Search Results (198)

With the development of shipping to harsh marine environment, it is very important to understand the transient behavior of a marine diesel engine in high sea conditions. Wave-induced hull motion will lead to severe load fluctuations and air-fuel ratio imbalance. In this study, an integrated simulation platform coupled with environmental loads, hull dynamics, propeller characteristics and a high-fidelity thermodynamic engine model was constructed to explore the response characteristics of the propulsion system. The model integrates a zero-dimensional multi-zone combustion method, turbocharger dynamic characteristics and an incremental PID governor, and has been verified based on the bench test data of TBD234V12 diesel engine and the 20 m Wigley standard ship. The simulation results under the sea conditions from level 7 to 9 show that the transient load has a nonlinear amplification effect. Specifically, from sea state 7 to sea state 9, the engine load fluctuation range expands by 2.0 times, while the main peak amplitude of speed fluctuation increases by 3.7 times. Furthermore, the peak exhaust pressure rises by 1.8 times, and the exhaust temperature fluctuation amplitude broadens by 35%. Frequency domain analysis further identified the low-frequency energy concentration phenomenon in the exhaust pressure spectrum and the precursor characteristics of compressor surge. The research results quantify the deterioration law of thermodynamic stability and mechanical stress under wave disturbance, and provide an important reference for the formulation of an engine robust control strategy and fatigue life assessment under high sea conditions. Full article

Sweeping jet (SWJ) actuators are widely used in active flow control, but explicitly resolving actuator-scale unsteadiness in full-configuration computational fluid dynamics (CFD) remains prohibitively expensive because of the small geometric scales and high-frequency oscillations involved. Existing reduced-order boundary-condition models constructed from exit-plane data alone can reproduce the observed switching waveform, but they treat the actuator as an input–output black box and provide limited insight into the internal dynamics that generate the response. This work develops a causal state-space reduced-order modeling framework that links internal mixing-chamber dynamics to time-resolved exit-plane boundary conditions. Proper orthogonal decomposition (POD) is used to obtain a low-dimensional representation of the internal flow, and a data-driven linear evolution operator is identified in the reduced space by least-squares regression of successive snapshot pairs. A POD truncation rank of $r=60$ is selected from cumulative-energy and validation-error sensitivity analyses, capturing well above 99% of the fluctuation energy while lying within the converged performance regime. A corresponding reduced operator is identified for the exit plane, and spectral comparison reveals near-neutrally stable oscillatory modes in both regions. Using a $\pm 1\%$ relative frequency-matching tolerance, the dominant reduced-operator modes exhibit a 28.3% frequency overlap, providing operator-level evidence that exit-plane oscillations are dynamically linked to internal coherent structures. This correspondence is further supported by cross-spectral coherence analysis between representative internal and exit-plane probe signals, which shows strong coherence at dynamically relevant frequencies. A delayed causal output mapping is then formulated in which the internal reduced state drives the exit-plane response after an identified lag of 149 time steps, corresponding to $2.98\times {10}^{-3}$ s. This delay provides a physically interpretable convective transport timescale from the mixing chamber to the actuator exit. Over the validation interval, the model maintains a mean relative $L_2$ error below 0.02, with maximum normalized errors below 0.04 for most of the prediction horizon, and localized increases are confined to rapid jet-switching events. Field-level reconstructions of streamwise velocity and total pressure show that the model captures both phases of the jet-switching cycle, with errors concentrated primarily in high-gradient shear-layer regions. Compared with exit-only reduced-order models, the proposed internal-driven formulation improves amplitude and phase fidelity over extended prediction horizons. The resulting framework provides a compact, interpretable, operator-based representation of SWJ actuator dynamics suitable for use as a CFD-embeddable dynamic boundary condition. Full article

Single-frequency fiber lasers (SFFLs) are essential for applications such as gravitational wave detection, high-precision spectroscopy, and inertial confinement fusion, requiring narrow linewidth, low noise, and high output power. Here, we present a comparative study of 1 μm waveband distributed Bragg reflector (DBR) SFFLs with varying cavity parameters. Numerically, we investigate the effects of key cavity parameters on laser performance by plotting contour maps of output power versus grating reflectivity and lasing wavelength. We also simulate intensity noise transfer functions from pump fluctuations. Increasing pump power shifts the relaxation oscillation peak to higher frequency and reduces its amplitude, which originates from the higher intracavity photon density that speeds up the damping of perturbations. Experimentally, we construct two lasers using 6.5 mm and 10.5 mm YDFs spliced between FBG pairs. These lasers employ low-reflectivity FBGs centered at 1053 nm and 1064 nm, with reflectivities of 74% and 55%, respectively. The corresponding maximum output powers are 29.7 mW and 197 mW. The 1053 nm SFFL exhibits a relative intensity noise (RIN) of −102 dBc/Hz at 2.07 MHz, a linewidth of 12.52 kHz, and a mode-hop-free tuning range of 0.64 nm. Although increasing the pump power suppresses the relaxation oscillation peak, it broadens the linewidth due to laser phase noise degradation caused by pump noise-induced temperature fluctuations in the gain fiber. For SFFLs, the output powers should be selected according to the specific application, as a higher output power inherently leads to a broader linewidth. These insights are essential for optimizing such lasers and underscore their strong potential for future applications. Full article

Background: Lumbar disc herniation (LDH) is the most common etiological cause of low back pain (LBP). Objective and precise pain evaluation is of significant clinical value. Functional near-infrared spectroscopy (fNIRS) as a noninvasive neuroimaging modality, has been increasingly validated to reflect subjective pain perception through hemodynamic correlates. This study aimed to analyze the fNIRS changes in patients with LDH about to receive Unilateral Biportal Endoscopy and to further explore the feasibility of fNIRS as an objective biomarkers for clinical assessment of LDH. Methods: Resting-state fNIRS data were acquired from 67 preoperative LDH patients and 20 healthy controls (HC). Brain functional maps—including z-standardized fractional amplitude of low-frequency fluctuations (zfALFF) and seed-based functional connectivity (FC)—were extracted and quantified. Group-level comparisons were performed between LDH and HC groups across four predefined regions of interest; additionally, correlation analyses were conducted between fNIRS metrics and clinical assessment scores within the LDH cohort. Results: Compared with HC, LDH patients exhibited significantly altered zfALFF in the medial prefrontal cortex (mPFC): decreased amplitude at channel CH12 (t = −2.031, p = 0.045) and increased amplitude at CH21 (t = 2.462, p = 0.016). Whole-brain FC analysis further revealed widespread changes—particularly between the parietal somatosensory cortex and prefrontal regions. Among all tested FC–clinical indicator associations, 56 reached statistical significance after FDR correction (q < 0.05). VAS_ lumbar and SF-36_SF exhibited the highest number of significant connections. Conclusions: LDH patients with LBP exhibit notable alterations in prefrontal resting-state ALFF and FC between the parietal somatosensory cortex and prefrontal cortex relative to HC. Importantly, these neural alterations exhibit significant associations with both pain severity (VAS) and long-term health-related quality of life (SF-36), thereby strengthening their candidacy as neural correlates meriting prospective validation as objective, mechanism-informed biomarkers for clinical evaluation of lumbar disc herniation (LDH). Moreover, these findings highlight candidate neural targets for future longitudinal studies investigating early prognostic prediction and treatment response monitoring in LDH. Full article

Background: Frequent nocturnal arousals are a core feature of comorbid insomnia and obstructive sleep apnea (COMISA), yet the underlying central mechanisms remain unclear. Identifying brain functional correlates of nocturnal awakenings may help clarify arousal-related mechanisms and inform potential interventional targets. Methods: A total of 99 participants (COMISA, insomnia alone, OSA alone, and healthy controls) underwent clinical assessments, polysomnography, and brain magnetic resonance imaging (MRI). MRI metrics were compared across groups, followed by correlation and regression analyses with the arousal index, adjusting for respiratory events and insomnia-related factors. Results: Patients with COMISA exhibited more severe insomnia symptoms, greater daytime dysfunction, and more frequent nocturnal awakenings than those with insomnia alone, although their arousal index did not differ from that of the OSA group. Patients with COMISA exhibited altered activity in the right cerebellar lobule VIII (Cerebelum_8_R), left middle temporal gyrus, and right inferior frontal gyrus, opercular part. Lower fractional amplitude of low-frequency fluctuations (fALFF) in the Cerebelum_8_R was associated with a higher arousal index. This association remained significant after controlling for insomnia severity and sleep efficiency but was attenuated after adjustment for AHI. Conclusions: Reduced functional activity in the Cerebelum_8_R was independently associated with sleep fragmentation in COMISA, independent of insomnia severity but potentially mediated by respiratory events. These findings suggest this region may be involved in arousal-related neural regulation and could represent a therapeutic target for the complex symptoms of COMISA. Trial Registration: Chinese Clinical Trial Registry, ChiCTR2500095809. Full article

Aging is a significant risk factor for several neurodegenerative diseases. Understanding brain aging processes is a fundamental step in identifying the early signs of pathological dysfunction. Nonetheless, regional functional changes are still poorly characterized. In this study, we employed Detrended Fluctuation Analysis (DFA) to investigate age-related changes in the scale-free temporal dynamics of blood oxygen level-dependent (BOLD) signal fluctuations derived from resting-state networks. We compared DFA to fractional amplitude of low-frequency fluctuations (fALFF) to assess their ability to discriminate between young and old adults. Significant decreases (p < 0.01) in fALFF in the visuospatial and dorsal default mode networks and in DFA in the salience network, were identified as key predictors of functional brain aging. Using machine learning, we showed that DFA and fALFF provide complementary information for predicting aging, with an accuracy of approximately 80% achieved only through their combined use. Overall, DFA captures alterations in scale-free temporal organization that complement conventional spectral measures, providing additional insight into network-specific functional aging. Full article

Permanent magnet synchronous motors (PMSMs) are utilized in demanding conditions and applications requiring precision and accuracy, such as servo systems. Especially at low speeds, the effects of cogging torque, current measurement and offset errors, improper controller gains, mechanical resonance, and torque fluctuations caused by load torque and flux result in fluctuations at various frequencies in the motor output speed. This study, motivated by two factors, proposes an extended state observer (ESO)-based multivariable fast response extremum-seeking (FESC) interval type-2 fuzzy PID (IT2FPID) controller to improve dynamic response and reduce speed ripple at low speeds in situations where all these negative factors could arise. This approach enables the real-time adaptation of parameters to counteract the decline in controller performance caused by the nonlinear characteristics of PMSMs and parameter fluctuations while also optimizing disturbance rejection in the speed response under varying operating conditions and existing speed ripple. The experimental results from the prototype setup validate that the proposed control mechanism is functional, valid, and precise in diminishing speed ripples during low-speed operations. The simulation and test outcomes of the control scheme show that speed noise at low speeds is reduced from 26% to 3% compared to traditional proportional-integral (PI) controller and supertwisting (STW) sliding mode controller (SMC) responses and that the scheme exhibits a 16–23% reduction in undershoot amplitude and faster recovery in the presence of load torque variations. Full article

When high-altitude aircraft operate in a low-density environment, the flow instability within their internal ducts poses a severe challenge to aerodynamic design and operational safety. Especially in the intake system of the tandem dual-fan configuration, the asymmetric flow caused by rotating machinery coupled with the low-density effect exacerbates flow distortion, momentum dissipation, and efficiency loss and may even trigger system instability risks such as rotational stall or surge. To address these challenges, this paper establishes a high-fidelity dynamic model of the internal flow field of the aircraft, based on the Reynolds-averaged Navier–Stokes equations and the SST k-ω turbulence model, combined with dynamic mesh technology. It reveals the unstable mechanism caused by angular momentum accumulation under co-rotation conditions and its intrinsic correlation with the degradation of aerodynamic performance. Inspired by the concept of micro-flow regulation, an active flow control strategy integrating discrete auxiliary injection and local geometric shape optimization is proposed. Numerical results show that by reasonably arranging auxiliary injection holes in the intake duct and optimizing local geometric fillets, the uniformity of intake flow can be effectively improved, and the formation of large-scale vortex structures can be suppressed. This method increases the system’s flow capacity by approximately 47.4%, significantly improves the total pressure recovery coefficient and fan aerodynamic efficiency, and reduces the amplitude of low-frequency pressure fluctuations by approximately 23.1%. Research shows that in high-altitude low-Reynolds-number conditions, micro-flow regulation combined with geometric reconstruction can effectively suppress flow instability induced by rotating machinery. This achievement provides a theoretical basis and feasible engineering path for aerodynamic stability design and optimization of key components, such as the aircraft intake and exhaust systems and thermal management systems, and is of significant value for improving the overall performance and reliability of high-altitude long-endurance aircraft. Full article

Underground bauxite comprehensive mechanized mining has attracted growing attention, yet regional differences in bauxite characteristics challenge its applicability and economic efficiency. The conical pick, a key cutting tool for this mining method, has cutting load characteristics that directly impact the cutting mechanism’s efficiency and reliability. Three typical bauxite samples from different mining areas were selected as research objects. After testing their composition and firmness coefficients, a linear cutting test bench was used to measure their tri-axial cutting forces at various cutting depths. Regression analysis and the linear fitting of cutting coefficients were conducted to study cutting force and normal force (two core cutting loads). The results show that power functions effectively describe the relationships between the cutting force, normal force, fluctuation coefficient and cutting depth. As the bauxite firmness coefficient and cutting depth rise, the cutting force peak value, fluctuation amplitude and frequency all increase. Excessively high or low cutting coefficients reduce the cutting efficiency; only when both the cutting coefficient and the depth are in an optimal range can the cutting efficiency reach its maximum. Full article

Research on centennial-scale precipitation variability within the Australian summer monsoon (AUSM) remains limited, particularly regarding its driving mechanisms and the sustainability-relevant implications for long-term water security and climate adaptation. Here, we use the TraCE-21ka transient simulation, which credibly reproduces the centennial periodicities documented in Holocene proxy records, to attribute the physical drivers of AUSM centennial variability. Attribution is conducted by contrasting the all-forcing (AF) simulation with four single-forcing experiments that isolate the effects of orbital parameters, ice sheets, meltwater flux, and greenhouse gases. Among these experiments, the meltwater-forcing run best reproduces the centennial periodicities found in the AF simulation, indicating that meltwater input is the leading contributor to Holocene AUSM centennial variability. We further identify a dynamical pathway in which Atlantic Meridional Overturning Circulation (AMOC) variability acts as the key mediator linking meltwater perturbations to Australian hydroclimate. The enhanced AMOC amplitude during the meltwater interval (0.14 at 9–8 ka BP), compared with much weaker fluctuations during the non-meltwater interval (0.01 at 4–3 ka BP), is accompanied by a ~200-year periodicity in AUSM precipitation. This periodicity arises through an interhemispheric teleconnection: a strengthened AMOC cools Southern Hemisphere sea surface temperatures, reduces moisture availability for northern Australia, and promotes large-scale subsidence that suppresses monsoon rainfall. By contrast, during 4–3 ka BP, when meltwater forcing was negligible, weaker AMOC variability coincides with warmer Southern Hemisphere sea surface temperature (SST), favoring cyclonic circulation over northwestern Australia, enhanced moisture convergence, and stronger ascent, ultimately intensifying AUSM precipitation. Beyond advancing process understanding, these results provide a sustainability-oriented framework for interpreting low-frequency hydroclimate variability relevant to Australia’s water resources and climate adaptation. Specifically, the identified meltwater–AMOC–SST–AUSM pathway offers a physical basis for developing and evaluating long-horizon indicators of monsoon-driven rainfall variability, informing monitoring strategies and scenario planning for drought–flood risk management, water allocation, and climate-resilient infrastructure. By linking centennial-scale monsoon variability to an identifiable remote driver, this study contributes to quantifying and contextualizing natural hydroclimate variability that can confound near-term trends, thereby supporting more robust sustainability assessments, adaptation policy design, and integrated water-resource management under ongoing climate change. Full article

Identifying the time-domain waveform type under broadband conditions is a basic but very challenging task. Traditional methods based on frequency domain or training models generally have the problems of high resource consumption, large delay, and unsuitability for hardware. This paper proposes a time-domain waveform recognition architecture based on an FPGA, which is integrated with multi-feature voting. Several lightweight time domain characteristics, such as high amplitude ratio, symmetry, slope uniformity, slope change rate, and flat-top characteristics, are extracted and directly used for waveform classification. Then classify sine waves, square waves, triangular waves, and noise in the time domain according to the decision-making mechanism of voting. In order to improve reliability under non-ideal conditions, adaptive thresholds and noise perception decision-making logic are used to suppress misclassifications caused by random fluctuations and jitter. The whole engineering design focuses on resource consumption and hardware efficiency, using a fully pipeline FPGA architecture. The experimental results prove that the system has the ability of high-precision identification, low power consumption, and real-time processing in the wide frequency band, providing an efficient and practical solution for embedded waveform recognition applications. Full article

Background: In temporal lobe epilepsy (TLE), locally reduced glucose metabolism (i.e., hypometabolism) is indicative of the epileptogenic onset zone (EZ). Here, we investigate the potential value of resting-state fMRI (rs-fMRI) for localizing the EZ with fluorodeoxyglucose positron emission tomography (FDG-PET) as ground truth. Methods: Twelve PET-positive patients (34.1 ± 13.1 y; 5 females) with unilateral drug-resistant TLE were included. FDG-PET and rs-fMRI were acquired simultaneously at a hybrid 3T PET-MR scanner. Hypometabolic regions were identified on the FDG-PET images by a nuclear medicine expert. The FDG-PET images were compared with a clinical FDG-PET control dataset with normal glucose uptake distribution. The output z-score maps were thresholded at z < −2 to produce a binary mask of the significantly hypometabolic regions. The hypometabolism masks were mirrored onto the contralateral hemisphere for the asymmetry comparison. Regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) were calculated from the rs-fMRI in conventional (0.01–0.1 Hz) and slow-3 (0.073–0.198 Hz) frequency bands. Asymmetry indices (AIs) were calculated using the ipsilateral and contralateral hypometabolic masks in the PET-positive subjects and assessed via the one-sample Wilcoxon test and Spearman correlation coefficients. Results: The AIs of conventional fALFF were significantly lower in the hypometabolic zone (p < 0.05). A significant negative correlation was found between the AIs of FDG-PET and fALFF in the slow-3 band (r = −0.62; p < 0.05). Conclusions: Conventional and slow-3 band fALFF showed a potential to mimic the FDG-PET findings in terms of EZ localization. Further research with extended cohorts and histopathological validation is required to determine the clinical value. Full article

The momentum transport and scale-dependent motion characteristics within vegetation canopies play a crucial role in shaping near-surface turbulent structures and exchange processes, yet the interactions among different turbulent scales and their statistical representations remain insufficiently understood. Based on a series of controlled wind tunnel experiments, this study identifies coherent turbulent structures using a phase-space algorithm constructed from streamwise velocity fluctuation u′, acceleration a, and jerk j, and compares transport efficiency (exuberance η). This study uses scale-wise (cut-off frequency) momentum flux contribution analysis, natural visibility graph (NVG), and large–small-scale amplitude modulation to examine transport and multiscale behaviors across different canopy densities, array layouts, and inflow conditions. Results show that canopy density (different C_d drag coefficient) is a primary factor governing transport efficiency. Under low-wind staggered configurations, increasing canopy density strengthens the contribution of low-frequency large-scale motions to total momentum flux. In contrast, high-wind aligned configurations intensify canopy-top shear, enhancing small-scale motions and thereby reducing the relative contribution of large-scale motions. NVG analysis further reveals that in high-density canopies, large-scale acceleration and deceleration events tend toward equilibrium, whereas deceleration events dominate consistently in low- and medium-density cases. Amplitude modulation results indicate that high-density cases exhibit highly consistent modulation behavior, followed by low-density cases, while medium-density cases display a pronounced height-dependent variation, characterized by a distinct modulation critical point. This study proposes a unified analytical framework integrating coherent structure detection, graph-theoretic analysis, multiscale transport characterization, and large–small-scale modulation, providing a comprehensive description of momentum transport and scale motions within canopy flows, and it offers new insight into the mechanisms governing complex vegetation canopy turbulence. Full article

Low-frequency oscillatory flow is a long-standing instability in cryogenic jet condensation systems and is closely associated with abnormal pressure fluctuations in propulsion pipelines. While previous studies mainly focused on operating conditions, the role of injector orifice layout in triggering low-frequency oscillations remains unclear. In this work, a three-dimensional numerical investigation was conducted to examine the effect of orifice layout on condensation-induced oscillatory flow in an oxygen jet condensation system. A curvature-coupled mass transfer model is employed, in which the interfacial mass transfer rate is dynamically linked to local vapor–liquid interfacial curvature, enabling accurate representation of interfacial evolution. A series of numerical cases are designed by varying the number, arrangement, and diameter of orifices under different combinations of mass rate, mass flux, and total injection area. Two distinct condensation patterns are identified: suck-back chugging and weak pulsation. Pronounced low-frequency oscillations are observed only for specific orifice layouts. When the total injection area and gaseous oxygen mass rate are maintained, chugging persists under different layouts, producing dominant frequencies of approximately 10~11 Hz and pressure amplitudes of about 80~120 kPa. Once either the total area or mass rate is altered, the system transitions to weak pulsation with pressure fluctuations below 3 kPa. These results demonstrate that low-frequency oscillatory flow is a layout-enabled instability rather than a mass-flux-controlled phenomenon, highlighting the importance of injector geometric design in regulating condensation-induced oscillations. Full article

Groundwater heavy metal contamination (GHMC) has drawn significant attention in China over recent decades due to industrialization. However, effective monitoring and early warning remain global challenges because of the limited understanding of heavy metal behavior in groundwater. This study conducts a detailed comparative analysis of heavy metals and conventional indicators using a long-term, high-frequency online monitoring program. Groundwater online monitoring is an automated system for real-time, continuous collection, and transmission of indicators via sensors and IoT platforms. Conventional indicators refer to the priority parameters used to assess basic water quality, hydrological characteristics and health risks in routine monitoring. Nineteen heavy metals and ten conventional indicators were monitored simultaneously, generating approximately 1.6 million data points over three years. The time series data show that online monitoring effectively captures abnormal changes in heavy metal levels. Abnormal heavy metal fluctuations appear as sharp, isolated spikes lasting at least several hours, while conventional indicators exhibit high-amplitude variations lasting over 30 h—indicating that heavy metal changes are harder to detect in a timely manner. Long-term comparisons also reveal low consistency between heavy metals and conventional indicators, supporting the need for independent heavy metal monitoring. In contrast, strong consistency among heavy metals suggests opportunities to streamline monitoring by selecting representative elements. Monitoring frequency optimization shows that daily measurement is sufficient for heavy metals, which is slightly more frequent than the typical three-day interval for most conventional indicators. Long-term data enable reliable early warnings for both indicator types, with predictions closely matching field observations. However, heavy metal alerts are shorter and less frequent than those for conventional indicators. Integrating both types into a unified early warning system enhances its comprehensiveness, accuracy and timeliness. This study provides a solid scientific foundation for efficient GHMC monitoring and early warning in groundwater in areas under the influence of industrial activities. Full article