Dynamic Behavior Research Articles (Page 1)

Purpose Fused deposition modeling (FDM) has gained much attention in recent years for producing porous scaffolds due to its customization, cost-effectiveness and compatibility with biodegradable materials. The purpose of this research is to investigate the influence of infill density, raster angle orientation and infill pattern on the mechanical and dynamic behavior of composite scaffolds. This study aims to optimize scaffold designs for applications requiring enhanced mechanical strength and vibration characteristics. Design/methodology/approach In this research work, carbon fiber-reinforced polylactic acid composite scaffolds are fabricated with different infill densities of 40%, 50% and 60% and raster angle orientations of 0°, 45° and 90°. Findings The free vibration test is performed on the scaffold printed with different infill patterns of circle, square and hexagonal shapes and infill densities of 40%, 50% and 60%. The natural frequency of the scaffolds produced by PLA/CF composites is determined experimentally. The scaffold (V9) with a hexagon infill pattern and 60% infill density has the highest value of natural frequency of 19.53 Hz. The mechanical properties, such as tensile, flexural, impact and hardness are determined experimentally. Originality/value The results showed that the composite scaffold (S9) with 60% infill density and 90° raster angle orientation has obtained high mechanical properties when compared with other scaffolds. Using scanning electron microscopy, the fractured composite scaffolds are analyzed to visualize the adhesion behavior of carbon fiber and polymer matrix.

Halogen bonds (XBs) represent strongly directional interactions, relevant for bond activation and often quoted in the context of Crystal Engineering. Bifurcated XBs, albeit rare, are unambiguously established in crystalline solids but do not correspond to an energetically favorable arrangement at the molecular level. Here the dynamic behavior of such a system, jointly described by experiment and theory, reconciles both aspects: Experiment shows that the cocrystal of 1,4-diiodobenzene and 1,4-dinitrobenzene with a symmetric bifurcated XB undergoes a rarely observed reversible crystal-to-crystal transition at 130K. The resulting low- temperature phase features an asymmetric bifurcated XB, a first step toward a more linear arrangement. Theoretical calculations based on revised van der Waals density functional theory and diffraction experiments conducted at high resolution agree remarkably well in their interpretation of transition temperature and relevance of interaction types. The XB is fluxional and entropy-favored in the symmetric high- temperature phase and locks into an asymmetric geometry with slightly more favorable Gibbs free energy at low temperature; the energy differences involved are extremely small. Theoretically derived and experimentally observed electron densities agree that the perceived directional interactions are weak rather than decisive synthons. Stacking of alternating diiodobenzene and dinitrobenzene molecules represents the most relevant contact.

The gyroscopic effect has significant impacts on the stability, dynamic behavior, and vibration characteristics of high-speed rotating systems. A floating offshore vertical axis wind turbine (FOVWT) exhibits gyroscope-like motions under combined wind–wave–current conditions; the attitude angles of the shaft connected to the platform change continuously in space, making the overall system’s gyroscopic effect more pronounced. From a geometric perspective, this study investigates a method to suppress the gyroscopic effect of floating offshore vertical axis wind turbines: replacing the conventional single-Φ rotor with a stagger-mounted double-layer double-Φ rotor. This configuration exploits the phase difference in circumferential (i.e., 360° around the rotor) aerodynamic loads experienced by the upper and lower rotors; the superposition of these loads ultimately reduces the platform’s pitch response. This study adopts computational fluid dynamics (CFD) for numerical simulations. First, using the NREL 5-MW OC4 floating horizontal axis wind turbine (FOHWT) platform as the research object, we computed the platform’s motion responses under different environmental conditions and verified the effectiveness of the numerical method through comparison with published literature data. Then, under the same marine environment, we compared the motion responses of the conventional single-Φ turbine and double-Φ turbines with different misalignment angles. The results show that modifying the Φ-type rotor configuration can effectively reduce the axial load on the rotor and enhance system stability. As the rotor misalignment angle increases from 15° to 90°, the pitch motion amplitude decreases from 20.6% to 11.8%, while the overall turbine power is only slightly reduced.

Coupled many-body quantum systems exhibit rich emergent physics with diverse stationary and dynamical behaviours. By engineering platforms with tunable and distinct coupling mechanisms, new insights emerge into the collective behaviour of coupled many body systems. Particles can be exchanged via evanescent or ballistic coupling: the former, based on proximity, yields large spectral splitting, while the latter requires strict phase-matching, analogous to phase-coupled harmonic oscillators and has a smaller impact on the energy landscape. We demonstrate an all-optically tunable quantum fluid dimer based on exciton-polariton condensates in a photonic crystal waveguide with hyperbolic (saddle-like) dispersion. Varying the dimer's angle relative to the grating tunes the coupling from evanescent to ballistic. We directly observe spectral features and mass flow shaped by the saddle dispersion. This work highlights photonic crystals as powerful platforms to explore condensed matter phenomena lying at the interface between delay-coupled nonlinear oscillators and tight binding physics.

Dynamical behaviors and soliton structures in the space-time conformable Wu-Zhang system arising in coastal design

Broadening our taxonomic scope beyond model species offers deeper insights into the evolutionary dynamics of genomic processes such as recombination and the proliferation of transposable elements (TEs). TEs can drive substantial genomic rearrangements, yet the interplay between TEs and recombination remains poorly understood. To investigate population-specific recombination patterns, we analysed the distribution of the species-specific Cla-element in the non-biting midge Chironomus riparius. This TE is known for its dynamic behaviour, exhibiting high numbers of unique insertions and population-specific distribution patterns. Its distribution showed no consistent association with recombination rates at the chromosome-wide scale. However, the Cla-element was often found outside haplotype blocks, suggesting it may be spatially separated from regions with low recombination. No strong association was found between the overall recombination landscape in C. riparius and the transposition activity of repetitive elements. Highlighting how the dynamics of transposable elements contribute to the complexity of genome evolution.

This study conducts a thorough analysis of the nonlinear fractional complex Heisenberg ferromagnetic-type Akbota (FCHFA) model to clarify its dynamic behavior. Through rigorous bifurcation analysis, we identify stability transitions and determine critical parameter thresholds, revealing the system’s sensitivity to perturbations. Employing advanced nonlinear dynamics techniques, we explore the fundamental mechanisms governing magnetization evolution. By integrating numerical simulations with analytical methods, we critically evaluate the role of fractional calculus in modeling long-range interactions and temporal memory effects in ferromagnetic systems. The FCHFA model, which incorporates nonlinear spin-wave phenomena and phase transitions, offers a robust framework for analyzing magnetization dynamics. Numerically validated solutions confirm the effectiveness of our methodology, providing new insights into phase transitions and nonlinear wave phenomena. Our findings highlight the crucial role of fractional derivatives in capturing complex magnetization behaviors, thereby enhancing theoretical understanding and broadening the applicability of fractional models in condensed matter physics. This work integrates fractional calculus with ferromagnetic theory, establishing a mathematically rigorous foundation for modeling systems with memory and nonlocal interactions. By rigorously validating numerical and analytical approaches, the study sets a precedent for investigating critical phenomena in fractional-order systems, with significant implications for device design in spintronics and magnetic materials. Furthermore, it demonstrates how fractional derivatives can effectively encapsulate the intricate dynamics of magnetization, including the interplay between memory effects and nonlinearity. By bridging theoretical developments with practical applications, this research not only advances the mathematical framework for studying complex magnetic materials but also opens avenues for innovative technological applications in the field of condensed matter physics.

This work deals with the dynamics of an ordinary differential equation system describing a Leslie-Gower predator-prey model with a generalist predator and a non-differentiable functional response proposed by M. L. Rosenzweig, given by h(x) = qxα with 0 < α < 1. Two aspects have a significant impact on the model: (1) the predator’s carrying capacity depends on both the favorite prey population and an alternative food source, and (2) consumers have access to an alternative food source. Among the main results, a separatrix curve Σ arises dividing the phase plane into regions with different dynamic behaviors. Trajectories above the separatrix curve Σ reach the vertical axis in finite time, while those below Σ may converge to positive equilibrium points, limit cycles, or homoclinic connections. Furthermore, the system is non-Lipschitz, implying non-uniqueness of solutions at points of the vertical axis. Several bifurcations, including saddle-node, homoclinic, Hopf, generalized Hopf, and Bogdanov-Takens bifurcations, are identified through the use of computational techniques. The dynamics of the system are visualized by presenting a bifurcation diagram in a convenient parameter space.

ConspectusThe production of value-added chemicals from CO2 has been a thriving topic of research for the past few decades because of its contribution to a circular carbon economy. Combined with CO2 capture and storage, thermocatalytic hydrogenation of CO2 to CH3OH with green or blue hydrogen, offers an attractive route to mitigate CO2 emissions and to decarbonize the chemical industry. Numerous studies have been focused on catalysts based on supported metallic nanoparticles; these catalysts consist of at least one transition or coinage metal and a promoter element combined with an oxide support to disperse the active phase. Besides Zn-promoters used in Cu-based hydrogenation catalysts, numerous reports point to Ga as a promoter for methanol synthesis. In recent years, Ga has been shown to convert almost all transition metals toward selective methanol synthesis, but its specific role remains a topic of discussions.In this Account, we summarize how surface organometallic chemistry (SOMC) has enabled the discovery of novel catalysts and the development of detailed structure-activity relationships. Particularly, we show that Ga uniquely generates alloys with transition and coinage (Cu) metal elements across groups 8-11 and converts them into selective methanol synthesis catalysts. Specifically, we highlight the role of M-Ga alloy formation, alloy stability, and the formation of M(Ga)-GaOx interfaces under reaction conditions. This has been possible thanks to the combination of SOMC, which enables the formation of supported nanoparticles with tailored compositions and interfaces, and state-of-the-art characterization including operando techniques along with computational modeling, including ab initio molecular dynamic calculations. Dynamic alloying-dealloying behaviors under reaction conditions and the formation of M/MGa-GaOx interfaces are identified as key drivers for efficient methanol formation.

Fractional calculus concept has proven to be a great, powerful, and effective tool in analyzing mathematical models across diverse various fields of scientific and engineering domains. A significant feature of this article is to investigate the novel Human T-cell Lymphotropic Virus (HTLV)/Human Papillomavirus (HPV)/Human Immunodeficiency Virus (HIV) multi-infection model, along with a computational numerical study and stability analysis to describe the modified Atangana-Baleanu-Caputo fractional order framework. The model performed stability analysis based on the Ulam-Hyers stability concept can be established by using the solution of existence and uniqueness conditions derived from the fixed-point techniques for the recommended problem. The multi-infection dynamical system behavior is expressed on the approximate solution of a two-step Lagrange interpolation polynomials numerical scheme utilizing a modified Atangana-Baleanu-Caputo fractional order framework, with all implementation and simulations conducted in Matrix Laboratory (MATLAB). Overall judgment shows that the numerical results of the recommended method significantly impact the multi-infection model behavior.

Urban heat is a growing concern especially under global climate change and continuous urbanization. However, the understanding of its spatiotemporal propagation behaviours remains limited. In this study, we leverage a data-driven modelling framework that integrates causal inference, network topology analysis and dynamic synchronization to investigate the structure and evolution of temperature-based causal networks across the continental United States. We perform the first systematic comparison of causal networks constructed using warm-season daytime and nighttime air temperature anomalies in urban and surrounding rural areas. Results suggest strong spatial coherence of network links, especially during nighttime, and small-world properties across all cases. In addition, urban heat dynamics becomes increasingly synchronized across cities over time, particularly for maximum air temperature. Different network centrality measures consistently identify the Great Lakes region as a key mediator for spreading and mediating heat perturbations. This system-level analysis provides new insights into the spatial organization and dynamic behaviours of urban heat in a changing climate.This article is part of the theme issue 'Urban heat spreading above and below ground'.

Abstract The regulation of signal transmission speed is one of the most important abilities of the biological nervous system. This study explores the mechanisms and methods for regulating signal transmission speed among nonmyelinated neurons within the same brain region, starting from spike-timing-dependent plasticity (STDP) of synapses. Building upon the Hodgkin-Huxley model, the dynamic behavior of synapses is incorporated, proposing the adaptive growth neuron (AGN) model. Artificial synaptic structures and neuronal physical nodes are also designed. The artificial synaptic structure has unidirectionality, memory capacity, and STDP, allowing it to connect neuronal physical nodes using branching and merging structures. Furthermore, the artificial synapse can adjust signal transmission speed, regulate functional competition between different regions of the neuromorphic network, and promote information interaction. The findings of this study will endow neuromorphic networks with the ability to regulate signal transmission speed over the long term, providing new insights for the development of neuromorphic networks.

In comparison to internal combustion engines, which usually have low frequency, broadband excitations, in electric vehicles, tonal excitations from the electric drivetrain are noticeable and disturbing. As the acoustic and structural dynamic behavior, often referred to as noise, vibration, and harshness (NVH), strongly influences customers’ quality perceptions, optimizing it is a key challenge in development. This study investigates the influence of static rotor–stator eccentricity on the NVH behavior of an electric drivetrain using a transient elastic multibody simulation (eMBS) model incorporating non-linear gear meshing, bearing contact, and electromagnetic forces. The analysis identifies the 36th order excitation of the electric machine as the dominant source, leading to a maximum total acceleration level of 152 dB. Two specific excitation directions were found to reduce this amplitude most effectively. However, varying the amount of static eccentricity in these directions resulted in only minor vibration reductions (<1.5 dB). The findings indicate that the symmetric mode shapes of the cylindrical housing govern the response, indicating that addressing the excitability of housing modes by developing asymmetric housing designs could offer a more effective approach for NVH optimizations of electric drivetrains.

Abstract The impact efficiency of water jets is closely associated with their transient characteristics and thermal effects. However, existing studies have predominantly focused on macroscopic impact effects, largely overlooking the intricate dynamic processes, which hinders a systematic understanding of how temperature variations influence the dynamic behavior of jets and, consequently, constrains the precise control and efficiency optimization of water jet technology. To address this issue, this study employs numerical simulations to systematically investigate the dynamic response and thermodynamic behavior of water jet impact in boreholes under various pressure and temperature conditions, thereby elucidating the dynamic impact characteristics induced by thermal coupling effects. The results indicate that the impact flow and temperature fields of the drilling water jet exhibit distinct time-dependent characteristics. Impact disturbance is positively correlated with pressure, while temperature variations have minimal effect. At 16 MPa, the peak axial velocity of water jet impact across temperatures is 185.67 m/s, and peak wall velocity is 79.78 m/s, with both velocity distributions remaining relatively consistent. Temperature significantly affects the thermal effect: at 333.15 K, the temperature change caused by impact is 1.83 times greater than at 293.15 K. Based on these findings, optimization recommendations for water jet technology are proposed considering energy synergy principles, to provide theoretical support for enhancement and optimization of hydraulic measures.

Accurately managing a CubeSat's orientation during the orbital injection phase is crucial for mission success. Concurrently, signal processing is vital for the CubeSat payload and its subsystems, particularly for the Attitude Control Subsystem (ACS). Typically, a CubeSat begins this phase with excessive angular velocity so that the controller needs to slew the CubeSat into small angle attitudes for normal operation mode. Cold gas thrusters are one method to perform this transition. This work applies an ACS algorithm during the orbital injection phase, of nonlinear dynamics behavior as angular velocities are high and perturbed in nature. Consequently, linear control methods may fail to meet performance and robustness requirements. To address this, we employ the State-Dependent Riccati Equation (SDRE) method, which is applicable to these types of nonlinear systems. The SDRE controller uses cold gas thruster torques to execute large-angle maneuvers, reducing high angular velocities. This study verifies the numerical simulator model, the control algorithm's functionality, and the signal between the controller and actuators, applying a full Monte Carlo perturbation model. Although the ACS algorithm is designed as a continuous-time system, it is now prepared for the next study phase, which involves analyzing discretization techniques and evaluating the sampling rate for the digital version of the SDRE controller.

Abstract Infrastructure systems such as bridges and high-rise buildings are susceptible to structural damage over long periods of service. To ensure their safe operation, it is essential to continuously monitor structural dynamics and detect potential damage based on changes in dynamic behavior. Detailed information about structural damage can be obtained from parameters including mass and stiffness, which are extracted from the identification results. This process of parameter estimation often requires measuring the responses of all degrees-of-freedom (DOFs). However, installing sensors at every DOF in large-scale structures is challenging. Moreover, conventional methods may fail to yield a unique solution when the number of sensors is insufficient. To address this issue, we propose a parameter estimation method that requires fewer sensors than the number of DOFs. The target structure in this study is a chain-like structure, a commonly used modeling approach for real-world systems such as high-rise buildings and offshore platforms. The method incorporates new prior information derived from physical laws and consists of two key steps: an algebraic approach followed by an optimization approach. In the algebraic approach, a general solution containing undetermined variables is obtained owing to the limited sensor configuration. Subsequently, these variables are solved in the optimization step using an objective function constructed from prior information. The effectiveness of the proposed method was validated through both simulations and experiments using only a single sensor.

This study investigates stochastic bifurcation in a generalized tristable Rayleigh–Duffing oscillator with fractional inertial force under both additive and multiplicative recycling noises. The system’s dynamic behavior is influenced by its inherent spatial symmetry, represented by the potential function, as well as by temporal symmetry breaking caused by fractional memory effects and recycling noise. First, an approximate integer-order equivalent system is derived from the original fractional-order model using a harmonic balance method, with minimal mean square error (MSE). The steady-state probability density function (sPDF) of the amplitude is then obtained via stochastic averaging. Using singularity theory, the conditions for stochastic P bifurcation (SPB) are identified. For different fractional derivative’s orders, transition set curves are constructed, and the sPDF is qualitatively analyzed within the regions bounded by these curves—especially under tristable conditions. Theoretical results are validated through Monte Carlo simulations and the Radial Basis Function Neural Network (RBFNN) approach. The findings offer insights for designing fractional-order controllers to improve system response control.

ABSTRACT Numerical research on low velocity impact (LVI) and compression after impact (CAI) responses of hybrid laminates where thick plies are mixed with thin plies at the ply level is limited, despite the widespread use of laminated composites in aircraft. This study aims to develop finite element (FE) models to simulate the LVI and CAI mechanical responses and damage behaviors of both thick‐ply and hybrid laminates without altering the intrinsic lamina and interface properties. The proposed FE models were validated by experimental data, showing good agreement in both impact and post‐impact responses. Results indicate that the inclusion of thin plies in hybrid laminates effectively suppresses matrix cracking and delamination propagation. Consequently, hybrid laminates exhibit a narrower region for matrix and delamination damages in the early stage, retaining larger residual thickness and indicating higher impact damage resistance compared with thick‐ply laminates. Under CAI loading, hybrid laminates exhibit a shorter delamination propagation distance along the width direction before the onset of global buckling compared with the thick‐ply laminate. This study demonstrates the feasibility of accurately predicting the dynamic responses and damage behaviors of thick‐ply and hybrid laminates using the same lamina and interface properties.

In this study, we investigate two fundamental fractal-fractional (FF) models: the competitive dynamics among Egyptian banks and the Brusselator system. For the banking model, optimal control strategies are proposed to mitigate profit downturns during crises, such as the COVID-19 pandemic, through a system of four fractional differential equations. Recognizing theslow convergence of traditional numerical methods, an efficient integration technique is developed to simulate both models with enhanced accuracy and computational efficiency. The simulation results reveal the dynamic behaviors of the studied systems for various FF-operator values, confirming the robustness and precision of the proposed approach when compared with the classical fourth-order Runge–Kutta method (RK4M). The presented technique offers a simple yet powerful framework for modeling and analyzing complex FF-based dynamical systems.

This study introduces an enhanced numerical approach for analyzing the dynamic behavior of a rotor-bearing system subjected to unbalanced excitation from a gearbox drive shaft. The Newmark-β method with the integration of a variable time-step algorithm was used, allowing the system to be solved rapidly and accurately without compromising stability. This technique enables a precise computation of displacement and torsional deformation of the rotating shaft during its operational cycle. The proposed computational model is validated against experimental data, showing deviations of displacement in normal operation below the critical speed of about 6%. A comprehensive parametric analysis is conducted to evaluate the influence of rotational speed, trial mass, and initial phase angle on the system dynamics. The findings confirm that our enhanced numerical approach yields rapid convergence and reliable predictions, making it a valuable tool for dynamic analysis of rotating systems.