Method and apparatus for consumed-resource prediction in nuclear facility decommissioning, and device and storage medium

Abstract

The embodiments of the present application belong to the technical field of nuclear power plant facilities. Provided are a method and apparatus for consumed-resource prediction in nuclear facility decommissioning, and a device and a storage medium. The method comprises: acquiring target plan information for nuclear facility decommissioning; decomposing the target plan information to obtain multiple pieces of sub-plan data and plan level information and level association information of each piece of sub-plan data; acquiring consumed-resource items for executing the sub-plan data to obtain multiple execution consumed-resource items; on the basis of the multiple execution consumed-resource items, performing consumed-resource prediction on each piece of sub-plan data to obtain target consumed-resource prediction data; and on the basis of the plan level information and the level association information, combining the target consumed-resource prediction data of the multiple pieces of sub-plan data, so as to obtain total consumed-resource prediction data for the target plan information. The embodiments of the present application can reduce the manpower required for redundant calculations due to insufficient prediction accuracy and improve the accuracy of consumed-resource prediction for nuclear facility decommissioning.

Description

Method and device for predicting loss resources of nuclear facility decommissioning, equipment and storage medium TECHNICAL FIELD

[0001] The present application relates to the technical field of nuclear power plant facilities, in particular to a method and device for predicting loss resources of nuclear facility decommissioning, equipment and storage medium. BACKGROUND

[0002] Nuclear facility decommissioning has the characteristics of long implementation cycle, great difficulty, and many unpredictable factors. A large amount of resource loss will be generated during the implementation process of nuclear facility decommissioning. Therefore, it is necessary to predict the loss resources of nuclear facility decommissioning before the nuclear facility decommissioning, so as to adjust the operation steps of nuclear facility decommissioning according to the predicted loss resources.

[0003] In the related art, the prediction of loss resources of nuclear facility decommissioning mainly involves manually inputting various indexes, loss resource items and loss resource prediction algorithms related to nuclear facility decommissioning, and then sequentially collecting loss resources generated by nuclear facility decommissioning from bottom to top to obtain resource loss prediction data of the entire nuclear facility decommissioning. However, the entire process requires manual input of a large amount of data, which not only consumes a lot of manpower, but also makes it difficult to determine some data, affecting the accuracy of the prediction of loss resources of nuclear facility decommissioning. Therefore, how to reduce manpower and accurately predict the loss resources of nuclear facility decommissioning has become a technical problem to be solved. SUMMARY

[0004] The main purpose of the embodiments of the present application is to provide a method and device for predicting loss resources of nuclear facility decommissioning, equipment and storage medium, which aims to reduce manpower and accurately predict the loss resources of nuclear facility decommissioning.

[0005] To achieve the above purpose, a first aspect of the embodiments of the present application provides a method for predicting loss resources of nuclear facility decommissioning, which comprises:

[0006] obtaining target scheme information of nuclear facility decommissioning;

[0007] decomposing the target scheme information to obtain a plurality of sub-scheme data and scheme level information and level association information of each sub-scheme data, wherein the sub-scheme data is used to represent the smallest execution link of nuclear facility decommissioning;

[0008] obtaining loss resource items for executing the sub-scheme data to obtain a plurality of execution loss resource items;

[0009] predicting loss resources of each sub-scheme data based on a plurality of execution loss resource items to obtain target loss resource prediction data;

[0010] According to the scheme level information and the level association information, the target loss resource prediction data of the plurality of sub-scheme data is combined to obtain total loss resource prediction data of the target scheme information.

[0011] In some embodiments, the target scheme information is decomposed to obtain a plurality of sub-scheme data, scheme level information and level association information of each sub-scheme data.

[0012] The target scheme information is split to obtain a plurality of sub-scheme data.

[0013] The hierarchical relationship information between the plurality of sub-scheme data is obtained.

[0014] The level association information of each sub-scheme data is determined based on the hierarchical relationship information.

[0015] The category of each sub-scheme data is obtained to obtain a sub-scheme category.

[0016] The sub-scheme data is processed according to the sub-scheme category and the level association information to obtain the scheme level information of each sub-scheme data.

[0017] In some embodiments, the loss resource item of the sub-scheme data is obtained to obtain a plurality of execution loss resource items.

[0018] The sub-scheme category of the sub-scheme data is obtained, the target scheme execution association parameter is selected from the preset candidate scheme execution association parameter based on the sub-scheme category, and the sub-scheme data is simulated according to the target scheme execution association parameter to obtain a plurality of execution loss resource items; wherein the target scheme execution association parameter is used as a parameter for simulating the minimum execution link of the nuclear facility decommissioning.

[0019] Alternatively,

[0020] The scheme association parameter prompt information is generated based on the target scheme execution association parameter, and the parameter loss resource item is received based on the feedback of the scheme association parameter prompt information, and the plurality of execution loss resource items are generated based on the target scheme execution association parameter and the parameter loss resource item.

[0021] In some embodiments, the target loss resource prediction data of each sub-scheme data is obtained based on the plurality of execution loss resource items.

[0022] The sub-scheme information of the sub-scheme data is obtained.

[0023] screening a selected scheme loss resource prediction model from preset candidate scheme loss resource prediction models according to the sub-scheme information;

[0024] performing loss resource prediction on the sub-scheme data by using the selected scheme loss resource prediction model and the plurality of execution loss resource items to obtain the target loss resource prediction data.

[0025] In some embodiments, the execution loss resource items include: an execution loss amount, an execution correlation coefficient, an execution duration, and an execution unit price; and the performing loss resource prediction on the sub-scheme data by using the selected scheme loss resource prediction model and the plurality of execution loss resource items to obtain the target loss resource prediction data includes:

[0026] performing loss resource prediction on the execution loss amount, the execution correlation coefficient, the execution duration, and the execution unit price by using the selected scheme loss resource prediction model to obtain the target loss resource prediction data.

[0027] In some embodiments, after the performing loss resource prediction on each of the sub-scheme data by using the plurality of execution loss resource items to obtain the target loss resource prediction data, the method further includes:

[0028] extracting a correction coefficient from a preset correction database according to the sub-scheme category;

[0029] performing correction processing on the target loss resource prediction data according to the correction coefficient to obtain updated loss resource prediction data;

[0030] updating the total loss resource prediction data according to the updated loss resource prediction data to obtain updated resource prediction data of the target scheme information.

[0031] In some embodiments, after the combining the target loss resource prediction data of the plurality of sub-scheme data according to the scheme level information and the level association information to obtain the total loss resource prediction data of the target scheme information, the method includes:

[0032] comparing the total loss resource prediction data with preset expected loss resource data to obtain an evaluation comparison result;

[0033] if the evaluation comparison result is that the total loss resource prediction data is greater than the expected loss resource data, performing scheme adjustment on the target scheme information according to the total loss resource prediction data to obtain updated scheme data.

[0034] To achieve the above object, a second aspect of the embodiment of the present application provides a nuclear facility decommissioning loss resource prediction device, which comprises:

[0035] a scheme obtaining module, configured to obtain target scheme information of decommissioning of a nuclear facility;

[0036] a decomposition module, configured to perform decomposition processing on the target scheme information to obtain a plurality of sub-scheme data, scheme level information of each of the sub-scheme data, and level association information; wherein the sub-scheme data is used to represent a minimum execution link of decommissioning of the nuclear facility;

[0037] a resource item obtaining module, configured to obtain execution loss resource items of the sub-scheme data to obtain a plurality of execution loss resource items;

[0038] a loss resource prediction module, configured to perform loss resource prediction on each of the sub-scheme data based on the plurality of execution loss resource items to obtain target loss resource prediction data;

[0039] a loss resource combination module, configured to combine the target loss resource prediction data of the plurality of sub-scheme data according to the scheme level information and the level association information to obtain total loss resource prediction data of the target scheme information.

[0040] To achieve the above object, a third aspect of the embodiments of the present application proposes a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the method for predicting loss resources of decommissioning of a nuclear facility according to the first aspect when executing the computer program.

[0041] To achieve the above object, a fourth aspect of the embodiments of the present application proposes a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method according to the first aspect.

[0042] The method and device for predicting loss resources of decommissioning of a nuclear facility, the equipment and the storage medium proposed in the present application can automatically obtain execution loss resource items of sub-scheme data by decomposing target scheme information into sub-scheme data, so that the execution loss resource items are obtained automatically without manual input, saving manpower. At the same time, after determining the execution loss resource items, target loss resource prediction data is obtained by performing loss resource prediction on the sub-scheme data according to the execution loss resource items, and finally, a plurality of target loss resource prediction data is combined based on scheme level information and level association information to obtain total loss resource prediction data of the entire target scheme information, so that the loss resource prediction of the target scheme information is simpler and more accurate, and the repeated calculation in manual calculation is reduced, and the efficiency of loss resource prediction in the decommissioning process of the nuclear facility is improved. BRIEF DESCRIPTION OF DRAWINGS

[0043] Fig. 1 is a flow chart of a method for predicting depletion resources in decommissioning of a nuclear facility according to an embodiment of the present application;

[0044] Fig. 2 is a flow chart of step S102 in Fig. 1;

[0045] Fig. 3 is a schematic diagram of decomposition of target scheme information in the method for predicting depletion resources in decommissioning of a nuclear facility according to an embodiment of the present application;

[0046] Fig. 4 is a system framework diagram of a system for predicting depletion resources in decommissioning of a nuclear facility in the method for predicting depletion resources in decommissioning of a nuclear facility according to an embodiment of the present application;

[0047] Fig. 5 is a flow chart of step S103 in Fig. 1;

[0048] Fig. 6 is another flow chart of step S103 in Fig. 1;

[0049] Fig. 7 is a flow chart of step S104 in Fig. 1;

[0050] Fig. 8 is a flow chart of a method for predicting depletion resources in decommissioning of a nuclear facility according to another embodiment of the present application;

[0051] Fig. 9 is a flow chart of a method for predicting depletion resources in decommissioning of a nuclear facility according to another embodiment of the present application;

[0052] Fig. 10 is a structural schematic diagram of a device for predicting depletion resources in decommissioning of a nuclear facility according to an embodiment of the present application;

[0053] Fig. 11 is a hardware structural schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0055] It should be noted that although the functional modules are divided in the device schematic diagram, and the logical order is shown in the flow chart, in some cases, the steps shown or described can be executed in a manner different from the module division in the device or the order in the flow chart. The terms "first", "second", etc. in the specification and claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the specification herein is for describing the embodiments of the present application only and is not intended to limit the present application.

[0057] First, the terms involved in this application are analyzed:

[0058] Nuclear facility decommissioning: is the action taken after the nuclear facility is out of service due to its expiration or other reasons, in order to fully consider the health and safety of workers and the public and environmental protection. The ultimate goal of decommissioning is to achieve unrestricted opening and use of the site. The methods of nuclear facility decommissioning include immediate removal, delayed removal, and in-situ burial.

[0059] Source investigation of nuclear facility decommissioning: refers to the investigation and evaluation of various sources, factors, steps and possible influences involved in the process of nuclear facility decommissioning.

[0060] Dismantling: refers to the process of permanently closing and dismantling nuclear facilities (such as nuclear power plants, nuclear fuel processing plants, etc.).

[0061] Waste treatment of nuclear facility decommissioning: waste treatment is particularly important during the process of nuclear facility dismantling, as it may contain radioactive waste and other hazardous substances. The general steps of waste treatment during the process of nuclear facility dismantling are: 1. Identification and classification; 2. Separation and treatment; 3. Disposal; 4. Monitoring and control; 5. Record and report.

[0062] Nuclear facility decommissioning has the characteristics of long cycle, great difficulty, many uncertain and unpredictable factors, and requires a large amount of manpower and funds during the implementation process. Therefore, before the decommissioning begins, it is necessary to predict the resource consumption of the nuclear facility decommissioning plan to analyze whether the current nuclear facility decommissioning plan meets the economic benefits, and to adjust the nuclear facility decommissioning plan according to the predicted resource consumption, so that the nuclear facility can be decommissioned efficiently and cost-effectively in the later period according to the nuclear facility decommissioning plan.

[0063] In related technologies, there is a software for evaluating nuclear facility decommissioning plans, which uses unit factor method to predict the resource consumption of nuclear facility decommissioning plans, and manually inputs various indicators involved in the nuclear facility plan, defines resource consumption items and resource consumption calculation formulas, etc., and automatically generates detailed reports for each execution link in the nuclear facility plan according to the manually input resource consumption calculation formulas, various indicators and resource consumption items. However, for different nuclear facility decommissioning plans, each time the various indicators, resource consumption items and resource consumption calculation formulas need to be manually input by artificial, and if multiple nuclear facility decommissioning plans need to be predicted for resource consumption, a large amount of manpower will be consumed. Moreover, in the prediction of resource consumption of nuclear facility decommissioning, some resource consumption items in some nuclear facility plans are difficult to determine, which will affect the prediction accuracy of resource consumption of nuclear facility decommissioning.

[0064] Based on this, the embodiment of the application provides a nuclear facility decommissioning loss resource prediction method and device, equipment and storage medium, aiming to realize the automation of nuclear facility decommissioning loss resource prediction, save manpower and improve the accuracy of nuclear facility decommissioning loss resource prediction.

[0065] The nuclear facility decommissioning loss resource prediction method and device, equipment and storage medium provided by the embodiment of the application are specifically described through the following embodiments. First, the nuclear facility decommissioning loss resource prediction method in the embodiment of the application is described.

[0066] The embodiment of the application can acquire and process related data based on artificial intelligence technology. The artificial intelligence (AI) is the theory, method, technology and application system for using digital computers or machine controlled by digital computers to simulate, extend and expand human intelligence, perceive environment, acquire knowledge and use knowledge to obtain the best results.

[0067] The artificial intelligence basic technology generally includes technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction system, mechatronics, etc. The artificial intelligence software technology mainly includes computer vision technology, robot technology, biometric technology, speech processing technology, natural language processing technology and machine learning / deep learning, etc.

[0068] The nuclear facility decommissioning loss resource prediction method provided by the embodiment of the application relates to the technical field of nuclear power plant nuclear facilities. The nuclear facility decommissioning loss resource prediction method provided by the embodiment of the application can be applied to a terminal, can be applied to a server side, and can also be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc.; the server side can be configured as an independent physical server, can be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN and basic cloud computing services such as big data and artificial intelligence platform; the software can be an application for realizing the nuclear facility decommissioning loss resource prediction method, etc., but is not limited to the above forms.

[0069] The application is operable in a variety of general purpose or special purpose computing system environments or configurations. Examples of computing systems, environments, and / or configurations that can be suitable for use with the application include personal computers, server computers, handheld or laptop devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. The application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in both local and remote computer storage media including memory storage devices.

[0070] FIG. 1 is an optional flowchart of a method for predicting a depletion resource of decommissioning a nuclear facility according to an embodiment of the application. The method of FIG. 1 can include, but is not limited to, steps S101-S105.

[0071] In step S101, target scheme information of decommissioning a nuclear facility is obtained.

[0072] In step S102, the target scheme information is decomposed to obtain a plurality of sub-scheme data and scheme level information and level association information of each sub-scheme data. The sub-scheme data is used to represent the minimum execution link of decommissioning a nuclear facility.

[0073] In step S103, a depletion resource item for executing the sub-scheme data is obtained to obtain a plurality of execution depletion resource items.

[0074] In step S104, each sub-scheme data is predicted for a depletion resource based on the plurality of execution depletion resource items to obtain target depletion resource prediction data.

[0075] In step S105, the target depletion resource prediction data of the plurality of sub-scheme data is combined according to the scheme level information and the level association information to obtain total depletion resource prediction data of the target scheme information.

[0076] The steps S101 to S105 shown in the embodiments of the present application decompose the target scheme information into multiple sub-scheme data, determine the scheme level information and level association information of each sub-scheme data, obtain the execution loss resource items by acquiring the loss resource items of the sub-scheme data, perform loss resource prediction on each sub-scheme data according to the multiple execution loss resource items to obtain target loss resource prediction data, and finally combine the multiple target loss resource prediction data into the total loss resource prediction data of the target scheme information according to the scheme level information. The sub-scheme data is used to represent the minimum execution link of the decommissioning of the nuclear facility. Therefore, by splitting the entire target scheme of the decommissioning of the nuclear facility into multiple sub-scheme data, collecting the execution loss resource items involved in each sub-scheme data, and then calculating the loss resource generated by each sub-scheme data, the resource data consumed by the decommissioning of the nuclear facility is determined by combining all the loss resources according to the level of the sub-scheme data, so that the loss resource prediction of the decommissioning of the nuclear facility does not need to manually input a large amount of data and loss resource calculation formula, and the loss resource prediction of the decommissioning of the nuclear facility is automated and accurate, reducing the manpower of the loss resource prediction of the decommissioning of the nuclear facility and improving the prediction accuracy of the loss resource of the decommissioning of the nuclear facility.

[0077] In step S101 of some embodiments, the target scheme information records the entire operation process of the decommissioning of the nuclear facility and which minimum execution link needs to be executed for each process. Specifically, the entire operation process of the decommissioning of the nuclear facility can be divided according to stages, each stage corresponds to a different process link, and each process link sets multiple minimum execution links of the decommissioning of the nuclear facility.

[0078] It should be noted that, as shown in FIG. 4, the loss resource prediction method of the decommissioning of the nuclear facility is applied to a loss resource prediction system of the decommissioning of the nuclear facility, and the loss resource prediction system of the decommissioning of the nuclear facility includes a scheme editing module, a loss resource prediction module, a three-dimensional simulation system module and a database module. The database module is used to support the storage of model data such as the model of the decommissioning scene simulation of the nuclear facility, the tool model, and the three-dimensional dose field. In addition, the database module also stores the execution loss resource items related to the execution of the decommissioning of the nuclear facility, as well as the evaluation formula for evaluating each sub-scheme data and the correction coefficient of the execution loss resource items. The three-dimensional simulation system module is called when the associated simulation of the minimum execution link in the decommissioning of the nuclear facility is performed, and the related configuration data required for the simulation process of the minimum execution link in the decommissioning of the nuclear facility is configured.

[0079] Referring to FIG. 2, in some embodiments, step S102 can include but is not limited to steps S201 to S205:

[0080] Step S201, the target scheme information is split to obtain multiple sub-scheme data;

[0081] Step S202, obtaining hierarchical relationship information between a plurality of sub-scheme data;

[0082] Step S203, determining level association information of each sub-scheme data based on the hierarchical relationship information;

[0083] Step S204, obtaining a category of each sub-scheme data to obtain a sub-scheme category;

[0084] Step S205, performing hierarchical processing on the sub-scheme data according to the sub-scheme category and the level association information to obtain the scheme level information of each sub-scheme data.

[0085] In steps S201 to S202 of some embodiments, the splitting of the target scheme information is completed on the decommissioning scheme editing module, that is, the target scheme information is initially split according to the decommissioning execution stages, and then further split according to the execution process in each stage until the smallest execution link is split to obtain sub-scheme data. In the splitting process, the hierarchical relationship information between each sub-scheme data is recorded to determine the level association information of each sub-scheme data according to the hierarchical relationship information. Specifically, as shown in FIG. 3, the target nuclear facility decommissioning needs to go through four stages, the first stage includes research and development, pre-decommissioning activities, device closing activities, plant site infrastructure and operation, the second stage includes spent fuel safe storage and conventional demolition, demolition, the third stage includes demolition activities in the control area, waste treatment, storage and disposal, and the fourth stage includes additional activities and miscellaneous expenses for plant site restoration, safe storage or burial. The execution process in each decommissioning execution stage can be divided according to the level to divide into the smallest execution link. In this embodiment, there are 18 kinds of smallest execution links for nuclear facility decommissioning, and the 18 smallest execution links are respectively ①, source item investigation; ②, cleaning and decontamination; ③, demolition and disassembly; ④, waste disposal; ⑤, waste preparation and transportation; ⑥, system or facility modification; ⑦, environmental restoration; ⑧, environmental remediation; ⑨, personnel employment; ⑩, equipment procurement; material procurement; project management; project benefits; preliminary work preparation; engineering design and technical services; supervision and completion acceptance; other engineering activities; Unpredictable activities. When the decommissioning plan of the nuclear facility is divided into the minimum execution links, the level association information between the minimum execution links needs to be determined to determine the association between different minimum execution links according to the level association information. For example, in the pre-decommissioning activity link, the minimum execution links of the same level association calculation include ①, ③, and ⑤, and the minimum execution link with the label ① is the source investigation, the minimum execution link with the label ③ is the demolition and disassembly, and the minimum execution link with the label ⑤ is the waste preparation and transportation. Therefore, there may be multiple associated minimum execution links in the same level to realize the execution of the level in parallel.

[0086] In step S204 of some embodiments, the sub-plan category of each sub-plan data is obtained, that is, the task activity type representing the execution of the sub-plan data. It should be noted that the process of splitting the target plan information by the decommissioning plan editing module is to split according to the task activity type level by level. Each level is subdivided into lower levels of execution links according to the task activity type and the level association information, until it is divided into the minimum execution links. As shown in FIG. 4, in the decommissioning plan editing module, the plan for decommissioning the nuclear facility is divided. First, it is divided into first-level task A and first-level task B according to the activity task type, and then it is further divided. The first-level task B is divided into the minimum execution link b, and the first-level task A can be divided into the second-level task A1. The second-level task A1 is divided into the minimum execution link a and the minimum execution link c. Therefore, by dividing the target plan information into multiple minimum execution links in advance in the decommissioning plan editing module, and determining the execution level information and the level association information of each minimum execution link. For example, the link level information of the minimum execution link c is the second level, and the link level information of the minimum execution link b is the first level. It should be noted that the link level information and the level association information of each minimum execution link are used for final resource consumption combination. The total consumption resource prediction data can be calculated level by level to obtain accurate total consumption resource prediction data.

[0087] In steps S201 to S205 shown in the embodiment, the target plan information is divided into multiple sub-plan data, and the plan level information and the level association information of each sub-plan data are determined, so that it is more convenient to calculate the total consumption resource prediction data of the target plan information subsequently.

[0088] In step S103 of some embodiments, the execution loss resource item of the sub-scheme data represents resource loss of items generated in the execution process of the sub-scheme data, and the resource loss of each item generated in the execution of the sub-scheme data is defined as the execution loss resource item. It should be noted that the execution loss resource item of each sub-scheme data can be determined by simulation or manually input. The selection steps of the simulation and manual input methods for determining the execution loss resource item are to obtain the calculation optimization information of each sub-scheme data, and select the loss resource item calculation method from the simulation and manual input methods according to the calculation optimization information. It should be noted that if the calculation optimization information of the sub-scheme data is the simulation method, the simulation method is selected as the calculation method of the loss resource item, and if the calculation optimization information is the manual input method, the manual input method is selected as the calculation method of the loss resource item. Specifically, simulation needs the help of a three-dimensional simulation system module, and the three-dimensional simulation system module is provided with simulation functions such as assembly, arrangement, cutting, decontamination, demolition, preparation, sorting, transfer and hoisting, so as to simulate the resource loss generated in the execution process of the sub-scheme data, that is, the resource loss generated in the implementation of the minimum execution link, so as to determine the execution loss resource item.

[0089] Referring to FIG. 5, in some embodiments, if the simulation calculation is used to determine the plurality of execution loss resource items, step S103 can be step S501:

[0090] In step S501, the sub-scheme category of the sub-scheme data is obtained, the target scheme execution associated parameter is selected from the pre-set candidate scheme execution associated parameter based on the sub-scheme category, and the target scheme execution associated parameter is used for simulation of the sub-scheme data, so as to obtain the plurality of execution loss resource items; wherein the target scheme execution associated parameter is used as the parameter for simulation of the minimum execution link of the nuclear facility decommissioning.

[0091] In step S501 of some embodiments, the candidate scheme execution associated parameter is a simulation configuration parameter involved in the simulation of the sub-scheme data, and also belongs to the associated parameter of the execution of the sub-scheme data. Specifically, the candidate scheme execution associated parameter can be data such as tools, equipment, materials and manpower involved in the execution of the sub-scheme data. It should be noted that different sub-scheme categories correspond to different candidate scheme execution associated parameters, so the candidate scheme execution associated parameter corresponding to the sub-scheme category of the sub-scheme data is used as the target scheme execution associated parameter.

[0092] The target scheme execution associated parameters are input into the three-dimensional simulation system module, so that the sub-scheme data are simulated by the three-dimensional simulation system module to output resource consumption generated in the execution process of the sub-scheme data, so as to obtain the execution consumption resource item. Specifically, the execution consumption resource item of the sub-scheme data is the resource consumption generated when the data of tools, equipment, materials, manpower and the like involved in the minimum execution link of the execution of the nuclear facility decommissioning process.

[0093] In step S501 shown in the embodiment, the three-dimensional simulation system module is used to simulate the sub-scheme data based on the target scheme execution associated parameters, so as to simulate the resource consumption items generated in the execution process of the sub-scheme data to obtain the execution consumption resource item, so that the execution consumption resource item is obtained automatically without manual input, and manpower is saved.

[0094] It should be noted that after simulation, if there are execution consumption resource items that cannot be simulated, the execution consumption resource items can be perfected by manual input.

[0095] Referring to FIG. 6, in some embodiments, step S103 can further include step S601:

[0096] In step S601, scheme associated parameter prompt information is generated based on the target scheme execution associated parameters, and parameter consumption resource items fed back to the scheme associated parameter prompt information are received, and a plurality of execution consumption resource items are generated based on the target scheme execution associated parameters and the parameter consumption resource items.

[0097] In step S601 of some embodiments, the scheme associated parameter prompt information is used to display the target scheme execution associated parameters, so that the user can know the execution consumption resource items needed for the implementation process of the sub-scheme data through the scheme associated parameter prompt information, that is, the data of tools, equipment, materials, manpower and the like involved in the minimum execution link of the execution of the nuclear facility decommissioning process are input to obtain the plurality of execution consumption resource items. The parameter consumption resource items are input by the user according to the scheme associated parameter prompt information, and correspond to each input item of the target scheme execution associated parameters, so that the target scheme execution associated parameters and the corresponding parameter consumption resource items are matched to obtain the resource data consumed in the execution of the sub-scheme data to obtain the plurality of execution consumption resource items.

[0098] In step S601 shown in the embodiment, the user is prompted to manually input the parameter items by using the scheme associated parameter prompt information, and the parameter consumption resource items fed back by the user are received, and then the parameter consumption resource items and the target scheme execution associated parameters are matched to determine the execution consumption resource items needed for the execution of the sub-scheme data, so as to realize the complete supplement of the execution consumption resource items and improve the accuracy of the prediction of the consumption resources of the nuclear facility decommissioning.

[0099] Referring to FIG. 7, in some embodiments, step S104 can include but is not limited to steps S701-S703:

[0100] Step S701, obtaining sub-plan information of the sub-plan data;

[0101] Step S702, screening a selected plan loss resource prediction model from the preset candidate plan loss resource prediction model according to the sub-plan information;

[0102] Step S703, performing loss resource prediction on the sub-plan data by the selected plan loss resource prediction model and the plurality of execution loss resource items to obtain target loss resource prediction data of the sub-plan data.

[0103] In steps S701-S702 of some embodiments, the sub-plan information represents information of the sub-plan data, and through the sub-plan information, it can be known which resource items are needed to complete the sub-plan data. Specifically, as shown in FIG. 3, there are 18 minimum execution links of the target nuclear facility decommissioning, i.e., 18 sub-plan data, which are source investigation, cleaning and decontamination, dismantling and disassembly, waste disposal, waste preparation and transportation, system or facility modification, environmental restoration, environmental renovation, personnel employment, equipment procurement, material procurement, project management, project income, preliminary work preparation, engineering design and technical services, supervision and completion acceptance, other engineering activities and unforeseen activities, and the loss resource data of each minimum execution link needs to involve complex calculation of the execution loss resource items. Therefore, the selected plan loss resource prediction model is screened from the candidate plan loss resource prediction model based on the sub-plan information, and the selected plan loss resource prediction model is a model for evaluating the minimum execution link, so as to realize the associated evaluation of the sub-plan data. Specifically, the candidate plan loss resource prediction model is stored in the database module, specifically a resource calculation formula, which is used to calculate the resource loss generated by the implementation of the minimum execution link.

[0104] In some embodiments, when the target loss resource prediction data of the sub-plan data is determined to be fixed evaluation data according to the sub-plan information, it is not necessary to perform resource loss prediction on the sub-plan data by the selected plan loss resource prediction model.

[0105] In step S703 of some embodiments, the resource loss prediction is performed on the sub-plan data by the selected plan loss resource prediction model and the plurality of loss resource items, specifically, based on unknowns in the selected plan loss resource prediction model, and the resource data items include resource loss categories and resource loss values, the resource loss value corresponding to each resource loss category is substituted into the unknowns in the selected plan loss resource prediction model, so as to obtain the target loss resource prediction data of the sub-plan data, so that the calculation of the target loss resource prediction data is simple.

[0106] That is, in some embodiments, the execution loss resource items include: execution loss amount, execution correlation coefficient, execution duration and execution unit price; the target loss resource prediction data is obtained by performing loss resource prediction on the sub-scheme data through the selected scheme loss resource prediction model and the plurality of execution loss resource items, including:

[0107] The target loss resource prediction data is obtained by performing loss resource prediction on the execution loss amount, the execution correlation coefficient, the execution duration and the execution unit price through the selected scheme loss resource prediction model.

[0108] It should be noted that the selected scheme loss resource prediction model is a resource loss calculation model corresponding to each sub-scheme data, that is, a cost calculation model of the minimum execution link execution. In the minimum execution link execution process, the execution loss resource items involved are devices, manpower, materials and the like consumed in the minimum execution link execution process, so the loss resource items include execution loss amount, execution correlation coefficient, execution duration and execution unit price. The execution loss amount is the materials consumed in executing the minimum execution link, the execution correlation coefficient is the coefficient involved in the execution process, the execution duration is the time consumed in executing the minimum execution link, and the execution unit price is the unit price of the devices, manpower and materials and the like consumed.

[0109] Specifically, the sub-plan data is the minimum execution link of the decommissioning process of the nuclear facility. If the minimum execution link is the source item investigation, the target loss resource prediction data is the source item investigation fee, and the calculation of the source item investigation fee can be the fixed price of the source item investigation in the pre-set fixed price table. In addition, the correlation calculation can be used, and the selected plan loss resource prediction model in the correlation calculation is the calculation formula of the source item investigation fee, and the calculation formula of the source item investigation fee is source item investigation fee=(source item investigation working hours*manual unit price DIM*first time coefficient DIM*radiation protection coefficient DIM)+(equipment use time*second time coefficient DIM*rental unit price DIM)+(consumables*consumables unit price DIM). Wherein, the source item investigation working hours, the manual unit price DIM, the first time coefficient DIM, the radiation protection coefficient DIM, the equipment use time, the second time coefficient DIM, the rental unit price DIM, the consumables, and the consumables unit price DIM are a plurality of execution loss resources, that is, execution loss amount, execution correlation coefficient, execution time length and execution unit price. Specifically, if the minimum execution link is the source item investigation, the execution unit price is the manual unit price when the source item investigation, the first time coefficient is the coefficient of the time consumed by the manual when the source item investigation, the radiation protection coefficient is the coefficient corresponding to the use of the radiation protection equipment or protective clothing when the source item investigation, the equipment use time is the time when the equipment is needed when the source item investigation, the second time coefficient is the coefficient of the time when the equipment is used when the source item investigation, the rental unit price is the unit price of the equipment rental, the consumables are the material consumption quantity needed in the process of the source item investigation, and the consumables unit price is the unit price of the consumed materials. Wherein, the equipment, personnel and the like used in the source item investigation are obtained by simulating the three-dimensional simulation system module. Therefore, by inputting each simulation execution loss resource item into the calculation formula of the source item investigation fee, the source item investigation fee is obtained, so that the calculation operation of the source item investigation fee is simple.

[0110] If the minimum execution link is dismantling and disintegrating, the target loss resource prediction data is the dismantling and disintegrating cost, and the dismantling and disintegrating cost can be calculated by searching the fixed quotation of dismantling and disintegrating in the pre-set fixed quotation table. In addition, the associated calculation can be adopted, in which the selected scheme loss resource prediction model is the calculation formula of the dismantling and disintegrating cost, and the calculation formula of the dismantling and disintegrating cost is dismantling and disintegrating cost=(dismantling and disintegrating working hours*manual unit price DIM*first time coefficient DIM*radiation protection coefficient DIM)+(equipment use time*second time coefficient*rental unit price DIM)+(consumables*consumables unit price DIM). Wherein, the dismantling and disintegrating working hours, the manual unit price DIM, the time coefficient DIM, the radiation protection coefficient DIM, the equipment use time, the time coefficient DIM, the rental unit price DIM, the consumables and the unit price DIM are a plurality of execution loss resource items, and are obtained by simulating the equipment and personnel selected in the three-dimensional simulation system module. Specifically, if the minimum execution link is dismantling and disintegrating, the manual unit price is the manual unit price during dismantling and disintegrating, the first time coefficient is the coefficient of the time consumed by the manual during dismantling and disintegrating, the radiation protection coefficient is the coefficient corresponding to the radiation protection equipment or protective clothing used during dismantling and disintegrating, the equipment use time is the time when the equipment is needed during dismantling and disintegrating, the second time coefficient is the coefficient of the time when the equipment is used during dismantling and disintegrating, the rental unit price is the unit price of equipment rental, the consumables are the material consumption quantity needed during dismantling and disintegrating, and the consumables unit price is the unit price of the consumed materials. Compared with the non-nuclear contaminated engineering, the packaging and treatment of waste need to be considered after the nuclear contaminated engineering, so some parts have certain requirements for the dismantling volume and size, and the influence of the radiation environment operation team working time needs to be considered. The equipment use time and the rental unit price are only for the case of renting equipment, if the equipment is purchased, the related cost is included in the equipment procurement cost.

[0111] If the minimum execution link is waste disposal preparation, the target loss resource prediction data is waste disposal preparation cost, and the calculation of waste disposal preparation cost can be the fixed quotation of demolition and disassembly in the pre-set fixed quotation table. In addition, correlation calculation can be used, and the selected scheme loss resource prediction model in the correlation calculation is the calculation formula of waste disposal preparation cost, and the calculation formula of waste disposal preparation cost is waste disposal preparation cost = (disassembly operation man-hour × labor unit price DIM × first time coefficient DIM × radiation protection coefficient DIM) + (equipment use time × second time coefficient × rental unit price DIM) + [consumables (cement, additives) × consumables unit price DIM] + (number of various packaging containers × packaging unit price DIM). Among them, the disassembly operation man-hour, labor unit price DIM, time coefficient DIM, radiation protection coefficient DIM, equipment use time, time coefficient DIM, rental unit price DIM, consumables, unit price DIM, and number of various packaging containers are multiple execution loss resource items, and the processing and packaging cost of radioactive waste is closely related to the processing technology and method, so the equipment, personnel, and main material consumption (cement, additives, etc.) selected during waste disposal preparation and the task execution process are obtained through the simulation system module. Specifically, if the minimum execution link is waste disposal preparation, the labor unit price is the unit price of labor during waste disposal preparation, the first time coefficient is the coefficient of the time consumed by labor during waste disposal preparation, the radiation protection coefficient is the coefficient corresponding to the use of radiation protection equipment or protective clothing during waste disposal preparation, the equipment use time is the time required for equipment during waste disposal preparation, the second time coefficient is the coefficient of the use time of equipment during waste disposal preparation, the rental unit price is the unit price of equipment rental, the consumables are the material consumption quantity required during demolition and disassembly, specifically the consumption quantity of cement or additives, the consumables unit price is the unit price of the consumed materials, and the number of various packaging containers is the number of waste disposal packaging containers. Among them, the equipment use time and rental unit price are only for the case of renting equipment, if the equipment is purchased, the related cost is included in the equipment procurement cost.

[0112] If the minimum execution link is waste disposal, the target loss resource prediction data is waste disposal fee, and the calculation of the waste disposal fee can be through the fixed price in the pre-set fixed price table. In addition, the associated calculation can be used, and the selected scheme loss resource prediction model in the associated calculation is the calculation formula of the waste disposal fee, and the calculation formula of the waste disposal fee is waste disposal fee = (waste package quantity x disposal site receiving unit price DIM). Wherein, the waste package quantity and the disposal site receiving unit price DIM are a plurality of execution loss resource items, and the processing and packaging cost of radioactive waste is closely related to the processing technology and method, so the waste package quantity and type generated after preparation are simulated through the simulation system module, and the disposal cost calculation is carried out to obtain a plurality of execution loss resource items. Specifically, the waste package quantity is the number of waste packages generated in the waste disposal process, and the external site receiving unit price is the unit price of each waste package received by the external site. It should be noted that the disposal cost of low and medium level waste is estimated according to the waste receiving unit price of the waste disposal site; the disposal cost of high level waste is estimated according to the historical experience unit price. The disposal unit price is added when setting the basic properties of the waste container, and can be modified when the cost is counted.

[0113] If the minimum execution link is the management related cost of project management, engineering design, supervision and acceptance, etc., the cost of such minimum execution link can be given based on the pre-set fixed price. In addition, the management cost = labor input working hours x labor unit price DIM can be used for calculation.

[0114] If the minimum execution link is an unpredictable link, the target loss resource prediction data is unpredictable fee, and the calculation of the waste disposal preparation fee can be through the fixed price of the unpredictable link in the pre-set fixed price table. The fixed unpredictable fee is calculated according to 25% of the total cost of nuclear facility decommissioning in the early stage of the decommissioning project. In addition, the associated calculation can be used, and the selected scheme loss resource prediction model in the associated calculation is the calculation formula of the unpredictable fee, and the unpredictable fee is the uncertainty analysis of the unpredictable cost of the decommissioning project using Monte Carlo method, which is not described in detail in this embodiment.

[0115] In the steps S701 to S703 shown in the embodiment, the selected scheme loss resource prediction model meeting the minimum execution link is selected, so that the minimum execution link is evaluated by the selected scheme loss resource prediction model and a plurality of execution loss resource items, so that the evaluation operation of the minimum execution link is automated, without manual calculation, and the target loss resource prediction data can be efficiently output.

[0116] In step S105 of some embodiments, the target loss resource prediction data of the plurality of sub-scheme data is combined to obtain the total loss resource prediction data according to the scheme level information and the level association information. Specifically, the target loss resource prediction data is combined level by level according to the scheme level information and the level association information. For example, as shown in FIG. 4, the target loss resource prediction data corresponding to the sub-scheme data a of the second task A1 and the minimum execution link c is combined to obtain the second loss resource prediction data corresponding to the second task A1, and then the second loss resource prediction data and the target loss resource prediction data corresponding to the minimum execution link b are combined to obtain the total loss resource prediction data of the target scheme information. Therefore, the calculation operation of the total loss resource prediction data is simple, and the loss resource prediction data of different level tasks can be clearly obtained, and the influence of the minimum execution link under which level task on the loss resource prediction data can be analyzed in detail.

[0117] Referring to FIG. 8, in some embodiments, after step S105, the loss resource prediction method for decommissioning of nuclear facilities can further include but is not limited to steps S801 to S803:

[0118] In step S801, a correction coefficient is extracted from a preset correction database according to the sub-scheme category;

[0119] In step S802, the target loss resource prediction data is corrected according to the correction coefficient to obtain updated loss resource prediction data;

[0120] In step S803, the total loss resource prediction data is updated according to the updated loss resource prediction data to obtain updated resource prediction data of the target scheme information.

[0121] It should be noted that the three-dimensional simulation system module may have errors when outputting a plurality of execution loss resource items during simulation, and it is difficult to accurately represent each resource loss of the sub-scheme data. Therefore, after the evaluation of the target scheme information is completed, the total loss resource prediction data needs to be corrected to obtain more accurate total loss resource prediction data.

[0122] In step S801 of some embodiments, the correction database is arranged in the database module, and the correction database stores a plurality of correction coefficients, and the correction coefficients are correction coefficients of a plurality of resource items involved in the sub-scheme data, and are stored in the correction database according to the sub-scheme category. Therefore, the correction coefficient is extracted from the correction database as the correction coefficient matched with the sub-scheme category, so that the correction coefficient is easy to extract.

[0123] In step S802 of some embodiments, after the correction coefficient is extracted, the correction coefficient can be used to correct the target loss resource prediction data of the sub-scheme data to obtain more accurate link evaluation data as the updated loss resource prediction data. Specifically, if the correction coefficient is a time correction coefficient, and the time correction coefficient represents the proportional coefficient between the actual time consumed by the sub-scheme data and the simulation time obtained by the three-dimensional simulation system module, when calculating the target loss resource prediction data, the simulation time is corrected according to the time correction coefficient to obtain a corrected time, and the updated loss resource prediction data is calculated according to the corrected time. It should be noted that if the sub-scheme data involves multiple resource items, multiple correction coefficients can be obtained to correct the target loss resource prediction data one by one. For example, if the sub-scheme data is a source item survey, the correction coefficient can be a time correction coefficient and a radiation protection correction coefficient, and the target loss resource prediction data of the source item survey is corrected according to the time correction coefficient and the radiation protection correction coefficient.

[0124] In step S803 of some embodiments, when the target loss resource prediction data of the sub-scheme data is updated, the total loss resource prediction data can be further corrected based on the updated loss resource prediction data to obtain more accurate updated resource prediction data, so that the resource loss prediction of the target scheme information is more accurate.

[0125] In steps S801 to S803 of the embodiment, by finding the correction coefficient associated with the sub-scheme data, the target loss resource prediction data of the sub-scheme data is corrected according to the correction coefficient to obtain more accurate updated loss resource prediction data, so as to realize more accurate resource loss prediction of the decommissioning of the nuclear facility.

[0126] Referring to FIG. 9, in some embodiments, after step S105, the loss resource prediction method for decommissioning of the nuclear facility can further include but is not limited to steps S901 to S902:

[0127] Step S901, comparing the total loss resource prediction data with the preset expected loss resource data to obtain an evaluation comparison result;

[0128] Step S902, if the evaluation comparison result is that the total loss resource prediction data is greater than the expected loss resource data, adjusting the target scheme information according to the total loss resource prediction data to obtain updated scheme data.

[0129] In step S901 of some embodiments, the expected loss resource data is the loss resource data preset for the user as the expected loss resource of the decommissioning of the nuclear facility. Therefore, by comparing the total loss resource prediction data and the preset expected loss resource data, an evaluation comparison result is obtained. It should be noted that if the evaluation comparison result is that the total loss resource prediction data is less than or equal to the expected loss resource data, it is determined that the implementation of the decommissioning scheme of the nuclear facility meets the preset expected loss resource, and if the evaluation comparison result is that the total loss resource prediction data is greater than the expected loss resource data, it indicates that the implementation of the decommissioning scheme of the nuclear facility will exceed the preset expected loss resource. Specifically, if the total loss resource prediction data is the decommissioning prediction cost of the decommissioning of the nuclear facility, and the expected loss resource data is the preset decommissioning preparation cost, if the decommissioning prediction cost exceeds the decommissioning preparation cost, it indicates that it is difficult to implement the decommissioning scheme of the nuclear facility.

[0130] In step S902 of some embodiments, when the evaluation comparison result is that the total loss resource prediction data is greater than the expected loss resource data, it indicates that it is difficult to implement the decommissioning scheme of the nuclear facility, and the decommissioning scheme of the nuclear facility needs to be adjusted to obtain an updated decommissioning scheme of the nuclear facility. It should be noted that in the process of adjusting the target scheme information, that is, adjusting the target scheme information according to the total loss resource prediction data, that is, adjusting the decommissioning scheme of the nuclear facility. Among them, the adjustment process will re-predict the loss resource of the adjusted decommissioning scheme of the nuclear facility until the updated loss resource data is less than or equal to the expected loss resource data, and then the adjusted decommissioning scheme of the nuclear facility is regarded as the updated decommissioning scheme of the nuclear facility.

[0131] Specifically, the embodiment adjusts the target scheme information based on the total loss resource prediction data, that is, adjusts the specific operation steps of the decommissioning scheme of the nuclear facility, so as to optimize the decommissioning operation of the decommissioning scheme of the nuclear facility, and save the resource loss of the decommissioning operation of the nuclear facility.

[0132] In steps S901 to S902 shown in the embodiment, by comparing the total loss resource prediction data and the expected loss resource data, the difficulty of implementing the decommissioning scheme of the nuclear facility is determined, and when the total loss resource prediction data is greater than the expected loss resource data, the target scheme information is adjusted according to the total loss resource prediction data to obtain an updated decommissioning scheme of the nuclear facility that can be implemented, so that the decommissioning operation of the nuclear facility can be realized.

[0133] In the embodiment of the present application, as shown in FIG. 4, the cost estimation of the target scheme information is taken as an example. The scheme editing module is used to classify the scheme of decommissioning the nuclear facility to obtain a plurality of minimum execution links. When the cost estimation of each minimum execution link is needed, the relevant execution parameters are extracted from the database module to obtain the target scheme execution associated parameters. Specifically, the target scheme execution associated parameters are the data of tools, equipment, materials, manpower and the like involved in the execution of the sub-scheme data. Then, the three-dimensional simulation system module is used to simulate each minimum execution link based on the target scheme execution associated parameters to output the resource items consumed in the implementation process of the minimum execution link as the execution loss resource items. The loss resource prediction module is used to perform detailed cost estimation of each minimum execution link based on the plurality of execution loss resource items to output the cost estimation value of each sub-scheme data. Finally, the plurality of cost estimation values are calculated step by step according to the level information of the minimum execution links in the scheme editing module to obtain the decommissioning cost of the scheme of decommissioning the nuclear facility, so that the decommissioning cost of the scheme of decommissioning the nuclear facility is calculated accurately and the manual input of the resource loss of each resource item is not needed, and only simulation is needed to realize, which saves a lot of manpower.

[0134] Referring to FIG. 10, the embodiment of the present application further provides a loss resource prediction device for decommissioning a nuclear facility, which can realize the loss resource prediction method for decommissioning a nuclear facility. The device comprises:

[0135] A scheme acquisition module 1001 is configured to acquire target scheme information for decommissioning a nuclear facility.

[0136] A decomposition module 1002 is configured to perform decomposition processing on the target scheme information to obtain a plurality of sub-scheme data, scheme level information and level association information of each sub-scheme data. The sub-scheme data is used to represent a minimum execution link for decommissioning a nuclear facility.

[0137] A resource item acquisition module 1003 is configured to acquire loss resource items for executing the sub-scheme data to obtain a plurality of execution loss resource items.

[0138] A loss resource prediction module 1004 is configured to perform loss resource prediction on each sub-scheme data based on the plurality of execution loss resource items to obtain target loss resource prediction data.

[0139] A loss resource combination module 1005 is configured to combine the target loss resource prediction data of the plurality of sub-scheme data according to the scheme level information and the level association information to obtain total loss resource prediction data of the target scheme information.

[0140] The specific implementation of the loss resource prediction device for decommissioning a nuclear facility is basically the same as the specific embodiments of the loss resource prediction method for decommissioning a nuclear facility, which will not be described here.

[0141] The embodiment of the present application further provides a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor realizes the above-mentioned method for predicting the loss resource of nuclear facility decommissioning when executing the computer program. The computer device can be any intelligent terminal such as a tablet computer, an on-board computer and the like.

[0142] Referring to FIG. 11, the hardware structure of the computer device of another embodiment is shown, which comprises:

[0143] The processor 1101 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit) or one or more integrated circuits, and is used to execute related programs to realize the technical solutions provided by the embodiments of the present application.

[0144] The memory 1102 can be implemented in the form of a ROM (Read-Only Memory), a static storage device, a dynamic storage device or a RAM (Random Access Memory). The memory 1102 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present application are implemented by software or firmware, the related program codes are stored in the memory 1102 and called and executed by the processor 1101 to realize the method for predicting the loss resource of nuclear facility decommissioning.

[0145] The input / output interface 1103 is used to realize information input and output.

[0146] The communication interface 1104 is used to realize the communication interaction between the device and other devices, which can realize communication through a wired manner (for example, a USB, a network cable and the like) or a wireless manner (for example, a mobile network, WIFI, Bluetooth and the like).

[0147] The bus 1105 is used to transmit information between various components (for example, the processor 1101, the memory 1102, the input / output interface 1103 and the communication interface 1104) of the device.

[0148] The processor 1101, the memory 1102, the input / output interface 1103 and the communication interface 1104 are connected to each other through the bus 1105 to realize the communication connection between them in the device.

[0149] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the loss resource prediction method for decommissioning of a nuclear facility.

[0150] The memory, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0151] The loss resource prediction method and device for decommissioning of a nuclear facility, the equipment and the storage medium provided by the embodiment of the present application are used to decompose target scheme information into sub-scheme data, automatically determine which resource consumptions are generated in the execution process of each sub-scheme data as execution loss resource items, make loss resource prediction on each sub-scheme data according to a plurality of execution loss resource items to obtain target loss resource prediction data, and combine a plurality of target loss resource prediction data based on scheme level information and level association information to obtain total loss resource prediction data of the target scheme information. Therefore, by dividing the scheme for decommissioning of a nuclear facility into a plurality of minimum execution links, then calculating resource items consumed in the implementation of each minimum execution link, and then predicting loss resources generated in the implementation of the minimum execution link according to a plurality of loss resource data, and finally summarizing the loss resources of a plurality of minimum execution links as total loss resources of the decommissioning of the nuclear facility, the loss resource prediction operation for decommissioning of a nuclear facility is automated and accurate.

[0152] The embodiments described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0153] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than those shown in the figures, or combine certain steps, or different steps.

[0154] The apparatus embodiments described above are merely exemplary, and the units described as separate units can or can not be physically separate, i.e., can be located in one place, or can be distributed over multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purposes of the embodiments.

[0155] Those skilled in the art can understand that all or some of the steps in the method disclosed above, the functional modules / units in the system and the device can be implemented as software, firmware, hardware and appropriate combinations thereof.

[0156] The terms "first", "second", "third", "fourth" and the like in the description of the application and in the claims of the foregoing drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of the terms so construed can be interchanged, such that the embodiments of the application described herein can be carried out in other than the order discussed herein without departing from the scope of the application. Further, the terms "comprise" and "comprising" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, product or apparatus that comprises a list of steps or units does not necessarily comprise only those steps or units but can include other not expressly listed steps or units.

[0157] It should be understood that in the present application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the relationship between associated objects, which means that there can be three relationships, for example, "A and / or B" can mean that there are three cases: only A, only B, and A and B at the same time, where A and B can be singular or plural. The character " / " generally represents that the associated objects before and after are in an "or" relationship. "At least one of the following" or the like means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can mean a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0158] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. For example, the apparatus embodiments described above are merely illustrative, for example, the division of the above units is merely a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some interfaces, apparatuses or units, and can be electrical, mechanical or other forms.

[0159] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they can be located in one place or distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0160] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0161] If the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part of the prior art that makes a contribution or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method of each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0162] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, which are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A method for predicting resource depletion during nuclear facility decommissioning, characterized in that, The method comprises: acquiring target scheme information of decommissioning of a nuclear facility; decomposing the target scheme information to obtain a plurality of sub-scheme data, scheme level information of each of the sub-scheme data, and level association information; wherein the sub-scheme data is used to represent a minimum execution link of decommissioning of the nuclear facility; acquiring execution loss resource items of the sub-scheme data to obtain a plurality of execution loss resource items; predicting loss resources of each of the sub-scheme data based on the plurality of execution loss resource items to obtain target loss resource prediction data; combining the target loss resource prediction data of the plurality of sub-scheme data according to the scheme level information and the level association information to obtain total loss resource prediction data of the target scheme information.

2. The method of claim 1, wherein, The decomposing the target scheme information to obtain a plurality of sub-scheme data, scheme level information of each of the sub-scheme data, and level association information comprises: splitting the target scheme information to obtain a plurality of sub-scheme data; acquiring hierarchical relationship information between the plurality of sub-scheme data; determining the level association information of each of the sub-scheme data based on the hierarchical relationship information; acquiring a category of each of the sub-scheme data to obtain sub-scheme categories; classifying the sub-scheme data according to the sub-scheme categories and the level association information to obtain the scheme level information of each of the sub-scheme data.

3. The method of claim 1, wherein, The acquiring execution loss resource items of the sub-scheme data to obtain a plurality of execution loss resource items comprises: acquiring a sub-scheme category of the sub-scheme data, screening target scheme execution association parameters from preset candidate scheme execution association parameters based on the sub-scheme category, and simulating the sub-scheme data according to the target scheme execution association parameters to obtain a plurality of execution loss resource items; wherein the target scheme execution association parameters are used as parameters for simulating the minimum execution link of decommissioning of the nuclear facility; or, generating scheme association parameter prompt information based on the target scheme execution association parameters, receiving parameter loss resource items fed back to the scheme association parameter prompt information, and generating a plurality of execution loss resource items based on the target scheme execution association parameters and the parameter loss resource items.

4. The method of claim 1, wherein, The predicting loss resources of each of the sub-scheme data based on the plurality of execution loss resource items to obtain target loss resource prediction data comprises: acquiring sub-scheme information of the sub-scheme data; screening a selected scheme loss resource prediction model from preset candidate scheme loss resource prediction models according to the sub-scheme information; predicting loss resources of the sub-scheme data by the selected scheme loss resource prediction model and a plurality of execution loss resource items to obtain the target loss resource prediction data.

5. The method of claim 4, wherein, The execution loss resource items comprise execution loss amount, execution correlation coefficient, execution duration, and execution unit price; and the predicting loss resources of the sub-scheme data by the selected scheme loss resource prediction model and a plurality of execution loss resource items to obtain the target loss resource prediction data comprises: The execution loss resource prediction model is used to predict the execution loss amount, the execution correlation coefficient, the execution time length and the execution unit price, so as to obtain the target loss resource prediction data.

6. The method of claim 2, wherein, After the target loss resource prediction data of each sub-scheme data is obtained by predicting the loss resource based on the multiple execution loss resource items, the method further comprises: extracting a correction coefficient from a preset correction database according to the sub-scheme category; correcting the target loss resource prediction data according to the correction coefficient, so as to obtain updated loss resource prediction data; updating the total loss resource prediction data according to the updated loss resource prediction data, so as to obtain the updated resource prediction data of the target scheme information.

7. The method according to any one of claims 1 to 6, characterized in that, After the total loss resource prediction data of the target scheme information is obtained by combining the target loss resource prediction data of the multiple sub-scheme data according to the scheme level information and the level association information, the method comprises: comparing the total loss resource prediction data with preset expected loss resource data, so as to obtain an evaluation comparison result; if the evaluation comparison result is that the total loss resource prediction data is greater than the expected loss resource data, adjusting the target scheme information according to the total loss resource prediction data, so as to obtain updated scheme data.

8. A device for predicting depleted resources of decommissioning a nuclear facility, characterized by, The device comprises: a scheme acquisition module configured to acquire target scheme information of nuclear facility decommissioning; a decomposition module configured to perform decomposition processing on the target scheme information, so as to obtain multiple sub-scheme data, scheme level information and level association information of each sub-scheme data; wherein the sub-scheme data is used to represent the minimum execution link of nuclear facility decommissioning; a resource item acquisition module configured to acquire loss resource items for executing the sub-scheme data, so as to obtain multiple execution loss resource items; a loss resource prediction module configured to predict the loss resource of each sub-scheme data based on the multiple execution loss resource items, so as to obtain target loss resource prediction data; a loss resource combination module configured to combine the target loss resource prediction data of the multiple sub-scheme data according to the scheme level information and the level association information, so as to obtain total loss resource prediction data of the target scheme information.

9. A computer device, comprising: The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the nuclear facility decommissioning loss resource prediction method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to implement the nuclear facility decommissioning loss resource prediction method of any one of claims 1 to 7.

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