核聚变空间推进器的初步需求分析

参考一种简化的、解析近似的计算模型，以地球到火星的对接任务和往返任务为例，对核聚变等离子体推进器性能关键参数如推进系统质量、比冲、任务时间、有效载荷份额及比功率等进行分析，得出了任务时间和有效载荷质量份额与聚变堆芯输出功率、推进器结构质量和比冲的依赖关系。在此基础上，结合核聚变地面商业堆的相关进展，对现有的技术做合理适当外推，理论计算表明:飞行任务能够在1~2个月内达到目的星球同时可携带超过10%的有效载荷份额，并提出了未来核聚变空间推进器的初步参数方案和设计构想，总体上能够为未来核聚变空间推进技术的发展提供一定的参考。      

A hybrid deep neural network based on multi-time window convolutional bidirectional LSTM for civil aircraft APU hazard identification

Safety is one of the important topics in the field of civil aviation. Auxiliary Power Unit(APU) is one of important components in aircraft, which provides electrical power and compressed air for aircraft. The hazards in APU are prone to cause economic losses and even casualties. So,actively identifying the hazards in APU before an accident occurs is necessary. In this paper, a Hybrid Deep Neural Network(HDNN) based on multi-time window convolutional neural network-Bidirectional Long Short-Term M...