During the COVID-19 pandemic face masks grew in importance as their use by the general population was recommended by health officials in order to minimize the risk of infection and prevent further spread of the virus. To ensure health protection of medical personal and other system relevant staff, it is of considerable interest to quickly test if a certain lot of filtering facepiece masks meets the requirements or if the permeability changes under different conditions. As certified penetrometers are rather expensive and were difficult to obtain during the COVID-19 pandemic, we describe two quite simple and cheap methods to quickly test the filter permeability based on an electronic cigarette. The first method uses a precision scale, the second method uses a light scattering detector to measure the filter penetration. To make sure these two methods yield reliable results, both were tested with freshly cut filter samples covering the range of approx. 7% to 60% permeability and compared to the results of a certified penetrometer. The comparison of the two methods with the certified penetrometer showed a good correlation and therefore allow a quick and rather reliable estimation of the permeability. Several examples about the use of faulty masks and the resulting health risks show that simple, fast, cheap and broadly available methods for filter characterization might be useful in these days.

The high reliable correlations between CBR and DCP in general proposed are presented in this paper. We analyzed the test data and correlations from many researchers to find the best equation for prediction the CBR from DCP test. The findings show that all correlations from existing paper are based on local material and cannot apply to soil in a different location in general purpose. New correlations between CBR and DCP were proposed and validated in this paper for general uses. The validation confirmed that these new correlations can predict well with higher R2.

Tracked vehicles play a significant role in engineering. Supportive trafficability is the salvation of any tracked vehicle. Terrain characteristics have a substantial impact on tracked vehicle mobility. We consider a tracked vehicle traversing known terrain in this paper. Vehicle-terrain interaction covers track-soil friction, soil compaction, traction, bearing capacity, and sinkage resistance. Identifying the soil parameters upon which a tracked vehicle moves will likely lead to more accurate traversability predictions, better traction control, and more accurate trajectory tracking. Conventional terramechanical models cannot adequately describe the connection between tracks and soil. Obtaining real-time measurements of the ground pressure of the soil as the unmanned tracked vehicle moves in the soil bin of dimensions 610 cm long, 245 cm wide, and 180 cm deep is challenging. The utilization of real-time data enables monitoring dynamic variations in ground pressure exerted by the operational components within a soil bin. A ground pressure monitoring device suitable for wet and dry soil was designed to reduce the accumulation of choked damp soil, clay, or mud in the sensor, sensor bracket, track, and other equipment. The device uses a pressure sensor, a data logger, and wireless measurement technology. It can simultaneously measure up to 8 pressure sensors and transmit measurement data remotely to a computer. This reduces the labor intensity of measuring personnel in muddy soil. Data analysis showed that the crewless tracked vehicle’s ground pressure and forward resistance increased with forward speed and vertical load. A law was also discovered explaining how ground pressure (sinkage) spreads between the trackpad and the soil. A general technique is presented in this paper that can be applied to any tracked vehicle. The conclusions show that the ground pressure measurement system works steadily in different humidity scenarios. In addition, the data that has been gathered can be transmitted to a computer using wireless communication methods.