Probability Distribution Function Mapping Method

• US 20110010140A1
• Filed: 07/13/2009
• Published: 01/13/2011
• Est. Priority Date: 07/13/2009
• Status: Abandoned Application

• Current Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Original Assignee: Northrop Grumman Corporation
• Inventors: Engel, Stephen J., Hoitsma, David H.
• Application Number:
  US12/501,542
• Publication Number:
  US 20110010140A1
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04

Abstract

A method includes: receiving a plurality of values of an input variable representative of a physical characteristic of a component or system, using a physics model to produce an estimate of an output for each of the input values, mapping the output estimates to the input values to produce an output probability density or cumulative distribution function for the physical characteristic at a future time, and outputting the probability density or cumulative distribution function. An apparatus that implements the method is also provided.

Claims

1. A method comprising:

receiving a plurality of values of an input variable representative of a physical characteristic of a component or system;

using a physics model to produce an estimate of an output for each of the input values;

mapping the output estimates to the input values to produce an output probability density or cumulative distribution function for the physical characteristic at a future time; and

outputting the probability density or cumulative distribution function.

2. The method of claim 1, wherein the physical characteristic comprises a crack length as a function of time or a time to failure as a function of crack length.

3. The method of claim 1, wherein the mapping step comprises:

fitting the estimates to a plurality of curves; and

using points on the curves to produce an output probability density for the physical characteristic at a future time.

4. The method of claim 3, wherein the step of using points on the curves to produce an output probability density for the physical characteristic at a future time selects values from corresponding points on the curves.

5. The method of claim 4, wherein the curves comprise one of:

a line or a spline.

6. The method of claim 4, wherein the curves are equi-probability curves.

7. The method of claim 4, further comprising:

taking a vertical slice of the curves.

8. The method of claim 7, further comprising:

computing the probability density or cumulative distribution function using points on the vertical slice.

9. The method of claim 1, wherein the probability density or cumulative distribution function is computed using interpolation.

10. The method of claim 1, wherein the input variables are random variables.

11. An apparatus comprising:

a processor having an input for receiving an input probability distribution of a variable for a stochastic process, wherein the processor uses a mapping function, which relates outputs to inputs, to produce an exact representation of an output distribution for the stochastic process.

12. The apparatus of claim 11, wherein the stochastic process represents a crack length as a function of time or a time to failure as a function of crack length.

13. The apparatus of claim 11, wherein the processor fits estimates to a plurality of curves and uses points on the curves to produce the output distribution.

14. The apparatus of claim 13, wherein the processor selects values from corresponding points on the curves.

15. The apparatus of claim 14, wherein the curves comprise one of:

a line or a spline.

16. The apparatus of claim 15, wherein the curves are equi-probability curves.

17. The apparatus of claim 15, wherein the processor takes a vertical slice of the curves.

18. The apparatus of claim 17, wherein the output distribution is computed using points on the vertical slice.

19. The apparatus of claim 11, wherein the output distribution is computed using interpolation.

20. The apparatus of claim 11, wherein the processor receives random input variables.