Occurrence Of Oscillations Research Articles

Dynamic phase transition region in electrically injected PT-symmetric lasers

Research on parity-time (PT) symmetry and exceptional points in non-Hermitian laser systems has been extensively conducted. However, in practical electrically injected PT-symmetric lasers, the frequency detuning and linewidth enhancement factor of the laser can influence the symmetry breaking of the system in another dimension. We find that the previous exceptional point now transforms into a dynamic phase transition region, where the states are temporally unstable, indicating the occurrence of multimode oscillation. The relative phase and field amplitude ratio in this region also exhibit many novel phenomena indicating its instability. This region can be manipulated by adjusting the coupling strength between adjacent waveguides and the pumping intensity in the loss waveguide. Experimentally, we characterize the near-field, far-field, and spectrum of several structures, and the results validate our theoretical model. This work elucidates the dynamic process and phase transition process of electrically injected PT-symmetric lasers, providing support for the practical application of PT-symmetric lasers.

KEEPING AN ELECTRON BEAM IN POTENTIAL WELL MAGNETIC SOLENOIDAL FIELD

An intense cylindrical magnetic field is considered in which potential well is created with the help of additional magnets. It is shown that the motion of electrons can be associated with model of three-dimensional oscillations in potential well. The results of numerical simulation of electron trajectories in gradient magnetic field with point secondary emission cathode located in the middle of the system are presented. The formation of the beam with energy of 55 keV in the radial and longitudinal directions during its transportation in solenoidal field with large gradient is considered. The operating modes of the gun are obtained, in which the particle experiences stable three-dimensional vibrations. The influence of the initial conditions during emission on the occurrence of oscillations is studied. It is shown that for the given electron energy and the fixed magnetic field, the parameter that determines the stability of particle motion is the polar angle of entry relative to the axis of the cylindrical magnetic field.

Real Time Prediction and Modelling of Power Grid System Stability and Load Balancing

Abstract The extensive geographical distribution of the power system determines its highly complex structure. The system includes key components such as generators, substations, transmission and distribution grids, and users. This system has characteristics such as nonlinearity, time-varying, and parameter uncertainty. Power system stability is inherently linked to its regular operational performance. This article uses Simulink models to simulate the working state of generators and circuit breakers during faults. Under the conditions of a synchronous generator with a rated power of 350MW, a voltage of 10.5KV, a three-phase parallel RLC load rated voltage of 115KV, and a power consumption of 300MW, when a short occurs on line, the speed and relative angle of the generator tend to a fixed value, and the system remains stable. When a fault occurs in the circuit within 0.1 seconds, the circuit breaker will cut off the faulty line within 0.6 seconds. Avoiding the occurrence of oscillations and unstable states in typical dynamic systems.

Effect of Blade Material of Steam Turbine Rotor on Aeroelastic Characteristics

Elements of powerful steam turbines are subjected to significant unsteady loads, in particular the rotor blades of the last stages. These loads, in some cases, can cause self-excited oscillations, which are extremely dangerous and have a negative impact on the efficiency and service life of the blade cascade. Therefore, when designing new or modernizing existing steam turbine stages, it is recommended to study the aeroelastic characteristics of the blades. The conditions for the occurrence of self-excited oscillations are influenced by both the geometric characteristics and the alloy from which the blade is made. To determine the effect of the blade material on the aeroelastic behaviour, a numerical analysis of the aeroelastic characteristics of the last stage blades made of steel and titanium alloy was performed. For the analysis, the method of simultaneous modeling of unsteady gas flow through the blade cascades and elastic vibrations of the blades (coupled problem) was used, which allows obtaining the amplitude-frequency spectrum of the interaction of unsteady loads and blade vibrations. The paper presents the results of numerical analysis for harmonic oscillations with a given amplitude and a given inter-blade phase angle, as well as for the regime of coupled vibration of blades under the action of unsteady aerodynamic forces. The dependences of the aerodamping coefficient on the inter-blade phase angle and the distribution of the coefficient along the blade are presented. The results of modeling the coupled vibration of the blades for the first six natural forms are presented in the form of a time-evolving displacement of the blade peripheral section, as well as forces and moments acting on the peripheral section. The corresponding amplitude-frequency spectra of displacements and loads in the peripheral section are also presented. The analysis of the results showed an insignificant difference in the characteristics of the proposed blade materials. For the first natural form of blade oscillations, the possibility of self-excited oscillations was found, and for the second form, there are conditions for the appearance of stable self-oscillations.

Sleep oscillations related to memory consolidation during aromatases inhibitors for breast cancer

Aromatase inhibitors (AIs) are associated with sleep difficulties in breast cancer (BC) patients. Sleep is known to favor memory consolidation through the occurrence of specific oscillations, i.e., slow waves (SW) and sleep spindles, allowing a dialogue between prefrontal cortex and the hippocampus. Interestingly, neuroimaging studies in BC patients have consistently shown structural and functional modifications in these two brain regions. With the aim to evaluate sleep oscillations related to memory consolidation during AIs, we collected polysomnography data in BC patients treated (AI+, n = 17) or not (AI-, n = 17) with AIs compared to healthy controls (HC, n = 21). None of the patients had received chemotherapy and radiotherapy was finished since at least 6 months, that limit the confounding effects of other treatments than AIs. Fast and slow spindles were detected during sleep stage 2 at centro-parietal and frontal electrodes respectively. SW were detected at frontal electrodes during stage 3. Here, we show lower frontal SW densities in AI + patients compared to HC. These results concord with previous reports about frontal cortical alterations in cancer following AIs administration. Moreover, AI + patients tended to have lower spindle density at C4 electrode. Regression analyses showed that, in both patient groups, spindle density at C4 electrode explained a large variance of memory performances. Slow spindle characteristics did not differ between groups and sleep oscillations characteristics of AI- patients did not differ significantly from those of both AI + patients and HC. Overall, our results add to the compelling evidence of the systemic effects of AIs previously reported in animals, with deleterious effects on cortical activity during sleep and associated memory consolidation in the current study. There is thus a need to further investigate sleep modifications during AIs administration. Longitudinal studies are needed to confirm these findings and investigation in other cancers on this topic should be conducted.

Delay induced Hopf bifurcation and its control in a fractional p53 protein oscillator model

The p53 protein is essential for cancer prevention. Research on p53 mathematical models is popular since its oscillatory dynamics were observed. However, there is little research on fractional-order p53 oscillators, as well as on Hopf bifurcation control. We therefore introduce fractional-order into a p53 oscillator model and propose a delayed state feedback bifurcation controller. The stability of positive equilibrium and the existence of Hopf bifurcation are studied analytically regarding delay as the bifurcation parameter in both controlled and uncontrolled scenarios. Numerical simulations are consistent with the analytical results. We reveal that a smaller fractional-order facilitates the stability of fixed point and a larger feedback gain advances the Hopf bifurcation point. The work may inspire cancer therapy by artificially controlling the occurrence of p53 oscillations.

Mitigating sub-synchronous oscillation using intelligent damping control of DFIG based on improved TD3 algorithm with knowledge fusion

The occurrence of sub-synchronous oscillation (SSO) phenomenon in doubly-fed induction generators (DFIGs)-based wind turbines threatens the secure and stable operation of the power grid. Conventional sub-synchronous damping controllers encounter challenges in adapting to the dynamic operating conditions of power systems. This paper introduces an Intelligent Sub-Synchronous Damping Controller (I-SSDC) for DFIGs that integrates deep reinforcement learning (DRL) and knowledge to address the limitations of conventional methods for SSO mitigation. The initial step involves formulating a framework for I-SSDC using the improved twin delayed deep deterministic policy gradient (TD3) algorithm incorporating Softmax. Following this, a surrogate model is constructed, employing Weighted Linear Regression and regularization. This model is designed to identify the predominant influencing factors of SSO, focusing on the selection of the output signal (installation position) to optimize decision-making in I-SSDC. The objective is to enhance the controller’s environmental adaptability and interpretability. Moreover, knowledge and experience related to SSOs are integrated into agent training to improve the exploration efficiency of the agent. Case studies under various operating conditions of the test power system validate the efficacy of the proposed I-SSDC in suppressing SSOs.

On the coupling of intracellular to glycolytic oscillations in yeast.

We have investigated the interplay between glycolytic oscillations and intracellular concentration in the yeastSaccharomyces cerevisiae. Intracellular concentration was measured using the fluorophore potassium-binding benzofuranisophthalate(PBFI). We found that is an essential ion for the occurrence of glycolytic oscillations and that intracellular concentration oscillates synchronously with other variables such as nicotinamide adenine dinucleotide hydride (NADH), intracellular adenosine triphosphate (ATP), and mitochondrial membrane potential. We also investigated if glycolysis and intracellular concentration oscillate in a number of yeast strains with mutations in transporters in the plasma membrane, mitochondrial membrane and in the vacuolar membrane. Most of these strains are still capable of showing glycolytic oscillations, but two strains are not: (i) a strain with a deletion in the mitochondrial Mdm38p transporter and (ii) a strain with deletion of the late endosomal Nhx1p ( ) transporter. In these two mutant strains intracellular concentration seems to be low, indicating that the two transporters may be involved in transport of into the cytosol. In the strain, Mdm38p oscillations in glycolysis could be restored by addition of the exchange ionophore nigericin. Furthermore, in two nonoscillating mutant strains with a defective V-ATPase and deletion of the Arp1p protein the intracellular is relatively high, suggesting that the V-ATPase is essential for transport of out of the cytosol and that the cytoskeleton may be involved in binding to reduce the concentration of free ion in the cytosol. Analyses of the time series of oscillations of NADH, ATP, mitochondrial membrane potential, and potassium concentration using data-driven modeling corroborate the conjecture that ion is essential for the emergence of oscillations and support the experimental findings using mutant strains.

Efficient construction and convergence analysis of sparse convolutional neural networks

In this paper, a new variant of convolutional neural network (CNN) based on L1 regularization is proposed. The main consideration is to generate a sparse weight matrix, i.e., to generate a sparse neural network model. To some extent, L1 regularization prevents the occurrence of overfitting and effectively improves the learning efficiency of the network. Unfortunately, the L1 regularization term is non-smooth, which leads to the occurrence of oscillations in experiments and poses a great challenge to the theoretical analysis. So, we overcome this drawback by using polishing techniques and rigorously prove the monotonicity of the error function and the strong and weak convergence theorems of the algorithm. Finally, numerical simulations on several data sets support our theoretical results and the superiority of the proposed algorithm.

MATRICS: The implicit matrix-free Eulerian hydrodynamics solver

Context. There exists a zoo of different astrophysical fluid dynamics solvers, most of which are based on an explicit formulation and hence stability-limited to small time steps dictated by the Courant number expressing the local speed of sound. With this limitation, the modeling of low-Mach-number flows requires small time steps that introduce significant numerical diffusion, and a large amount of computational resources are needed. On the other hand, implicit methods are often developed to exclusively model the fully incompressible or 1D case since they require the construction and solution of one or more large (non)linear systems per time step, for which direct matrix inversion procedures become unacceptably slow in two or more dimensions. Aims. In this work, we present a globally implicit 3D axisymmetric Eulerian solver for the compressible Navier–Stokes equations including the energy equation using conservative formulation and a fully simultaneous approach. We use the second-order-in-time backward differentiation formula for temporal discretization as well as the κ scheme for spatial discretization. We implement different limiter functions to prohibit the occurrence of spurious oscillations in the vicinity of discontinuities. Our method resembles the well-known monotone upwind scheme for conservation laws (MUSCL). We briefly present efficient solution methods for the arising sparse and nonlinear system of equations. Methods. To deal with the nonlinearity of the Navier–Stokes equations we used a Newton iteration procedure in which the required Jacobian matrix-vector product was reconstructed with a first-order finite difference approximation to machine precision in a matrix-free way. The resulting linear system was solved either completely matrix-free with a combination of a sufficient Krylov solver and an approximate Jacobian preconditioner or semi-matrix-free with the incomplete lower upper factorization technique as a preconditioner. The latter was dependent on a standalone approximation of the Jacobian matrix, which was optionally calculated and needed solely for the purpose of preconditioning. Results. We show our method to be capable of damping sound waves and resolving shocks even at Courant numbers larger than one. Furthermore, we prove the method’s ability to solve boundary value problems like the cylindrical Taylor-Couette flow (TC), including viscosity, and to model transition flows. To show the latter, we recover predicted growth rates for the vertical shear instability, while choosing a time step orders of magnitude larger than the explicit one. Finally, we verify that our method is second order in space by simulating a simplistic, stationary solar wind.

Damping Characteristics Improvement of Wind-PV Hybrid System by Coordinated Optimization of SVC-POD Controller Parameters

Background: With the increasing penetration of new energy resources such as wind farms and photovoltaic power plants, there is concern about the stability of power systems. Methods: Aiming at the low-frequency oscillation issue of the wind-PV hybrid system, a coordinated optimal design strategy based on Static Var Compensator (SVC) and Power Oscillation Damping (POD) control is proposed. Modal analysis is used to locate the controller, then the Whale Optimization Algorithm (WOA) is introduced to optimize the SVC-POD controller parameters. To solve the wind-PV hybrid energy system's low frequency oscillation issues, the damping ratio and angular velocity of the generator rotor are considered in the objective function. Results: Taking IEEE four-machine two-area system as an example, several working conditions are designed, including changing the power of the contact line. The eigenvalue analysis and simulation findings verify that the suggested proposed method can successfully raise the damping ratio of the system, keep the generator speed stable, and restrain the occurrence of low-frequency oscillation. Conclusion: Simulation results demonstrate that this method efficiently suppresses the lowfrequency oscillation and increases the robustness of the system.

SiC MOSFET Active Gate Drive Circuit Based on Switching Transient Feedback

Due to the influence of parasitic internal parameters and junction capacitance, the silicon carbide (SiC) power devices are frequently marred by significant overshoots in current and voltage, as well as high-frequency oscillations during the switching process. These phenomena can severely compromise the reliability of SiC-based power electronic converters during operation. This study delves into the switching transient of the SiC MOSFET with the goal of establishing a quantitative correlation between the gate driving current and the overshoot in both the drain-source voltage and the drain current. In light of these findings, the innovative active gate drive (AGD) circuit, which features an adjustable gate current, is introduced. Throughout the switching process, the AGD circuit employs a dynamic monitoring and feedback mechanism that is responsive to the gate voltage and rate of change in the drain-source voltage and drain current of the SiC MOSFET. This adjustment enables gate driving current to be actively modified, thereby effectively mitigating the occurrence of overshoots and oscillations. To empirically validate the efficacy of the proposed AGD circuit in curbing voltage and current overshoots and oscillations, a double-pulse experimental setup was meticulously constructed and tested.

Acoustic Design Parameter Change of a Pressurized Combustor Leading to Limit Cycle Oscillations

When aiming to cut down on the emission of nitric oxides by gas turbine engines, it is advantageous to have them operate at low combustion temperatures. This is achieved by lean premixed combustion. Although lean premixed combustion is a proven and promising technology, it is also very sensitive to thermoacoustic instabilities. These instabilities occur due to a coupling between the unsteady heat release rate of the flame and the acoustic field inside the combustion chamber. In this paper, this coupling is investigated in detail. Two acoustic design parameters of a swirl-stabilized pressurized preheated air (300 °C)/natural gas combustor are varied, and the occurrence of thermoacoustic limit cycle oscillations is explored. The sensitivity of the acoustic field as a function of combustion chamber length (0.9 m to 1.8 m) and reflection coefficient (0.7 and 0.9) at the exit of the combustor is investigated first using a hybrid numerical and analytical approach. ANSYS CFX is used for Unsteady Reynolds Averaged Navier-Stokes (URANS) numerical simulations, and a one-dimensional acoustic network model is used for the analytical investigation. Subsequently, the effects of a change in the reflection coefficient are validated on a pressurized combustor test rig at 125 kW and 1.5 bar. With the change in reflection coefficient, the combustor switched to limit cycle oscillation as predicted, and reached a sound pressure level of 150 dB.

Research of bubble motion and correction of drag coefficient in viscous oil at low Reynolds number

As the core fundamental components in the field of fluid transmission and control, viscous oil fluid components determine the technological level of fluid machinery and high-end equipment. However, bubbles as effective cavitation nuclei widely exist in the interior of viscous oil fluid components, directly affecting their performance and technological development. In order to reveal the bubble motion characteristics in viscous oil and establish a high-precision prediction method, this paper focuses on No. 110 technical white oil and develops a visualized observation system for studying the motion characteristics and morphological features of bubbles in viscous oil. The bubble motion trajectory, rising rate, and force state are analyzed, and a prediction model for the drag coefficient is proposed and corrected. The research results indicate that during the rising process, the bubble morphologies in viscous oil show an elliptical shape. The oil temperature has a significant influence on the bubble motion characteristics, with the occurrence of oscillations during the rise process after reaching 80 °C. Additionally, a new prediction model for the drag coefficient of bubble is fitted, where the relative error of bubble motion rate can be controlled within 5.5% for 0.3 < Re < 50. This research provides significant theoretical significance and engineering application value.

Non-radial oscillations in newly born compact star considering effects of phase transition

Abstract The massive stars end their lives by supernova explosions leaving central compact objects that may evolve into neutron stars. Initially, after birth, the star remains hot and gradually cools down. We explore the matter and star properties during this initial stage of the compact stars considering the possibility of the appearance of deconfined quark matter in the core of the star. At the initial stage after the supernova explosion, the occurrence of non-radial oscillation in the newly born compact object is highly possible. Non-radial oscillations are an important source of GWs. There is a high chance for GWs from these oscillations, especially the nodeless fundamental (f-) mode to be detected by next-generation GW detectors. We study the evolution in frequencies of non-radial oscillation after birth considering phase transition and predicting the possible signature for different possibilities of theoretical compact star models.

Mutations make pandemics worse or better: modeling SARS-CoV-2 variants and imperfect vaccination.

COVID-19 is a respiratory disease triggered by an RNA virus inclined to mutations. Since December 2020, variants of COVID-19 (especially Delta and Omicron) continuously appeared with different characteristics that influenced death and transmissibility emerged around the world. To address the novel dynamics of the disease, we propose and analyze a dynamical model of two strains, namely native and mutant, transmission dynamics with mutation and imperfect vaccination. It is also assumed that the recuperated individuals from the native strain can be infected with mutant strain through the direct contact with individual or contaminated surfaces or aerosols. We compute the basic reproduction number, , which is the maximum of the basic reproduction numbers of native and mutant strains. We prove the nonexistence of backward bifurcation using the center manifold theory, and global stability of disease-free equilibrium when , that is, vaccine is effective enough to eliminate the native and mutant strains even if it cannot provide full protection. Hopf bifurcation appears when the endemic equilibrium loses its stability. An intermediate mutation rate leads to oscillations. When increases over a threshold, the system regains its stability and exhibits an interesting dynamics called endemic bubble. An analytical expression for vaccine-induced herd immunity is derived. The epidemiological implication of the herd immunity threshold is that the disease may effectively be eradicated if the minimum herd immunity threshold is attained in the community. Furthermore, the model is parameterized using the Indian data of the cumulative number of confirmed cases and deaths of COVID-19 from March 1 to September 27 in 2021, using MCMC method. The cumulative cases and deaths can be reduced by increasing the vaccine efficacies to both native and mutant strains. We observe that by considering the vaccine efficacy against native strain as 90%, both cumulative cases and deaths would be reduced by 0.40%. It is concluded that increasing immunity against mutant strain is more influential than the vaccine efficacy against it in controlling the total cases. Our study demonstrates that the COVID-19 pandemic may be worse due to the occurrence of oscillations for certain mutation rates (i.e., outbreaks will occur repeatedly) but better due to stability at a lower infection level with a larger mutation rate. We perform sensitivity analysis using the Latin Hypercube Sampling methodology and partial rank correlation coefficients to illustrate the impact of parameters on the basic reproduction number, the number of cumulative cases and deaths, which ultimately sheds light on disease mitigation.

Adaptive myelination causes slow oscillations in recurrent neural loops.

The brain is known to be plastic, i.e., capable of changing and reorganizing as it develops and accumulates experience. Recently, a novel form of brain plasticity was described which is activity-dependent myelination of nerve fibers. Since the speed of propagation of action potentials along axons depends significantly on their degree of myelination, this process leads to adaptive change of axonal delays depending on the neural activity. To understand the possible influence of the adaptive delays on the behavior of neural networks, we consider a simple setup, a neuronal oscillator with delayed feedback. We show that introducing the delay plasticity into this circuit can lead to the occurrence of slow oscillations which are impossible with a constant delay.

Automated methods for analyzing and predicting self-oscillations in agricultural systems

The article presents the study of automated methods used for analysis and prediction of auto oscillations in agricultural systems. Auto oscillations arising in control systems and electronics have a negative impact on the reliability of electrical equipment, effective control of the operation of units and systems. The influence of optimization of parameters: frequency and amplitude of auto oscillations, which allow to use effectively technological resources, increase the service life of equipment, reduce the cost of repair and replacement, is shown. The obtained value of the amplitude of auto oscillations can be used to monitor the level of the control signal, also the estimation of amplitude shows the degree of impact on the environment or other components of the system. As a result of research, the automated method for analysis and forecasting of auto oscillations in electric drives is offered, principles and technologies of occurrence of unstable modes are studied, the practical example of application of the method of forecasting of auto oscillations in the technological systems having in structure the electric drive. Methods based on data processing, mathematical modeling and machine learning are used. Particular attention is paid to harmonic linearization for revealing the conditions of occurrence and control of auto oscillations. The proposed methods are based on modern data processing algorithms, artificial intelligence, machine learning and a deep understanding of technological processes. The proposed models and methods ensure the creation of stable and reliable solutions, along with the identification of general regularities, minimizing the influence of random factors, which emphasizes the importance of using the proposed techniques. Automated methods of analysis and forecasting of auto oscillations increase the efficiency of resource use, allow to optimize production processes, and make technological systems of agriculture more resistant to changes in external conditions.

Long-period Ap stars discovered with TESS data: Cycles 3 and 4

One of the most challenging aspects of the Ap stars is the extreme differentiation of their rotation periods, which span more than five orders of magnitude. The physical origin of this differentiation remains poorly understood. The consideration of the most slowly rotating Ap stars represents a promising approach to gain insight into the processes responsible for the rotational braking to which the Ap stars are subject. However, historically, the study of these stars focused primarily on the most strongly magnetic among them. This bias introduced an ambiguity in the conclusions that could be drawn, as it did not allow the distinction between the rotational and magnetic effects, nor the investigation of possible correlations between rotational and magnetic properties. We previously showed that the identification of super-slowly rotating Ap (ssrAp) star candidates (defined as Ap stars that have rotation periods Prot > 50 d) through systematic exploitation of the available TESS photometric observations of Ap stars is an effective approach to build a sample devoid of magnetic bias. This approach rests on the presence of brightness spots on the surface of Ap stars that are not distributed symmetrically about their rotation axes and show long-term stability, hence are responsible for photometric variations with the stellar rotation period. In our previous analyses of TESS Cycle 1 and Cycle 2 data, we interpreted the Ap stars showing no such variability over the 27-d duration of a TESS sector as being ssrAp star candidates. Here, we applied the same approach to TESS Cycle 3 and Cycle 4 observations of Ap stars. We show, however, that two issues that had not been fully appreciated until now may lead to spurious identification of ssrAp star candidates. On the one hand, a considerable fraction of the Ap stars in the existing lists turn out to have erroneous or dubious spectral classifications. On the other hand, the TESS data processing may remove part of the variability signal, especially for stars with moderately long periods (20 d ≲ Prot ≲ 50 d). After critical evaluation of these effects, we report the identification of 25 new ssrAp star candidates and of eight stars with moderately long periods. Combining this list with the lists of ssrAp stars from Cycles 1 and 2 and with the list of ssrAp stars that were previously known but whose lack of variability was not detected in our study, we confirmed at a higher significance level the conclusions drawn in our earlier work. These include the lower rate of occurrence of super-slow rotation among weakly magnetic Ap stars than among strongly magnetic ones, the probable existence of a gap between ∼2 and ∼3 kG in the distribution of the magnetic field strengths of the ssrAp stars, and the much higher rate of occurrence of rapid oscillations in ssrAp stars than in the whole population of Ap stars. The next step to gain further understanding of the ssrAp stars will be to obtain high-resolution spectra of those for which such observations have not been made yet, to constrain their rotation velocities and their magnetic fields.

Impact of climate variability on moonfish (Mene maculata) catch rate in the waters off southwestern Taiwan

AbstractA commercially significant small coastal forage fish, moonfish (Mene maculata), accounts for almost 98% of Taiwanese purse seine capture, primarily in the southwestern Taiwan region. Research indicates that climate indices affect coastal fish catch and dispersal, while the link between moonfish and climatic variability in this region is still unclear. This study found that the delayed period of Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO) and North Pacific Gyre Oscillation (NPGO) affect moonfish distribution and catch rates off southwestern Taiwan. Understudied are the environmental factors connected to these oscillations and their delayed consequences on moonfish catch rates. We focussed on Taiwan purse seiner capture rates (catch per unit effort or CPUE) of moonfish in southwestern Taiwan from 2014 to 2020 and delayed oscillation occurrences up to 5 years to better understand these processes. CPUE demonstrated a 3 to 4‐year positive connection (r > 0.5) with NPGO, NPO and PDO. The region's moonfish catch rates were most affected by NPGO with a 4‐year lag, followed by a 3‐year lag of PDO and lastly a 4‐year lag of NPO, according to the results of generalized additive models (GAMs). All the three oscillations had the greatest impact on moonfish catchability when a lag of >2 years was present. Between 2014 and 2020, moonfish CPUE fluctuated, peaking in 2019. The climatic parameters that affect moonfish in southwestern Taiwan and the Taiwanese purse seine fisheries catches are shown by this study.