Search Results (4,876)

The upscaling of turbines in the offshore wind industry has been unprecedented, as compared to 5–6 MW rated turbines 10 years ago. A typical 20–26 MW rated turbine in modern commercial applications (MingYang MySE 18.X-20 MW installed in 2025 and 26 MW prototype by Dongfang Electric tested in 2025) has been demonstrated. This scaling has been made possible by increasing rotor diameters (>250 m) and hub heights (>150–180 m) to achieve capacity factors of up to 55–65%, annual energy generation of more than 80 GWh/turbine, and significant decreases in levelised cost of energy (LCOE) to current values of up to 63–65 USD 2023/MWh globally averaged in 2023 (with minor variability in 2024 due to market changes and new regional areas). The paper analyses turbine upscaling over three levels of hierarchy, including turbine scale—rated capacity and physical aspect, project scale—multi-gigawatts of farms, and market scale—the global pipeline > 1500 GW level, and combines techno-economic evaluation, structural evaluation of loads, and infrastructure needs assessment. The upscaling has the advantage of reducing the number of turbines dramatically (e.g., 500 to 67 turbines in a 1 GW farm, as turbine size is increased to 15 MW) and balancing-of-plant (BoP) CAPEX (turbine-to-turbine foundations and cables) by some 20 to 30 percent per unit of capacity, and serial production learning rates of between 15 and 18% per doubling of capacity. But the problems that come with the increase in ultra-large designs are nonlinear increments in mass and load (i.e., blade-root and tower-bending moments), logistical constraints (blades > 120 m, nacelle up to 800–1000 tonnes demanding special vessels and ports), supply-chain issues (rare-earth materials, vessel shortages increase day rates by 30–50%), and technology limitations (aeroelastic compounded by numerical differences between reference 5 MW, 10 MW, and 15 MW models), it becomes evident that there is a significant increase in deflections of the tower and blades and platform surge/pitch responses with continued increases in power levels, but without a correspondingly mature infrastructure. The regional differences (mature ports of Europe vs. U.S. Jones Act restrictions vs. scale-up of vessels/manufacturing in China) lead to the necessity of optimisation depending on the context. The analysis concludes that, to the extent of mature markets with adapted logistics, continuous upscaling is an effective business strategy and can result in 5 to 12 percent further reductions in LCOE, but beyond that point, gains become marginal or even negative, as risks and costs increase. The competitiveness of the future depends on multi-scale/multi-market-based approaches—modular-based families of turbines, programmatic standardisation, vibration control innovations, and industry coordination towards supply-chain alignment and standards. Its major strength is that it transcends mere size–cost relationships and shows how nonlinear structural processes, aero-hydro-servo-elastic interactions, and bottlenecks in logistical systems are becoming more determinant of the efficiency of ultra-large turbines. The study demonstrates that upscaling turbines has LCOE benefits through the support of associated improvements in installation facility, supply-chain preparedness, and structural vibration control potential, based on the comparisons of quantitative loads, techno-economic scaling trends, and regional market differentiation. Full article

To overcome the drawbacks of conventional wedge cut blasting—high peak particle velocity (PPV), low blasthole utilization, and a high proportion of large fragments—this paper proposes a delayed blasting method for wedge cut blasting. By integrating the rock-fracturing process of wedge cut blasting, the mechanisms of rock breaking and vibration reduction are investigated and confirm the method through field tests. The results indicate that the rock breaking process can be divided into two stages, the stage of fracture propagation and the stage of cavity ejection, and a rock breaking criterion for wedge cut delayed blasting is established. Considering differences in the vibration waveforms generated by different types of cut holes, a vibration waveform fitting method for wedge cut delayed blasting is proposed. Furthermore, the generation time of the blast-induced free surface during the rock breaking process is calculated, and a calculation Equation for the optimal delayed time is derived. Field tests in the Qi Jiazhuang tunnel show that, compared with conventional blasting, the proposed delayed blasting method increases blasthole utilization by 23.8%, reduces the large fragment rate by 67.4%, lowers PPV by 53.7%, and increases the dominant vibration frequency by 42.0%. These results significantly improve the wedge cut blasting performance and construction safety. Full article

Long-distance coal gangue slurry transportation pipelines are critical components of underground coal mine green backfilling systems, yet blockage failures severely threaten their safe and efficient operation. Existing distributed acoustic sensing (DAS)-based monitoring methods for such pipelines suffer from three key limitations: insufficient fixed-point quantitative accuracy, lack of verified blockage-specific characteristic indicators, and limited quantitative severity assessment capability. To address these gaps, this paper proposes a novel feature-level fusion monitoring method integrating DAS, fiber Bragg grating (FBG), and piezoelectric accelerometers for accurate blockage identification and quantitative evaluation in coal gangue slurry pipelines. A slurry pipeline circulation test platform with gradient blockage simulation (0% to 76.42%) and a synchronous multi-sensor monitoring system were developed. Through multi-domain signal analysis, three blockage-correlated characteristic frequencies were identified and cross-validated by synchronous multi-sensor data: 1.5 Hz (system background vibration), 26 Hz (blockage-induced fluid–structure resonance, verified by the Euler–Bernoulli beam theory with a theoretical value of 25.7 Hz), and 174 Hz (transient flow impact). The DAS phase change rate exhibited a unimodal nonlinear response to blockage degree, with the peak occurring at 40.94% blockage. On this basis, a sine-fitting quantitative inversion model was developed, achieving a high goodness of fit (R² = 0.985), and leave-one-out cross-validation confirmed its excellent robustness with a mean relative prediction error of 3.77%. Finally, a collaborative monitoring framework was built to fully leverage the complementary advantages of each sensor, realizing full-process blockage monitoring covering global blockage localization, precise quantitative severity calibration, and high-frequency transient risk early warning. The proposed method provides a robust experimental and technical foundation for real-time early warning, precise localization, and quantitative diagnosis of long-distance slurry pipeline blockages and holds important engineering application value for the safe and efficient operation of underground coal mine green backfilling systems. Full article

Finned tubes contribute to the heat transfer performance of heat exchangers by increasing the surface area; they also modify patterns within the flow around the tubes and thus increase the likelihood of flow-induced vibrations (FIVs), which can undermine structural integrity. The tradeoff between improved heat transfer and minimized vibration risks is thus of concern in the optimization of finned tube designs. This paper examines the vibration behavior of circular finned tubes fitted in a parallel triangular configuration when subjected to crossflow conditions with particular reference to the structural response as opposed to thermal performance. In this study, two tube bundles arranged in a 30° parallel triangular layout were tested. The test tube has pitch-to-diameter (P/D) ratios of 1.16 and 1.37 and fin densities of 3, 6, and 9. In this study, experiments were conducted in a low-speed closed-loop water tunnel, which also involved the fabrication of circular finned tubes, the preparation of test bundles, and vibration response measurements. The key parameters analyzed in this experiment were the vibration amplitude, damping, pitch ratio, and fin density. Based on the free-stream velocity range of 0.13–0.28 m/s in a 300 mm × 300 mm closed-circuit water tunnel (hydraulic diameter $D_h=0.3$ m), the Reynolds number ranged from 3.9 × 10⁴ to 8.4 × 10⁴ (water at 20 °C). The results of this experiment demonstrate that by increasing the fin density, the vibration amplitudes can be reduced, which also raises the critical velocities. Reducing the pitch ratio from 1.37 to 1.16 produced an onset of instability approximately 53% earlier than the onset of instability at the ratio of 1.37. The bandwidth of the pitch ratio of 1.16 at the same fin density of 9 was almost 45% lower than that at 1.37, which confirms that the system at 1.16 is much more unstable. In general, the 1.37 pitch ratio offers 3 times higher stability margins than those of 1.16 for the fin densities under study. The development of optimal finned tube heat exchanger designs that reduce flow-induced vibrations without sacrificing thermal performance is aided by these findings, which provide information on the relationship between the fin density, pitch ratio and vibration behavior. Full article

This work presents an original implementation of the digital sampling pipeline for spaceborne Fourier Transform Spectrometers (FTSs). The implementation aims at improving the robustness of the spectrometer to harsh environmental conditions, including mechanical vibrations and a wide operational temperature range, avoiding the use of dedicated electronic hardware for the interferometer mirrors’ speed control and interferogram sampling. The FTS configuration is based on the constant time step sampling of the interferometer using a standard ADC (Analogue to Digital Converter), along with two metrology laser channels. The development tool is a MATLAB-based simulator developed to emulate the FTS and, in particular, the generation and acquisition of interferograms, incorporating harmonic vibrations and detector noise. The simulator was exploited to compare state-of-the-art techniques and newly implemented variants. An improvement of the arccosine method is first proposed, revising the normalisation process to exploit the full set of recorded data without discarding critical points. Subsequently, methods using two reference channels have been developed and evaluated. Two implementations are considered: two references at the same wavelength with an optimised phase shift (i.e., π/2) and two references at different wavelengths. Different data fusion strategies are compared in terms of spectral uncertainty, varying types of simulated disturbances and noise amplitudes. Results show that the optimal combination of two same-wavelength references consistently outperforms any other configuration, yielding lower average spectral errors and more stable performance over the frequency range and for a lower SNR of reference channels. Conversely, dual-wavelength strategies exhibit reduced accuracy, though they offer flexibility when fixed phase shifts cannot be maintained. The optimal combination of two same-wavelength reference channels, phase-shifted, is a promising configuration for spaceborne FTSs, so the development and test of an instrument breadboard is envisaged as the consequent development of this work. Full article

Scalability of the original test design for the box assembly with removable component (BARC) structure is of interest in the field of experimental structural analysis. As complex structures become increasingly difficult to test experimentally the larger they become, it is a common test practice to use a scaled-down representative model to understand the characteristics of these systems. For complex structures with non-rigid boundary conditions, there exists a gap in understanding the effects of scalability and welding. To gain a better understanding of the outcomes of this phenomenon, the dynamical effects of upscaling the dimensions of the BARC structure are analyzed. Three variations of the BARC are investigated experimentally and computationally, namely, the original BARC system, the BARC system upscaled at 1.5 times the size of the original model, and the BARC system upscaled at two times the size of the original model. The original BARC is tested to investigate the properties of the predetermined boundary conditions. Because the upscaled BARC systems are manufactured using welding, an investigation of the variability of results due to welding imperfections is conducted to evaluate its effects on the vibrational properties of the systems. The dominant resonant frequencies of the three systems are identified through an impact hammer test. The results are then compared to those obtained through finite element analysis, in which both datasets show agreement. In general, as the BARC system is upscaled, the resonant frequencies decrease without inducing mode switching for the selected boundary conditions, indicating that the larger systems are less rigid. To understand the trends of nonlinear softening/hardening and nonlinear damping, forced vibration experiments conducted in the form of true random and controlled stepped-sine excitations are performed. The results show that, in general, as the BARC system is upscaled, changes in the nonlinear properties of the system are induced. With regard to the effects of using welding to manufacture BARC systems, the results prove that variations in welding can lead to non-negligible variations in the vibratory responses of the BARC system. Additionally, several types of harmonic vibrational testing are investigated to understand the physics behind their varied responses. Overall, this work shows that upscaling the BARC system can be beneficial to researchers who require a less rigid system for investigations and that manufacturing of BARC systems by welding can be a cost-effective alternative to subtractive manufacturing. Full article

Carbon capture, utilization, and storage (CCUS) plays an important role in meeting the European Union’s target to reduce greenhouse gas emissions by 55% by 2030 and become carbon neutral by 2050. Accurate flow metering is required throughout the carbon capture and storage (CCS) chain to meet fiscal and regulatory requirements. To establish accurate CO₂ flow metering, flow meters must be calibrated with traceability to international standards of measurement at relevant flow conditions. To ensure confidence, reliability, and comparability of calibration results, calibration facilities perform interlaboratory comparisons. However, there is currently a lack of CO₂ gas flow meter calibration facilities. The flow metering calibration facilities of VSL, NEL, INRIM, DNV, and FORCE participated in an interlaboratory comparison with CO₂ up to 400 m³/h and 31 bar(a) to compare the calibration results with several flow metering principles. At the intermediate-scale facilities of NEL, VSL, and INRIM, the difference in results between the VSL and INRIM facilities were within the facilities’ CMC values, while NEL’s facility showed a significant difference primarily due to vibrational relaxational effects of CO₂ with small critical flow Venturi nozzles. At the large-scale facilities of NEL, DNV, and FORCE, 91% of the test points passed the equivalency criteria in the range of 20 m³/h to 400 m³/h with a Coriolis meter, confirming traceability for carbon dioxide across the facilities. Overall, the interlaboratory comparison has made it possible for the CCUS industry to calibrate gaseous CO₂ flow meters with traceability to international standards. Full article

The cleaning unit is a key functional component of grain combine harvesters, yet its operating parameters are still predominantly adjusted according to operator experience, resulting in limited adaptability to fluctuating working conditions. To enhance the intelligence and stability of the cleaning process, this study develops a fuzzy control approach supported by data-driven performance modeling. Based on multi-condition bench experiments, feeding rate, fan speed, cleaning sieve vibration frequency, and sieve opening were selected as input variables. Gaussian Process Regression (GPR) models were established to describe the nonlinear relationships between operating parameters and cleaning loss rate and impurity rate, and impurity rate was inferred online to compensate for the absence of a reliable sensor. Taking feeding rate variation as the primary disturbance, a dual-input fuzzy control strategy was designed using loss rate monitoring and model-predicted impurity rate as feedback signals. Simulation and bench test results show that, under small and moderate load disturbances (±20% and ±35%), the proposed method reduces either impurity rate or cleaning loss rate through coordinated parameter adjustment. Under large disturbances (±50%), performance deterioration cannot be fully eliminated, but its extent is alleviated compared with open-loop conditions. Full article

Energy harvesting has emerged as a promising solution for powering aircraft structural health monitoring (SHM) systems by exploiting ambient vibration energy. This work presents a novel clustered piezoelectric energy harvester (CPEH) designed to enable autonomous sensing and wireless data transmission in aircraft structures. Aircraft sections experience complex, multiple vibration modes during flight; however, the proposed harvester is specifically designed to exploit the oscillatory motion of the vertical tail unit (VTU) of a VUT-100 Cobra aircraft during the cruise phase. The energy harvester employs a clustered piezoelectric cantilever configuration incorporating magnetic stiffness nonlinearity, which enhances vibration-induced strain and enables effective frequency tuning. The nonlinear magnetic interaction broadens the operational bandwidth and improves energy conversion performance under low excitation amplitudes. The system is tuned to operate over a broadband frequency range of 110–130 Hz, with optimal performance achieved at acceleration amplitudes of less than 0.5 g, corresponding to the measured VTU vibration levels during the cruise phase of the flight. An experimental prototype was tested in the laboratory under aircraft cruise-phase vibration conditions, successfully achieving maximum power of 0.041 mW at optimum resistance of 390 KΩ and 5.45 mJ of stored energy in a 1000 µF capacitor within 10 min, confirming the feasibility of the proposed harvester for aircraft SHM applications. Full article

Small fiber neuropathy (SFN) is an early and common manifestation of diabetic polyneuropathy in type 2 diabetes mellitus (T2DM), often presenting with pain, dysesthesia, and autonomic dysfunction. Conventional diagnostic methods primarily assess large nerve fibers and may miss early small fiber damage, while skin biopsy, though considered the reference standard, is invasive. Corneal confocal microscopy (CCM) offers a rapid, noninvasive alternative for visualizing and quantifying small nerve fiber pathology in vivo. This was a monocentric observational study including 80 adults with T2DM (18–75 years), conducted at Alexandrovska Hospital, Sofia. Peripheral neuropathy was evaluated using a modified Neuropathy Disability Score and CCM-derived corneal nerve fiber density (CNFD), length (CNFL), and branching density (CNBD). Autonomic and sudomotor function were assessed by cardiovascular reflex tests and Sudoscan. Additional measures included vibration perception threshold, carotid intima–media thickness, body composition analysis, and laboratory parameters. Autonomic neuropathy was present in 66.7% and peripheral neuropathy in 57.5% of participants. Affected patients were older and had higher BMI and longer diabetes duration; peripheral neuropathy was additionally associated with higher HbA1c. Corneal nerve parameters negatively correlated with diabetes duration, HbA1c, intima–media thickness, and vibration threshold. Patients with diabetic retinopathy showed significantly reduced CNFD and CNFL. ROC analysis demonstrated significant discriminative ability of the HRV index for identifying peripheral neuropathy and of CNFD for detecting sudomotor dysfunction. These findings support CCM as a valuable, noninvasive marker of small fiber damage, closely linked to metabolic control, vascular impairment, and both sensory and autonomic dysfunction in T2DM. Full article

Tension leg platform (TLP) floating offshore wind turbines (FOWTs) show strong potential for future commercial deployment for the advantages in global performance, cost efficiency, and economic spatial utilization. However, as system sizes expand and multi-source vibrations become more prominent, the integrated design and dynamic responses of the FOWT system grow increasingly complex. This research presents the design of a TLP foundation for a 22 MW FOWT and examines its dynamic response under extreme sea states via a combined numerical and experimental approach. An integrated numerical model of the TLP FOWT is established and subsequently calibrated using data obtained from a 1:64 scale physical model test in a wind-wave flume. By using the calibrated model, the reliability of the TLP FOWT was further validated through an extended Ultimate Limit State (ULS) analysis under a 50-year return period metocean data in the East China Sea. Numerical study demonstrates that the extreme motion responses under 50-year return period data comply with safe operational limits, and the safety factors meet standard specifications. Therefore, this study provides a systematic design scheme along with valuable model test data. These contributions serve as a critical reference for the design and research of future large-megawatt TLP FOWTs. Full article

Railway traffic monitoring requires robust detection technologies capable of operating reliably under real-world vibration and environmental conditions. In this work, we present the design and validation of an optical vibration sensor based on a Single-mode–Multimode–Single-mode (SMS) fiber structure for Light Rail Vehicle (LRV) detection. The sensing mechanism relies on multimodal interference in the multimode fiber (MMF), where rail-induced vibrations modify the guided mode distribution and, consequently, the transmitted optical intensity. The optical signal is converted to voltage and processed through an embedded acquisition system. Additionally, we conducted tests with freight trains and maintenance trains in order to evaluate the applicability of the sensor in other types of trains besides the LRV. We conducted laboratory experiments to assess mechanical stability, sensibility, and packaging strategies, followed by supervised field tests on an operational LRV line. The recorded time-domain signal exhibited clear modulation during train passage, and first-derivative and sliding-window variance analyses were applied to reliably identify vibration events, even in the presence of slow baseline drift. In addition, frequency-domain analysis was performed by applying the Fast Fourier Transform (FFT) to the measured signal, enabling the identification of characteristic low-frequency spectral components induced by train passage. A quantitative sensitivity assessment was further carried out by correlating the integrated spectral energy (0–12 Hz) with vehicle weight, yielding a linear response with a sensitivity of 0.0017 a.u./t and coefficient of determination $R^2=0.933$. The proposed solution demonstrated stable operation using commercially available low-cost components, confirming the feasibility of SMS-based optical sensing for railway monitoring. These results indicate strong potential for future deployment in traffic safety systems and distributed sensing networks. Full article

A new procedure for diagnosing damage to the fuel injection system of marine engines, along with vibration acceleration signal symptoms, is explored with a related built, developed, and tested measuring system. This work fills an important gap given the current lack of a scientific solution to this problem. A vibration acceleration signal sensor, mounted on a holder elaborated on by the authors, is positioned on the injection pipe between the injection pump and the injector. The output signals from the sensor are sent to an acquisition and analysis system, which is used for processing the signals in the time, amplitude, frequency, and time–frequency domains. Experimental choices, using multiple parameters for a given signal analysis field, are based on the location of the optimal sensor, the direction of the sensor mounting, and the selection of a cumulative diagnostic symptom. The vibration acceleration signals recorded along the injection pipe are found to have the strongest magnitude. This article compares diagnostic values from these signals with previously determined upper and lower limits. As a result, the tested fuel injection system is classified as either able or disabled, using unparalleled tolerance ranges given for both the upper and lower limits. The values of the limits are determined based on the average value for an ability state plus or minus three times the standard error of this mean, which has not been reported in the literature previously. Multiple regression models are developed that relate identified symptoms to the state features of the fuel injection system. In addition, artificial neural networks and machine learning are used to detect developing damage. The probability of correctly classifying the states of the diagnostic parameters is 0.467, alongside a diagnostic accuracy of ≤±4%, with the network correctly classifying the state when the testing accuracy is at least 70.0%. Full article

Steels remain among the most widely used structural and engineering materials in modern infrastructure, energy systems, and industrial facilities. Their long-term reliability depends critically on the early detection of corrosion damage and microstructural degradation. This review surveys recent advances in two complementary families of non-destructive evaluation (NDE) methods: magnetic techniques, including magnetic Barkhausen noise (MBN), magnetic flux leakage (MFL), eddy current testing (ECT), and magnetic hysteresis analysis; and electrochemical methods including electrochemical impedance spectroscopy (EIS), linear polarization resistance (LPR), scanning vibrating electrode technique (SVET), and electrochemical noise (EN). Recent progress in sensor miniaturization, signal processing algorithms, and multi-technique integration is reviewed. Particular attention is given to the sensitivity of these methods to microstructural changes reported in the literature, including carbide dissolution, phase transformations, temper embrittlement, and sensitization in stainless steels, as well as to the conditions under which such sensitivity has been demonstrated. The potential synergy between magnetic and electrochemical monitoring is discussed as a possible pathway toward more robust, condition-based maintenance frameworks. Challenges related to field deployment, environmental interference, calibration, and data interpretation are identified, and future directions—including machine learning-assisted analysis and multi-physics sensor arrays—are outlined. Full article

Field breeding trial-plot harvesting is one of the key processes in crop breeding, as any mixing between varieties during harvest directly leads to the invalidation of breeding data. Therefore, achieving zero-residue self-cleaning inside the machine during harvesting is essential. Existing studies have largely relied on simulations to optimize cleaning parameters. However, research specifically targeting the synergistic design of the mechanical and pneumatic components of the cleaning device to achieve efficient and thorough self-cleaning in complex real-world conditions remains lacking. To address this issue, this paper presents a novel cleaning system specifically designed for efficient self-cleaning and optimizes its key parameters. Key structural parameters of the straw walker, vibrating sieve, and cleaning fan were analyzed, establishing preliminary ranges for crank speed, sieve-airflow angle, and fan speed. A test bench was developed, and single-factor experiments were conducted to investigate the effects of these parameters on core self-cleaning indicators, including the self-cleaning rate and self-cleaning time. The optimal parameter combination was obtained using the Box–Behnken design (BBD) response surface methodology: a crank speed of 390.80 r/min, a sieve-airflow angle of 29.88°, and a fan speed of 1995 r/min. Bench tests validated that the system achieved excellent cleaning performance while ensuring a self-cleaning rate of 100% and a reduced self-cleaning time of 20 s. The system’s effectiveness was further validated through field experiments using a 4LX1 prototype harvester on three wheat varieties. Results demonstrated zero grain mixing between plots, with self-cleaning times of 9–12 s. Both bench and field test results exceeded the relevant standards, effectively resolving the long-standing issue of grain residue in trial plot harvesting. Through dual validation, this study provides a referential solution for addressing grain residue and establishes a theoretical foundation for the synergistic design of efficient and precision breeding harvest technologies. Full article