CN115183777A - Nuclear radiation environment path planning method - Google Patents
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Abstract
The invention discloses a nuclear radiation environment path planning method, which comprises the following steps: 1) Gridding a nuclear radiation environment area, and determining a starting point and an end point of path planning; 2) Setting a dose rate limit value, and treating grids meeting the safety limit value in the nuclear radiation environment area as barriers; 3) And calculating the total dose cost in the process by taking the accumulated dose as an actual cost and the estimated dose as an estimated cost, guiding the path by adopting an improved A-star algorithm, and planning the final path by taking the minimum estimated total dose cost F (n). The method not only considers the influence of the dose rate of the nuclear radiation field and the existence of the barrier on the safety and the traveling of the personnel, but also considers how to quickly find out the path with the minimum dose cost in the set dose rate limit value, and can meet the optimal path planning requirement of the personnel in the radiation environment.
Description
Technical Field
The invention relates to a path planning technology, in particular to a path planning method for a nuclear radiation environment.
Background
In typical radioactive working environments such as a radiation control area of a nuclear power plant, workers are at risk of receiving radiation exposure. Since the radiation is invisible and not directly perceptible by the human body, the risk of exposure of personnel to the radioactive environment is greatly increased. Meanwhile, because the radiation distribution of the radiation source is unclear, when the radiation source moves in a radiation working place, only rough qualitative path planning can be carried out according to past experience, so that the exposure dose of the personnel exceeds the standard when the equipment is overhauled, replaced, cleaned and retired.
At present, most of path planning research based on the A star algorithm is concentrated in the field of autonomous mobile robots, and partial research only considers the problem of shortest path. Path planning studies for personnel working in a radiation environment are rare and radiation hazards to the personnel from radioactive sources are ignored, particularly radiation that exceeds occupational exposure dose limits. Compared with the traditional A-star algorithm which only considers the obstacles and the shortest distance, the improved A-star algorithm provided by the patent comprehensively considers 4 factors of non-uniform radiation field dosage rate, accumulated dosage, shortest path and obstacles, and can meet the optimal path planning requirement of personnel in a radiation environment.
Disclosure of Invention
The invention aims to solve the technical problem of providing a nuclear radiation environment path planning method aiming at the defects in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a nuclear radiation environment path planning method comprises the following steps:
1) Gridding a nuclear radiation environment area, and determining a starting point and an end point of path planning;
2) Setting a dose rate limit value, and treating grids which exceed a safety limit value in a nuclear radiation environment area as obstacles;
3) Calculating the total dose cost in the process by taking the accumulated dose as an actual cost and the estimated dose as an estimated cost, and guiding a path by adopting an improved A-star algorithm;
F(n)＝G(n)+H(n)
wherein F (n) is the total dose cost from the starting node, via the candidate node, to the target node ultimately; g (n) is the actual cost estimate for reaching the candidate node from the starting node; h (n) is a heuristic estimated cost from the current preprocessed candidate node to the target node;
the actual cost G (n) is represented by the accumulated dose between any two grid nodes, calculated by the product of dose rate and travel time per grid
In the formula, G (N) is the actual dose cost from the starting node S to the candidate node N; d k (x,y)、D k+1 (x, y) are the dose rates at grid nodes k, k +1, respectively; l is the side length of each grid cell; v is the person's travel speed; delta. For the preparation of a coating k To adjust the coefficients, δ when grid nodes k and k +1 are in a horizontal or vertical positional relationship k Taking 1.0; when the grid nodes k and k +1 are in a diagonal position relationship, δ k Taking 1.4;
h (n) estimating the product of the average dose rate of the radiation field obtained by the Monte Carlo algorithm and the shortest time from the candidate node to the total target node;
a Monte Carlo random sampling area is defined as a rectangle formed by connecting an expansion node and a target node, and (x, y) are coordinates of the expansion node, wherein x =1,2,3.. M, and y =1,2,3.. N;
wherein the content of the first and second substances,
in the formula I min The shortest distance between the candidate grid node and the target grid node is obtained; w is the horizontal distance between the candidate node and the target node, and h is the horizontal distance between the candidate node and the target nodePerpendicular distance of D k (x, y) is the dose rate at grid node k; v is the person's travel speed;
4) The final path planning is minimized with an estimate of the total dose cost F (n).
The invention has the following beneficial effects:
1. the invention provides an improved A-star algorithm guided nuclear radiation environment path planning method, which is used for meeting the optimal path planning requirement of personnel in a radiation environment, can be used for overhauling a nuclear power plant and an ocean nuclear power platform and nuclear emergency rescue, comprehensively considers 4 factors including non-uniform radiation field dosage rate, accumulated dosage, a shortest path and barriers, and has advantages and reference significance in engineering application;
2. the method not only considers the influence of the dose rate of the nuclear radiation field and the existence of the barrier on the safety and the traveling of personnel, but also considers how to quickly find out the path with the minimum dose cost in the set dose rate limit value, and can meet the optimal path planning requirement of the personnel in the radiation environment.
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The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a method of an embodiment of the present invention;
FIG. 2 is a schematic diagram of an eight-direction search according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a Monte Carlo random sampling area according to an embodiment of the present invention;
fig. 4 is a schematic diagram of shortest path estimation according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a nuclear radiation environment path planning method includes the following steps:
1) Gridding a nuclear radiation environment area, and determining a starting point and an end point of path planning;
2) Setting a dose rate limit value, and treating grids which exceed a safety limit value in a nuclear radiation environment area as obstacles;
3) Calculating the total dose cost in the process by taking the accumulated dose as an actual cost and the estimated dose as an estimated cost, and guiding a path by adopting an improved A-star algorithm;
F(n)＝G(n)+H(n) (1)
wherein F (n) is the total dose cost from the starting node, via the candidate node, to the target node ultimately; g (n) is the actual cost estimate for reaching the candidate node from the starting node; h (n) is a heuristic estimated cost from a currently preprocessed candidate node to a target node;
compared with the traditional A star algorithm, the improved A star algorithm considers the accumulated dose and the shortest path at the same time.
The actual cost G (n) is represented by the accumulated dose between any two grid nodes, calculated by the product of dose rate and travel time for each grid
The model of the cumulative dose between two adjacent grid nodes in a two-dimensional grid plane is shown in fig. 1. In fig. 2, the central node is a candidate grid node, and 1,2,3, 4, 5, 6, 7, and 8 are eight direction expansion nodes of the candidate grid node, so that the actual dose cost from the start node S to the candidate node N can be estimated by equation (2).
In the formula: g (N) is the actual dose cost (mSv) from the starting node S to the candidate node N; d k (x,y)、D k+1 (x, y) is the dose rate (mSv/h) at mesh nodes k, k +1, respectively; l is the side length (m) of each grid cell; v is the person's travel speed (m/h); when two adjacent grid nodes are in horizontal or vertical position relationship, the orientation is delta as shown by grids 1, 3, 5 and 7 in FIG. 2 k Taking 1.0; when two adjacent grid nodes are in diagonal position relationship, the orientation is delta as shown by grids 2, 4, 6 and 8 in FIG. 2 k 1.4 is taken.
H (n) estimating the product of the average dose rate of the radiation field obtained by the Monte Carlo algorithm and the shortest time from the candidate node to the total target node;
the monte carlo random sampling area is defined as a rectangle formed by connecting the extension node and the target node, as shown by a blue shaded area in fig. 3. In the figure, N is a candidate node, G is a target node, and m1, m2 and m3 are expansion nodes. Assuming that the speed of the person is constant, the shortest time can be equivalent to the shortest path, the schematic diagram of the shortest path estimation is shown in fig. 4, w and h are the horizontal and vertical distances between the candidate node and the target node, respectively, the main function of the min (h, w) function is to extract the minimum value of h and w, and the formula of the shortest path is shown in formula (3). For an mxn grid, the estimated dose cost H (N) can be estimated according to equation (4), (x, y) is the coordinates of the extended nodes, (x =1,2,3.. M, y =1,2,3.. N), and (x, y) is the coordinate system with the boundary of the sampling region as the x, y axis.
4) The final path plan is given with the minimum estimate of the total dose cost F (n).
Where F (n) is the total dose cost estimate (mSv) of the person from the starting node S to the target node G.
5) And calculating average dose cost. After path planning is completed, it is necessary to perform path backtracking and calculate the maximum dose rate, the minimum dose rate and the length of a path traveled in the whole process, and further calculate the travel time, the total dose cost and the average dose cost so as to accurately compare the advantages and disadvantages of the path planned by the improved a-star algorithm and the traditional a-star algorithm. For two points in a two-dimensional plane where an obstacle exists, the euclidean distance (i.e., the straight line between the two points is the shortest) may represent the distance between the two points in an actual situation.
The method adopts the Euclidean distance to express the actual path length of the personnel, calculates the total dose cost from the starting point S to the end point G in the whole process according to the formula (2), and can calculate the average dose cost of the personnel in the whole process by combining the travel time
As shown in formula (6).
In the formula: (x) k ,y k ) And (x) k+1 ,y k+1 ) The coordinates of any two adjacent grid nodes in the path traveled.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.
Claims (3)
1. A nuclear radiation environment path planning method is characterized by comprising the following steps:
1) Gridding a nuclear radiation environment area, and determining a starting point and an end point of path planning;
2) Setting a dose rate limit value, and treating grids meeting the safety limit value in the nuclear radiation environment area as barriers;
3) Calculating the total dose cost in the process by taking the accumulated dose as an actual cost and the estimated dose as an estimated cost, guiding a path by adopting an improved A-star algorithm, and planning the final path by taking the minimum estimated total dose cost F (n);
F(n)＝G(n)+H(n)
wherein F (n) is the total dose cost from the starting node through the candidate node to the target node; g (n) is the actual cost estimate to reach the candidate node from the starting node; h (n) is a heuristic estimated cost from the current preprocessed candidate node to the target node;
the actual cost G (n) is calculated by the product of the dose rate and the travel time per grid;
h (n) estimating the product of the average dose rate of the radiation field obtained by the Monte Carlo algorithm and the shortest time from the candidate node to the total target node;
a Monte Carlo random sampling area is defined as a rectangle formed by connecting an expansion node and a target node, and (x, y) are coordinates of the expansion node, wherein x =1,2,3.. M, and y =1,2,3.. N;
wherein the content of the first and second substances,
in the formula I min Is the shortest distance between the candidate grid node and the target grid node; w is the horizontal distance between the candidate node and the target node, h is the vertical distance between the candidate node and the target node, D k (x, y) is the dose rate at grid node k; v is the person's travel speed.
2. The nuclear radiation environment path planning method according to claim 1, wherein in step 3), the actual cost G (n) is calculated by multiplying the dose rate and the travel time of each grid, and specifically as follows:
in the formula, G (N) is the actual dose cost from the starting node S to the candidate node N; d k (x,y)、D k+1 (x, y) are the dose rates at grid nodes k, k +1, respectively; l is the side length of each grid cell; v is the person's travel speed; delta k To adjust the coefficients, δ when grid nodes k and k +1 are in a horizontal or vertical positional relationship k Taking 1.0; when grid nodes k and k +1 are in diagonal position relationship, δ k Taking 1.4; n is the total number of nodes through which the process travels.
3. The nuclear radiation environment path planning method according to claim 1, wherein in the step 3), H (n) is estimated by multiplying the average dose rate of the radiation field obtained by the monte carlo algorithm by the shortest time from the candidate node to the total target node; the method comprises the following specific steps:
a Monte Carlo random sampling area is defined as a rectangle formed by connecting extension nodes and target nodes, and (x, y) are coordinates of the extension nodes, wherein x =1,2,3.. M, and y =1,2,3.. N;
wherein, the first and the second end of the pipe are connected with each other,
in the formula I min Is the shortest distance between the candidate grid node and the target grid node; w is the horizontal distance between the candidate node and the target node, h is the vertical distance between the candidate node and the target node, D k (x, y) is the dose rate at grid node k; v is the person's travel speed.
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