Linear Shaped Charge Cutting Property and Charge Cutting Mechanism of Mg-Gd-Y-Zn Alloy

The linear shaped charge cutting technology is an effective technology for aircraft separation. It can separate invalid components from aircrafts timely to achieve light-weight. Magnesium alloy is the lightest metal material, and can be used to cast effective light-weight components of an aircraft construction. However, the application study of the linear shaped charge cutting technology on magnesium alloy components is basically blank. In response to the demand for the linear separation of magnesium alloys, the Mg-12Gd-0.5Y-0.4Zn alloy is selected to carry out the target shaped charge cutting test. The effects of the shaped charge line density, cutting thickness, and mechanical properties on the cutting performance of the alloy are studied. The shaped charge cutting mechanism is analyzed through the notch structure. The results show that the linear shaped charge cutting performance is significantly affected by the penetration and the collapse. The higher the linear density is, the stronger the ability of the linear shaped charge cutter is, and the greater the penetration depth is, which is advantageous. However, the target structure will be damaged when it is too large (e.g., 4.5 g?m-1). Within 12 mm, when the cutting thickness of the target increases, the penetration depth increases. The lower the tensile strength is, the greater the penetration depth is, and the more conducive the penetration depth to the shaped charge cutting is. When the elongation (EL) increases to 12%, the collapse of the target is incomplete and the target cannot be separated. When the tensile strength of the Mg-Gd-Y-Zn alloy is less than 350 MPa, the EL is less than 6.5%, the cutting thickness is less than 12 mm, and the linear shaped charge cutting of the magnesium alloy can be achieved stably.     

基于布尔感知模型的N段有向覆盖与 K重全向覆盖

针对无线传感器网络节点的布尔感知模型，在满足覆盖要求的条件下，文章对N段有向感知中邻近段之间等概率跳变或以恒定角速度ω扫描2种情况，分别给出传感器节点工作在有向感知模型下的分段数Ⅳ与全向模型下的覆盖重数K之间的关系表达式。之后，进一步对节点以恒定角速度∞扫描，考虑时间积累的条件下，给出了时间m、分段数N与覆盖重数K的表达式。通过以上研究，可以将有向感知模型的覆盖问题转化为求取全向感知模型下的覆盖重数问题。