Smoke detection layout validation

Patent metadata

Field	Value
Publication number	US-11257354-B2
Application number	US-201916518531-A
Country	US
Kind code	B2
Filing date	Jul 22, 2019
Priority date	Jul 22, 2019
Publication date	Feb 22, 2022
Grant date	Feb 22, 2022

Abstract

Provided are embodiments for a system for validating a smoke detection layout, where the system includes a memory and a processor. The processor is configured to receive one or more inputs, model transport and dispersion of smoke to a smoke detector of an environment based on the one or more inputs, wherein the model is based on computational fluid dynamics (CFD) function, and select a subset of input parameters from the one or more inputs to test. The processor is also configured to test the smoke detection system layout using the selected subset of input parameters, determine an alarm time probability using uncertainty quantifications for the selected subset of input parameters, and provide the alarm time probability and confidence level for the selected subset parameters. Also provided are embodiments for a method to validate a smoke detection system layout.

First claim

What is claimed is:

1. A method to validate a smoke detection system layout, the method comprising:
receiving one or more inputs;
modeling transport and dispersion of smoke to a smoke detector of an environment based on the one or more inputs, wherein the model is based on computational fluid dynamics (CFD) function;
selecting a subset of input parameters from the one or more inputs to test;
testing the smoke detection system layout using the selected subset of input parameters;
determining an alarm time probability using uncertainty quantifications for the selected subset of input parameters;
providing the alarm time probability and confidence level for the selected subset of input parameters;
updating the selected subset of input parameters, wherein a number of input parameters of the updated subset of input parameters is less than a number of input parameters of the selected subset of input parameters;
re-testing the smoke detection system layout using the updated subset of input parameters;
determining an alarm time probability using uncertainty quantifications for the updated subset of input parameters; and
providing the alarm time probability and confidence level for the updated subset of input parameters.

2. The method of claim 1 , further comprising displaying a visual output of results of the test.

3. The method of claim 1 , wherein the CFD function is configured to compute the model based on at least one of time, position, and flow of smoke that can be detected by a smoke detector.

4. The method of claim 1 , further comprising optimizing the smoke detection layout, wherein the optimizing includes modifying a number of smoke detectors and locations of the smoke detectors for the smoke detection layout.

5. The method of claim 1 , wherein the CFD function is configured to compute the model based on a smoke detector type and the detection system layout.

6. The method of claim 1 , wherein the CFD function is configured to compute the model based at least in part on a geometry and contents of the protected environment.

7. The method of claim 1 , wherein the CFD function is configured to compute the model based at least in part on an ambient temperature, pressure, or ventilation schedule of the environment.

8. The method of claim 1 , wherein the CFD function is configured to compute the model based on a smoke output and location of a smoke source.

9. The method of claim 8 , wherein the smoke output includes at least one of a concentration, velocity, temperature, or particle size distribution of the smoke.

10. A system comprising:
a memory; and
a processor coupled to the memory configured to:
receive one or more inputs;
model transport and dispersion of smoke to a smoke detector of an environment based on the one or more inputs, wherein the model is based on computational fluid dynamics (CFD) function;
select a subset of input parameters from the one or more inputs to test;
test the smoke detection system layout using the selected subset of input parameters;
determine an alarm time probability using uncertainty quantifications for the selected subset of input parameters;
provide the alarm time probability and confidence level for the selected subset of input parameters;
update the selected subset of input parameters, wherein a number of input parameters of the updated subset of input parameters is less than a number of input parameters of the selected subset of input parameters;
re-test the smoke detection system layout using the updated subset of input parameters;
determine an alarm time probability using uncertainty quantifications for the updated subset of input parameters; and
provide the alarm time probability and confidence level for the updated subset of input parameters.

11. The system of claim 10 , further comprising a display to display a visual output of results of the test.

12. The system of claim 10 , wherein the CFD function is configured to computes the model based on at least one of time, position, and flow of smoke that can be detected by a smoke detector.

13. The system of claim 10 , wherein the environment comprises at least one of a cargo bay, electronics bay, avionics cooling space, lavatory, or storage space.

14. The system of claim 10 , wherein the CFD function is configured to compute the model based on a smoke detector type and the detection system layout.

15. The system of claim 10 , wherein the CFD function is configured to compute the model based at least in part on a geometry and contents of the protected environment.

16. The system of claim 10 , wherein the CFD function is configured to compute the model based at least in part on an ambient temperature, pressure, or ventilation schedule of the environment.

17. The system of claim 10 , wherein the CFD function is configured to compute the model based on a smoke output and location of a smoke source.

18. The system of claim 17 , wherein the smoke output includes at least one of a concentration, velocity, temperature, or particle size distribution of the smoke.

Assignees

• Kidde Tech Inc

Inventors

• Daly Amanda J
• Bell Kenneth
• Simpson Terry
• Corn May L
• Sankaran Vaidyanathan
• Cao Changmin
• Gottiparthi Kalyana
• Wang Ke

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06F2113/08

  Fluids · CPC title

• G08B17/10

  Actuation by presence of smoke or gases {, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means} · CPC title

• G06F2111/10

  Numerical modelling · CPC title

• G08B29/043 Primary

  of fire detection circuits · CPC title