A state-aware adaptive pathfinder for dynamic minimum dose path planning during an emergency in a complex radioactive environment

摘要

Optimal walking-path planning is one of the most effective measures to minimize radiation exposure of workers in radioactive environments. Several algorithms have been proposed to control workers' exposure especially during normal operations of a nuclear facility. However, when an emergency or accident occurs, the radioactive environment becomes dynamic and complex, rendering the conventional shortest path algorithms non-optimal and inefficient. This work presents a state-aware adaptive pathfinder (SAP), a method to solve the minimum dose path for an emergency worker in a dynamic nuclear environment. The algorithm dynamically tracks and updates the state of both the radiation source and the (human) target, and adaptively presents the minimum dose path based on the current state. The advantages of the proposed SAP approach are evaluated in two experiments with eight (8) different scenarios. In the first experiment, a minimum dose walking path is obtained for a worker in a static environment with three scenarios. In the second experiment, cumulative dose by the emergency worker along a path is dynamically computed in three scenarios that define both the worker and the radiation source moving in uniform and non-uniform speed. Compared with conventional methods, the results show that the proposed SAP is simpler, more flexible, and effective for path planning in a complex radioactive environment. The performance evaluation result of SAP in both static and dynamic environments, and during a nuclear emergency is discussed in this paper.