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An Accelerated Simulation Assessment Approach for Mission Success Probability of Multi-State Phased Mission Systems

机译：多状态分阶段任务系统任务成功概率的加速仿真评估方法

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The mission success probability assessment of multi-state phased mission systems (MS-PMS) under complex mission were studied. A general simulation framework of the system under complex mission based on discrete event simulation is established. The Monte Carlo method is used to generate the sample of random events, and accelerated sampling methods such as forced transitions and failure biasing are added to improve the sampling efficiency of small probability events, and the sampling statistics are modified to ensure the unbiasedness of the estimates. Taking the warship navigation mission as an example, it is found that the accelerated sampling method can effectively improve the sampling probability of small probability events in the mission regardless of the mission time. The main reason for the failure of the mission can be found by this simulation method, which can provide a basis for improving the success probability of the mission.
机译：研究了复杂任务下多状态分阶段任务系统（MS-PMS）的任务成功概率评估。建立了基于离散事件仿真的复杂任务系统通用仿真框架。蒙特卡罗方法用于生成随机事件的样本，并添加了加速采样方法（如强制转换和故障偏好）以提高小概率事件的采样效率，并修改了采样统计信息以确保估计值的无偏性。以军舰航行任务为例，发现加速采样方法可以有效提高任务中小概率事件的采样概率，而与任务时间无关。通过这种仿真方法可以发现任务失败的主要原因，可以为提高任务成功概率提供基础。

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