Oscillation Characteristics Research Articles

Study on the coupling mechanism and suppression characteristics of swirl premixing combustion self-excited oscillation

The numerical simulation method was used to study the mutual influence of flow field disturbance, vortex change, flame structure change, heat release pulsation, and pressure pulsation on the coupling mechanism and suppression characteristics of self-excited oscillations. The results indicate that perturbations from the jet have a direct impact on the structure of the flame and the alteration of the vortex. Vortex changes have a direct impact on heat release and flame structure. Changes in flame structure can cause pulsations in heat release. Oscillatory combustion is caused by the coupling of multiple factors, including heat release pulsations, flow field perturbations, acoustic vibrations, vortex variations, and flame variations. Pressure pulsations can be suppressed by a circumferentially arranged jet. The optimal solution for suppressing pressure pulsations can be achieved by adjusting the optimal jet angle (φ) and jet rotation direction. Adjusting the value of |φ| can solve the problems of poor local ΔPmax suppression caused by upstream swirled interference and the narrow range of downstream influence of the jet, at |φ| = 10°, the suppression effect is more pronounced in the counter-rotating direction than in the forward-rotating direction.

Correlating analysis and optimization between hydropower system parameters and multi-frequency oscillation characteristics

This paper aims to study the relationship between multi-frequency oscillation characteristics and parameters of hydro-turbine governing systems (HTGS), as well as improve the system oscillation quantification accuracy and primary frequency regulation performance. Firstly, an HTGS model with multi-frequency oscillation characteristics is established using an actual hydropower system as the object. Then, system oscillation components and the sources of each oscillating link are identified using eigenvalue and correlation analysis. To address the issue that sub-wave interference with dominant oscillation quantization, we innovatively incorporate correlation and frequency indexes into quantification process, and the dominant oscillations of complex HTGS are accurately quantified. On this basis, the detailed partitioning of control parameters is established to obtain the guide graph quickly reflecting the relationship between control parameters and system oscillations. Finally, an integrated optimization strategy with ultra-low frequency oscillation (ULFO) safety and regulation performance constraints is constructed, and control parameters are further optimized under two typical parameter setting methods. The results indicate over 90 % of the stable parameters enable the system to enter ULFO mode, and optimized control parameters utilizing proposed strategy increase regulation speed by 46 % while effectively suppressing ULFO. This paper provides a powerful tool and novel ideas for complex HTGS oscillation analysis and parameter optimization.

Proposing a physical mechanism to explain various observed sources of QPOs by simulating the dynamics of accretion disks around the black holes

We propose a mechanism to explain the low-frequency QPOs observed in X-ray binary systems and AGNs. To achieve this, we perturbed stable accretion disks around Kerr and EGB black holes at different angular velocities, revealing characteristics of shock waves and oscillations on the disk. By applying this perturbation to scenarios with varying alpha values for EGB black holes and different spin parameters for Kerr black holes, we numerically observed changes in the disk dynamic structure and its oscillations. Through various numerical models, we found that the formation of one- and two-armed spiral shock waves on the disk serves as a mechanism for generating QPOs. We compared the QPOs obtained from numerical calculations with the low-frequency QPOs observed in X-ray binary systems and AGN sources, finding high consistency with observations. We observed that the shock mechanism, leading to QPOs, explains the X-ray binaries and AGNs studied in this article. Our numerical findings indicate that QPOs are more strongly dependent on the EGB constant than on the black hole spin parameter. However, we highlighted that the primary impact on oscillations and QPOs is driven by the perturbation angular velocity. The results from the models showed that the perturbation asymptotic speed at V∞=0.2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_{\\infty }=0.2$$\\end{document} independently generates QPO frequencies, regardless of the black hole spin parameter and the EGB coupling constant. Therefore, for the moderate value of V∞\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_{\\infty }$$\\end{document}, a two-armed spiral shock wave formed around the black hole is suggested as a decisive mechanism in explaining low-frequency QPOs.

The influence of boreal summer intraseasonal oscillations on precipitation extremes and their characteristics in Southeast Asia

The regional characteristics of the boreal summer intraseasonal oscillations (BSISO) over southeast Asia are presented. The northeastward transition of the BSISO is characterised by 4 phases, such that convection is enhanced over the Philippines and Indochina in phase 1 and suppressed over Peninsular Malaysia, Borneo and Java. The opposite is true in phase 3. The role of BSISO in modulating extreme precipitation is highlighted, showcasing how its phases impact both the frequency and intensity of extreme precipitation events across the region. Using a method to detect and characterise precipitation features in terms of precipitating areas and their associated object properties, this study shows distinct shifts in precipitation regimes during different phases of the BSISO. Phase 1 exhibits increased large-scale convective activity, particularly affecting regions like the South China Sea and northern Philippines, linked to increased tropical storm frequency but reduced localised extreme precipitation events. In contrast, Phase 3, with active convection over Peninsular Malaysia, Borneo and Sumatra, shows intensified extreme precipitation from smaller to medium-sized areas. BSISO phases also modify the distribution of small and large precipitation objects over land, ocean, and coastal regions. This classification of precipitation regimes provides detailed insights into how the BSISO’s large-scale envelope modifies regional precipitation extremes through various precipitation properties. This information could benefit probabilistic predictions of regional extreme precipitation events at subseasonal time scales.

High-Performance Bidirectional Microelectrode Array for Assessing Sevoflurane Anesthesia Effects and In Situ Electrical Stimulation in Deep Brain Regions.

Precise assessment of wakefulness states during sevoflurane anesthesia and timely arousal are of paramount importance to refine the control of anesthesia. To tackle this issue, a bidirectional implantable microelectrode array (MEA) is designed with the capability to detect electrophysiological signal and perform in situ deep brain stimulation (DBS) within the dorsomedial hypothalamus (DMH) of mice. The MEA, modified with platinum nanoparticles/IrOx nanocomposites, exhibits exceptional characteristics, featuring low impedance, minimal phase delay, substantial charge storage capacity, high double-layer capacitance, and longer in vivo lifetime, thereby enhancing the sensitivity of spike firing detection and electrical stimulation (ES) effectiveness. Using this MEA, sevoflurane-inhibited neurons and sevoflurane-excited neurons, together with changes in the oscillation characteristics of the local field potential within the DMH, are revealed as indicative markers of arousal states. During the arousal period, varying-frequency ESs are applied to the DMH, eliciting distinct arousal effects. Through in situ detection and stimulation, the disparity between these outcomes can be attributed to the influence of DBS on different neurons. These advancements may further our understanding of neural circuits and their potential applications in clinical contexts.

Fenobam modulates distinct electrophysiological mechanisms for regulating excessive gamma oscillations in the striatum of dyskinetic rats

Gamma oscillations have been frequently observed in levodopa-induced dyskinesia (LID), manifest as broadband (60-120 Hz) and narrowband (80-110 Hz) gamma activity in cortico-striatal projection. We investigated the electrophysiological mechanisms and correlation of gamma oscillations with dyskinesia severity, while assessing the administration of fenobam, a selective metabotropic glutamate receptor 5 (mGluR5) antagonist, in regulating dyskinesia-associated gamma activity. We conducted simultaneous electrophysiological recordings in Striatum (Str) and primary motor cortex (M1), together with Abnormal Involuntary Movement Scale scoring (AIMs). Phase-amplitude coupling (PAC), power, coherence, and Granger causality analyses were conducted for electrophysiological data. The findings demonstrated increased beta oscillations with directionality from M1 to Str in parkinsonian state. During on-state dyskinesia, elevated broadband gamma activity was modulated by the phase of theta activity in Str, while M1 → Str gamma causality mediated narrowband gamma oscillations in Str. Striatal gamma power (both periodic and aperiodic power), periodic power, peak frequency, and PAC at 80 min (corresponding to the peak dyskinesia) after repeated levodopa injections across recording days (day 30, 33, 36, 39, and 42) increased progressively, correlating with total AIMs. Additionally, a time-dependent parabolic trend of PAC, peak frequency and gamma power was observed after levodopa injection on day 42 from 20 to 120 min, which also correlated with corresponding AIMs. Fenobam effectively alleviates dyskinesia, suppresses enhanced gamma oscillations in the M1-Str directionality, and reduces PAC in Str. The temporal characteristics of gamma oscillations provide parameters for classifying LID severity. Antagonizing striatal mGluR5, a promising therapeutic target for dyskinesia, exerts its effects by modulating gamma activity.

The influence of roll angles on unsteady aerodynamics in a canard‐configured missile

AbstractDuring the initial stage of vertical launch, a missile may exhibit an uncertain roll angle (φ) and a high angle of attack (α). This study focuses on examining the impact of roll angle variations on the flow field and the unsteady aerodynamics of a canard‐configured missile at α = 75°. Simulations were performed using the validated k‐ω SST turbulence model. The analysis encompasses the temporal development of vortices, the oscillatory characteristics of the lateral force, and the fluctuation of kinetic energy distribution within the framework of proper orthogonal decomposition (POD). The results indicate that the flow field surrounding the canard‐configured missile is characterized by inconsistent shedding cycles of Kármán‐like and canard‐separated vortices. A distinct transition zone is identified between these vortices, where vortex tearing and reconnection phenomena occur. With increasing roll angles from 0° to 45°, there is an observed shift in the dominant frequency of the lateral force from the higher frequency associated with Kármán‐like vortex shedding to the lower frequency of canard vortex shedding. The shedding frequency of Kármán‐like vortices corresponds to the harmonics of the canard vortex shedding frequency, indicative of a higher‐order harmonic resonance. The frequency of the lateral force is observed to decrease with an increase in roll angle, except in configurations lacking distinct canard‐separated vortices, which are characterized by a “+” shape. The POD analysis reveals that the majority of the fluctuation energy is concentrated in the oscillations and shedding of the canard‐separated vortices, leading to pressure fluctuations that are primarily observed on the canard and the downstream region of the canard.

Spindle chirp and other sleep oscillatory features in young children with autism

ObjectivesTo determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism. MethodsAutomated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35–8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD). ResultsPosterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient. ConclusionsFor the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.

Frequency and amplitude of flashing-induced instability in an open natural circulation loop

Several nuclear reactor designs rely on passive containment cooling systems. The so-called containment wall condenser relies on natural circulation loops to extract heat from high-temperature steam in the containment to a water tank at ambient pressure. In such passive systems, phase changes can happen and cause flow instabilities in the cooling loop. The flashing-induced instability occurs when the heated fluid in the riser suddenly vaporizes due to a hydrostatic pressure decrease. This instability causes periodic flow peaks, which are of major concern but whose characteristics have not been studied quantitatively.This paper presents two analytical models that predict the flashing frequency and a maximum flow amplitude from geometry and basic operating parameters such as power level and reservoir temperature. The expressions are derived from a physical analysis and do not involve any calibration constants. The flashing frequency appears to be driven by the power level, the inlet temperature and the riser pipe geometry. For the amplitude, the maximum flow rate can be expressed in a Froude number that depends only on the total pressure losses. These models are validated against PASI experiments and system-scale simulations with the CATHARE 3 code, both performed as part of the European Commission funded PASTELS project. Additional data from numerous experimental studies in the literature are used to extend the validity range of the frequency model.Successfully validated against experimental data and additional simulations, these models provide an explicit relationship between oscillations characteristics and design parameters, making them valuable tools for nuclear engineers.

Scale-invariant breathing oscillations and transition of the electron energization mechanism in magnetized discharges

Scale-invariant breathing oscillations are observed in similar magnetized discharges at different spatiotemporal scales via fully kinetic particle-in-cell simulations. With an increase in the similarity invariant B/p, i.e., the ratio of magnetic field to pressure, breathing oscillations are triggered, leading to an appreciable time-averaged potential fall outside the sheath. With the onset and development of breathing oscillations, the electron energization mechanism shifts from sheath energization to direct Ohmic heating in the ionization region due to the change in the potential fall inside and outside the cathode sheath. Based on the scale invariance of the Boltzmann equation and its collision term, the characteristics of breathing oscillations and the transition of the electron energization mechanism are confirmed to be scale-invariant under similar discharge conditions.

The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device

In recent years, brainprint recognition has emerged as a novel method of personal identity verification. Although studies have demonstrated the feasibility of this technology, some limitations hinder its further development into the society, such as insufficient efficiency (extended wear time for multi-channel EEG cap), complex experimental paradigms (more time in learning and completing experiments), and unclear neurobiological characteristics (lack of intuitive biomarkers and an inability to eliminate the impact of noise on individual differences). Overall, these limitations are due to the incomplete understanding of the underlying neural mechanisms. Therefore, this study aims to investigate the neural mechanisms behind brainwave recognition and simplify the operation process. We recorded prefrontal resting-state EEG data from 40 participants, which is followed up over nine months using a single-channel portable brainwave device. We found that portable devices can effectively and stably capture the characteristics of different subjects in the alpha band (8-13Hz) over long periods, as well as capturing their individual differences (no alpha peak, 1 alpha peak, or 2 alpha peaks). Through correlation analysis, alpha-band activity can reveal the uniqueness of the subjects compared to others within one minute. We further used a descriptive model to dissect the oscillatory and non-oscillatory components in the alpha band, demonstrating the different contributions of fine oscillatory features to individual differences (especially amplitude and bandwidth). Our study validated the feasibility of portable brainwave devices in brainwave recognition and the underlying neural oscillation mechanisms. The fine characteristics of various alpha oscillations will contribute to the accuracy of brainwave recognition, providing new insights for the development of future brainwave recognition technology.

An experimental study on in-cylinder soot formation and flame oscillation of renewable fuel blends in an optical engine

Methanol has been widely recognized as a promising alternative fuel for mitigating greenhouse gas emissions. However, its application in internal combustion engines often necessitates blending with a high-reactivity fuel to address challenges related to ignitability and combustion stability. In this study, a two-color method was employed in a single-cylinder optical engine to investigate the characteristics of soot formation and flame oscillation of methanol blended with a high-reactivity fuel, hydrogenated catalytic biodiesel (HCB), under partially premixed combustion (PPC) modes. The blended fuels include M15 (15% methanol, 60% HCB, and 25% n-octanol) and M25 (25% methanol, 60% HCB, and 25% n-octanol), with pure hydrogenated catalytic biodiesel M0 (100% HCB) serving as the reference fuel. N-octanol was utilized as the co-solvent to enhance the stability of the mixture. The results indicate that, employing double-injection strategies, as the methanol content increases in the blended composition, leading to a postponed peak cylinder pressure and heat release rate during combustion. Thanks to the high-level premixed combustion and higher oxygen content, the increases of alcohol blending significantly reduced in-cylinder soot formation. Double-injection strategies reduced soot production effectively and resulted in a more uniform soot distribution compared to single-injection strategies. In terms of flame oscillation, its amplitude primarily correlates with the rate of cylinder pressure rise, while the methanol content within the blends exerts a minor impact on flame oscillation. Double-injection strategies contributes to a more uniform fuel distribution, ensuring a smoother heat release process and significantly reducing flame oscillation amplitudes compared to single-injection strategies.

Diagnosis of unsteady disturbance characteristics induced by the tip leakage vortex in a compressor based on data-driven modal decomposition methods

The structural information about the tip leakage vortex at the design point remains largely unknown. Here, the dynamic mode decomposition method is utilized to visualize the main coherent structures corresponding to unsteady disturbance frequencies induced by the tip leakage vortex of an isolated rotor at the design point. The results show that the tip clearance size has a significant impact on unsteady disturbance characteristics at the blade tip region. The flow field within the blade tip region can be categorized into four distinct regions: the formation region of the main tip leakage vortex (MTLV), the formation region of the secondary tip leakage vortex (STLV), the merging zone where the MLTV and the STLV interact, and the vortex shedding zone induced by the leakage vortex breakdown. The disturbance peak in the frequency domain decreases from 121.3 RF to 70.96 RF as the tip clearance size increases from 1.5% blade height to 2%, resulting in a reduction of 41.36%. The increase in the tip clearance size amplifies unsteady disturbances caused by the MTLV and STLV. The STLV exhibits more pronounced oscillatory characteristics than the MTLV. The unsteady disturbance induced by the MLTV mainly occurs at around 0.5 blade passing frequency (BPF). In contrast, high-frequency unsteady disturbances (>1 BPF) in the flow field are caused by vortex shedding resulting from the interaction and collision between the STLV and the MTLV. A better understanding of the unsteady disturbance characteristics induced by leakage vortex benefits the study of stall warning technology.

Optimized MMC passive impedance shaping method for high frequency oscillation suppression

Recent years, there have been several high-frequency oscillation events in modular multilevel converter (MMC) based DC current projects. Considering the wideband oscillation characteristics of this issue, passive MMC impedance shaping methods are superior solutions for their advantages over the active methods in enhancing the broadband damping level. However, the optimization of parallel passive devices mainly focused on reactive power compensation and the suppression of characteristic harmonics generated by low-level inverters, which is not applicable to MMC systems. To address the optimization design problem of passive damping devices, this paper proposes an optimized design method for passive filters by analyzing the relationship between the passive damping device and the impedance shaping effect of the inverter. The proposed method reduces the capacity of the passive damping device while ensuring system stability margin. Finally, the effectiveness of the proposed passive impedance shaping strategy is verified through time-domain simulations considering changes in AC side operating conditions and power reduction operation of the MMC.

Human local field potentials in motor and non-motor brain areas encode upcoming movement direction

Limb movement direction can be inferred from local field potentials in motor cortex during movement execution. Yet, it remains unclear to what extent intended hand movements can be predicted from brain activity recorded during movement planning. Here, we set out to probe the directional-tuning of oscillatory features during motor planning and execution, using a machine learning framework on multi-site local field potentials (LFPs) in humans. We recorded intracranial EEG data from implanted epilepsy patients as they performed a four-direction delayed center-out motor task. Fronto-parietal LFP low-frequency power predicted hand-movement direction during planning while execution was largely mediated by higher frequency power and low-frequency phase in motor areas. By contrast, Phase-Amplitude Coupling showed uniform modulations across directions. Finally, multivariate classification led to an increase in overall decoding accuracy (>80%). The novel insights revealed here extend our understanding of the role of neural oscillations in encoding motor plans.

Bursting oscillation characteristics and adaptive high‐order differential feedback controller of doubly fed induction generator system

SummaryTo address the problem of bursting oscillations in doubly fed induction generator (DFIG) systems under external disturbances, an analysis method based on fast‐slow dynamics and a control strategy based on an adaptive high‐order differential feedback controller (AHODFC) is proposed. The fast‐slow dynamics analysis method was adopted to reveal the formation mechanism of bursting oscillations from the DFIG system owing to the multi‐timescale coupling effect of perturbation, that is, the oscillation is in the form of a bursting oscillation with alternating large‐amplitude oscillation and micro‐amplitude oscillation. A control strategy based on the AHODFC with a high‐order differentiator (HOD) was proposed to address the problem of bursting oscillations in the DFIG system. The control strategy of the AHODFC has smooth control‐rate characteristics, does not depend on the exact mathematical model of the controlled system, and has good applicability and robustness to various types of bursting oscillations caused by different disturbance amplitudes and system parameters. Our simulations verified the feasibility and effectiveness of the proposed method.

Regressing bubble cluster dynamics as a disordered many-body system

The coherent dynamics of bubble clusters are of fundamental and industrial importance, and are elusive due to the complex interactions of disordered bubble oscillations. Here we introduce and demonstrate a method for decomposition of the Lagrangian time series of bubble dynamics data by combining theory and principal component analysis. The decomposition extracts coherent features of bubble oscillations based on their energy, in a way similar to proper orthogonal decomposition of Eulerian flow field data. This method is applied to a dataset of spherical clusters under harmonic excitation at different amplitudes, with various nuclei density and polydispersity parameters. Results indicate that the underlying correlated mode of oscillations is isolated in a single dominant feature in cavitating regimes, independent of the nuclei's parameters. A systematic data analysis procedure further suggests that this feature is globally controlled by the dynamic cloud interaction parameter of Maeda and Colonius (J. Fluid Mech., vol. 862, 2019, pp. 1105–1134) that quantifies the mean-field interactions, regardless of initial polydispersity or nonlinearity. The method provides a simplified and comprehensive representation of complex bubble dynamics as well as a new path to reduced-order modelling of cavitation and nucleation.

An acoustic weighing method based on oscillation signal and feature enhanced network

Acoustic weighing is a promising method for non-contact mass measurement of tiny objects as it avoids contamination and contact losses. However, due to the highly nonlinear nature of the acoustic field, some parameters of the mechanism model of acoustic weighing cannot be accurately simulated, thereby reducing the accuracy of acoustic weighing. To improve the accuracy of acoustic weighing, we propose an acoustic weighing method based on oscillating signals and feature enhancement network. Firstly, to drive the object oscillation and collect oscillation data, an acoustic levitation-based data acquisition system is constructed. Then, to break the limitations of the mechanism model, a feature enhancement network named CNN-BiLSTM-SE is proposed, which directly establishes the correlation between oscillating signals and actual mass. Finally, these data are used to train and test the proposed network model, validating the effectiveness of the model. Experimental results show that the method achieves high accuracy in measuring object mass, following the actual measurements with remarkable consistency. In addition, our approach is also suitable for acoustic weighing of small and sensitive objects, opening up new perspective for the study and application of nonlinear acoustic systems.

Characteristics of a microfluidic single-gate oscillator

Characteristics of a microfluidic single-gate oscillator

On the nonlinear dynamic characteristics of forced acoustic oscillations in a heat-driven thermoacoustic engine

On the nonlinear dynamic characteristics of forced acoustic oscillations in a heat-driven thermoacoustic engine