis of the flow reveals the following: A modal pairing phenomenon exists in the swirling flow, starting from the swirling section downstream of the guide-vane. The flow converts from a basic pipe flow to swirling flow. Compared to the vane section, the composite PVC in the swirling section exhibits mutual momentum exchange, leading to increasingly fragmented evolution of the vortex core over time and space. The application of vortex identification criteria to the reconstructed reduced-order model reveal that the precessing vortex core exhibits a tendency to spiral downstream along the guide-vane twist direction, with its rotation direction perfectly aligned with the guide-vane twist. As the Reynolds number of the bounded swirling flow increases, the circumferential precession of the PVC exhibits a linear weakening trend. As the relative length l/d of the guide-vane to the pipe increases, the circumferential precession of the PVC shows a linear strengthening trend. The wall shear stress analysis results indicate that the stress coefficient magnitude near the downstream location of the guide-vane is approximately zero, representing the lowest value across the entire flow. The region exhibits a rotational precession trend downstream. The stress coefficient magnitude between guide-vanes is relatively high, about 0.1 times dynamic pressure of approaching flow, and this trend also develops downstream with a rotational precession tendency. Full article

This study presents a comprehensive experimental investigation of a 2.2 kW brushless DC (BLDC) motor integrated with a three-shaft planetary gearbox, focusing on overall energy efficiency, battery state of charge (SOC) estimation, and real-time speed control under variable load conditions. In the first stage, the gearbox transmission ratio was experimentally verified to establish the kinematic relationship between the BLDC motor and the eddy current dynamometer shafts. In the second stage, the motor was operated in open loop mode at fixed reference speeds while variable load torques ranging from 1 to 7 N.m were applied using an AVL dynamometer. Electrical voltage, current, and rotational speed were measured in real time through precision transducers and a data acquisition interface, enabling computation of overall efficiency and SOC via the Coulomb counting method. The open loop results demonstrated that maximum efficiency occurred in the intermediate-to-high-speed region (2000 to 2800 rpm) and at higher load torques (5 to 7 N.m) while locking the third gearbox shaft produced negligible parasitic losses. In the third stage, a proportional–integral–derivative (PID) controller was implemented in closed loop configuration to regulate motor speed under the same variable load scenarios. The closed loop operation improved the overall efficiency by approximately 8–20 percentage points within the effective operating range of 1600–2500 rpm, reduced speed droop, and ensured precise tracking with minimal overshoot and steady-state error. The proposed methodology provides an integrated experimental framework for evaluating the dynamic performance, energy efficiency, and battery utilization of BLDC motor planetary gearbox systems, offering valuable insights for electric vehicle and hybrid electric vehicle (HEV) drive applications. Full article

This study investigates the generation and suppression of the whistling noise caused by flow through the narrow gap of a vehicle’s side mirror, an aerodynamic phenomenon often reported as a source of discomfort to passengers. The research employs a simultaneous approach, combining wind tunnel experiments to determine the geometries and wind conditions at a flow speed of 22 m/s contributing to whistle generation at between 7 kHz and 8 kHz with numerical simulations utilizing compressible Large Eddy Simulation (LES) techniques for an in-depth investigation of the underlying aerodynamics. The Simplified Side-mirror Model (SSM) is developed, enabling precise wind visualization, and facilitating the identification of fundamental aerodynamic sound sources via vortex sound theory. The analysis reveals that the whistling sound is intricately linked to edge tone phenomena, driven by vortex shedding and flow instabilities at the angled shape in a narrow gap. Building on these insights, the study introduces the Suppressed Whistle Model (SWM), a configuration including shapes resembling a vortex generator that successfully mitigates the whistling by disrupting the identified flow structures causing the whistling sound. The suggested design is validated through wind visualization, comparing the numerical flow structures with the experimental ones. The experimental whistling sound pressure level of SWM decreases by about 20 dB compared to SSM, and a similar trend can be confirmed in the numerical results. Full article

The eddy current damper (ECD), as a high-performance seismic protection device, has been increasingly applied in the field of civil engineering. However, most existing finite element software lacks a nonlinear constitutive model for this type of damper, and an equivalent simplified model capable of accurately capturing its real damping characteristics under complex seismic excitations has not yet been established. To address this gap, this paper proposes a stochastic optimization framework for calibrating a bilinear ECD model, using the Wouterse model as a reference. Specifically, the core of this framework employs a Monte Carlo Simulation (MCS) approach, in which a suite of spectrum-compatible seismic excitations is generated and analyzed to evaluate the corresponding stochastic structural responses. The Grey Wolf Optimizer (GWO) is then utilized to minimize the discrepancy between the dynamic responses predicted by the proposed bilinear model and those of the reference model. A key outcome of this study is a practical bilinear model in which these parameters can be treated as constants, enabling designers to focus exclusively on the physical parameters $f_{\mathrm{m}\mathrm{a}\mathrm{x}}$ and $v_{\mathrm{c}\mathrm{r}}$. This study bridges the gap between high-fidelity simulations and practical engineering design, providing a feasible pathway for integrating ECDs into existing finite element software for dynamic analysis. Full article

This article introduces a mesoscale eddy detection algorithm that employs orthogonal transformations of flow field data, and subsequently, for simplicity, it is abbreviated as the OG algorithm. By implementing orthogonal geometric transformations on sea surface flow field data and examining the geometric properties of the transformed data, the study establishes criteria for the identification of mesoscale eddies based on these geometric attributes. The research utilizes sea surface flow field data sourced from the Copernicus Marine Environment Monitoring Service and validates the proposed algorithm through experimental comparisons with the traditional Velocity Geometry-based algorithm (VG algorithm). The findings indicate that the OG algorithm exhibits superior accuracy and computational precision in the detection of mesoscale eddies and in the calculation of each eddy’s center when juxtaposed with the VG algorithm. Additionally, the OG algorithm not only excels in identifying standard eddies but also shows promising applicability in the detection of eccentric and dual-core eddies. Mesoscale eddies play a crucial role in ocean dynamics and significantly influence ocean circulation, heat transport, and ecosystems. Therefore, the development of a more efficient and precise mesoscale eddy detection algorithm holds substantial importance for advancing research in ocean dynamics and climate forecasting. Full article

Sediment plumes threatening benthic ecosystems are one of the environmental hazards associated with seafloor interventions such as bottom trawling, cabling, dredging, and marine mining operations. This study focuses on sediment plume release from hypothetical future deep-sea mining activities, emphasizing its interaction with turbulent ocean currents in regions characterized by complex seafloor topography. In such environments, turbulent lee waves may significantly enhance the scattering of released sediments, pointing to the clear need for appropriate impact assessment frameworks. Global-scale models are limited in their ability to resolve sufficiently high Reynolds numbers to accurately represent turbulence generated by seafloor topography. To overcome these limitations and effectively assess lee wave dynamics, models must incorporate the full physics of turbulence without simplifying the Navier–Stokes equations and must operate with significantly finer spatial discretization while maintaining a domain large enough to capture the full topographic signal. Considering a seamount in the Lofoten Basin of the Norwegian Sea as an example, we present a novel numerical analysis that explores the interplay between lee wave turbulence and sediment plume dispersion using a high-resolution Large Eddy Simulation (LES) framework. We show that the turbulence occurs within semi-horizontal channels that emerge beyond the topographic highs and extend into sheet-like tails close to the seafloor. In scenarios simulating sediment release from various sites on the seamount, our model predicts distinct behavior patterns for different particle sizes. Particles with larger settling velocities tend to deposit onto the seafloor within 50–200 m of release sites. Conversely, particles with lower settling velocities are more susceptible to turbulent transport, potentially traveling greater distances while experiencing faster dilution. Based on our scenarios, we estimate that the plume concentration may dilute below 1 ppm at about 2 km distance from the release site. Although our analysis shows that mixing with ambient seawater results in rapid dilution to low concentrations, it appears crucial to account for the effects of topographic lee wave turbulence in impact assessments related to man-made sediment plumes. Our high-resolution numerical simulations enable the identification of sediment particle size groups that are most likely affected by turbulence, providing valuable insights for developing targeted mitigation strategies. Full article

Underground gas storage (UGS) is critical to national reserves and seasonal peak-shaving, and its safe operation is integral to energy security. In UGS surface process pipelines, heterogeneous bimetal composite pipes—carbon-steel substrates lined with stainless steel—are widely used but susceptible under coupled thermal–pressure–flow loading to geometry-induced instabilities (local buckling, adhesion, and collapse), which can restrict flow, concentrate stress, and precipitate rupture and unplanned shutdowns. Conventional ultrasonic testing and magnetic flux leakage have limited sensitivity to such instabilities, while standard eddy-current testing is impeded by the ferromagnetic substrate’s high permeability and electromagnetic shielding. This study introduces magnetically saturated pulsed eddy-current testing (MS-PECT). A quasi-static bias field drives the substrate toward magnetic saturation, reducing differential permeability and increasing effective penetration; combined with pulsed excitation and differential reception, the approach improves defect responsiveness and the signal-to-noise ratio. A prototype was developed and evaluated through mechanistic modeling, numerical simulation, laboratory pipe trials, and in-service demonstrations. Field deployment on composite pipelines at the Hutubi UGS (Xinjiang, China) enabled rapid identification and spatial localization of liner collapse under non-shutdown or minimally invasive conditions. MS-PECT provides a practical tool for composite-pipeline integrity management, reducing the risk of unplanned outages, enhancing peak-shaving reliability, and supporting resilient UGS operations. Full article

The topic of the present study is the aerodynamic performance of a Natural Laminar Flow (NLF) wing for UAVs at low speed. The basis is a thoroughly tested NLF airfoil in the wind tunnel of NASA which is well-customized for light aircrafts. The aim of this work is the numerical verification that a typical wing design (tapered with moderate aspect ratio and wash-out), being constructed out of aerodynamically highly efficient NLF airfoils during cruise, can deliver high aerodynamic loading under minimal freestream turbulence as well as realistic atmospheric conditions of intermediate turbulence. Thus, high mission flexibility is achieved, e.g., short take off/landing capabilities on the deck of ship where moderate air turbulence is prevalent. Special attention is paid to the effect of the Wing Tip Vortex (WTV) under minimal inflow turbulence regimes. The flight conditions are take off or landing at moderate Reynolds number, i.e., one to two millions. The numerical simulation is based on an open source CFD code and parallel processing on a High Performance Computing (HPC) platform. The aim is the identification of both mean flow and turbulent structures around the wing and subsequently the formation of the wing tip vortex. Due to the purely three-dimensional character of the flow, the turbulence is resolved with advanced modeling, i.e., the Improved Delayed Detached Eddy Simulation (IDDES) which is well-customized to switch modes between Delayed Detached Eddy Simulation (DDES) and Wall-Modeled Large Eddy Simulation (WMLES), thus increasing the accuracy in the shear layer regions, the tip vortex and the wake, while at the same time keeping the computational cost at reasonable levels. IDDES also has the capability to resolve the transition of the boundary layer from laminar to turbulent, at least with engineering accuracy; thus, it serves as a high-fidelity turbulence model in this work. The study comprises an initial benchmarking of the code against wind tunnel measurements of the airfoil and verifies the adequacy of mesh density that is used for the simulation around the wing. Subsequently, the wing is positioned at near-stall conditions so that the aerodynamic loading, the kinematics of the flow and the turbulence regime in the wing vicinity, the wake and far downstream can be estimated. In terms of the kinematics of the WTV, a thorough examination is attempted which comprises its inception, i.e., the detachment of the boundary layer on the cut-off wing tip, the roll-up of the shear layer to form the wake and the motion of the wake downstream. Moreover, the effect of inflow turbulence of moderate intensity is investigated that verifies the bibliography with regard to the performance degradation of static airfoils in a turbulent atmospheric regime. Full article

In this study, the modeling of rough surfaces by eddy-viscosity-based roughness models is investigated, specifically focusing on surfaces representative of deterioration in aero-engines. In order to test these models, experimental measurements from a rough T106C blade section at a Reynolds number of 400 K are adopted. The modeling framework is based on the k-ω-SST with Dassler’s roughness transition model. The roughness model is recalibrated for the k-ω-SST model. As a complement to the available experimental data, a high-fidelity test rig designed for scale-resolving simulations is built. This allows us to examine the local flow phenomenon in detail, enabling the identification and rectification of shortcomings in the current RANS models. The scale-resolving simulations feature a high-order flux-reconstruction scheme, which enables the use of curved element faces to match the roughness geometry. The wake-loss predictions, as well as blade pressure profiles, show good agreement, especially between LES and the model-based RANS. The slight deviation from the experimental measurements can be attributed to the inherent uncertainties in the experiment, such as the end-wall effects. The outcomes of this study lend credibility to the roughness models proposed. In fact, these models have the potential to quantify the influence of roughness on the aerodynamics and the aero-acoustics of aero-engines, an area that remains an open question in the maintenance, repair, and overhaul (MRO) of aero-engines. Full article

Under harsh sea states, the dynamic characteristics of ocean mesoscale eddies (OMEs) become significantly more complex, posing substantial challenges to their accurate detection and identification. In this study, we propose an artificial intelligence detection method for OMEs based on the domain adaptation technique to accurately perform pixel-level segmentation and ensure its effectiveness under harsh sea states. The proposed model (LCNN) utilizes large kernel convolution to increase the model’s receptive field and deeply extract eddy features. To deal with the pronounced cross-domain distribution shifts induced by harsh sea states, an adversarial learning framework (ADF) is introduced into LCNN to enforce feature alignment between the source (normal sea states) and target (harsh sea states) domains, which can also significantly improve the segmentation performance in our constructed dataset. The proposed model achieves an accuracy, precision, and Mean Intersection over Union of 1.5%, 6.0%, and 7.2%, respectively, outperforming the existing state-of-the-art technologies. Full article

The increasing demand for effective flow control in supersonic boundary layers, particularly for mitigating shock-wave boundary-layer interactions, underscores the need to explore optimized micro-vortex generator (MVG) configurations. This study investigates the aerodynamic performance of two different MVG configurations: a two-MVG setup with a pair of close parallel-positioned MVGs and a three-MVG arrangement that includes an additional upstream unit. Both are examined within a Mach 2.5 flow regime, aiming to improve mixing and energize the boundary layer. Large Eddy Simulations (LES) were performed using high-order numerical schemes. A newly developed vortex identification method was utilized to characterize vortex structures, while turbulent kinetic energy (TKE) metrics were integrated to quantify turbulence. Findings reveal that the two-MVG configuration produces regular, symmetric vortex pairs with limited interaction. This results in a steady increase in TKE and a thickened momentum boundary layer—indicative of notable energy loss. In contrast, the three-MVG setup generates more intricate and interactive vortex formations that significantly elevate TKE levels, rapidly expand the turbulent region, and reduce energy loss downstream. The peak TKE occurs before tapering slightly. Instantaneous flow analysis further highlights chaotic, hairpin-dominated vortex structures in the three-MVG case, compared to the more orderly ones observed in the two-MVG case. Overall, the three-MVG configuration demonstrates superior mixing and boundary-layer energization potential, albeit with greater structural complexity. Full article