30 results about "Nuclear data" patented technology

The invention discloses a machine learning-based kernel data verification method, which comprises the following steps of: firstly, obtaining simulated effective proliferation factors and actually measured effective proliferation factors of a plurality of kernel experiment references, and calculating to obtain a difference value; 2, calculating nuclear data sensitivity characteristics of each experimental reference, wherein the nuclear data sensitivity characteristics comprise a sensitivity coefficient for a nuclear reaction cross section and experimental metadata; thirdly, constructing a machine learning model based on a random forest, and performing training by taking the kernel data sensitivity characteristics as input and the effective multiplication factor difference value as output; and finally, carrying out model feature importance analysis, and identifying kernel data sensitivity features which have significant influence on effective proliferation factor differences. The nuclear data verification method based on machine learning is established for the first time, and is used for identifying potential defects in nuclear reaction data or deviation of experimental references.

The invention discloses an electron beam bunch superposition method and device, and the beam bunch energy of the head part and the tail part of an electron beam bunch is different by adopting a beam energy absorption effect. And then a plurality of alpha magnets are utilized, so that the movement path of the high-energy beam bunches at the head of the beam bunch string is long, the movement path of the low-energy beam bunches at the tail of the beam bunch string is short, and longitudinal superposition and compression of the beam bunch string are achieved. And the alpha magnet can simultaneously realize an achromatic function, so that the transmission envelope after the beam bunch is compressed and superposed is not greatly increased. And the obtained shorter pulse beam can be used for scientific research application such as nuclear data measurement.

The invention discloses a fission yield experiment data screening method, and relates to the technical field of nuclear data evaluation.The method comprises the steps that S1, fission yield experiment data are obtained from an EXOR database, and the experiment data are grouped; s2, fitting each group of fission yield experimental data by adopting a Zp model, and determining model parameters; the fission yield is calculated according to the determined model parameters, so that a yield calculation value is obtained; s3, calculating the deviation between the fission yield experiment data and the fission yield calculation value obtained in the step S2; and S4, screening the experimental data according to the deviation obtained in the step S3. According to the method provided by the invention, the evaluation efficiency can be effectively improved, the research period is shortened, and technical support is provided for further establishing an experimental database.

This invention discloses a monolithic, high-performance integrated nuclear and chemical gas detector, belonging to the field of nuclear and chemical detection technology. The invention includes a nuclear radiation detection module, a chemical gas detection module, and a central control and processing module. The nuclear radiation detection module and the chemical gas detection module are integrated and both connected to the central control and processing module. The nuclear radiation detection module includes a sampling module and a nuclear data output module, while the chemical gas detection module includes a chemical gas sampling module, a gas analysis module, and a gas data output module. This invention achieves integrated detection of both nuclear radiation and chemical gases. Through modular design and central control coordination, it enables simultaneous acquisition and analysis of nuclear radiation and chemical gases, achieving efficient and integrated monitoring of nuclear and chemical substances. Simultaneously, the integrated detection modules significantly reduce size and power consumption, making it more suitable for portable applications and improving the efficiency and comprehensiveness of early warning in hazardous scenarios.

The present invention discloses a method for rapidly calculating the dose in boron neutron capture therapy. First, a nuclear database suitable for the human body and based on a deterministic method is prepared. Then, a corresponding model is established according to human body model parameters and treatment plan design parameters. Finally, a highly efficient deterministic program is used to perform neutron-photon transport calculations on the established model to obtain the dose distribution results, thereby realizing rapid calculation of the dose in boron neutron capture therapy.

The application discloses a kind of fast preparation method and device of xenon or krypton gas source for nuclear data measurement, to solve the problem that prior art cannot carry out fast enrichment purification preparation source to low concentration xenon (Xe) or krypton (Kr) in component complex raw gas.Its method specifically includes: step 1, at 10-30 ℃ temperature, using pretreatment adsorption column to pretreat raw gas, remove H2O, part CO2 and organic gas in raw gas;Step 2, using enrichment purification adsorption column to adsorb and intercept Xe or Kr in pretreated gas, adsorption interception time is determined according to the sample amount of raw gas;Step 3, using heating and carrier gas purging combination desorption separation method to purify Xe or Kr adsorbed and intercepted on the enrichment purification adsorption column;Step 4, enrichment purification adsorption column is pumped to negative pressure 5-15kPa, and it is heated to 160-200 ℃, and temperature is kept for a predetermined period of time, generally 5-15min, so that Xe or Kr is desorbed from the enrichment purification adsorption column, and Xe or Kr gas source is obtained.

The invention provides a Gaussian-Seidel-based MMPA burnup equation set accelerated solving method, belongs to the field of reactor physical calculation, and aims to solve the technical problems of high solving complexity, long calculation time and low efficiency of an existing MMPA burnup equation set. The method comprises the following steps: firstly, based on current reactor burnup working condition parameters, accurately constructing a burnup matrix under the current burnup condition through nuclear data processing and burnup chain modeling; the method comprises the steps that firstly, an MMPA burnup equation is constructed, an MMPA burnup equation set suitable for Gaussian Seidel iteration solution is obtained through derivation, finally, an iteration convergence criterion is set, and the Gaussian Seidel iteration method is adopted for conducting iteration solution on the MMPA burnup equation set till the convergence condition is met; and finally, outputting a nuclide density distribution result at a corresponding moment. According to the method, the calculation efficiency can be greatly improved on the premise that the calculation precision is guaranteed, and the problems that a traditional MMPA burnup equation is high in solving complexity and long in calculation time consumption are solved.

The application discloses a multi-nucleus neutron nuclear reaction data verification method and device based on deep learning, comprising the following steps: determining a target nucleus to be evaluated, and obtaining multi-dimensional physical characteristic data of the target nucleus from a preset evaluation nuclear database and an experimental database; performing physical perception preprocessing and feature splicing on the multi-dimensional physical characteristic data to obtain a physical characteristic vector of the target nucleus; constructing and training a nuclear data correction model with uncertainty quantification capability; determining evaluation cross-section data and uncertainty data of the target nucleus according to the nuclear data correction model and the physical characteristic vector, and encapsulating the evaluation data of the target nucleus according to the evaluation cross-section data and the uncertainty data; verifying the evaluation data based on particle transport simulation, and optimizing the evaluation nuclear database according to the verified evaluation data. The application improves the efficiency and reliability of neutron nuclear reaction data evaluation and verification, and can be applied to the technical field of data processing.

The invention relates to the technical field of nuclear reactor core physics, in particular to a similarity evaluation method based on mutual information. The invention discloses a similarity evaluation method based on mutual information and a random sampling method. Carrying out nuclear data sampling based on the multi-group covariance matrix, carrying out neutronics calculation, and carrying out comprehensive evaluation by utilizing mutual information coefficients between different sections of nuclear data and output responses and mutual information coefficients of same-type responses of two reactor systems so as to determine a similarity result. The method provided by the invention can evaluate the similarity between the application design system and the reference experiment system by taking any output response of the nuclear reactor as a similarity judgment basis. The method can effectively solve the ubiquitous problem of insufficient experimental quantity conforming to the traditional similarity evaluation standard in the novel reactor model confirmation work, and is beneficial to further improving the precision of the model confirmation work so as to accelerate the engineering application process of designing the reactor type.

The invention discloses a method for making a slow luminescence sub-ACE format database. The method comprises the following steps: firstly, calculating a slow luminescence sub-generation section based on a fission yield sub-library and a decay sub-library of an evaluation kernel database; the decay photon energy spectrum is processed into an equal probability energy bond form, so that slow-emission photon energy distribution can be obtained; in order to ensure that the average energy of the slow luminophors obtained through calculation is the same as the average energy of the slow luminophors given in the evaluation kernel database, a slow luminophor generation cross section is corrected; and finally, storing the slow luminescence quantum generation cross section and slow luminescence quantum energy angle distribution information in an ACE format database. The invention provides a manufacturing method of a slow luminescence sub-ACE format database. The slow luminescence sub-ACE format database is considered in a Monte Carlo program, and the method has the advantages of being high in calculation precision and high in calculation speed.

The invention discloses a critical parameter prediction method, a readable storage medium and a device, and belongs to the technical field of nuclear systems, and the prediction method comprises the steps: determining a to-be-predicted new nuclear system and a calculated value of an existing critical experiment; calculating sensitivity vectors of the new nuclear system and the critical experiments to the nuclear data; on the basis of the calculated value and the sensitivity vector, in combination with the relationship between the experimental value of the existing experiment, the experimental uncertainty and the critical experimental coefficient, constructing a calculation formula of the critical parameter predicted value and the predicted uncertainty of the new nuclear system; solving a coefficient of a critical experiment enabling the uncertainty of the prediction parameters to be minimum; and substituting the coefficient into the two calculation formulas to obtain a predicted value and the uncertainty thereof. The method is stored in the readable storage medium. The device comprises a terminal program for executing the steps of the method. According to the method, the information of a plurality of critical experiments can be effectively integrated, the critical parameters can be more reliably and accurately predicted under the condition of lack of very similar critical experiments, and the uncertainty of the prediction parameters can be more effectively compressed.

The present application relates to a kind of neutronics calculation uncertainty quantification method, system, equipment and medium, belong to neutronics calculation field.The method includes: based on the covariance information in nuclear data evaluation library making nuclear data covariance library;Using direct numerical perturbation method calculates the sensitivity coefficient of nuclear reaction cross section to spallation neutron source;According to the nuclear data covariance library and the sensitivity coefficient, the uncertainty of spallation neutron source is calculated;According to the nuclear data covariance library and the uncertainty of spallation neutron source, using Latin hypercube sampling method is sampled to generate calculation sample;Based on the calculation sample, the ADS neutronics calculation result is obtained by executing ADS neutronics calculation;The uncertainty of the ADS neutronics calculation result is determined by performing mathematical statistics analysis to the ADS neutronics calculation result.The present application improves the calculation efficiency and calculation accuracy of the uncertainty of ADS neutronics calculation.

The embodiment of the invention relates to the field of data processing methods particularly suitable for matrix or vector calculation of specific functions, in particular to a method for determining a subcritical limit value of a target nuclear fuel cycle process scene. According to the method for determining the subcritical limit value of the target nuclear fuel cycle process scene provided by the embodiment of the invention, the reference experiment is screened according to the target nuclear fuel cycle process scene, so that the selected reference experiment data meeting the predetermined requirements are obtained, and the quality of the reference experiment data for verification is improved; correcting kernel data adopted by theoretical calculation of the selected reference experiment, so that the theoretical calculation is closer to a real physical scene; according to the corrected nuclear data, the offset and uncertainty of the calculation tool are determined, the uncertainty level caused by the calculation tool is reduced, unnecessary conservative assumptions are reduced, under the same safety level, the limiting conditions of the nuclear fuel circulation process are reduced, and the processing capacity of nuclear materials in nuclear fuel circulation process equipment is improved.

The application discloses a kind of production methods of delayed photon ACE format database, first, the fission yield sublibrary and decay sublibrary of evaluation nuclear database are used to calculate the delayed photon production cross section;The delayed photon energy distribution can be obtained by processing the decay photon spectrum into the form of equal-probability energy band;To ensure that the average energy of the delayed photon obtained by calculation is the same as the average energy of the delayed photon given in the evaluation nuclear database, the delayed photon production cross section is corrected;Finally, the delayed photon production cross section, the delayed photon energy angle distribution information is stored in the ACE format database.The application proposes a kind of production method of delayed photon ACE format database, and the method has the advantages of high calculation accuracy and fast calculation speed in Monte Carlo program.

The invention relates to a separation device and method for fission products zirconium, niobium, molybdenum, antimony and silver, belongs to the technical field of fission product separation, and solves the technical problems that fission product separation cannot be synchronized and nuclear data test precision is low. The separation device comprises a liquid storage tank unit, a color layer separation unit, a waste liquid collector, a product collection unit, a valve and a delivery pump. Liquid in the liquid storage tank unit enters the color layer separation unit through the conveying pump, liquid flowing out of the color layer separation unit enters the product collection unit or the waste liquid collector, and the color layer separation unit is used for fission product separation. The separation method comprises the steps of preparation before separation, zirconium-niobium-molybdenum-antimony-silver adsorption, washing, zirconium separation and purification, molybdenum-niobium separation and purification, antimony separation and purification, silver separation and purification and zirconium-niobium-molybdenum-antimony-silver desorption. The device and the method are used for fission product synchronous separation and nuclear data test and analysis.

The present invention discloses a method for measuring ( n , α ) reaction angle differential cross section method, belongs to the field of nuclear data measurement technology. The present invention uses a screen ionization chamber and a gas sample to measure the anode pulse rise time and anode amplitude, and obtains the projection length of the nuclear reaction event track parallel to the neutron incident direction through the anode pulse rise time. One projection length corresponds to two α The particle emission angle; the difference in anode amplitude can distinguish the same projection length but α The events with different particle emission angles are divided into different categories according to the two-dimensional spectrum of anode amplitude-anode pulse rise time through the V-shaped event area on it. α The number of events is obtained by measuring the particle emission angle, and the differential cross section of the reaction angle to be measured can be obtained by combining the number of reaction nuclei to be measured and the corresponding neutron flux. The present invention can be used to measure ( n , α ) reaction, which has the characteristics of a large number of sample nuclei to be tested, high detection efficiency, and is not restricted by the detector placement angle.

The invention discloses a kernel data multi-modal knowledge graph construction method, and relates to the technical field of knowledge graphs. The kernel data multi-modal knowledge graph construction method comprises the following steps: S1, acquiring multi-modal data in the field of kernel science and technology, wherein the multi-modal data comprises text modal data and image modal data; s2, constructing a multi-modal knowledge graph ontology of the kernel data; s3, integrating target detection, relation prediction and character recognition technologies for the image modal data to realize automatic extraction of entities, relations and attributes; s4, extracting structured knowledge from the text modal data by adopting a rule-based method; and S5, realizing fusion of the image knowledge and the text knowledge through entity alignment, and storing a fusion result into a graph database to complete construction of the kernel data multi-modal knowledge graph. By adopting the multi-modal knowledge graph construction method for the kernel data, deep fusion and knowledge mining of the kernel data can be realized, and data support is provided for multi-modal question answering, retrieval and recommendation application of the kernel data.

The application discloses a method for manufacturing a photonuclear database for improving the calculation precision of a reactor photonuclear, and the method comprises the following steps: obtaining photonuclear data of a first plurality of nuclides and performing format conversion to obtain photonuclear data in a first data format; performing calculation on the photonuclear data of a second plurality of nuclides in the first plurality of nuclides, and comparing the photonuclear data of the second plurality of nuclides according to the photonuclear calculation results; obtaining photonuclear data in a second data format according to the comparison results of the photonuclear data and the photonuclear data in the first data format, obtaining a first photonuclear database according to the photonuclear data in the first data format and an index file, and obtaining a second photonuclear database according to the photonuclear data in the second data format; and performing reactor data test on the first and second photonuclear databases respectively to obtain corresponding database test results. Through iterative feedback, the application obtains a continuous-energy photonuclear database with high precision and high reliability, and can significantly improve the calculation precision and efficiency of the neutron-photon coupling transport in a reactor.

The invention discloses a method for measuring a (n, alpha) reaction angle differential cross section, and belongs to the technical field of nuclear data measurement. Anode pulse rising time and anode amplitude are obtained through measurement of a screen grid ionization chamber and a gas sample, the projection length, parallel to the neutron incidence direction, of a nuclear reaction event track is obtained through the anode pulse rising time, and one projection length corresponds to two alpha particle emergence angles; the events with the same projection length and different alpha particle emergent angles can be distinguished according to different anode amplitudes, so that according to the anode amplitude-anode pulse rise time two-dimensional spectrum, the events with different alpha particle emergent angles are divided through the V-shaped event area on the two-dimensional spectrum to obtain the number of events; and the to-be-measured reaction angle differential cross section can be obtained by combining the to-be-measured reaction nuclear number and the corresponding neutron flux. The device can be used for measuring the angle differential cross section of (n, alpha) reaction, and has the characteristics that the number of nucleuses of a sample to be measured is large, the detection efficiency is high, and the device is not limited by the placement angle of a detector.

The application discloses a kind of multi-parameter nuclear data adjustment methods of fast reactor, first, for the multiple critical measurement experiments of existing zero-power experimental device, control rod value measurement experiment and cavitation reactivity measurement experiment, the χ coefficient and IS factor of all experiments are calculated respectively, and with a certain experiment as benchmark experiment, the similarity coefficient of all experiments and benchmark experiment is calculated, according to the screening criterion corresponding to similarity coefficient, χ coefficient and IS factor, select the experiment that can be used for nuclear data adjustment, second, using the measurement results of the experiment screened out, including effective neutron multiplication factor, control rod value and cavitation reactivity, based on Bayes theorem, nuclear data is adjusted, finally, three judgment criteria are used to screen the adjusted nuclear data, and the unreasonable nuclear data is discarded or limited range, finally, the adjusted nuclear data is obtained.The more accurate nuclear data is obtained, so as to improve the core physical calculation precision and confidence of fast reactor.

The embodiment of the invention relates to the field of nuclear reactors, in particular to a method for determining a subcritical limit value of a target nuclear fuel cycle process scene. According to the method, kernel data is adopted to correct a selected reference experiment, so that the uncertainty of kernel data introduction is reduced; different subcritical limit values are respectively determined according to the corrected nuclear data, and the subcritical limit value of the target nuclear fuel cycle process scene is determined in combination with the different subcritical limit values, so that the correlation degree between the selected reference experiment and the target nuclear fuel cycle process scene is enhanced, and the uncertainty introduced by extrapolation of the selected reference experiment data is reduced. By combining the two technical means, the uncertainty generated by factors such as calculation, experiments and extrapolation considered in the operation process of the nuclear fuel circulation process is reduced, unnecessary conservative assumptions are reduced, under the same safety level, the limiting conditions of the nuclear fuel circulation process are reduced, and the safety of the nuclear fuel circulation process is improved. And the processing capacity of nuclear materials in nuclear fuel circulation process equipment is improved.

The invention discloses a multi-nuclide neutron nuclear reaction data verification method and device based on deep learning, and the method comprises the steps: determining a to-be-evaluated target nuclide, and obtaining the multi-dimensional physical feature data of the target nuclide from a preset evaluation nuclear database and an experiment database; performing physical perception preprocessing and feature splicing on the multi-dimensional physical feature data to obtain a physical feature vector of the target nuclide; constructing and training a kernel data correction model with uncertainty quantification capability; determining evaluation cross section data and uncertainty data of the target nuclide according to the kernel data correction model and the physical feature vector, and packaging according to the evaluation cross section data and the uncertainty data to obtain evaluation data of the target nuclide; and verifying the evaluation data based on particle transport simulation, and optimizing the evaluation kernel database according to the verified evaluation data. The efficiency and reliability of neutron nuclear reaction data evaluation and verification are improved, and the method can be applied to the technical field of data processing.

The invention relates to a device and a method for measuring absolute yields of long-range alpha particles and tritium in fission nuclear triple splitting, belongs to the technical field of nuclear data measurement, and solves the technical problems of low measurement efficiency and low precision of light charged particles in fission nuclear triple splitting. The measuring device comprises a screen-grid ionization chamber, a cathode, a grid electrode, an anode, a shielding electrode, an aluminum film, a four-component alpha source for scale, and a data acquisition and processing system. The aluminum film covers the sample well containing the fission target material and is used for shielding part of bipartite fission fragments and decay alpha particles. The measurement method comprises the following steps: measuring the dichotomous fission fragments by using the screen-grid ionization chamber under the conditions of no aluminum film and low-pressure working gas, simulating the measurement process of the dichotomous fission fragments, measuring the light charged particles in the three-split transformation by using the screen-grid ionization chamber under the conditions of aluminum film and high-pressure working gas, simulating the measurement process of the light charged particles in the three-split transformation, and simulating the measurement process of the light charged particles in the three-split transformation. And obtaining the absolute yield of long-range alpha particles in the tri-split transformer, and obtaining the absolute yield of tritium in the tri-split transformer.

The invention relates to a nuclear data critical reference test automatic trend analysis method and system, a storage medium and equipment, and the method comprises the steps: (1) selecting critical reference experiment feature information and the nuclear reaction section sensitivity of a critical reference experiment effective proliferation factor keff to each nuclide-reaction channel, and carrying out the screening of frequent item sets through association rule analysis; (2) establishing a linear regression model and analyzing by taking the nuclear reaction section sensitivity of the corresponding nuclide-reaction channel under each screened frequent item set condition as an independent variable and the C / E value of keff as a dependent variable, judging whether the C / E value of keff meets a trend analysis requirement or not, and screening out all effective data combinations meeting the requirement; and (3) drawing all the obtained effective data results into a chart and outputting the chart. According to the method, the critical keff automatic trend analysis based on nuclide-reaction channel sensitivity is realized, and the efficiency bottleneck of large-scale critical reference analysis is broken through.

The present application relates to a kind of statistical and physical combination (n, alpha) reaction cross section experimental data evaluation method, belong to nuclear data evaluation technical field, the method includes the following steps: investigation and collection existing (n, alpha) reaction cross section experimental data, and collect the relevant information of experimental data, determine the experimental method of experimental data, experimental purpose, detector information, to experimental data is mathematically and physically analyzed, understand the distribution law of experimental data, find implicit variable;According to implicit variable, experimental data is classified and analyzed to obtain experimental data evaluation result;And with the experimental data after evaluation as the basis, obtain recommended excitation function by mathematical fitting etc..The method of the present application starts from two aspects of mathematics and physics, finds the "implicit variable" that influences the accuracy of data in Simpson paradox, from the angle of experimental data evaluation, can effectively avoid the occurrence of PPP problem, effectively improve the accuracy of evaluation data and the efficiency of evaluation work.

The present invention relates to a nuclear data measurement device, in particular to a gamma ray angle correlation measurement device and a measurement method based on the device, which solves the problems of time-consuming and labor-intensive measurement, inability to take into account both early and late measurements of nuclides with short half-lives, and difficulty in ensuring measurement accuracy when using the existing gamma ray angle correlation measurement device for measurement. The device is special in that it includes at least six detectors distributed in a circle along a detector placement ring; the central axis of each detector is located in the same plane and passes through the center of the detector placement ring; the detector placement ring is a virtual circle; among the angles between the central axes of every two detectors of at least six detectors, at least one angle is 90°; one angle is 180°; the sum of the number of angles that are greater than 90° and less than 180°, or greater than 90° and less than 180°, plus the number of angles that are greater than 90° and less than 180° after converting the angles greater than 0° and less than 90° according to the angle correlation symmetry principle, is greater than or equal to 8, and the 8 angles are not equal to each other.

A method for calculating multi-group data of nuclear fuel considering resonance upscattering effects includes: 1. For nuclides in the nuclear fuel with resonant scattering cross-sections, a nuclear data processing program generates a resonance upscattering correction factor table for their total cross-section, fission cross-section, and absorption cross-section; 2. A fuel assembly calculation program performs resonance calculations to obtain the average multi-group cross-section of the nuclides, and interpolates the average multi-group cross-section in a traditional multi-group cross-section table that does not consider resonance upscattering to obtain the corresponding dilution cross-section; 3. Using the dilution cross-section, interpolation in the resonance upscattering correction factor table yields a correction factor, which is used to correct the average multi-group cross-section, resulting in a nuclear fuel multi-group cross-section considering resonance upscattering effects. This method solves the problem that fuel assembly calculation programs using ultrafine group methods for resonance calculations cannot consider resonance upscattering effects, providing accurate multi-group data for neutron transport calculations and improving the calculation accuracy of nuclear reactor safety parameters such as the effective multiplication coefficient and fuel temperature coefficient.

The application discloses a kind of nuclear data inspection method, device, electronic equipment and storage medium, to solve the problem of not comprehensive, low efficiency of inspection in the evaluation of nuclear data inspection in prior art.The method comprises: obtaining different evaluation nuclear data of the target nuclear element to be inspected, and a plurality of specific energy release experimental values;Unit conversion is carried out on each specific energy release experimental value, and a plurality of specific energy release calibration values are obtained;The specific energy release calculation value of the target nuclear element to be inspected under different evaluation nuclear data is calculated respectively;Draw the nuclear data experimental discrete curve of each specific energy release calibration value with energy variation, and draw the nuclear data calculation discrete curve of each specific energy release calculation value with energy variation;Data comparison is carried out based on nuclear data experimental discrete curve and nuclear data calculation discrete curve, and according to the comparison result, the evaluation nuclear data is inspected.

The application discloses a method for manufacturing a neutron-photon nuclear database suitable for reactor multi-group Monte Carlo calculation, and the method comprises the following steps: generating first format data of a single nuclear element by using an evaluation nuclear database; merging first format data of a plurality of nuclear elements obtained based on the first format data of the single nuclear element to obtain a database of the first format data; performing data processing on the database of the first format data to obtain a database of second format data related to a problem; and converting the database of the second format data into a database of third format data by using a preset format conversion program. The application improves the efficiency of the accompanying calculation of the Monte Carlo program, further improves the shielding calculation precision of the Monte Carlo program, checks the multi-group determinism, verifies the multi-group parameter processing function of the determinism, inherits the advantages of the Monte Carlo program, and has a powerful geometric processing function.

The invention discloses a nuclear database management system based on a nuclear dynamic detection technology, and relates to the technical field of nuclear data management, and the system comprises a data collection and processing module which is used for deploying a high-precision sensor on a nuclear facility, collecting dynamic detection nuclear data of the nuclear facility and original data of environmental parameter data in real time, in view of the influence of environmental parameter data on dynamic detection kernel data, original data is preprocessed by using a noise suppression and drift compensation algorithm, and preprocessing kernel data is generated in combination with anomaly detection processing of a storage medium and then transmitted to a data quality monitoring module; according to the method, the high-precision sensor is deployed in the nuclear facility to collect the original data, and the noise suppression and drift compensation algorithm is combined with the storage medium anomaly detection processing for preprocessing, so that the accuracy and reliability of nuclear data collection are ensured, the influence of environmental factors and noise on the data is effectively reduced, and the data quality is ensured.