Method of selective corrosion rate analysis for a fluid processing plant

• US 6,047,241 A
• Filed: 10/23/1997
• Issued: 04/04/2000
• Est. Priority Date: 10/23/1997
• Status: Expired due to Fees

• Current Assignee: E2G CORR Solutions LLC
• Original Assignee: Michael T. Sparago
• Inventors: Sparago, Michael T.
• Primary Examiner(s): Hoff, Marc S.
• Assistant Examiner(s): Bui, Bryan
• Application Number:
  US08/956,909
• Time in Patent Office: 894 Days
• Field of Search: 702/33, 702/34, 702/35, 702/36, 702/179, 702/180, 73/86, 73/592, 73/804, 376/249, 376/305
• US Class Current: 702/34
• CPC Class Codes: G01N 17/02 Electrochemical measuring systems for weathering, corrosion or corrosion-protection measurement
• CPC Class Codes: G21C 17/00 Monitoring; Testing measuring in general G01; Maintaining
• CPC Class Codes: G21D 3/001 Computer implemented control
• CPC Class Codes: Y02E 30/00 Energy generation of nuclear origin
• CPC Class Codes: Y02E 30/30 Nuclear fission reactors

Abstract

A method of selective corrosion rate analysis is shown for generating an inspection and replacement schedule for a fluid processing plant. The method includes the steps of identifying a system from a division of the plant into one or more systems wherein each system has mechanical components that are expected to experience a common corrosion environment, and wherein each system has at least one thickness measurement location for performing thickness inspections. The next steps are establishing system corrosion data for each thickness measurement location and running the data through a plurality of corrosion engineering models. Running the corrosion engineering models includes coordinating the system corrosion data of the thickness measurement locations into a plurality of physical relationship data groups, and applying a plurality of statistical distribution/goodness-of-fit tests to each physical relationship data group. The final step is selecting a best fitting corrosion engineering model for generating an inspection schedule for the fluid containment components within each system of the plant. In a preferred embodiment of the method of selective corrosion rate analysis, the step of running the corrosion engineering models includes the additional step of identifying sub-populations within the application of the statistical distribution/goodness-of-fit tests so that identification of such sub-populations assists the user in identifying unknown corrosion mechanisms, and establishing specific inspection schedules for the sub-populations.

Claims

1. A method of selective corrosion rate analysis for generating an inspection schedule for a fluid processing plant, comprising the steps of:

a. identifying a system from a division of the plant into one or more systems wherein each system has mechanical fluid containment components that are expected to experience a common corrosive environment and each system has at least one thickness measurement location for performing thickness inspections;

b. establishing system corrosion data for each thickness measurement location in the system;

c. running the system corrosion data through a plurality of corrosion engineering models; and

d. selecting a best fitting corrosion engineering model for generating a remaining life and optimum inspection schedule for each thickness measurement location in the system by running the system corrosion data through the selected best fitting corrosion engineering model.

2. The method of selective corrosion rate analysis of claim 1, wherein the step of running the system corrosion data through a plurality of corrosion engineering models comprises the further steps of coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups, applying a plurality of statistical distributions to each physical relationship data group, and applying a goodness-of-fit test to results of application of the statistical distributions to identify a combination of a physical relationship data group and statistical distribution as the best fitting corrosion engineering model that most accurately describes actual system corrosion behavior.

3. The method of selective corrosion rate analysis of claim 2, wherein the step of running the system corrosion data through a plurality of corrosion engineering models comprises the further step of combining results of the statistical distributions that are not significantly different and identifying as sub-populations results of the statistical distributions that vary significantly from statistical distribution results of other physical relationship data groups and applying the goodness-of-fit test to the sub-population results.

4. The method of selective corrosion rate analysis of claim 2, wherein the step of coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups further comprises a step of coordinating the system corrosion data for each thickness measurement location into at least a first group having all of the system thickness measurement locations grouped randomly and a second group having all the thickness measurement locations grouped according to different sized mechanical components in which the thickness measurement locations are located.

5. The method of selective corrosion rate analysis of claim 4, wherein the step of coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups further comprises a step of coordinating the system corrosion data for each thickness measurement location into at least a third group having all the system thickness measurement locations grouped according to different mechanical components in which the thickness measurement locations are located.

6. The method of selective corrosion rate analysis of claim 5, wherein the step of coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups further comprises a step of coordinating the system corrosion data for each thickness measurement location into at least a fourth group having all the system thickness measurement locations grouped according to their differing orientations within mechanical components.

7. The method of selective corrosion rate analysis of claim 6, wherein the step of coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups further comprises a step of coordinating the system corrosion data for each thickness measurement location into at least a fifth group having some system thickness measurement locations grouped according to a consecutive positional location of the thickness measurement locations defining a zone of higher corrosion rates than other thickness measurement locations grouped according to their locations being outside the zone.

8. The method of selective corrosion rate analysis of claim 1, further comprising transferring operational information to a corrosion engineering model library, the operational information being drawn from selection of the best fitting model and from a statistical analysis applied to all thickness measurement locations after generating the remaining life and optimum inspection schedule, wherein the corrosion engineering model library integrates the operational information and passes the information to an historical corrosion rate data base to modify system corrosion data for each thickness measurement location and thereby effect subsequent running of the corrosion engineering models.

9. The method of selective corrosion rate analysis of claim 1, further comprising a step of integrating system risk reliability criteria after the selecting a best fitting corrosion engineering model step and before the generating an optimum inspection schedule step, wherein the system risk reliability criteria defines a risk-reliability level for the system based on system risk considerations.

10. The method of selective corrosion rate analysis of claim 1, further comprising a step of integrating inspection costs data into the step of generating an optimum inspection schedule step.

11. A method of selective corrosion rate analysis for generating an inspection schedule for a fluid processing plant, comprising the steps of:

a. identifying a system from a division of the plant into one or more systems wherein each system has mechanical fluid containment components that are expected to experience a common corrosive environment and each system has at least one thickness measurement location for performing thickness inspections;

b. establishing for each thickness measurement location system corrosion data drawn from an historical corrosion rate data base;

c. running the system corrosion data through a plurality of corrosion engineering models, including coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups the data groups being at least a first group having all of the thickness measurement locations grouped randomly and a second group having all system thickness measurement locations grouped according to different sized mechanical components in which the thickness measurement locations are located, applying a plurality of statistical distributions to each physical relationship data group, and applying a goodness-of-fit test to results of application of the statistical distributions to identify a combination of a physical relationship data group and statistical distribution as a best fitting corrosion engineering model that most accurately describes actual system corrosion behavior;

d. selecting the best fitting corrosion engineering model for generating a remaining life and optimum inspection schedule for each thickness measurement location in the system by running the system corrosion data through the selected best fitting corrosion engineering model; and

repeating steps a,b,c,d for each system in the plant.

12. The method of selective corrosion rate analysis of claim 11, further comprising a step of integrating system risk reliability criteria after the selecting a best fitting corrosion engineering model step and before the generating an optimum inspection schedule step, wherein the system risk reliability criteria defines a risk-reliability level for the system based on system risk considerations.

13. The method of selective corrosion rate analysis of claim 12, further comprising a step of integrating inspection costs data into the step of generating an optimum inspection schedule step.

14. The method of selective corrosion rate analysis of claim 13, further comprising transferring operational information to a corrosion engineering model library, the operational information being drawn from selection of the best fitting model and from a statistical analysis applied to all thickness measurement locations after generating the remaining life and optimum inspection schedule, wherein the corrosion engineering model library integrates the operational information and passes the information to an historical corrosion rate data base to modify system corrosion data for each thickness measurement location and thereby effect subsequent running of the corrosion engineering models.

15. The method of selective corrosion rate analysis of claim 14, wherein the step of running the system corrosion data through a plurality of corrosion engineering models comprises the further step of combining results of the statistical distributions that are not significantly different and identifying as sub-populations results of the statistical distributions that vary significantly from statistical distribution results of other physical relationship data groups and applying the goodness-of-fit test to the sub-population results.

16. The method of selective corrosion rate analysis of claim 15, wherein the step of coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups further comprises a step of coordinating the system corrosion data for each thickness measurement location into at least a third group having all system thickness measurement locations grouped according to different mechanical components in which the locations are located, a fourth group having all system thickness measurement locations grouped according to their differing orientations within the mechanical components, and a fifth group having some system thickness measurement locations grouped according to a consecutive positional location of the locations defining a zone of higher corrosion rates than other thickness measurement locations grouped according to their locations being outside the zone.

17. A method of selective corrosion rate analysis for generating an inspection schedule for a fluid processing plant, comprising the steps of:

a. identifying a system from a division of the plant into one or more systems wherein each system has mechanical fluid containment components that are expected to experience a common corrosive environment and each system has at least one thickness measurement location for performing thickness inspections;

b. establishing system corrosion data for each thickness measurement location in the system;

c. running the system corrosion data through a plurality of corrosion engineering models including applying a plurality of statistical distributions to a plurality of physical relationship data groups, wherein the plurality of statistical distributions include at least a Normal, a Log Normal and a Weibull statistical distribution; and

d. selecting a best fitting corrosion engineering model for generating a remaining life and optimum inspection schedule for each thickness measurement location in the system by running the system corrosion data through the selected best fitting corrosion engineering model.

18. The method of selective corrosion rate analysis of claim 17, wherein the step of running the system corrosion data through a plurality of corrosion engineering models comprises the further steps of coordinating the system corrosion data for each thickness measurement location into a plurality of physical relationship data groups, applying the plurality of statistical distributions to each physical relationship data group, and applying a goodness-of-fit test to results of application of the statistical distributions to identify a combination of a physical relationship data group and statistical distribution as the best fitting corrosion engineering model that most accurately describes actual system corrosion behavior.

19. The method of selective corrosion rate analysis of claim 18, further comprising a step of integrating inspection costs data into the step of generating an optimum inspection schedule step.

20. The method of selective corrosion rate analysis of claim 19, further comprising a step of integrating system risk reliability criteria after the selecting a best fitting corrosion engineering model step and before the generating an optimum inspection schedule step, wherein the system risk reliability criteria defines a risk-reliability level for the system based on system risk considerations.