Multiple Frequency Research Articles

Compressible effect on the mutual interaction of two cavitation bubbles in radial oscillations and translational motion

In this study, we considered the compressible effect on the mutual interaction of two cavitation bubbles by correcting the sound field emitted by one bubble in the radial equations of the other bubble to first order in the Mach number of the flow, and the effect is represented by the incident wave acting on bubbles. The results illustrates that the incident wave can enhance the resonance response at the redistributed resonance frequency, which leads to an increase in radial acceleration and the secondary Bjerknes force, and rapid approach of bubbles. Furthermore, the influence of incident wave on the interaction of bubbles driven at lower frequencies is more significant, due to resonance enhancement caused by the proximity of natural frequencies and frequency multiplications of the external sound field. Our findings reveal that the compressible effect is not only critical to interaction in radial oscillations, but also in translational motion.

Photonic generation and transmission of dual-band double-TBWP chirped microwave waveforms with frequency multiplication and immunity to dispersion-induced power fading

A novel photonic approach for generating and transmitting dual-band double-time bandwidth product (TBWP) chirped microwave waveforms with frequency multiplication and immunity to dispersion-induced power fading is proposed. Utilizing an integrated dual-drive dual-parallel Mach-Zehnder modulator (DD-DPMZM), single-sideband modulation of the RF input and suppression of odd-order optical sidebands are achieved. By adjusting the RF input's centre frequency and the DD-DPMZM's bias voltages, dual-band waveforms with frequency multiplication are realized, enabling transmission through optical fibres without dispersion-induced power fading. Experimental validation demonstrates successful transmission over dispersion compensation modules equivalent to 60 km or 20 km of single-mode fibre. The proposed system features a simplified architecture, reconfigurability, and robust anti-dispersion capabilities, making it highly suitable for distributed multi-band radar networks over optical fibre links.

The effects of treatment, clinical and demographic factors on recovery of orientation after ECT: A care network study

BackgroundTime to reorientation after electroconvulsive therapy (ECT) has been shown to predict retrograde amnesia and is a useful measure for monitoring patients over the acute treatment course. This study investigated the effects of treatment, clinical and demographic factors on the recovery of orientation after ECT. MethodsData from 555 ECT patients across two different clinical CARE Network sites were analysed. The main outcome variable was recovery of orientation on the 10-Item Orientation Questionnaire assessed after every ECT treatment. A linear mixed-effects repeated measures model was used to predict the recovery of orientation across the ECT course based on multiple factors, including age, gender, electrode montage, ECT number and frequency, diagnosis, and baseline cognitive impairment. ResultsType of ECT demonstrated a significant effect (F(2, 2341) = 48.414, p = 0.000): individuals who received right unilateral (RUL) ultrabrief ECT or bifrontal ECT had higher orientation scores compared to those who received RUL brief pulse ECT. Older age groups and female patients had lower orientation scores. Baseline global cognitive functioning significantly influenced orientation scores (F(3, 2339) = 43.597, p = 0.000), with individuals with no or mild cognitive impairment exhibiting higher scores. LimitationsThe study involved a retrospective analysis of de-identified data, which may have introduced inherent biases with missing data. ConclusionsThis large-scale retrospective, real-world study showed that recovery of orientation after ECT was most affected by ECT type, though age, gender, and baseline level cognitive impairment also affected outcomes. These findings can inform the interpretation of post ECT orientation scores, facilitating its monitoring and optimisation of patient outcomes.

Optimal acquisition time estimation method for CSEM with high-order pseudo-random signal

High-order pseudo-random signal is gradually being applied in controlled-source electromagnetic (CSEM) exploration. In contrast to the conventional single-frequency sweep mode, the high-order pseudo-random signal enables simultaneous transmission of multiple frequencies. However, estimating a fixed acquisition time based on observed noise levels often results in poor adaptability for high-order pseudo-random signal, which only require reception of one set of waveform. In this study, we presented an estimation method for acquisition time for CSEM with high-order pseudo-random signal using an improved logistic function. The improved logistic function was proposed to introduce a time-decay factor into the governing equation for the first time. By considering the transformation rule of noise statistical characteristics with time, the specific parameters of the function have been determined to better describe the dynamic evolution process of the signal quality. The effective frequencies were extracted at various acquisition times based on the noise evaluation number, and the resulting quantity of effective frequencies was used as the fitting target. Guidance for the fieldwork was determined based on the average time of the saturation period, in accordance with the properties of the function. The reliability of the improved logistic function was validated through a transmission current data simulation. The proposed method was demonstrated through the measured data from both strong and weak interference areas.

Fronto-Central Changes in Multiple Frequency Bands in Active Tactile Width Discrimination Task.

The neural basis of tactile processing in humans has been extensively studied; however, the neurophysiological basis of human width discrimination remains relatively unexplored. In particular, the changes that occur in neural networks underlying active tactile width discrimination learning have yet to be described. Here, it is hypothesized that subjects learning to perform the active version of the width discrimination task would present changes in behavioral data and in the neurophysiological activity, specifically in networks of electrodes relevant for tactile and motor processing. The specific hypotheses tested here were that the performance and response latency of subjects would change between the first and the second blocks; the power of the different frequency bands would change between the first and the second blocks; electrode F4 would encode task performance and response latency through changes in the power of the delta, theta, alpha, beta, and low-gamma frequency bands; the relative power in the alpha and beta frequency bands in electrodes C3 and C4 (Interhemispheric Spectral Difference-ISD) would change because of learning between the first and the second blocks. To test this hypothesis, we recorded and analyzed electroencephalographic (EEG) activity while subjects performed a session where they were tested twice (i.e., two different blocks) in an active tactile width discrimination task using their right index finger. Subjects (n = 18) presented high performances (high discrimination accuracy) already in their first block, and therefore no significant improvements were found in the second block. Meanwhile, a reduction in response latency was observed between the two blocks. EEG recordings revealed an increase in power for the low-gamma frequency band (30-45 Hz) for electrodes F3 and C3 from the first to the second block. This change was correlated with neither performance nor latency. Analysis of the neural activity in electrode F4 revealed that the beta frequency band encoded the subjects' performance. Meanwhile, the delta frequency band in the same electrode revealed a complex pattern where blocks appeared clustered in two different patterns: an Upper Pattern (UP), where power and latency were highly correlated (Rho = 0.950), and a sparser and more uncorrelated Lower Pattern (LP). Blocks belonging to the UP or LP patterns did not differ in performance and were not specific to the first or the second block. However, blocks belonging to the LP presented an increase in response latency, increased variability in performance, and an increased ISD in alpha and beta frequency bands for the pair of electrodes C3-C4, suggesting that the LP may reflect a state related to increased cognitive load or task difficulty. These results suggest that changes in performance and latency in an active tactile width discrimination task are encoded in the delta, alpha, beta, and low-gamma frequency bands in a fronto-central network. The main contribution of this study is therefore related to the description of neural dynamics in frontal and central networks involved in the learning process of active tactile width discrimination.

Online vibration monitoring using laser vibrometer and acoustic emission techniques in robotic milling CFRP composites

Carbon fiber reinforced polymer (CFRP) material has superior mechanical properties, often utilized in the aerospace industry. However, its prone to surface defects such as burrs and delamination under the influence of machining vibration, thereby compromising component quality. This study evaluated the relevant vibration signal features via signal processing methods, and investigated the effect of machining parameters on machining stability during robotic milling of CFRP composite. Specifically, the study assessed machining status by analyzing milling signals and compared surface quality between vibration and stable machining stages, the former corresponds to a larger Sa on the machined surface, with more pronounced profile fluctuations. Machining vibration manifests distinct characteristics in laser vibrometer signals, exhibiting in time-frequency plots with short-term signal enhancements at multiple frequencies. This phenomenon occurs more frequently during entry and exit stages. The results indicated that feed speed has a limited effect on milling stability within the selected parameter range, and severe machining vibration occurred at lower spindle speed (12,000 rpm) and higher milling depth (2 mm). Corresponding surface defects formation mechanisms were discussed, revealing that the formation of uncut burrs at the top was related to axial milling force, while interlayer debonding cracks stemmed from variations in fiber orientation between adjacent layers.

A Nanosecond level current pulse capture taper optical fiber probe based on micron level NV color center diamond

Abstract This work demonstrates a micron-sized nanosecond current pulse probe using a quantum diamond magnetometer. A micron-sized diamond crystal affixed to a fiber tip is integrated on the end of a conical waveguide. We demonstrate real-time visualization of a single 100 nanosecond pulse and discrimination of two pulse trains of different frequencies with a coplanar waveguide and a home-made PCB circuits. This technique finds promising applications in the display of electronic stream and to be used as a pulse discriminator to Simultaneously receive and demodulate multiple pulse frequencies. This method of detecting pulse current is expected to provide further detailed analysis of the internal working state of the chip.

Transmission anomalies in 2D photonic crystals from the checkerboard family: from broken to hidden symmetries and plasmon “spoofing”

In a field representation, the main symmetry of the electromagnetic response of complementary metal film structures is described by the Babinet principle, which is expected to be strictly obeyed by structures in vanishingly thin films of a perfect electric conductor. On the other hand, a softer version of this based on transmittance, the transmittance Babinet principle (TBP), is not so restrictive. The goal of this work is to study how severely this broken symmetry affects the optical response of such structures. We consider two geometrically distinct series of planar complementary structures from the checkerboard family: regular and bowtie. The self-complementary structure of these series is known to be very singular and breaks even the rigorous Babinet principle. Here, we study complete simulated transmittance spectral maps (T-Maps), which accumulate the whole spectral response of an entire series of structures in a single plot. The ab initio simulated T-Maps of these 2D photonic crystals were simulated for linearly polarized waves propagating perpendicular to these planar structures, made in a vanishingly thin film of a perfect electric conductor. While we confirm the expected long wavelength validity of the TBP, we show that in the frequency range where diffraction effects dominate, the standard derivation of the TBP no longer applies, and with the help of our T-Maps, we demonstrate a total collapse of the TBP in the structures considered. We show that this broken symmetry practically eliminates all but one transmission band on the hole side of the T-Maps and that the remaining strong band is a “spoof” plasmon, free of multiple frequency replicas, an important feature for optical filter applications. In addition, by symmetry arguments and simulations, we discovered that the T-Maps for bowtie and doubled-period regular structures are identical. We discuss how this hidden symmetry can benefit various applications by providing a convenient scaling, whereby simplified structures can deliver a tailored response.

Phase and amplitude simultaneously coding metasurface with multi-frequency and multifunctional electromagnetic modulations

The integration of multiple functionalities into a single, planar, ultra-compact metasurface has presented significant opportunities for enhancing capacity and performance within compact 5G/6G communication systems. Recent advances in multifunctional metasurfaces have unveiled comprehensive wavefront manipulations utilizing phase, polarization transmission/reflection, and coding apertures. Despite these developments, there remains a critical need for multifunctional metasurfaces with expanded channel capabilities, including multiple operational frequencies, minimal crosstalk, and high-efficiency computable array factors. This study introduces a multifunctional metasurface that integrates phase- and amplitude simultaneous coding meta-atoms at dual frequencies. By altering the polarization of electromagnetic (EM) waves, it is possible to reshape the wave-fronts of reflected waves at these frequencies. The coding metasurface proficiently manipulates both x and y linearly polarized waves through phase and amplitude coding at dual frequencies, thereby enabling distinct functionalities such as anomalous reflection, reflection imaging, and vortex wave beam generation. Both theoretical analysis and full-wave simulation confirm the anticipated functionalities of the designed devices, paving the way for advancements in integrated communication systems with diverse functionalities.

Optimization of multiple rotational inertia double tuned mass damper for offshore wind turbines under earthquake, wind, and wave loads

This study introduces a framework for designing an optimal multiple rotational inertia double tuned mass damper (MRIDTMD) with multiple tuning frequencies to effectively mitigate vibrations in offshore wind turbines (OWTs) subjected to combined wind, wave, and seismic loads. The framework comprises a coupled numerical model of an OWT with an MRIDTMD, an intelligent optimization algorithm, and parallel computing technology. First, coupled governing equations of motion for an OWT with an MRIDTMD under seismic conditions are derived based on multibody dynamics and fully coupled analysis theories in FAST v8. Subsequently, an MRIDTMD submodule is developed and integrated into FAST v8 to establish a coupled analysis model for an OWT with MRIDTMDs using an updated simulation tool. Furthermore, an intelligent optimization algorithm and parallel computing technology are introduced to establish the framework, and the MRIDTMDs are optimized. Moreover, the efficiency of the optimized MRIDTMD is assessed based on observed reductions in the OWT responses under combined seismic cases. Subsequently, comparisons with an optimized multiple tuned mass damper (MTMD) and a parametric study are conducted. The effectiveness and robustness of the optimized MRIDTMD and the improved mitigation effects of the MRIDTMD compared with the MTMD owing to the additional inerter are proved.

Harnessing graph state resources for robust quantum magnetometry under noise

Precise measurement of magnetic fields is essential for various applications, such as fundamental physics, space exploration, and biophysics. Although recent progress in quantum engineering has assisted in creating advanced quantum magnetometers, there are still ongoing challenges in improving their efficiency and noise resistance. This study focuses on using symmetric graph state resources for quantum magnetometry to enhance measurement precision by analyzing the estimation theory under time-homogeneous and time-inhomogeneous noise models. The results show a significant improvement in estimating both single and multiple Larmor frequencies. In single Larmor frequency estimation, the quantum Fisher information spans a spectrum from the standard quantum limit to the Heisenberg limit within a periodic range of the Larmor frequency, and in the case of multiple Larmor frequencies, it can exceed the standard quantum limit for both noisy cases. This study highlights the potential of graph state-based methods for improving magnetic field measurements under noisy environments.

SynFlowMap: A synchronized optical flow remapping for video motion magnification

Motion magnification refers to the process of spatially amplifying small movements in a video to reveal important information about a scene. Several motion magnification methods have been proposed, but most of them introduce perceptible and annoying visual artifacts. In this paper, we propose a method that first analyzes the optical flow between the original frame and the corresponding frames, which are motion-magnified with other methods. Then, the method uses the generated optical flow map and the original video to synthesize a combined motion-magnified video. The method is able to amplify the motion by larger values, invert the direction of the motion, and combine filtered motion from multiple frequencies and Eulerian methods. Amongst other advantages, the proposed approach eliminates artifacts caused by Eulerian motion-magnification methods. We present an extensive qualitative and quantitative analysis of the results compared to the main approaches for Eulerian methods. A final contribution of this work is a new video database for motion magnification that allows the evaluation of quantitative motion magnification.

Application of the AI2 Climate Emulator to E3SMv2's Global Atmosphere Model, With a Focus on Precipitation Fidelity

AbstractCan the current successes of global machine learning‐based weather simulators be generalized beyond 2‐week forecasts to stable and accurate multiyear runs? The recently developed AI2 Climate Emulator (ACE) suggests this is feasible, based upon 10‐year simulations with a network trained on output from a physics‐based global atmosphere model using a grid spacing of approximately 110 km and forced by a repeating annual cycle of sea‐surface temperature. Here we show that ACE, without modification, can be trained to emulate another major atmospheric model, EAMv2, run at a comparable grid spacing for at least 10 years with similarly small climate biases—a prerequisite to wider applicability. With an analysis that combines multiple temporal, spatial, and frequency domain perspectives, we show that ACE faithfully represents the spatiotemporal structure of EAMv2 precipitation and related variables. Finally, we show that a pretrained ACE network is able to adapt to a new global climate model simulation data set with 10 fewer training steps than when starting from random initialization, all while still maintaining low levels of climate bias. Further analysis of these fine‐tuning experiments reveal ACE's intriguing ability to interpolate between distinct global climate models.

MOCNN: A Multiscale Deep Convolutional Neural Network for ERP-Based Brain-Computer Interfaces.

Event-related potentials (ERPs) reflect neurophysiological changes of the brain in response to external events and their associated underlying complex spatiotemporal feature information is governed by ongoing oscillatory activity within the brain. Deep learning methods have been increasingly adopted for ERP-based brain-computer interfaces (BCIs) due to their excellent feature representation abilities, which allow for deep analysis of oscillatory activity within the brain. Features with higher spatiotemporal frequencies usually represent detailed and localized information, while features with lower spatiotemporal frequencies usually represent global structures. Mining EEG features from multiple spatiotemporal frequencies is conducive to obtaining more discriminative information. A multiscale feature fusion octave convolution neural network (MOCNN) is proposed in this article. MOCNN divides the ERP signals into high-, medium- and low-frequency components corresponding to different resolutions and processes them in different branches. By adding mid- and low-frequency components, the feature information used by MOCNN can be enriched, and the required amount of calculations can be reduced. After successive feature mapping using temporal and spatial convolutions, MOCNN realizes interactive learning among different components through the exchange of feature information among branches. Classification is accomplished by feeding the fused deep spatiotemporal features from various components into a fully connected layer. The results, obtained on two public datasets and a self-collected ERP dataset, show that MOCNN can achieve state-of-the-art ERP classification performance. In this study, the generalized concept of octave convolution is introduced into the field of ERP-BCI research, which allows effective spatiotemporal features to be extracted from multiscale networks through branch width optimization and information interaction at various scales.

A power spectrum approach to the search for axion-like particles from resolved galaxy clusters using CMB as a backlight

Axions or axion-like particles (ALPs) are hypothetical particles predicted by beyond standard model theories, which make one of the dark matter candidates. These particles can convert into photons and vice-versa in the presence of a magnetic field, with a probability decided by its coupling strength gaγ . One of the ways to detect these particles is by using the Cosmic Microwave Background (CMB) as a backlight. As the CMB photons pass through a galaxy cluster, they can get converted into ALPs in the mass range 10-15 eV to 10-11 eV through resonant conversion in the presence of cluster magnetic fields. This leads to a polarized spectral distortion (α-distortion) in the CMB as the photon polarization parallel to the magnetic field in the galaxy cluster is involved in the conversion. The fluctuations in the magnetic field and electron density in a galaxy cluster lead to spatially varying α-distortion around the cluster, with a power spectrum that is different from the lensed E-mode and B-mode CMB polarization power spectrum for the standard model of cosmology. By measuring the difference in the polarization power spectrum around a galaxy cluster from the all-sky signal, one can find new α-distortion in the sky. For the resolved galaxy clusters, if the redshift, electron density, and magnetic field profiles of the cluster can be constrained using optical, X-ray, and radio observations, one can measure the coupling strength gaγ from the ALP power spectrum. The contamination from CMB and galactic foregrounds such as synchrotron and dust can be mitigated by using multiple frequency bands by leveraging on the difference in the spectral shape of the signal from foregrounds. Using the ILC technique to clean the foregrounds, we show that the new power spectrum-based approach of the resolved galaxy clusters from upcoming CMB experiments such as Simons Observatory and CMB-S4 can detect (or put constraints) on the ALP-photon coupling strength of gaγ < 5.2 × 10-12 GeV-1 and gaγ < 3.6 × 10-12 GeV-1 at 95% C.I. respectively for ALPs of masses 10-13 eV or for smaller gaγ for lighter ALP masses.

Stable construction and analysis of MDD modular networks based on multi-center EEG data

BackgroundThe modular structure can reflect the activity pattern of the brain, and exploring it may help us understand the pathogenesis of major depressive disorder (MDD). However, little is known about how to build a stable modular structure in MDD patients and how modules are separated and integrated. MethodWe used four independent resting state Electroencephalography (EEG) datasets. Different coupling methods, window lengths, and optimized community detection algorithms were used to find a reliable and robust modular structure, and the module differences of MDD were analyzed from the perspectives of global module attributes and local topology in multiple frequency bands. ResultsThe combination of the Phase Lag Index (PLI) and the Louvain algorithm can achieve better results and can achieve stability at smaller window lengths. Compared with Healthy Controls (HC), MDD had higher Modularity (Q) values and the number of modules in low-frequency bands. In addition, MDD showed significant structural changes in the frontal and parietal-occipital lobes, which were confirmed by further correlation analysis. ConclusionOur results provided a reliable validation of the modular structure construction method in MDD patients and contributed strong evidence for the changes in emotional cognition and visual system function in MDD patients from a new perspective. These results would afford valuable insights for further exploration of the pathogenesis of MDD.

Layered heterogeneous structures integrated device for multiplication, division arithmetic unit and multiple-physical sensing

A layered heterogeneous structure (LHS), consisting of silver, liquid crystal, and nonlinear dielectric layers, is proposed to realize functions of computing and sensing. By leveraging the optical Tamm state, the intrinsic absorption principle of liquid crystal, and nonlinear effects, the design of an integrated device capable of passive multiplication and division operations, along with high-performance multi-physical quantity sensing functionalities, is achieved. The given LHS exhibits Janus properties, with different physical functions manifested depending on the direction of electromagnetic wave (EW) propagation. During forward propagation of EWs, the LHS displays high and sharp absorptivity peaks at 774.8 and 1517.6 nm. The relationship between the two peaks approximates a frequency multiplication factor of 1.960, enabling signal multiplication. Furthermore, the two absorptivity peaks at different wavelengths facilitate the sensing of serum creatinine solution concentration and external pressure, with sensitivity (S), quality factors (Q), and figure of merit (FOM) of 266.76 μmol L−1/nm and 213.33 GPa/nm, as well as 248.76 and 348.22, 84.1 L (μmol)−1 and 49.06 GPa−1, respectively. During backward propagation of EWs, absorptivity peaks with distinct resolutions are observed at 1423 and 2809 nm, with a multiple relationship between them of 1.974, enabling frequency doubling for signal division. Additionally, the absorptivity curve facilitates temperature sensing over a wide range from 257 to 347 K. Owing to the unique temperature S of liquid crystal, different sensitivities and resolutions are observed at 257 to 297 K and 307 to 347 K, with S of 1.015 and 0.686 K/nm, and corresponding Q and FOM of 21.57 and 12.576, 0.076 K−1 and 0.003 04 K−1, respectively.

Efficient Forced Response Minimization Using a Full-Viscosity Discrete Adjoint Harmonic Balance Method

A forced response induced by inlet distortion and blade row interactions can lead to high-cycle fatigue failure, especially when the unsteady excitation frequency is close to the natural vibration frequency of a blade. This paper presents the study of forced response sensitivity analysis and minimization using a full-viscosity unsteady discrete adjoint method. The goal is to improve the aeroelastic performances of turbomachinery blades and simultaneously constrain/improve aerodynamic performances. The decoupled modal reduction method is used to compute the forced response, which is considered the objective function in adjoint-based design optimization. To analyze aeroforcing and aerodamping flow and adjoint fields efficiently, the harmonic balance method and its adjoint counterpart developed by an automatic differentiation tool are applied. Two cases—the NASA Rotor 67 with inlet distortion and a three-row configuration with multiple fundamental frequencies in the second row—are used to demonstrate the effectiveness of the aerodynamic and aeroelastic coupled design optimization system developed in this work. For the latter case, the Fourier-transform-based method that first decomposes and then matches the time and space modes at two sides of an interface is used for interface coupling. The almost-periodic Fourier transform method is used to determine the time instances for cases with multiple fundamental frequencies.

Linear Time-Periodic theory-based novel stability analysis method for voltage-source converter under unbalanced grid conditions

Small-signal stability analysis is essential for the safe operation and parameter design of power electronic-dominated grids. Unbalanced conditions introduce more frequency-coupling terms, which are unneglectable in the stability assessment. This paper proposes a novel Linear Time-Periodic (LTP) theory-based stability analysis method and focuses on grid-connected voltage-source converters (VSCs) without improved unbalancing controls. Firstly, the analysis of fundamental solutions of the LTP system reveals that each LTP mode is characterized by a unique damping factor and multiple oscillation frequencies, defined by LTP eigenvalues and related transformation vectors, i.e., (λi,Vi(t)). Then, a method for calculating (λi,Vi(t)) is proposed using the characteristic matrix of the Harmonic State-Space (HSS) model. An iterative sorting method based on the time-domain interpretation of HSS eigenvalues/eigenvectors is proposed to determine accurate (λi,Vi(t)) in the case of the minimum truncation order. Finally, generalized definitions and calculation methods of the widely used indicators for modal analysis are presented to assess system stability and guide the parameter design. Numerical and simulation results verify the proposed stability analysis method and indicate its advantages compared to the existing Floquet and HSS methods.

Analysis of axial force variations and seismic performance of subway station columns under earthquake loading

Central column failure is a predominant seismic damage mode in subway station structures. During seismic events, the central columns’ vertical compressive force, as indicated by the axial compression ratio (ACR), undergoes continuous variations, significantly impacting both their failure modes and the seismic performance. This study involved establishing a finite element model of a subway station and conducting time history analyses to identify the distinct variation patterns of ACR in central columns for various seismic design scenarios. Based on these summarized patterns, appropriate ACR variations were designed for the columns, and the validity of the column model was confirmed using experimental data, enabling analyses of their failure modes and hysteresis characteristics under cyclic loads. Lastly, a sensitivity analysis of the parameters associated with the central columns was performed. The results demonstrated that the horizontal displacement and the ACR of the top of the central column were asynchronous, the frequency of the latter was 1.4–3.8 times that of the former, and the amplitude of the ACR was 0.08–0.68. When the frequency of the variable ACR was odd times, the damage and hysteresis curve of the column showed obvious asymmetry and harmfulness, and it exacerbated the damage to the core concrete of the column. Compared to applying a constant ACR, the bearing capacity and energy dissipation of the column were even reduced by about 50 % and 74 %, respectively. The specimens with the upper limit value of 0.95 of variable ACR had even more adverse effects on the damage and hysteresis behavior of the column than the scheme with a constant ACR of 0.95. In addition, the even multiple frequency of variable ACR had a limited effect on the seismic performance of the column, but the harm caused by the large amplitude variation of variable ACR could not be ignored. As to the impacts of structural parameters under cyclic loadings, elevating the longitudinal reinforcement ratio and decreasing the stirrup spacing within the central columns would substantially enhance energy dissipation capacity, with a maximum increase of about 69 %. Meanwhile, for columns with the same cross-sectional area, square columns exhibited superior hysteresis behavior compared to their circular counterparts. The findings of this study could provide guidance for the engineering design of the central columns.