Abstract
The design of cable pathways is indispensable components in the layout design of nuclear power plants. In nuclear power plants, cables exhibit characteristics of being numerous in quantity, diverse in types, and having multiple installation standards. At present, the layout design of cable pathways in a typical nuclear power plant has always been carried out relying heavily on engineering experience. Depending solely on manual deployment not only results in low efficiency but may also not yield the most optimal solutions. To mitigate the human factors on the design and expedite the generation of economically superior solutions, we propose an automatic layout method.
In this method, spatial discretization of nuclear power plant civil structures and equipment is achieved using a grid-based approach, and cable path searches are conducted within the grid map using the A* algorithm. Considering the drawbacks of the traditional A* algorithm’s slow pathfinding in large plants and complex environments, we present an improved A* algorithm tailored for cable layout in nuclear power plants. Firstly, according to the characteristic of prioritizing cable installation along the walls, delineate feature lines along the walls throughout the entire plant area. The feature lines intersect with each other, forming a network that connects various rooms. The A* algorithm prioritizes pathfinding along the feature lines during the routing process, significantly reducing the number of traversed nodes. Finally, the cost function of the A* algorithm has been redesigned to better reflect the actual layout costs. In the traditional A* algorithm, the cost function is designed to assess the distance cost from the start node to the goal node. For the cable layout problem, this cost not only includes the actual length of cable routing but also account for other factors such as bend costs, wall penetration costs, etc.
The aforementioned methods have been implemented in the C# programming language and have undergone testing. The results confirm the feasibility of the proposed method.
