By means of experiments in microgravity conditions, we show that granular systems subjected to sinusoidal vibrations respond either by harmonic or gaslike dynamics, depending on the parameters of the vibration, amplitude and frequency, and the container size, while subharmonic response is unstable, except for extreme material properties and particular initial conditions. The absence of subharmonic response in vibrated granular systems implies that granular dampeners cannot reveal higher-order resonances, which makes them even more attractive for technical applications. Extensive molecular dynamics simulations support our findings.

No abstract

The validation of a DVI approach for the dynamics of granular material focuses on comparing the experimental and simulation results of granular flow for two tests in the Chrono::Engine simulation environment. A macro scale validation was previously carried out through examination of granular flow in PBR reactors [1]. For this work, an aluminum rig was designed and fabricated to measure the flow rate of a given amount of micro scale granular material flowing due to gravity through a slit. The flow was initiated by using a Newport UMR8.25 translational stage and Newport LTA-HL precision linear actuator to open and close the slit steadily. Once the slit was open, the weight of the granular material was transmitted to the processor via a router connected to a Cooper LFS242 Tension/Compression Cell (Serial No. 286284) and graphed over time. A model of the flow meter was created in Chrono::Engine and the results were matched to experimental runs by changing the friction coefficient between particles. After the friction coefficient of the particles was determined to be 0.15, several experimental runs with differing slit sizes were run. These flow rates were compared to the weight versus time data that Chrono::Engine output for the corresponding slit size. Runs for gap sizes of 1.5mm, 2.0mm, 2.5mm and 3.0mm were performed with 0.0624 N of granular material, which amounted to approximately 39,000 spheres with 500μm in diameter. These gap sizes corresponded to an experimental flow rate of 1.41E-2 N/s, 2.59E-2 N/s, 4.00E-2 N/s, and 4.44E-2 N/s, and a simulated flow rate of 1.40E-2 N/s, 2.62E-2 N/s, 4.05E-2 N/s, and 4.48E-2 N/s, respectively. Based on this experiment, Chrono::Engine had less than a 2% error in calculating the flow rate of the granular material through a slit. In addition to comparing flow rates, the pile repose angle from the experimental runs was compared to the simulation results. A description of the GPU execution model along with its memory spaces is provided to illustrate its potential for parallel scientific computing. The equations of motion associated with the dynamics of many rigid bodies are introduced and a solution method is presented. The solution method is designed to map well on the parallel hardware, which is demonstrated by an order of magnitude reductions in simulation time for large systems that concern the dynamics of granular material.

No abstract

This study outlines an approach for speeding up the simulation of the dynamic response of vehicle models that include hysteretic nonlinear tire components. The method proposed replaces the hysteretic nonlinear tire model with a surrogate model that emulates the dynamic response of the actual tire.The approach is demonstrated via a dynamic simulation of a quarter vehicle model. In the proposed methodology, training information generated with a reduced number of harmonic excitations is used to construct the tire hysteretic force emulator using a Neural Network (NN) element. The proposed approach has two stages: a learning stage, followed by an embedding of the learned model into the quarter car model. The learning related main challenge stems from the attempt to capture with the NN element the behavior of a hysteretic element whose response depends on its loading history. The methodology is demonstrated in conjunction with a simple nonlinear quarter vehicle system as well as an ADAMS based model that uses a complex tire element. The results obtained with the surrogate model prove to be accurate and are obtained at a fraction of the CPU time required to handle the original models. The approach proposed is anticipated to be useful for reducing the duration of vehicle simulations, or when a tire model is not available but experimental data can be used to generate a surrogate model.t) x sp Sprung mass displacement ) (t x tire Tire displacement ) (t y Base displacement tire m Tire mass sp m Sprung mass sus k Suspension stiffness sus c Suspension damping coefficient tire k Tire stiffness tire c Tire damping coefficient ) (t q Restoring force ) (t g Non-hysteretic component of restoring force ) (t z Hysteretic component of restoring force , ,n κ β γ Hysteretic loop shape's control parameters t A Instantaneous amplitude t ω Instantaneous frequency t ∆ Integration time step