JPH08210958A - Breakage monitoring method for piping and pressure vessel - Google Patents

Abstract

PURPOSE: To measure the breakage probability in the life end of a piping and pressure vessel by combining the thermal stress acting on the vicinity of an evaluating point with the internal pressure stress change on an input condition of the cracking length density inversely operated from a material test. CONSTITUTION: A notched round bar tension test piece 27 is broken by a tension test, the numerical simulation of a FEM analysis 28 is executed, a Weibull stress analysis 29 is performed by use of the post tape to provide a Weibull distribution 30. A constant (n) 31 for regulating a cracking length probability distribution 16 is calculated from this distribution, and combined with the other probability distribution to prepare a probability variable data base 13. On the other hand, a local thermal stress 3 is evaluated on an input condition of the fluid temperature change 1 by a temperature sensor 10, and an internal pressure stress 5 is also calculated from the pressure change 4 from a pressure measuring point 11 to determine the total stress 12. A fatigue breakage generating probability 23 is calculated 21 from the total stress by use of a base 13, and a crack through probability 24 and a rupture probability 25 are determined by probability fatigue and creep crack progress analysis 22.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION The present invention calculates the probability density distribution of the microcrack length inherent in a material, calculates the stress acting on the pipe / pressure vessel in real time, and calculates the fracture probability of the pipe / pressure vessel online. It relates to a method for monitoring the breakdown of pipes and pressure vessels that is evaluated and predicted in.

[0002]

2. Description of the Related Art A conventional pipe / pressure vessel damage monitoring method is based on a random variable database 13 prepared in advance as shown in FIG.
0, pressure change 4 and total stress 12 by Green's function method 2
And stochastic fatigue damage calculation 21, stochastic fatigue-
A creep crack growth analysis 22 is performed to obtain a penetration probability 24 and a fracture probability 25.

[0003]

In the conventional fracture monitoring method for pipes and pressure vessels shown in FIG. 2, since the crack depth probability distribution cannot be obtained from ordinary material tests, the distribution obtained from the literature (for example, The database is created by using Marshall (distribution) .However, the crack depth probability distribution is one of the variables that most greatly affects the fracture probability evaluation.
Therefore, if the actual distribution of cracks and the literature values were different, the prediction results could be significantly different.

The present invention is proposed in view of the above-mentioned problems, and the purpose thereof is to predict the probability of breakage at the point of interest such as the end of life of pipes and pressure vessels and to predict the operation of the plant. The point is to provide a method for monitoring the destruction of pipes and pressure vessels that can be used to improve and determine when to replace equipment.

[0005]

In order to achieve the above object, the pipe / pressure vessel fracture monitoring method according to the present invention calculates the crack length density backward from a material test, and uses this as an input condition to obtain a value near an evaluation point. The thermal stress acting on the pipe / pressure vessel is evaluated in real time from the attached fluid temperature sensor by the Green's function method, and the internal pressure stress change based on the data of the pressure sensor is combined with this to evaluate the fatigue crack growth prepared in advance,
The probabilistic fracture mechanics analysis is performed using the probability density distribution function of material data for brittle fracture, and the feature is that the fracture probability of pipes and pressure vessels is predicted and monitored.

[0006]

The pipe / pressure vessel fracture monitoring method according to the present invention uses the Green's function method to calculate the crack length density from the material test and calculate the crack length density as an input condition from the fluid temperature sensor near the evaluation point. The thermal stress acting on the pressure vessel is evaluated in real time, the internal pressure stress change based on the data of the pressure sensor is combined with this, and the probability density distribution function of the material data on fatigue crack growth and brittle fracture prepared in advance is used for stochastic analysis. Fracture mechanics analysis is performed to predict and monitor the failure probability of pipes and pressure vessels.

[0007]

EXAMPLES Next, the method for monitoring the breakdown of a pipe / pressure vessel of the present invention will be described with reference to an example shown in FIG. Fracture the notched round bar tensile test piece 27 by a tensile test, and
After performing the numerical simulation of the analysis 28, the Weibull stress analysis 29 is performed using the post tape.

Since the Weibull stress σ _W is obtained in this manner, the Weibull stress σ _W is plotted on the Weibull probability paper to obtain the Weibull distribution 30. Since the parameter m is obtained from this distribution, the constant n31 that defines the crack length probability distribution 16 is calculated. The random variable database 13 is maintained together with other probability distributions. On the other hand, using the temperature change 1 of the fluid temperature sensor 10 as an input condition, the Green's function method 2
The local thermal stress 3 is evaluated by. At the same time, pressure measurement point 11
Calculate the internal pressure stress 5 from the pressure change 4 from the total stress 1
Ask for 2.

Further, the probability of fatigue fracture occurrence 23 is calculated from the stochastic fatigue damage calculation 21 using the random variable database 13. Further, the probability of crack penetration 24 and the probability of fracture 25 are calculated by the stochastic fatigue-creep crack growth analysis 22. The obtained probability is compared with the screening criteria 26 to improve the operation method of the plant or stop the plant.
It is used to judge the construction time of ISI.

According to the present invention, a plurality of notch round bars are subjected to a tensile test when the database is constructed as described above, the wiper stress at the time of breaking is obtained by FEM numerical analysis simulation, and this is plotted on a Weibull probability paper. According to the local approach method, the parameter of the Weibull distribution of n and Weibull stress σ _W that defines the probability distribution of crack length a (generally expressed by f (a) = Aa ^-n ) that is the starting point of fracture m
Since there is a relationship of m = 2n + 1 with (see "Equation 1" below), n is calculated by back calculation by a tensile test. Then, the probability distribution f (a) = Aa- ⁿ is incorporated into the database as a crack length probability density function.

[0011]

[Equation 1]

[0012]

As described above, the pipe / pressure vessel failure monitoring method of the present invention uses the Green's function method from the fluid temperature sensor installed near the evaluation point, with the crack length density calculated backward from the material test and using this as the input condition. Evaluate the thermal stress acting on the piping and pressure vessel in real time, combine it with the internal pressure stress change based on the data of the pressure sensor, and use the probability density distribution function of the material data on fatigue crack growth and brittle fracture prepared beforehand to calculate the probability. Theoretical failure mechanics analysis to predict and monitor the failure probability of pipes and pressure vessels, so it is possible to predict the failure probability at the point of interest such as the end of life of the pipes and pressure vessels, improving plant operation, It can be used to determine when to replace equipment.

[Brief description of drawings]

FIG. 1 is a block diagram showing an embodiment of a method for monitoring damage of a pipe / pressure vessel according to the present invention.

FIG. 2 is a block diagram showing a conventional pipe / pressure vessel breakdown monitoring method.

[Explanation of symbols]

 1 Fluid temperature change 2 Green's function method 3 Local thermal stress 4 Pressure change 5 Internal pressure stress 6 S-N curve 7 Fatigue damage calculation 8 Crack stability evaluation 9 Equivalent thermal bending stress 10 Fluid temperature sensor 11 Pressure measurement point 12 Total stress 13 Random variable database 14 Probability distribution of SN curve 15 Crack density probability distribution 16 Crack length probability distribution 17 Crack aspect ratio probability distribution 18 Fatigue / creep crack propagation constant probability distribution 19 Flow stress probability distribution 20 Fracture toughness probability distribution 21 Probabilistic Fatigue Damage Calculation 22 Probabilistic Fatigue-Creep Crack Growth Analysis 23 Fatigue Failure Occurrence Probability 24 Penetration Probability 25 Fracture Probability 26 Screening Criteria 27 Notched Round Bar Tensile Specimen 28 FEM Analysis 29 Weibull Stress Analysis 30 Weibull Distribution 31 n

Claims (1)

[Claims] A thermal stress acting on a pipe / pressure vessel is evaluated in real time by the Green's function method from a fluid temperature sensor installed near the evaluation point, and the crack length density is calculated back from the material test and used as input conditions. Probabilistic fracture mechanics analysis is performed using the probability density distribution function of material data on fatigue crack growth and brittle fracture prepared in advance by combining internal pressure stress changes based on pressure sensor data, and the fracture probability of pipes and pressure vessels. A method for monitoring the breakdown of pipes and pressure vessels, which is characterized by predicting and monitoring