NEA-0429 REMO.
REMO, Failure Analysis of System with Reparable and Standby Components by Monte-Carlo
NAME OR DESIGNATION OF PROGRAM, COMPUTER, NATURE OF PHYSICAL PROBLEM SOLVED, METHOD OF SOLUTION, RESTRICTIONS ON THE COMPLEXITY OF THE PROBLEM, CPU, FEATURES, AUXILIARIES, STATUS, REFERENCES, REQUIREMENTS, LANGUAGE, OPERATING SYSTEM OR MONITOR UNDER WHICH PROGRAM IS EXECUTED, OTHER RESTRICTIONS, NAME AND ESTABLISHMENT OF AUTHOR, MATERIAL, CATEGORIES
[ top ]
[ top ]
To submit a request, click below on the link of the version you wish to order.
Only liaison officers are authorised to submit online requests. Rules for requesters are
available here.
| Program name | Package id | Status | Status date |
|---|---|---|---|
| REMO | NEA-0429/01 | Tested | 01-OCT-1975 |
Machines used:
| Package ID | Orig. computer | Test computer |
|---|---|---|
| NEA-0429/01 | IBM 370 series | IBM 370 series |
[ top ]
3. NATURE OF PHYSICAL PROBLEM SOLVED
The program REMO calculates the overall reliability of a system using the reliability parameters of its elementary components.
Systems formed by reparable and standby components in any mixture can be treated with REMO. Furthermore, due to the fact that the standby effect is treated in an open subroutine the user can obtain a good approximation to the real case at the cost of some programming work.
The results of a REMO run are:
(a) The probability that the system fails before a fixed time.
(b) The list of the more frequent minimal cut sets.
The program REMO calculates the overall reliability of a system using the reliability parameters of its elementary components.
Systems formed by reparable and standby components in any mixture can be treated with REMO. Furthermore, due to the fact that the standby effect is treated in an open subroutine the user can obtain a good approximation to the real case at the cost of some programming work.
The results of a REMO run are:
(a) The probability that the system fails before a fixed time.
(b) The list of the more frequent minimal cut sets.
[ top ]
4. METHOD OF SOLUTION
The code uses a sort of Monte Carlo simulation in order to generate a large statistics of system failures.
The logical connection of the events is described by a conventional fault tree. One of the two different types of importance sampling can be brought in action by the user in the case that simple analogue simulation is very insufficient. Details of these variance reducing devices are given and discussed in the report.
The code uses a sort of Monte Carlo simulation in order to generate a large statistics of system failures.
The logical connection of the events is described by a conventional fault tree. One of the two different types of importance sampling can be brought in action by the user in the case that simple analogue simulation is very insufficient. Details of these variance reducing devices are given and discussed in the report.
[ top ]
5. RESTRICTIONS ON THE COMPLEXITY OF THE PROBLEM
The maximum number of components is 100. The failure law assigned to each component can be of the exponential or Weibull type. The repair times can be assumed constant or random distributed with an exponential law. Each component, when repaired, must be considered good as new. No restart device is implemented in order to save the partial results if execution time is too long for a single run on the computer.
The maximum number of components is 100. The failure law assigned to each component can be of the exponential or Weibull type. The repair times can be assumed constant or random distributed with an exponential law. Each component, when repaired, must be considered good as new. No restart device is implemented in order to save the partial results if execution time is too long for a single run on the computer.
[ top ]
[ top ]
[ top ]
[ top ]
[ top ]
[ top ]
[ top ]
[ top ]
[ top ]
NEA-0429/01
| File name | File description | Records |
|---|---|---|
| NEA0429_01.001 | SOURCE PROGRAM (F4) EBCDIC | 594 |
| NEA0429_01.002 | TREE SUBROUTINE (F4) FOR SAMPLE PROBLEM | 18 |
| NEA0429_01.003 | JCL | 11 |
| NEA0429_01.004 | REMO SAMPLE PROBLEM DATA | 16 |
| NEA0429_01.005 | REMO SAMPLE PROBLEM PRINTED OUTPUT | 214 |
[ top ]
- G. Radiological Safety, Hazard and Accident Analysis
- P. General Mathematical and Computing System Routines
Keywords: Monte Carlo method, fault tree analysis, reliability, system failure analysis.