To investigate the rotation vibration dynamics of the pulleys and the tension arms, and to estimate the vibrations of the belts and the slip ratio between the belt and the pulleys in the engine front-end accessory drive systems, a systematic modelling and analytical method is proposed for engine front-end accessory drive systems; this can be used for modelling engine front-end accessory drive systems with different layouts and different numbers of tensioners, including automatic and fixed tensioners. In the modelling, the rotational pulleys are classified as fixed-axis pulleys and moveable-axis pulleys (such as the pulley in the tensioner). Moreover, the belt spans are classified as the belt spans between the two fixed pulleys, and the belt spans adjacent to the pulley of a tensioner. The equations of motion for each type of pulley and the tension calculation equations for each type of belt span are developed. In this way, the equations of motion for all the pulleys and the tensioner arms can be obtained easily, irrespective of the layout of the tensioners. To obtain the dynamic rotational vibration responses of an engine front-end accessory drive system by the conventional Runge–Kutta method, high-efficiency algorithms or methods are also proposed for calculating the tangent-point coordinates between a belt and the adjacent pulleys and the belt length of the contact arc on one pulley. The proposed modelling and analysis methods are validated by modelling different layouts of the engine front-end accessory drive systems with different types and numbers of tensioners, and also by comparisons between the calculated dynamic vibration responses of the pulleys and the belts and the real experimental data.

Motivated by the theoretical interest in reconstructing long 3D trajectories of individual birds in large flocks, we developed CoMo, a comoving camera system of two synchronized cameras coupled with rotational stages, which allows us to dynamically follow the motion of a target flock. With the rotation of the cameras, we overcome the limitations of standard static systems that restrict the duration of the collected data to the short interval of time in which targets are in the cameras common field of view, but, at the same time, we change, in time, the external parameters of the system, which have then to be calibrated frame by frame. We address the calibration of the external parameters measuring the position of the cameras and their three angles of yaw, pitch, and roll in the system home configuration (rotational stage at an angle equal to 0°) and combining this static information with the time-dependent rotation due to the stages. We evaluate the robustness and accuracy of the system by comparing reconstructed and measured 3D distances in what we call 3D tests that show a relative error of the order of 1%. The novelty of the work presented in this article is not only on the system itself but also on the approach that we use in the tests, which we show to be a very powerful tool in detecting and fixing calibration inaccuracies, and it, for this reason, may be relevant for a broad audience.

A comparative study of honeycomb rubber coatings of the same material and total mass subjected to underwater explosion has been carried out in this article. Three types of cell topologies were considered: hexachiral honeycomb, reentrant honeycomb, and circular honeycomb. Three groups of live underwater explosion tests with different attack angles and stand-off distances were conducted on the stiffened metal boxes covered with the coatings. The free field water pressure and wall pressure near the coating’s wet surface were monitored. The acceleration peaks at typical test locations on the inner structure were selected as the major comparative criterions. As a theoretical extension to the test work, finite element simulations have been undertaken using ABAQUS/Explicit software package to provide insights into the coating’s working mechanism and the relation between compression behavior and water blast shock resistance. The results show that the protective effects of different coatings are consistent under different attack angles and stand-off distances. Compression performance depends on the coating structure and plays a dominant role in the underwater shock resistance. Although structural absorbed energy has a significant contribution in the shock resistance, soft coating can substantially reduce the total incident impulse at the initial fluid–structure interaction stage. Furthermore, a smaller fraction of incident impulse is transferred to the honeycomb coating with lower compressive strength.