CN107644694A - A kind of nuclear power plant's large break crash analysis method - Google Patents
A kind of nuclear power plant's large break crash analysis method Download PDFInfo
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Abstract
The present invention provides a kind of nuclear power plant's large break crash analysis method, including：Step S1, establish Main physical phenomenon and transient state that power plant model is used to catch the large-break LOCA of reality；Step S2, analyze and determine to influence the key parameter of Main physical phenomenon and transient state；Step S3, classifies to key parameter, and key parameter is at least divided into conservative hypothesis parameter, sampling parametric and punishment parameter；Step S4, to it is conservative assume parameter setting most severe condition it is assumed that and uncertain quantitative analysis is carried out to sampling parametric and punishment parameter, with obtain setting it is horizontal under targeted parameter value；Step S5, selection punishment model carries out punishment processing from punishment parameter, the targeted parameter value under the targeted parameter value envelope setting obtained with the punishment parameter obtained after being handled using punishment is horizontal.Implement the embodiment of the present invention, reduce the sample calculation of the best-estimated+Uncertainty Analysis Method, and reduce the conservative nargin determined by practical method.
Description
Technical field
The present invention relates to nuclear power plant's crash analysis technical field, more particularly to a kind of nuclear power plant's large break crash analysis side
Method.
Background technology
Reactor coolant lose accident, abbreviation loss of-coolant accident (LOCA) (LOCA), refer to primary Ioops pressure boundary produce cut or
Rupture, or valve are opened by mistake and opened, and cause the accident of primary Ioops cooling agent loading amount reduction.Wherein, large-break LOCA (LB
LOCA), because accident phenomenon is extremely complex, consequence is serious, (acceptance criteria of the general limit of the accident is involucrum peak value temperature to its allowance
Degree, PCT) economy of nuclear power plant is directly limit, it is one of most important design basis accident.
Nuclear power developing initial stage, using conservative analysis method and it is assumed that the assessment mould that conservative LOCA analysis methods use
Type must strictly observe annex K requirement,, can not due to the limitation of cognition and the shortcoming of instrument under historical conditions at that time
Artificially define data and the uncertainty of model, and have to introduce enough conservative in each side of crash analysis it is assumed that
Therefore, it is relatively conservative finally to analyze obtained result.
Then NRC develops a kind of the best-estimated+Uncertainty Analysis Method, it is desirable to quantifies one by one in crash analysis not
Certainty (primary condition, boundary condition, procedural model parameter etc.) is, it is necessary to carry out substantial amounts of sample calculation.Mutually more conservative evaluation
Method, the best-estimated+Uncertainty Analysis Method define the difference between result of calculation and its actual value by analysis of uncertainty
Away from more reasonably being evaluated safety allowance.But the best-estimated analysis method, need every time to ginseng during practice
Number carries out complicated analysis of uncertainty, carries out substantial amounts of sample calculation, therefore result is not conservative enough.
1992, enamel agate was logical and EDF is begun setting up and come to a conclusion really practical method based on the best-estimated program CATHARE
(DRM).It is determined that it is that its target is exactly to use statistical analysis technique based on statistics and the method for determining calculating by practical method (DRM)
Quantify all uncertainties, obtained uncertainty is quantified with conservative model covering, so as to be reduced on the premise of conservative
Excessive conservative hypothesis caused by non-quantized uncertainty.It is determined that by the conservative of practical method (DRM) between conservative analysis method
Between the best-estimated analysis method, however, with the raising of design requirement, DRM method is gradually difficult to meet design of nuclear power plant
The requirement of balance of economy and security, although this method reduces too conservative factor than conservative approach, but still have larger
Non-quantized uncertainty, the larger allowance excavated be present.
The content of the invention
The technical problems to be solved by the invention are, there is provided a kind of nuclear power plant's large break crash analysis method, to avoid
Substantial amounts of analysis of uncertainty calculates, and improves the reasonability and accuracy of analysis.
A kind of nuclear power plant's large break crash analysis method provided by the invention, it may include：
Step S1, establish Main physical phenomenon and transient state that power plant model is used to catch the large-break LOCA of reality；
Step S2, analyze and determine to influence the key parameter of the Main physical phenomenon and transient state；
Step S3, the key parameter is classified, the key parameter is at least divided into conservative hypothesis parameter, sampling ginseng
Number and punishment parameter；
Step S4, to the conservative hypothesis parameter setting most severe condition it is assumed that and to the sampling parametric and described punishing
Penalty parameter carries out uncertain quantitative analysis, to obtain the targeted parameter value under setting level；
Step S5, selection punishment model carries out punishment processing from the punishment parameter, to obtain after being handled using punishment
The targeted parameter value envelope that obtains of punishment parameter described in setting it is horizontal under targeted parameter value.
Wherein, also include after step s 5：
Step S6, the targeted parameter value obtained after punishment is handled obtain with the best-estimated+Uncertainty Analysis Method
Targeted parameter value is compared, if the best-estimated+uncertainty described in the targeted parameter value envelope obtained after punishment processing
Analysis method obtains targeted parameter value, it is determined that the target component obtained after punishment processing meets conservative requirement.
Wherein, the step S4 is specifically included：To the conservative hypothesis parameter setting most severe condition it is assumed that and to described
Sampling parametric and the punishment parameter carry out uncertain quantitative analysis, to obtain under 95% confidence level, under 95% probability
Targeted parameter value；
The step S5 is specifically included：Punishment processing is carried out to the punishment parameter using punishment model, so that at punishment
Under 95% confidence level described in the targeted parameter value envelope obtained after reason, the targeted parameter value under 95% probability.
Wherein, in the step S4, when assuming the conservative hypothesis parameter setting most severe condition, reference is most severe
Sequence of events, single failure criteria, the authentication area of technical specifications and different parameters, fuel recycle when accident occurs
At least one of factor.
Wherein, the worst sequence of events includes supply of electric power, pump operation state, cut classification and cut peace note
At least one of availability of pipeline.
Wherein, the different parameters include any in temperature, pressure, water level and equipment availability.
Wherein, in the step S4, by least one of mathematical statistics method or sensibility analysis method to the sampling
Parameter carries out uncertain quantitative analysis.
Wherein, the mathematical statistics method includes any in parameter statistic and nonparametric methods in statistics.
Wherein, the parameter statistic includes any in traditional parameters statistic law and Irving's factorization method.
Wherein, the nonparametric methods in statistics includes any in Wilks methods and Bootstrap bootstraps.
Wherein, in step s 5, uncertain quantitative analysis is carried out to the punishment parameter to specifically include：
Analysis of uncertainty is carried out to the punishment parameter using response surface analysis.
Wherein, in the step S5, the selection of the punishment model need to meet following two principles：
A, ensure that the punishment parameter can be by the punishment model envelope；
B, selected punishment model should not result in the cut accident point being calculated and deviate truly.
Wherein, described conservative each design parameter assumed in parameter, the sampling parametric and the punishment parameter
It is divided into always according to source any in physical model statistic property, initial condition parameters and boundary condition.
Wherein, the target component includes peak cladding temperature and fuel can oxide thickness is at least one.
The beneficial effect of the embodiment of the present invention is：
The present invention is the Large break LOCA method of conservative processing superposition analysis of uncertainty.Relative to most preferably estimating
Calculation+analysis of uncertainty, method of the invention punish model by introducing, avoid substantial amounts of sample calculation, add one again
Fixed conservative；Relative to determining to discuss practical method DRM, method of the invention to input parameter (that is, key parameter) no
Certainty has carried out further quantization, reduces excessive conservative allowance.Therefore, method of the invention can both simplify calculating,
Ensure certain allowance, and can avoids excessively guarding, and has certain practical value.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is the schematic flow sheet of nuclear power plant's large break crash analysis method of the embodiment of the present invention.
Fig. 2 is the refinement schematic flow sheet of nuclear power plant's large break crash analysis method of the embodiment of the present invention.
Embodiment
The explanation of following embodiment is refer to the attached drawing, can be to the specific embodiment implemented to the example present invention.
Refer to shown in Fig. 1, the embodiment of the present invention provides a kind of nuclear power plant's large break crash analysis method, including：
Step S1, establish Main physical phenomenon and transient state that power plant model is used to catch the large-break LOCA of reality；
Step S2, analyze and determine to influence the key parameter of the Main physical phenomenon and transient state；
Step S3, the key parameter is classified, the key parameter is at least divided into conservative hypothesis parameter, sampling ginseng
Number and punishment parameter；
Step S4, to the conservative hypothesis parameter setting most severe condition it is assumed that and being carried out to the sampling parametric not true
Qualitative quantization is analyzed, to obtain the targeted parameter value under setting level；
Step S5, selection punishment model carries out punishment processing from the punishment parameter, to obtain after being handled using punishment
The targeted parameter value envelope that obtains of punishment parameter described in setting it is horizontal under targeted parameter value.
In the specific implementation, it may also include after step S5：
Step S6, the targeted parameter value obtained after punishment is handled obtain with the best-estimated+Uncertainty Analysis Method
Targeted parameter value is compared, if the best-estimated+uncertainty described in the targeted parameter value envelope obtained after punishment processing
Analysis method obtains targeted parameter value, it is determined that the target component obtained after punishment processing meets conservative requirement.
Each step is described in detail respectively below in conjunction with Fig. 2.
In step sl：
First, based on project analysis experience, Binding experiment research and numerical simulation result of calculation, to large-break LOCA
Main physical phenomenon and transient state confirmed (step 101).For example, for cold end large-break LOCA transient state, mainly
There are 8 main physical phenomenons：The energy release of-fuel；The stagnation behavior of-blowdown phase reactor core；- involucrum of blowdown phase-
Cooling agent conducts heat；- ECCS water enters the process of pressure vessel；Involucrum-cooling agent the heat transfer in stage is flooded in-vibration again；- nitrogen enters
Enter the effect of primary Ioops；- stabilization floods involucrum-cooling agent heat transfer in stage again；- flood again stage liquid entrainment effect.
Then, the procedure manual of analysis the best-estimated program CATHARE programs, users' guidebook, programmer manual, standard journey
Sequence model and relational expression assess file, to determine the ability (step 102) of the best-estimated program CATHARE simulation particular phenomenons；
Subsequently, based on the best-estimated program CATHARE, establish and optimize the seizure Main physical phenomenon and transient state
Power plant model (step 103).First, according to CATHARE GB user's manual, master pattern is established to power plant, then to net
Lattice are analyzed, and finally make it that grid number is minimum, while still can analyze important phenomenon.The flow is assessed according to program first
And application experience determines grid, then compared by separating experiment and procedure result/experiment value of integral experiment, to power plant model
Grid is iterated analysis, finally gives optimal model meshes, while guaranteeing to capture important phenomenon so that calculates
Amount of analysis is less.EDF and FRAMATOME has developed jointly a series of optional model.
Then, extra assessment (step 104), such as LOFT-L2.5 tests have also been carried out to model；UPTF7 tests (are steamed
The improvement of vapour generator (SG) liquid entrainment model) and UPTF10 tests (improvement of pressure vessel descending branch phase separation model)
Deng.
In step s 2：
According to step S1 defined in Main physical phenomenon, progressively analyze the key influence factor of each phenomenon, and sieve
Select key parameter (step 105).The key parameter of each Main physical phenomenon of influence is finally given.
In step s3：
First, key parameter is divided into by three groups of physical model, primary condition and boundary condition according to source.Then, refer to
CSAU flows obtain the Uncertainty distribution of key parameter.On the basis of optimal power plant model grid, the related ginseng of procedural model
Several uncertainties pass through large break evaluating matrix quantitative analysis.The uncertainty of procedural model, then mesh generation is being determined
On the basis of carry out numerical simulation, and compared with experiment value after obtain.In addition, the uncertainty of power plant's parameter then derives from
The project file and technical specification of manufacturer.Thus it is final, three groups of key parameters are categorized as conservative hypothesis parameter, sampling parametric
And punishment parameter classification (step 106).For example, for the cold section of large break crash analysis of CPR1000 power plant, 70 are selected altogether
Remaining individual key parameter, is shown in Table 1.
Table 1
In step s 4：
Analysis of uncertainty can be carried out for each LB LOCA each peak cladding temperature value (PCT).For example, to every
Individual peak cladding temperature value (PCT) is obtained under 95% confidence level, the parameter value under 95% probability.Carrying out analysis of uncertainty
When, assume that parameter setting extreme conditions assumes (step 107) to conservative, when setting extreme conditions hypothesis, reference：
Worst sequence of events (such as availability of supply of electric power, pump operation state, cut classification and cut peace note pipeline)；It is single
Fault criteria；The authentication area of some technical specifications and different parameters (temperature, pressure, water level, equipment availability)；Accident
Fuel recycle (phase in longevity of average reactor core) during generation.It is also possible to use response surface analysis is not true to punishment parameter progress
Qualitative analysis (step 108), to introduce corresponding punishment model.In addition, suitable statistical method is also used, to sampling parametric
Uncertain quantitative analysis is carried out, to obtain under 95% confidence level, the parameter value (step 109) under 95% probability.
Uncertain quantitative analysis to sampling parametric is specifically used：
1st, mathematical statistics method
The mathematical statistics method of quantization uncertainty is divided into 2 kinds of parameter statistic and nonparametric methods in statistics.
Parameter statistic has traditional parameters statistic law and Irving's factor statistics method：
On traditional parameters statistic law：
According to traditional parameter statistic, whether normal state is obeyed using appropriate Methods of Normality Test test samples first
Distribution；When sample meets normal distribution, then sample average (μs) and population mean (μp) and sample standard deviation (σs) and overall mark
Accurate poor (σp) relation be：Meet that t is distributed,Meet χ2It is distributed [6].
Determination for the confidential interval of statistic, under same confidence level, two-sided confidence interval higher limit is than single
Side confidential interval higher limit is big, but for reactor safety parameter, according to its actual physical meaning, only focuses on its unilateral confidence
Section higher limit.
Falling the probability expression in confidential interval for given confidence level 1- α=95%, t distribution statisticses amounts is：
When tabling look-up to obtain tα(n-1) after, μpUnilateral confidential interval can be completely by μsAnd σsDetermine, expression formula is as follows：
Similarly, due toMeet χ2Distribution, for given confidence level 1- α=95%, χ2Distribution statisticses amount
The probability expression fallen in confidential interval is：
When tabling look-up to obtainAfterwards, σpUnilateral confidential interval can be by sample standard deviation σsDetermine, expression formula is as follows：
It is conservative to be considered as unilateral confidential interval higher limit as μpAnd σpEstimate, i.e.,：
Further estimation meets the higher limit of 95% probable value, i.e.,：
Y95/95=μp+1.645×σp
On Irving's factorization method：
Statistical disposition is carried out using Irving's factorization method, first has to examine result of calculation whether full using the appropriate method of inspection
Sufficient normal distribution, if meeting normal distribution, table look-at obtains Irving's factor (kowen), and pass through μsAnd σsObtain 95%
Meet the unilateral confidence upper limit value (Y of 95% probability under confidence level95/95), i.e.,：
Y95/95=μs+kowen×σs
On nonparametric statistical method：
Nonparametric statistical method comes from direct monte carlo method, is characterized in not going to directly obtain output parameter [as wrapped
Shell peak temperature (PCT)] probability-distribution function.Nonparametric methods in statistics is a kind of system independent of the distribution of certain particular theory
Estimating method is counted, it is inferred and what is examined is not population parameter, is not dependent on the totality point of certain specific theoretical distribution
Cloth feature, relative loose is required to the condition of data information, it is applied widely.Nonparametric statistical method include Wilks methods and
Bootstrap bootstraps.
On Wilks methods：
The characteristics of Wilks methods is the probability-distribution function for being not required to obtain output parameter (such as PCT), but in certain confidence
Upper confinement boundary value of the sampled population in certain probability level is obtained under level.Nonparametric statistics sampling techniques can be obtained by random sampling
To the error tolerance bound of unknown distribution parameter, the random of the expectation tolerance bound that meets confidence degree can be calculated by Wilks formula
Sampling samples capacity.Wilks formula are：
β=(1- γ)N
In formula, β is confidence level；γ is probability level；N is sample size.
The borders value of 95% (γ=0.95) is obtained with the confidence level of 95% (β=0.95) by statistical analysis.
Substituting into calculating, can to obtain sample size be N=59, i.e., for single output variable, takes the maximum in 59 sample values to be
Under the confidence level of 95% (β=0.95), the borders value of 95% (γ=0.95) probable value.Guba proposed in 2003
The more typically theory of property, it can be applied to export multiple variables [such as PCT, local maxima oxygenation efficiency (LMO), total oxygenation efficiency simultaneously
(CWO) situation].Guba formula are：
Confidence level β=0.95 is taken, probability level γ=0.95, p are output variable number, take p=1, calculate to obtain N=
59；P=2 is taken, calculates to obtain N=93；P=3 is taken, calculates to obtain N=124.
On Bootstrap bootstraps：
The basic thought of Bootstrap bootstraps is：Make have the sampling put back to, sample in the range of having n initial data
This capacity is still n, and the probability that each object of observation is pumped to is equal, as 1/n [7].It regards sample as entirety, will be from sample
The middle obtained subsample of sampling is referred to as Bootstrap samples, often obtains a Bootstrap sample and just calculates statistic
Observation, n times (General N=1000 or more) are repeated, N number of observation of the statistic is just obtained, so as to obtain the statistic
Experience distribution, then carry out statistical inference.It is soft by computer herein because the amount of calculation of Bootstrap bootstraps is very big
Part MATLAB calculates to handle, and obtains the μ under 95% confidence levelBootstrapAnd σBootstrapValue, further pass through normality
The method of inspection examine result of calculation whether Normal Distribution；If Normal Distribution, the upper limit of 95% probability level is obtained
It is worth and is：
Y=μBootstrap+1.645×σBootstrap
2nd, susceptibility assays
This method comes from the improved thermal-hydraulic of Westinghouse Electric's calculating departure from nucleate boiling ratio (DNBR) design limitation and set
Meter method (ITDP) [8], herein for LOCA uncertainty quantitative analysis.Assuming that between input parameter independently of each other, each parameter
Value xi is in its nominal value μiNeighbouring small range disturbance.Target component y change and the variation relation of each input parameter are：
Sensitivity factor is defined by differential approximationAbove formula is integrated to obtain
Make xi=μi(i=1, then 2,3 ..., n), y=μy.According to formula of error transmission：
In formula, σi/μiFor coefficient of deviation, represent that each variable deviates the degree of nominal value.
According to central-limit theorem, if sequence of random variables x1, x2..., xn, separate and limited mathematic expectaion
With variance, then y=f (x1,x2..., xn) level off to normal distribution[6].So y is under 95% probability level
Unilateral higher limit is：
Y=μy+1.645×σy。
In the specific implementation, the target component of the embodiment of the present invention may be used also in addition to it can be peak cladding temperature value (PCT)
For fuel can oxide thickness.
In step s 5：
For double 95 values of PCT that envelope step S4 is obtained, the present invention introduces conservative nargin in power plant model, is referred to as punishing
Processing is penalized (to refer mainly to carry out punishment processing to punishment model) (step 110).The selection of punishment model needs to meet following two
Principle：
A, ensure that the punishment parameter can be by the punishment model envelope；
B, selected punishment model should not result in the cut accident point being calculated and deviate truly.
But reality calculating analysis in, due to different parameters to the influence degree of transient process and PCT results not
Together, in order to neither influence transient process as much as possible, while energy envelope PCT double 95 is worth simultaneously again, final to may be selected to several ginsengs
Number is punished.Table 2 is a kind of punishment model concluded.
Table 2
As shown in table 2, step S5 so-called punishment processing it is actual for determine can double 95 values of envelope PCT punish model
Excursion.By analysis, the rightmost one of table 2 arrange it is final determine 8 can double 95 values of envelope PCT the change model for punishing model
Enclose.
In the specific implementation, can by step S110 punishment handle after punishment parameter obtain target component result of calculation with most
The targeted parameter value that good estimation+Uncertainty Analysis Method obtains is compared, if the target ginseng obtained after punishment processing
The best-estimated described in value envelope+Uncertainty Analysis Method obtains targeted parameter value, it is determined that the mesh obtained after punishment processing
Mark parameter meets conservative and requires (step 111).
By described above, the beneficial effects of the present invention are：
The present invention is the Large break LOCA method of conservative processing superposition analysis of uncertainty.Relative to most preferably estimating
Calculation+analysis of uncertainty, method of the invention punish model by introducing, avoid substantial amounts of sample calculation, add one again
Fixed conservative；Relative to determining to discuss practical method DRM, method of the invention to input parameter (that is, key parameter) no
Certainty has carried out further quantization, reduces excessive conservative allowance.Therefore, method of the invention can both simplify calculating,
Ensure certain allowance, and can avoids excessively guarding, and has certain practical value.
Above disclosure is only preferred embodiment of present invention, can not limit the right model of the present invention with this certainly
Enclose, therefore the equivalent variations made according to the claims in the present invention, still belong to the scope that the present invention is covered.
Claims (14)
1. a kind of nuclear power plant's large break crash analysis method, including：
Step S1, establish Main physical phenomenon and transient state that power plant model is used to catch the large-break LOCA of reality；
Step S2, analyze and determine to influence the key parameter of the Main physical phenomenon and transient state；
Step S3, the key parameter is classified, the key parameter be at least divided into it is conservative assume parameter, sampling parametric with
And punishment parameter；
Step S4, to the conservative hypothesis parameter setting most severe condition it is assumed that and joining to the sampling parametric and the punishment
Number carries out uncertain quantitative analysis, to obtain the targeted parameter value under setting level；
Step S5, selection punishment model carries out punishment processing from the punishment parameter, is punished with what is obtained after being handled using punishment
Targeted parameter value under setting is horizontal described in the targeted parameter value envelope that penalty parameter obtains.
2. according to the method for claim 1, it is characterised in that also include after step s 5：
Step S6, the target that the targeted parameter value obtained after punishment is handled obtains with the best-estimated+Uncertainty Analysis Method
Parameter value is compared, if the best-estimated+analysis of uncertainty described in the targeted parameter value envelope obtained after punishment processing
Method obtains targeted parameter value, it is determined that the target component obtained after punishment processing meets conservative requirement.
3. according to the method for claim 1, it is characterised in that
The step S4 is specifically included：To the conservative hypothesis parameter setting most severe condition it is assumed that and to the sampling parametric
Uncertain quantitative analysis is carried out with the punishment parameter, to obtain under 95% confidence level, the targeted parameter value under 95% probability；
The step S5 is specifically included：Punishment processing is carried out to the punishment parameter using punishment model, so that after punishment processing
Under 95% confidence level described in obtained targeted parameter value envelope, the targeted parameter value under 95% probability.
4. the method according to claim 1 or 3, it is characterised in that in the step S4, to the conservative hypothesis parameter
When setting most severe condition hypothesis, with reference to worst sequence of events, single failure criteria, technical specifications and different parameters
Authentication area, at least one of fuel recycle factor when accident occurs.
5. according to the method for claim 4, it is characterised in that the worst sequence of events includes supply of electric power, pump
At least one of availability of running status, cut classification and cut peace note pipeline.
6. according to the method for claim 4, it is characterised in that the different parameters include temperature, pressure, water level and set
It is any in standby availability.
7. the method according to claim 1 or 3, it is characterised in that in the step S4 by mathematical statistics method or
At least one of sensibility analysis method carries out uncertain quantitative analysis to the sampling parametric.
8. according to the method for claim 7, it is characterised in that the mathematical statistics method includes parameter statistic and non-ginseng
It is any in number statistic law.
9. according to the method for claim 8, it is characterised in that the parameter statistic includes traditional parameters statistic law and Europe
It is any in literary factorization method.
10. according to the method for claim 8, it is characterised in that the nonparametric methods in statistics include Wilks methods and
It is any in Bootstrap bootstraps.
11. according to the method for claim 1, it is characterised in that in step s 4, the punishment parameter is not known
Property quantitative analysis specifically includes：
Analysis of uncertainty is carried out to the punishment parameter using response surface analysis.
12. the method according to claim 1 or 11, it is characterised in that in the step S5, the choosing of the punishment model
Following two principles need to be met by selecting：
Ensure that the punishment parameter can be by the punishment model envelope；
The cut accident point being calculated that selected punishment model should not result in deviates true.
13. according to the method for claim 1, it is characterised in that conservative hypothesis parameter, the sampling parametric and the institute
Each design parameter stated in punishment parameter is divided into physical model statistic property, initial condition parameters and boundary condition always according to source
In it is any.
14. according to the method for claim 1, it is characterised in that the target component includes peak cladding temperature and fuel
Involucrum oxide thickness is at least one.
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| CN111144752A (en) * | 2019-12-26 | 2020-05-12 | 西安交通大学 | Nuclear power plant loss of coolant accident safety injection flow demand analysis method based on genetic algorithm |
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