Two types of grounding systems are recommended for use in the international standard IEC 62305-3, Part 3: Physical damage to structures and life hazard. One of these is a radial-based grounding system (type-A), which is used in soil resistivities of up to 3000 Omega m and is considered in this paper. It is a well-known fact that during lightning strikes, only a part of the grounding wire contributes to dissipating the lightning current into the surrounding soil. This effective part of the grounding system depends on several features, such as soil resistivity, burial depth, and rise time of the dissipated lightning current. The effect of all of these features on the effective length of the type-A grounding system is explored in this paper. A suitable supervised machine learning regression model is developed, which will enable readers to accurately approximate the effective length of the type-A grounding system for realistic values of input features. The trained model in the paper yielded an R2 value of 0.99998 on the test set. In addition, two simple mathematical formulas are also provided, which produce similar but less accurate results (R2 values of 0.989883 and 0.998557, respectively).

Water ice exists in the permanently shadowed region (PSR) of the moon. It can become a vital survival material for the lunar base and provide fuel for the moon to make the moon a relay station for deep space exploration. For in-situ sampling and detection of lunar water ice, the design of sampling equipment has to consider the mechanical properties of the icy lunar regolith (ILR) to be broken during the drilling process. According to the mineral and chemical composition of the soil in the PSR, basalt rocks and anorthosite rocks are selected as two basic raw materials to simulate lunar soil. Multiple sets of ILR simulated samples are prepared with different raw material ratios (five kinds), water content (5-25 wt%), dry density (bulk density, excluding water, 1.45-1.97 g/cm(3)), and temperature (-240 to-10 degrees C). Uniaxial compressive strength (UCS) tests are carried out on these samples. A comprehensive mapping model between the UCS and the above four factors is constructed using multiple nonlinear regression methods. Based on the existing remote sensing data, the relationships or hypotheses of the subsurface dry density, temperature, and water content with depth are given. Furthermore, the UCS and drillability grade of ILR are predicted to change with depth. The results show that the ratio of raw materials has far less influence on the UCS than the other three factors. When the sample temperature is lower than-180 degrees C, the degree of influence of temperature changes on the UCS is significantly reduced. The UCS of the sample increases nonlinearly with the increase of dry density. The samples have an extreme strength value in the saturated water content state. This study provides a standard for the design of the equipment for drilling detection of water ice and lays a foundation for presetting operating procedures of the drilling tool. (C) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.