Effect of Conditioning on PU Foam Matrix Materials Properties

This article deals with the characterization of the thermal-induced aging of soft polyurethane (PU) foams. There are studied thermal and mechanical properties by means of thermal analysis, tensile, compression and dynamic mechanical vibration testing. It was found in this study, that the increasing relative humidity of the surrounding atmosphere leads to the initiation of the degradation processes. This is reflected in the observed decreased mechanical stiffness. It is attributed to the plasticization of the PU foams wall material. It is in agreement with the observed increase of the permanent deformation accompanied simultaneously with the decrease of Young’s modulus of elasticity. The latter phenomenon is studied by the novel non-destructive forced oscillations vibration-damping testing, which is confirmed by observed lower mechanical stiffness thus indicating the loss of the elasticity induced by samples conditioning. In parallel, observed decreasing of the matrix hardness is confirming the loss of elastic mechanical performance as well. The effect of conditioning leads to the significant loss of the PU foam’s thermal stability.

Energy harvesting through a piezoelectric sensor

Energy harvesting through motion caused by wind is a unique way of finding an alternative energy source for several electronic devices. Piezo-electronic sensors, which harvest energy from small vibrations and movements, are investigated by many researchers nowadays. This paper conducted an experimental study to find an alternative energy source for diverse electronics with forced oscillations from a fan. The relations between the force applied by wind and the oscillation of a paper strip were studied.

Nonlinear oscillations of a sandwich plate with a 3D-printed honeycomb core

A three-layer sandwich plate with a FDM-printed honeycomb core made of polycarbonate is considered. The upper and lower faces of the sandwich are made of a carbon fiber-reinforced composite. To study the response of the sandwich plate, the honeycomb core is replaced with a homogeneous layer with appropriate mechanical properties. To verify the honeycomb core model, a finite-element simulation of the representative volume of the core was performed using the ANSYS software package. A modification of the high-order shear theory is used to describe the structure dynamics. The assumed-mode method is used to simulate nonlinear forced oscillations of the plate. The Rayleigh–Ritz method is used to calculate the eigenfrequencies and eigenmodes of the plate, in which the displacement of the plate points during nonlinear oscillations are expanded. This technique allows one to obtain a finite-degree-of-freedom nonlinear dynamic system, which describes the oscillations of the plate. The frequency response of the system is calculated using the continuation approach applied to a two-point boundary value problem for nonlinear ordinary differential equations and the Floquet multiplier method, which allows one to determine the stability and bifurcations of periodic solutions. The resonance behavior of the system is analyzed using its frequency response. The proposed technique is used to analyze the forced oscillations of a square three-layer plate clamped along the contour. The results of the analysis of the free oscillations of the plate are compared with those of ANSYS finite-element simulation, and the convergence of the results with increasing number of basis functions is analyzed. The comparison shows that the results are in close agreement. The analysis of the forced oscillations shows that the plate executes essentially nonlinear oscillations with two saddle-node bifurcations in the frequency response curve, in which the periodic motion stability of the system changes. The nonlinear oscillations of the plate near the first fundamental resonance are mostly monoharmonic. They may be calculated using the describing function method.

Prediction of the VIV Responses Based on the Numerical Solutions of Controlled Motion

The study of forced and free vibration of a cylinder has long been isolated. The internal relationship between free vibration and forced vibration has rarely been investigated. In this paper, the relationship between the forced and free vibration of a cylinder was established. A series of numerical simulations of a cylinder undergoing forced oscillations at a wide range of vibration amplitudes and frequencies were carried out, with the flow solver viv-FOAM-SJTU developed based on the open-source platform OpenFOAM. Complex demodulation analysis was conducted to quantify the spatial-temporal phase relationship between the forces and the displacement of the cylinder. It was found that, at some particular oscillating amplitudes and frequencies, the phase angle switched between positive and negative values, which corresponds to a vortex mode transferring from the 2P mode to the 2 P O mode. This distinct new mode “ 2 P O ” was closely related to the intermittent jumping between lower and upper branches of the amplitude responses of VIV. A prediction model was developed to obtain the VIV amplitude responses based on the numerical results of forced oscillation. The prediction results of three points located separately in the initial, upper, and lower branches of VIV agreed well with experimental measurements of an elastically mounted cylinder. This prediction model was thus expected to be suitable for predicting the response of VIV.

Resonant Learning in Scale-free Networks

Over the last decades, analyses of the connectivity of large biological and artificial networks have identified a common scale-free topology, where few of the network elements, called hubs, control many other network elements. In monitoring the dynamics of networks hubs, recent experiments have revealed that they can show behaviors oscillating between ON and OFF states of activation. Prompted by these observations, we ask whether the existence of oscillatory hubs states could contribute to the emergence of specific network dynamical behaviors. Here, we use Boolean threshold networks with scale-free architecture as representative models to demonstrate how periodic activation of the network hub can provide a network-level advantage in learning specific new dynamical behaviors. First, we find that hub oscillations with distinct periods can induce robust and distinct attractors whose lengths depend upon the hub oscillation period. Second, we determine that a given network can exhibit series of different attractors when we sequentially change the period of hub pulses. Using rounds of evolution and selection, these different attractors could independently learn distinct target functions. We term this network-based learning strategy resonant learning, as the emergence of new learned dynamical behaviors depends on the choice of the period of the hub oscillations. Finally, we find that resonant learning leads to convergence towards target behaviors over an order of magnitude faster than standard learning procedures. While it is already known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle based on forced oscillations of the network hub.