Dynamic Properties Research Articles

Optimization of cycloid wheel shaping based on thermal mixed lubrication and wear characteristics

The cycloid pinwheel mechanism plays a key role in the function of RV reducers, making the lubrication and wear characteristics of the cycloid tooth profile vital areas of research. This study uses the RV-20E reducer as a case study to analyze the time-varying contact force and relative velocity between the cycloid wheel and the pinwheel, factoring in the system's dynamic properties. A transient contact model for thermal mixed lubrication of the cycloid tooth profile was developed, incorporating friction and temperature rise, and was based on a rough surface model of the dynamic bonding interface. This model enabled the calculation of oil film thickness, contact stress, and wear volume at the interface between the cycloid wheel and the pinwheel. Additionally, the study assessed the impact of traditional shaping methods on wear characteristics and derived a fitted cycloid tooth profile for the profile grinding process. These findings provide valuable insights into improving the lifespan of RV reducers.

Dynamic mechanical properties and damage constitutive modelling of paste phyllite under triaxial impact testing

Dynamic mechanical properties and damage constitutive modelling of paste phyllite under triaxial impact testing

Shock compression behavior and dynamic strength properties of preheated tantalum: Role of crystal anisotropy

Shock compression behavior and dynamic strength properties of preheated tantalum: Role of crystal anisotropy

Dynamic properties of mortar with oyster shell sand replacement

Dynamic properties of mortar with oyster shell sand replacement

Dynamics of convolutional recurrent neural networks near their critical point

We examine the dynamical properties of a single-layer convolutional recurrent network with a smooth sigmoidal activation function, for small values of the inputs and when the convolution kernel is unitary, so all eigenvalues lie exactly at the unit circle. Such networks have a variety of hallmark properties: the outputs depend on the inputs via compressive nonlinearities such as cubic roots and both the and the depend sensitively on the inputs as power laws, both diverging as the input →0. The basic dynamical mechanism is that inputs to the network generate ongoing activity, which in turn controls how additional inputs or signals propagate spatially or attenuate in time. We present analytical solutions for the steady states when the network is forced with a single oscillation and when a background value creates a steady state of “ongoing activity” and derive the relationships shaping the value of the temporal decay and spatial propagation length as a function of this background value. Published by the American Physical Society 2024

Enhanced performance and robustness in anti-lock brake systems using barrier function-based integral sliding mode control

Abstract In anti-lock brake systems (ABS), the primary goal of the controller is to maximize vehicle deceleration by maintaining the slip ratio at an optimal level. This work presents a fresh approach that enhances ABS performance by integrating a sliding mode controller with a barrier function. This method combines integral sliding mode control with adaptive laws informed by barrier functions, effectively managing external disturbances and uncertainties in inertia. A significant benefit of this approach is that it does not require prior knowledge of the upper limits of these uncertainties and disturbances, thanks to the barrier function-based sliding mode control. The system state is initially aligned with the switching manifold, ensuring robust compensation for any uncertainties and disturbances right from the start of braking. During the sliding mode phase, dynamic properties are finely tuned to ensure that the system’s performance remains consistent. The effectiveness and reliability of the proposed controller have been demonstrated through numerical simulations conducted in MATLAB/Simulink, proving its capability across a range of road conditions.

Emergent topological quasiparticle kinetics in constricted nanomagnets

The ubiquitous domain wall kinetics under magnetic field or current application describes the dynamic properties in nanostructured magnets. However, when the geometrical size of a nanomagnetic system is constricted to the limiting domain wall length scale, the competing energetics between anisotropy, exchange, and dipolar interactions can cause emergent kinetics due to quasiparticle relaxation, similar to bulk magnets of atomic origin. This paper presents a joint experimental and theoretical study to support this argument: constricted nanomagnets, made of antiferromagnetic and paramagnetic neodymium thin film with honeycomb motif, reveal fast kinetic events at picosecond timescales due to the relaxation of topological quasiparticles that persist to low temperature in the absence of any external stimuli. This discovery is especially important considering the fact that paramagnets or antiferromagnets have no net magnetization. Yet, the kinetics in neodymium nanostructures is quantitatively similar to that found in ferromagnetic counterparts and only varies with the thickness of the specimen. This suggests that a universal, topological quasiparticle-mediated dynamical behavior can be prevalent in nanoscopic magnets, irrespective of the nature of the underlying magnetic material. Published by the American Physical Society 2024

Self-Rectifying Memristor-Based Reservoir Computing for Real-Time Intrusion Detection in Cybersecurity.

The increasing sophistication of cybersecurity threats, driven by the proliferation of big data and the Internet of Things (IoT), necessitates the development of advanced real-time intrusion detection systems (IDSs). In this study, we present a novel approach that integrates NiO-doped WO3-x/ZnO bilayer self-rectifying memristors (SRMs) within a reservoir computing (RC) framework for IDS applications. The proposed crossbar array architecture exploits the exceptional dynamic properties of SRMs, achieving a classification accuracy of 93.07% on the CSE-CIC-IDS2018 data set, while demonstrating ultrahigh information-processing efficiency. Our approach not only leverages the tunable characteristics of memristors but also addresses the challenge of sneak path currents in large-scale integration, offering a robust and scalable solution for next-generation IDS. This work exemplifies the power of emerging electronics in enhancing cybersecurity through innovative hardware implementations.

Discrete air model for large scale rapid filling process contained entrapped air

In this paper, a discrete air model (DAM) is developed to capture the discontinuous characteristics of air at different locations during the rapid filling process in long-range, large-scale water pipeline. By introducing the continuity and momentum equations of air and combining them with the water control equation and the interface continuity equation, an improved model based on the uniform air is derived. The accuracy of the model is verified by comparing it with experimental data and the results of the original uniform air model (UAM). Subsequently, a long-range, large-scale pipeline was considered to investigate the dynamic properties of air in large systems, which had not been covered in previous studies. Additionally, the influence of air dynamic characteristics on initial air volume affected by different air lengths and various pipe diameters in large systems – is further studied. Results show that an increased pipe diameter expands the contact area of the air–water interface, often resulting in the UAM underestimating the maximum peak pressure. The propagation process of transient waves in air is divided into three stages: propagation stage with multiple variation, maximum value stage with interface propulsive, and stability stage with several fluctuations, which corresponds to the pressure fluctuation curve. This explains the occurrence of small fluctuations and peaks in the curve. Therefore, the peak pressure simulated by the proposed DAM offers a better understanding of wave behaviours.

Dynamic mechanical properties of steel fiber-reinforced reactive powder concrete after the exposure to high-temperatures

Dynamic mechanical properties of steel fiber-reinforced reactive powder concrete after the exposure to high-temperatures

A high-throughput framework for lattice dynamics

AbstractWe develop an automated high-throughput workflow for calculating lattice dynamical properties from first principles including those dictated by anharmonicity. The pipeline automatically computes interatomic force constants (IFCs) up to 4th order from perturbed training supercells, and uses the IFCs to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free energy and entropy. It performs phonon renormalization for dynamically unstable compounds to obtain real effective phonon spectra at finite temperatures and calculates the associated free energy corrections. The methods and parameters are chosen to balance computational efficiency and result accuracy, assessed through convergence testing and comparisons with experimental measurements. Deployment of this workflow at a large scale would facilitate materials discovery efforts toward functionalities including thermoelectrics, contact materials, ferroelectrics, aerospace components, as well as general phase diagram construction.

Integrating Mathematical and Computational Biochemistry with an Exploration of the Toxicological and Physical Dimensions of Novichok Agents: A QSAR and Molecular Dynamics Investigation

In recent decades, and particularly over the last few years, nerve agents have emerged as an ongoing threat yet to be neutralized. Specifically, Novichok, also known as A-class nerve agents, poses a significant risk to civilization due to the potential for terrorism and asymmetric threats. In the present study, we present results on toxicological properties, including calculated lipophilicity through QSAR analysis, as well as an array of physical and dynamic properties estimated via Molecular Dynamics Simulations.

Dry polymer model for a string of pushers: Nontrivial scaling of tumbling time with shear rate

Understanding the dynamics of active polymers is an important component for modeling the dynamic response of biological cells and microorganisms when subjected to external forces. A minimal computational model of active filaments that captures all the essential features of activity-induced filament motion is required to study large systems of dense suspensions. In this paper we present a model of a dry active polymer, compare its steady-state static and dynamic properties with those of a polymer consisting of extensile stresslets, and show that the two models give very similar results. When subjected to shear flow, both models show two distinct regimes in the tumbling interval as a function of shear rate, with a diffuse crossover regime in between. At high shear rate, the active and passive polymers follow the same power law for the tumbling interval. However, the tumbling interval is smaller than that of the passive polymer for low shear rates and larger for the high shear rate. We show that activity-induced large bends increase the coupling of the polymer with the shear gradient in the low-shear-rate regime, leading to a decrease in the tumbling interval. However, in the high-shear-rate regime, the active forces on the folds at the end of the stretched polymer prevent it from tumbling, leading to a larger tumbling interval. We show that the critical shear rate, at which the tumbling interval versus the shear-rate curve of the active polymer crosses that of the passive polymer, is determined by the balance of bending and shear forces and increases with κ/N3, where κ is the bending coefficient and N is the length of the polymer. Published by the American Physical Society 2024

Constructing keyed strong S-box with optimized nonlinearity using nondegenerate 2D hyper chaotic map

Abstract In the realm of information security, the nonlinearity of an S-Box is a pivotal attribute for ensuring its effectiveness. S-Boxes randomly generated with chaotic maps, however, often exhibit insufficient nonlinearity. To construct a robust S-Box with enhanced nonlinearity, we have developed a nondegenerate two-dimensional hyper chaotic map (2D-NDHCM). We rigorously evaluated its dynamic properties through bifurcation and phase diagrams, Lyapunov exponents, Kolmogorov entropy, correlation dimension, and randomness tests to assess the map's resilience. Subsequently, we employed the 2D-NDHCM to devise a novel algorithm for constructing and optimizing a keyed strong S-Box, leveraging simulated annealing technique to achieve superior nonlinearity. Finally, We conducted performance analyses of the optimized S-Box using the classic six criteria, and the results confirmed the algorithm's practicality and effectiveness.

On the Thermal Conductivity and Local Lattice Dynamical Properties of NASICON Solid Electrolytes.

The recent development of solid-state batteries brings them closer to commercialization and raises the need for heat management. The NASICON material class (Na1+xZr2PxSi3-xO12 with 0 ≤ x ≤ 3) is one of the most promising families of solid electrolytes for sodium solid-state batteries. While extensive research has been conducted to improve the ionic conductivity of this material class, knowledge of thermal conductivity is scarce. At the same time, the material's ability to dissipate heat is expected to play a pivotal role in determining efficiency and safety, both on a battery pack and local component level. Dissipation of heat, which was, for instance, generated during battery operation, is important to keep the battery at its optimal operating temperature and avoid accelerated degradation of battery materials at interfaces. In this study, the thermal conductivity of NaZr2P3O12 and Na4Zr2Si3O12 is investigated in a wide temperature range from 2 to 773 K accompanied by in-depth lattice dynamical characterizations to understand underlying mechanisms and the striking difference in their low-temperature thermal conductivity. Consistently low thermal conductivities are observed, which can be explained by the strong suppression of propagating phonon transport through the structural complexity and the intrinsic anharmonicity of NASICONs. The associated low-frequency sodium ion vibrations lead to the emergence of local random-walk heat transport contributions via so-called diffusons. In addition, the importance of lattice dynamics in the discussion of ionic transport as well as the relevance of bonding characteristics typical for mobile ions on thermal transport, is highlighted.

First-principles study of the structural, electronic, dielectric, and dynamical properties of gallium nitride in the graphite-like hexagonal P63/mmc phase

First-principles study of the structural, electronic, dielectric, and dynamical properties of gallium nitride in the graphite-like hexagonal P63/mmc phase

Improvement of Stockbridge Damper Design for Cable-Stayed Bridges

Stockbridge dampers are widely used to mitigate the vibrations of cable-stayed bridges and of many other cable-suspended or cable structures exposed to the action of pedestrians, traffic or wind load. Within the current research work, one of the most effective and likely used damper types, the Stockbridge damper, was investigated to support its design and application within the daily engineering praxis. The Stockbridge damper has a relatively simple structural layout, which ensures its modular design allows it to easily adapt the damper to cables having different dynamic properties (eigenfrequencies, mass, etc.). This paper focuses on two main research areas: (i) to understand the static and dynamic behaviour of the damper and the stay cable interaction to investigate the effectiveness of its damping; (ii) to study the sensitivity of the natural frequencies of the damper to the design parameters. The final aim of the research is to develop a simple design method that is easy to apply in engineering practice and allows the efficient adaptation of the Stockbridge damper to different cable-stayed bridges. Key findings include the recommendation to position the damper at approximately 20% of the cable length for optimal attenuation, the importance of detuning to maintain effectiveness under varying cable forces, and the observation that increasing the damper mass improves efficiency, particularly for detuned elements.

Sports biomechanical analysis of knee joint injuries in table tennis players

Table tennis is a fast-paced, explosive sport that puts a lot of strain and stress on players’ lower limbs, particularly their knee joints. This work built a thorough mathematical model to investigate the dynamic and kinematic properties of the knee joint under various motion situations, with the goal of better understanding the biomechanical behavior of the knee joint in table tennis. A model of knee joint motion that takes into account the two degrees of freedom—flexion, extension, and rotation—is put forth based on the concepts of human biomechanics and kinematics theory. This model uses the Newton Euler equation to explain the mechanical behavior of the knee joint and integrates internal forces like muscle forces and external factors like ground reaction forces for torque balance analysis. This study offers a thorough examination of the force distribution and knee joint trajectory in table tennis using numerical simulation techniques. The findings show that the knee joint undergoes considerable compression and shear forces during intense activity, and that the joint’s stress properties vary significantly depending on the kind of movement. This finding is a valuable resource for table tennis players’ knee joint injury prevention and rehabilitation.

Numerical and experimental evaluations of the impact attenuation of a rail-fastening assembly

The stability of railway tracks relies on a complex arrangement of rail, rail pad, rail clip, sleeper, and ballast. Impact forces from wheel-rail irregularities can lead to concrete sleeper cracking. Traditional experimentation to assess impact attenuation of a rail-fastening assembly (BS EN 13146-3) is both costly and time-consuming. In this study, an experiment-finite element analysis coupling method was utilized. Dynamic properties of the rail pad were experimentally determined and incorporated them into finite element analysis (FEA) to simulate impact attenuation, which was then experimentally validated. Investigating the damping constant ( cP) and dynamic stiffness ( kP) of the rail pad revealed that while increasing cP doesn’t significantly alter sleeper strain, reducing kP decreases the initial peak strain. Therefore, the impact attenuation is primarily influenced by kP. This approach not only reduces evaluation costs and time but also aids in rail-fastening assembly design, analysis, maintenance, and development.

A Rapid Numerical Method for Nonlinear Generalized Time-Fractional Kawahara Equations via Domination Polynomials of Complete Graph.

Abstract The key objective of this study is to examine the nonlinear Time-fractional generalized Kawahara equation (N-TF-GKE), a significant nonlinear equation that appears in a variety of physical domains, including ion-acoustic waves in plasmas, shallow water waves, and nonlinear acoustics. This Equation exhibits complex dynamic properties, most notably the appearance of shock waves, solitary waves, and chaotic solutions. We use a graph theoretic polynomial approach to obtain numerical solutions of the N-TF-GKE. We present the dominance polynomials of complete graphs (DPC), a new class of graph polynomials, to develop an efficient operational integration matrix to approximate the N-TF-GKE. The N-TF-GKE transformed into a collection of nonlinear algebraic equations with the standard collocation points. We acquire the numerical solutions for the Domination polynomial using Newton's approach. We validate the efficiency and robustness of our domination polynomial collocation method (DCM) with a set of numerical experiments and comparative analyses.