International Journal of Impact Engineering

A pre-trained artificial neural network is provided for predicting the scaled penetration depth P/L of a rod penetrating into a semi-infinite target, based on the rod length-over-diameter ratio L/D, the impact velocity and the density and hardness of the target and projectile materials. The tensorflow keras sequential network is stored as neural_network.h5 in hierarchical data format (HDF5). The script main.py demonstrates an application of the neural network. Alternatively, the notebook main.ipynb or its static version main.html may be consulted.

Data for the dynamic elastic strain of cylindrical explosion containment vessel and the blast loading generated by the cylindrical charge at the center of the vessel

The deformation of the impacted plates and the ture stress strain relationship of polyurea are presented in the data.

Data from 152 ballistic experiments on CLT panels made from Spruce Pine Fir - South (tab 1) and Southern Yellow Pine (tab 2).

This dataset includes the results of laboratory impact tests conducted on natural-scale double-wythe unreinforced brick masonry walls. The walls were spanning vertically between two reinforced concrete slabs and were subjected to low-velocity drop-weight pendulum tests in which they were repeatedly hit until the opening of a breach in the center of the wall. The tests were instrumented with both hard-wired and optical measurements, the latter consisting of high-speed cameras and digital image correlation techniques. Investigated in these tests were the out-of-plane response of the walls and their capacity to resist the impacts. The axial load applied on the top of the walls was varied for two wall configurations and monitored throughout the tests to study the effect of arching on the failure mechanism produced and number of repeated hits needed to open the breach. Of interest was also the evidence of cracking, more specifically the way it initiated on the undamaged walls and next propagated upon consecutive hits. The data generated from the tests is made here available and documented to support further investigations on masonry structures subjected to extreme actions. The dataset includes four ZIP files, ordered from 01 to 05, along with an auxiliary PDF document describing the content and organization of the data. Test implementation and test results that are built upon this data are presented and discussed in the following research article: Godio M, Flansbjer M, Williams Portal N (2023) Low-velocity out-of-plane impact tests on double-wythe unreinforced brick masonry walls instrumented with optical measurements, International Journal of Impact Engineering To cite this data in your work please refer to the article. The Authors

This dataset contains tabulated values for how the stress in a high frequency waveform will be divided between each of the first four propagating modes, for longitudinal waves in cylindrical pressure bars, up to a normalised frequency of fa/c0=0.9. This data can be used to perform four-mode dispersion correction of high frequency signals, such as overpressure measurements from blast loading using Hopkinson pressure bars. Data was calculated using LS-DYNA to model the propagation of single-frequency pulses in a long steel pressure bar. At each normalised frequency a short, raised-cosine windowed sinusoidal forcing function was applied to the end of the bar. The stress in the bar dispersed into multiple modal 'pulses' as it propagated, allowing the contribution of each mode to be calculated from the amplitude of the pulses. Values are provided up to a normalised frequency of fa/c0 = 0.9, where f is frequency, a is the radius of the bar, and c0 is the one-dimensional wave speed. The table indicates whether the values are modelled directly in LS-DYNA (M) or calculated by interpolation of the modelled results (I). More details are available in our Impact Engineering paper below:

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