NESC1082 SIGPI.
SIGPI, Probabilistic System Performance by Fault-Tree Analysis
NAME OR DESIGNATION OF PROGRAM, COMPUTER, DESCRIPTION OF PROGRAM OR FUNCTION, METHOD OF SOLUTION, RESTRICTIONS ON THE COMPLEXITY OF THE PROBLEM, TYPICAL RUNNING TIME, UNUSUAL FEATURES OF THE PROGRAM, RELATED AND AUXILIARY PROGRAMS, STATUS, REFERENCES, MACHINE REQUIREMENTS, LANGUAGE, OPERATING SYSTEM UNDER WHICH PROGRAM IS EXECUTED, OTHER PROGRAMMING OR OPERATING INFORMATION OR RESTRICTIONS, NAME AND ESTABLISHMENT OF AUTHORS, MATERIAL, CATEGORIES
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| Program name | Package id | Status | Status date |
|---|---|---|---|
| SIGPI | NESC1082/01 | Tested | 07-DEC-1989 |
| SIGPI | NESC1082/02 | Tested | 07-DEC-1989 |
Machines used:
| Package ID | Orig. computer | Test computer |
|---|---|---|
| NESC1082/01 | Many Computers | CRAY X-MP |
| NESC1082/02 | DEC VAX 11/750 | DEC VAX 8810 |
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3. DESCRIPTION OF PROGRAM OR FUNCTION
SIGPI computes the probabilistic performance of complex systems by combining cut set or other binary product data with probability information on each basic event. SIGPI is designed to work with either coherent systems, where the system fails when certain combinations of components fail, or noncoherent systems, where at least one cut set occurs only if at least one component of the system is operating properly. The program can handle conditionally independent components, dependent components, or a combination of component types and has been used to evaluate responses to environmental threats and seismic events. The three data types that can be input are cut set data in disjoint normal form, basic component probabilities for independent basic components, and mean and covariance data for statistically dependent basic components.
SIGPI computes the probabilistic performance of complex systems by combining cut set or other binary product data with probability information on each basic event. SIGPI is designed to work with either coherent systems, where the system fails when certain combinations of components fail, or noncoherent systems, where at least one cut set occurs only if at least one component of the system is operating properly. The program can handle conditionally independent components, dependent components, or a combination of component types and has been used to evaluate responses to environmental threats and seismic events. The three data types that can be input are cut set data in disjoint normal form, basic component probabilities for independent basic components, and mean and covariance data for statistically dependent basic components.
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4. METHOD OF SOLUTION
SIGPI uses two fast complementary methods to compute the probabilistic performance of complex systems: the pi method and the sigma method. The pi method exploits the fact that defined system components are often statistically independent conditional to the environment in which they are embedded. The sigma method computes the probability of combinations of components produced by the pi method by disjointing and partitioning the components, thereby allowing the exact computation of performance. The computational complexity of the overall process is a polynomial function of the number of components. When statistical independence is not possible, dependent data can be used in the calculation, although both speed and accuracy may suffer.
SIGPI uses two fast complementary methods to compute the probabilistic performance of complex systems: the pi method and the sigma method. The pi method exploits the fact that defined system components are often statistically independent conditional to the environment in which they are embedded. The sigma method computes the probability of combinations of components produced by the pi method by disjointing and partitioning the components, thereby allowing the exact computation of performance. The computational complexity of the overall process is a polynomial function of the number of components. When statistical independence is not possible, dependent data can be used in the calculation, although both speed and accuracy may suffer.
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6. TYPICAL RUNNING TIME
The running time depends on the complexity of the problem. The same problems required from 3.8 seconds to 53 minutes on the DEC VAX11/785 and from 0.1 to 5.3 seconds on the CDC CYBER170/875.
The running time depends on the complexity of the problem. The same problems required from 3.8 seconds to 53 minutes on the DEC VAX11/785 and from 0.1 to 5.3 seconds on the CDC CYBER170/875.
NESC1082/01
NEA-DB ran the test cases included in this package on a CRAY-XMP/2800 computer. CPU times varied from 6.1 to 9.5 seconds.NESC1082/02
NEA-DB ran the test cases included in this package in interactive mode on a VAX 8810 computer.[ top ]
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| Package ID | Status date | Status |
|---|---|---|
| NESC1082/01 | 07-DEC-1989 | Tested at NEADB |
| NESC1082/02 | 07-DEC-1989 | Tested at NEADB |
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NESC1082/01, included references:
- C. Yuelys-Miksis:SIGPI Cray, CDC (Single-Precision) Version Tape
Description and Implementation Information.
NESC Note 88-80 (June 30, 1988)
- C.J. Patenaude:
SIGPI: A User's Manual for Fast Computation of the Probabilistic
Performance of Complex Systems.
NUREG/CR-4800, UCID-20679 (September 1986).
NESC1082/02, included references:
- C. Yuelys-Miksis:SIGPI DEC VAX (Double-Precision) Version Tape
Description and Implementation Information.
NESC Note 88-79 (June 30, 1988)
- C.J. Patenaude:
SIGPI: A User's Manual for Fast Computation of the Probabilistic
Performance of Complex Systems.
NUREG/CR-4800, UCID-20679 (September 1986).
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NESC1082/01
On CDC CYBER 830, 450,000 (octal) words of main storage are required to run the test cases.[ top ]
| Package ID | Computer language |
|---|---|
| NESC1082/01 | FORTRAN-77 |
| NESC1082/02 | FORTRAN-77 |
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13. OPERATING SYSTEM UNDER WHICH PROGRAM IS EXECUTED
VMS 4.0, 4.5 (DEC VAX11), CTSS (Cray1), NOS 2.4.3 (CDC CYBER170/875).
VMS 4.0, 4.5 (DEC VAX11), CTSS (Cray1), NOS 2.4.3 (CDC CYBER170/875).
NESC1082/01
COS 1.17 (CRAY-XMP/2800) with CFT 1.14 compiler.NESC1082/02
VMS V5.0-1 (VAX8810) with FORTRAN V5.0-1 compiler.[ top ]
14. OTHER PROGRAMMING OR OPERATING INFORMATION OR RESTRICTIONS
Full-word Boolean operations AND, OR, and NOT must be available. The test problem output produced with the DEC VAX version may differ from the output shown in the reference document due to variations in operating systems and available memory. The dependent case test problems can be run on a CDC only if LCM is available. A dummy XERROR subroutine is included in the Cray, CDC version of SIGPI. The Cray version may be run on CDC machines by disabling the lines with - CRAY - in columns 73-78 and enabling those with --CDC-- in columns 73-78 as well as utilizing the appropriate machine constants in Function RIMACH, and presetting memory to zero.
Full-word Boolean operations AND, OR, and NOT must be available. The test problem output produced with the DEC VAX version may differ from the output shown in the reference document due to variations in operating systems and available memory. The dependent case test problems can be run on a CDC only if LCM is available. A dummy XERROR subroutine is included in the Cray, CDC version of SIGPI. The Cray version may be run on CDC machines by disabling the lines with - CRAY - in columns 73-78 and enabling those with --CDC-- in columns 73-78 as well as utilizing the appropriate machine constants in Function RIMACH, and presetting memory to zero.
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NESC1082/01
| File name | File description | Records |
|---|---|---|
| NESC1082_01.001 | Information file | 175 |
| NESC1082_01.002 | SSIG.FOR | 1901 |
| NESC1082_01.003 | CSIG.FOR | 1433 |
| NESC1082_01.004 | FUN.FOR | 1460 |
| NESC1082_01.005 | PDEP.FOR | 511 |
| NESC1082_01.006 | PRE.FOR | 663 |
| NESC1082_01.007 | SD.FOR | 3365 |
| NESC1082_01.008 | SDC.FOR | 1743 |
| NESC1082_01.009 | SDP.FOR | 819 |
| NESC1082_01.010 | SIO.FOR | 304 |
| NESC1082_01.011 | DPDEP.FOR | 678 |
| NESC1082_01.012 | XERROR.DUM | 3 |
| NESC1082_01.013 | XERROR.FOR | 1053 |
| NESC1082_01.014 | DTEST.DAT | 17 |
| NESC1082_01.015 | PTEST.DAT | 114 |
| NESC1082_01.016 | TEST1.DAT | 5 |
| NESC1082_01.017 | TEST2.DAT | 5 |
| NESC1082_01.018 | TEST3.DAT | 20 |
| NESC1082_01.019 | TEST4.DAT | 20 |
| NESC1082_01.020 | SMPL1.DAT | 1 |
| NESC1082_01.021 | SMPL2.DAT | 2 |
| NESC1082_01.022 | SMPL3.DAT | 2 |
| NESC1082_01.023 | SMPL4.DAT | 2 |
| NESC1082_01.024 | SMPL5.DAT | 2 |
| NESC1082_01.025 | SMPL6.DAT | 2 |
| NESC1082_01.026 | SMPL7.DAT | 2 |
| NESC1082_01.027 | SMPL8.DAT | 2 |
| NESC1082_01.028 | Print out of smple problem B.4.1 | 139 |
| NESC1082_01.029 | Print out of smple problem B.4.2 | 137 |
| NESC1082_01.030 | Print out of smple problem B.4.5 | 165 |
| NESC1082_01.031 | Print out of smple problem B.4.6 | 164 |
| NESC1082_01.032 | CONVI.FOR | 24 |
| NESC1082_01.033 | CRAY JCL | 41 |
NESC1082/02
| File name | File description | Records |
|---|---|---|
| NESC1082_02.001 | INFORMATION FILE | 110 |
| NESC1082_02.002 | SSIG.FOR | 1779 |
| NESC1082_02.003 | CSIG.FOR | 1353 |
| NESC1082_02.004 | FUN.FOR | 1155 |
| NESC1082_02.005 | PRE.FOR | 637 |
| NESC1082_02.006 | PDEP.FOR | 511 |
| NESC1082_02.007 | SD.FOR | 3212 |
| NESC1082_02.008 | SDC.FOR | 1652 |
| NESC1082_02.009 | SDP.FOR | 764 |
| NESC1082_02.010 | SIO.FOR | 277 |
| NESC1082_02.011 | DPDEP.FOR | 679 |
| NESC1082_02.012 | DTEST.DAT | 17 |
| NESC1082_02.013 | PTEST.DAT | 114 |
| NESC1082_02.014 | TEST1.DAT | 5 |
| NESC1082_02.015 | TEST2.DAT | 5 |
| NESC1082_02.016 | TEST3.DAT | 20 |
| NESC1082_02.017 | TEST4.DAT | 20 |
| NESC1082_02.018 | PRINTOUT OF SAMPLE PROBLEM B.4.1 | 3 |
| NESC1082_02.019 | PRINTOUT OF SAMPLE PROBLEM B.4.2 | 3 |
| NESC1082_02.020 | PRINTOUT OF SAMPLE PROBLEM B.4.3 | 9 |
| NESC1082_02.021 | PRINTOUT OF SAMPLE PROBLEM B.4.4 | 9 |
| NESC1082_02.022 | PRINTOUT OF SAMPLE PROBLEM B.4.5 | 5 |
| NESC1082_02.023 | PRINTOUT OF SAMPLE PROBLEM B.4.6 | 5 |
| NESC1082_02.024 | PRINTOUT OF SAMPLE PROBLEM B.4.7 | 11 |
| NESC1082_02.025 | PRINTOUT OF SAMPLE PROBLEM B.4.8 | 4 |
| NESC1082_02.026 | CONVI.FOR | 29 |
| NESC1082_02.027 | SIGPI.OPT | 5 |
| NESC1082_02.028 | SIGPI.COM | 21 |
Keywords: fault tree analysis, mathematical models, probability, system failure analysis.